Science, Faculty of
Chemistry, Department of
DSpace
UBCV
Maschmeyer-Tombs, Tristan
Doctor of Philosophy - PhD
University of British Columbia
The ability to quantitatively monitor chemical species through a reaction allows for insight to enhance process efficiency and/or safety. Nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical technique, known for the ability to provide structural and quantitative data in a non-destructive manner. There has been significant growth in the development and availability of benchtop NMR spectrometers in the last decade. The use of permanent magnets result in smaller applied magnetic fields, a decrease in sensitivity and signal dispersion, but a more compact size and affordable cost. Particularly, benchtop NMR can allow for the powerful analytical capabilities associated with NMR spectroscopy to enter non-traditional settings, such as a synthetic laboratory. Therefore, this thesis focuses on leveraging these systems for reaction monitoring. First, an on-line continuous-flow benchtop NMR system is explored. Particular attention is given to the impact of flow on the mixing behaviour of analyte within the flow cell, mixing/emptying behaviour, the spin-lattice relaxation time, and sensitivity of data measurement with two sets of acquisition parameters. The complex nature of continuous-flow analyses prompted the development and application of an on-line stopped-flow benchtop NMR system, with all hardware centrally controlled with a Python script. The utility of this system was showcased using difficult to monitor model reaction systems. These reactions include activation of a carboxylic acid with sulfuryl fluoride (SO₂F₂) and carbamate formation as a result of an alcohol reacting with an isocyanate resultant from a modified Curtius rearrangement. An external calibration quantitative NMR (qNMR) method is further highlighted, allowing for robust qNMR analyses without an internal standard or special hardware. The utility of the qNMR method is demonstrated by monitoring all synthetic steps of a highly relevant chemical transformation to the pharmaceutical industry: 1,1’-carbonyldiimidazole (CDI) mediated amide coupling. Lastly, on-line stopped- and continuous-flow benchtop NMR systems were compared for reaction monitoring, using two model reactions: a homogenous imination reaction and the activation of a carboxylic acid using perfluorobutanesulfonyl fluoride (PBSF). The on-line stopped-flow benchtop NMR system resulted in more robust quantitative analyses and, therefore, more easily achievable mechanistic information.
ADVANCING BENCHTOP NUCLEAR MAGNETIC RESONANCE (NMR) SPECTROSCOPY AS A TOOL FOR PHARMACEUTICAL DEVELOPMENT by Tristan Maschmeyer-Tombs B.Sc. with Honors, University of California, Santa Cruz, 2018 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Chemistry) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) December 2023 © Tristan Maschmeyer-Tombs, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Advancing Benchtop Nuclear Magnetic Resonance (NMR) Spectroscopy as a Tool for Pharmaceutical Development submitted by Tristan Maschmeyer-Tombs in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Chemistry Examining Committee: Jason E. Hein, Associate Professor, Chemistry, UBC Supervisor Parisa Mehrkhodavandi, Professor, Chemistry, UBC Supervisory Committee Member Glenn M. Sammis, Professor, Chemistry, UBC University Examiner Dan Bizzotto, Professor, Chemistry, UBC University Examiner Additional Supervisory Committee Members: Martin E. Tanner, Professor, Chemistry, UBC Supervisory Committee Member Raymond J. Andersen, Professor, Chemistry, UBC Supervisory Committee Member iii Abstract The ability to quantitatively monitor chemical species through a reaction allows for insight to enhance process efficiency and/or safety. Nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical technique, known for the ability to provide structural and quantitative data in a non-destructive manner. There has been significant growth in the development and availability of benchtop NMR spectrometers in the last decade. The use of permanent magnets result in smaller applied magnetic fields, a decrease in sensitivity and signal dispersion, but a more compact size and affordable cost. Particularly, benchtop NMR can allow for the powerful analytical capabilities associated with NMR spectroscopy to enter non-traditional settings, such as a synthetic laboratory. Therefore, this thesis focuses on leveraging these systems for reaction monitoring. First, an on-line continuous-flow benchtop NMR system is explored. Particular attention is given to the impact of flow on the mixing behaviour of analyte within the flow cell, mixing/emptying behaviour, the spin-lattice relaxation time, and sensitivity of data measurement with two sets of acquisition parameters. The complex nature of continuous-flow analyses prompted the development and application of an on-line stopped-flow benchtop NMR system, with all hardware centrally controlled with a Python script. The utility of this system was showcased using difficult to monitor model reaction systems. These reactions include activation of a carboxylic acid with sulfuryl fluoride (SO2F2) and carbamate formation as a result of an alcohol reacting with an isocyanate resultant from a modified Curtius rearrangement. An external calibration quantitative NMR (qNMR) method is further highlighted, allowing for robust qNMR analyses without an internal standard or special hardware. The utility of the qNMR method is demonstrated by monitoring all synthetic steps of a highly relevant chemical transformation to the pharmaceutical industry: 1,1’-carbonyldiimidazole (CDI) mediated amide coupling. Lastly, on-line stopped- and continuous- iv flow benchtop NMR systems were compared for reaction monitoring, using two model reactions: a homogenous imination reaction and the activation of a carboxylic acid using perfluorobutanesulfonyl fluoride (PBSF). The on-line stopped-flow benchtop NMR system resulted in more robust quantitative analyses and, therefore, more easily achievable mechanistic information. v Lay Summary The ability of a chemist to understand what happens when chemicals are mixed in a reaction solution is critical not only to predict the outcome and what is chemically produced, but also for understanding how a reaction may be performed with a higher degree of safety and/or efficiency. Many analytical tools may be leveraged to do so, where “snapshots” of a chemical reaction and present chemical species are taken at a particular time. Herein, we leverage benchtop nuclear magnetic resonance (NMR) spectroscopy as one of these tools and investigate the use of flow systems to interrogate reactions. This work highlights key considerations with the flow systems applied and highlights one type of configured system that allows the technique to be easily approachable to non-experts. Furthermore, in this work we highlight a method to quantify chemical components using a benchtop NMR. vi Preface Chapter 1. All the contents were written by me with feedback from my supervisor, Dr. Jason E. Hein. The chapter serves as an outline of topics and theory relevant for the remainder of the thesis. None of the content in this chapter has been previously published. Chapter 2. This chapter is adapted from the following journal article, previously published in Magnetic Resonance in Chemistry: • T. Maschmeyer, P. L. Prieto, S. Grunert, J. E. Hein. Exploration of continuous-flow benchtop NMR acquisition parameters and considerations for reaction monitoring. Magn. Reson. Chem. 2020, 58, 1234–1248. All experiments were conceived by Dr. Jason E. Hein and me, where all experimental work was conducted by me (either in person or remote). Dr. Jason E. Hein was involved with some of the experimental setup during the limited physical access to the labs due to COVID-19. The Python script leveraged in the study was written by Hein lab colleague, Veronica Lai. I additionally wrote the manuscript, which was edited and proof-read by all coauthors (Paloma L. Prieto, Shad Grunert, and Dr. Jason E. Hein). Chapter 3. This chapter is adapted from the following journal article, previously published in Reaction Chemistry & Engineering: • T. Maschmeyer, L. P. E. Yunker, J. E. Hein. Quantitative and convenient real-time reaction monitoring using stopped-flow benchtop NMR. React. Chem. Eng. 2022, 7, 1061–1072. vii All experiments were conceived by Dr. Jason E. Hein and me. Dr. Lars P. E. Yunker wrote all of the Python code. All other experimental work was conducted by me. I wrote the manuscript, which was edited and proof-read by all coauthors (Dr. Lars P. E. Yunker and Dr. Jason E. Hein). Chapter 4. This chapter is adapted from an accepted manuscript from Magnetic Resonance in Chemistry. All experiments were conceived by Dr. Jason E. Hein, Dr. Thomas C. Malig, Dr. José G. Napolitano, and me. All experimental work was conducted by Dr. José G. Napolitano or me (all at Genentech, Inc. in South San Francisco, CA, USA). The experimental work conducted by me was performed in the summer of 2022, where NMR data measured by Dr. José G. Napolitano is explicitly stated in the chapter. I wrote the manuscript, which was edited and proof-read by all coauthors (Breanna Conklin, Dr. Thomas C. Malig, Dr. David J. Russell, Dr. Kenji L. Kurita, Dr. Jason E. Hein, and Dr. José G. Napolitano). Chapter 5. This chapter is adapted from an accepted manuscript from Magnetic Resonance in Chemistry. All experiments were conceived by Dr. Jason E. Hein and me. All experimental work was conducted by me at Genentech, Inc. in South San Francisco, CA, USA (summer 2022). I wrote the manuscript, which was edited and proof-read by all coauthors (Dr. David J. Russell, Dr. José G. Napolitano, and Dr. Jason E. Hein). viii Table of Contents Abstract .......................................................................................................................................... iii Lay Summary .................................................................................................................................. v Preface ........................................................................................................................................... vi Table of Contents ........................................................................................................................ viii List of Tables ............................................................................................................................... xvi List of Figures ............................................................................................................................. xix List of Symbols ................................................................................................................................ l List of Abbreviations .................................................................................................................... liv Acknowledgements ..................................................................................................................... lviii Dedication ..................................................................................................................................... lxi Epigraph ...................................................................................................................................... lxii Chapter 1: Introduction ................................................................................................................. 1 1.1 Nuclear magnetic resonance (NMR) spectroscopy ................................................................. 3 1.1.1 The basics of NMR theory and the vector model .................................................................................. 4 1.1.2 Pulse NMR spectroscopy ..................................................................................................................... 13 1.1.3 Relaxation and NMR ........................................................................................................................... 25 1.1.3.1 Spin-lattice relaxation (T1) ......................................................................................................... 27 1.1.3.2 Spin-spin relaxation (T2) ............................................................................................................. 30 1.1.4 Observation of different nuclei with NMR spectroscopy .................................................................... 33 1.1.5 Effect of external magnetic field strength (B!) on NMR spectra ......................................................... 41 ix 1.1.6 Monitoring reactions with NMR spectroscopy .................................................................................... 49 1.1.6.1 Reactions monitored in a standard NMR tube ........................................................................... 50 1.1.6.2 In-situ stopped-flow NMR ......................................................................................................... 51 1.1.6.3 Rapid injection NMR ................................................................................................................. 52 1.1.6.4 In-situ continuous-flow NMR .................................................................................................... 53 1.1.6.5 On-line continuous-flow NMR ................................................................................................... 55 1.1.6.6 On-line stopped-flow NMR ........................................................................................................ 59 1.2 Overview of thesis ..................................................................................................................... 61 Chapter 2: On-line continuous-flow benchtop NMR, exploration of acquisition parameters and considerations for reaction monitoring ............................................................................... 62 2.1 Introduction .............................................................................................................................. 62 2.2 Investigation into continuous-flow conditions ....................................................................... 66 2.2.1 Direct visual observation of flow/mixing behaviour ........................................................................... 66 2.2.2 Observation of flow behaviour via 1H NMR ....................................................................................... 71 2.2.3 Determination of spin-lattice relaxation time (T1) and observed spin-lattice relaxation time (T1*) with flow…… ............................................................................................................................................................. 74 2.2.4 Signal-to-noise ratio (SNR) determination with various flow rates .................................................... 77 2.2.5 Signal-to-noise ratio (SNR) determination with various reaction vial temperatures ........................... 84 2.3 Conclusion ................................................................................................................................. 87 2.4 Experimental and further data ............................................................................................... 89 2.4.1 General ................................................................................................................................................. 89 2.4.1.1 Chemicals ................................................................................................................................... 89 2.4.1.2 NMR data collection, processing, and analysis .......................................................................... 89 2.4.2 Experimental procedures and further relevant data ............................................................................. 90 2.4.2.1 Direct visual observation of flow and mixing behaviour ........................................................... 90 x 2.4.2.1.1 Experimental procedure ......................................................................................................... 90 2.4.2.1.2 Further data relevant to section .............................................................................................. 91 2.4.2.2 Observation of flow behaviour via 1H NMR .............................................................................. 92 2.4.2.2.1 Experimental procedure ......................................................................................................... 92 2.4.2.2.2 Further data relevant to section .............................................................................................. 93 2.4.2.3 Determination of spin-lattice relaxation time (T1) and observed spin-lattice relaxation time (T1*) with flow…. ................................................................................................................................................... 96 2.4.2.3.1 Experimental procedure ......................................................................................................... 96 2.4.2.3.2 Further data relevant to section .............................................................................................. 97 2.4.2.4 Signal-to-noise ratio (SNR) determination with various flow rates ......................................... 102 2.4.2.4.1 Experimental procedure ....................................................................................................... 102 2.4.2.4.2 Further data relevant to the section ...................................................................................... 103 2.4.2.5 Signal-to-noise ratio (SNR) determination with various reaction vial temperatures ............... 106 2.4.2.5.1 Experimental procedure ....................................................................................................... 106 2.4.2.5.2 Further data relevant to the section ...................................................................................... 106 Chapter 3: Quantitative and convenient real-time reaction monitoring using on-line stopped-flow benchtop NMR ................................................................................................................... 108 3.1 Introduction ............................................................................................................................ 108 3.2 Designing an on-line stopped-flow benchtop NMR system ................................................ 111 3.2.1 System hardware and remote control ................................................................................................. 111 3.2.2 Benchtop 19F NMR data processing and analysis .............................................................................. 113 3.2.3 Benchtop 19F NMR data acquisition parameter selection .................................................................. 114 3.2.4 Quantitative method development and verification ........................................................................... 117 3.3 Application of on-line stopped-flow benchtop NMR system to reaction monitoring ...... 119 3.3.1 Sulfuryl fluoride (SO2F2) generation and hydrolysis ......................................................................... 119 3.3.2 Activation of a carboxylic acid with sulfuryl fluoride (SO2F2) ......................................................... 123 xi 3.3.3 Modified Curtius rearrangement with diphenylphosphoryl azide (DPPA) ........................................ 128 3.3.4 Simultaneous reaction monitoring via stopped-flow benchtop NMR and ReactIR - comparison of orthogonal monitoring techniques .................................................................................................................... 136 3.4 Conclusion ............................................................................................................................... 139 3.5 Experimental and further data ............................................................................................. 141 3.5.1 General ............................................................................................................................................... 141 3.5.1.1 Chemicals ................................................................................................................................. 141 3.5.1.2 NMR data collection, processing, and analysis ........................................................................ 141 3.5.1.3 Hazards and experimental precautions ..................................................................................... 142 3.5.2 Stopped-flow benchtop NMR system details ..................................................................................... 142 3.5.2.1 General physical description .................................................................................................... 142 3.5.2.2 Description of workflow with Python script and stopped-flow NMR system ......................... 144 3.5.2.3 Calibration of system’s peristaltic pump .................................................................................. 147 3.5.2.4 Volume determination of benchtop NMR stopped-flow system .............................................. 148 3.5.2.5 Determination of flow rate for subsequent analyses with benchtop NMR stopped-flow system…….. ................................................................................................................................................ 149 3.5.3 19F NMR data acquisition parameter selection .................................................................................. 151 3.5.3.1 Radiofrequency (RF) pulse calibration .................................................................................... 151 3.5.3.2 Spin-lattice relaxation time (T1) estimations ............................................................................ 152 3.5.3.3 Radiofrequency (RF) pulse excitation over 220 ppm spectral range ....................................... 157 3.5.3.4 19F NMR concentration conversion factor (CCF) determination and verification ................... 158 3.5.3.5 Monitoring change in NMR response with differing ionic strength ........................................ 159 3.5.4 Reaction monitoring and further relevant data ................................................................................... 160 3.5.4.1 Reactions involving sulfuryl fluoride (SO2F2) ......................................................................... 160 3.5.4.1.1 Capture and hydrolysis of sulfuryl fluoride (SO2F2) ........................................................... 160 3.5.4.1.2 Activation if a carboxylic acid with sulfuryl fluoride (SO2F2) ............................................ 162 3.5.4.2 Reactions relevant to Modified Curtius rearrangement ............................................................ 164 xii 3.5.4.2.1 Stepwise Curtius rearrangement and carbamate formation - hexafluoroisopropyl alcohol (3.16) addition prior to heat .................................................................................................................... 164 3.5.4.2.2 Modified Curtius rearrangement and carbamate formation - reagents added directly after one another to a heated solution .................................................................................................................... 165 3.5.4.2.3 Stepwise Curtius rearrangement and carbamate formation - heat prior to hexafluoroisopropyl alcohol (3.16) addition ............................................................................................................................ 167 3.5.4.2.4 Mitsunobu type reaction between diphenylphosphoryl azide (DPPA) and hexafluoroisopropyl alcohol (3.16) ......................................................................................................... 168 3.5.4.2.5 Simultaneous reaction monitoring via stopped-flow benchtop NMR and ReactIR - comparison of orthogonal monitoring techniques .................................................................................. 169 3.5.5 Product Characterization .................................................................................................................... 172 3.5.5.1 4-fluorobenzoyl fluoride (3.11) ................................................................................................ 172 3.5.5.2 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl)carbamate (3.17) ..................................... 173 Chapter 4: A reliable external calibration method for reaction monitoring with benchtop NMR..................................................................................................................................................... 174 4.1 Introduction ............................................................................................................................ 174 4.2 Preparing a concentration conversion factor (CCF) .......................................................... 178 4.3 Application to reaction monitoring: CDI mediated activation .......................................... 184 4.4 Conclusion ............................................................................................................................... 192 4.5 Experimental and further data ............................................................................................. 193 4.5.1 General ............................................................................................................................................... 193 4.5.1.1 Chemicals ................................................................................................................................. 193 4.5.1.2 NMR data collection, processing and analysis ......................................................................... 193 4.5.1.3 Hazards and experimental precautions ..................................................................................... 194 4.5.2 On-line stopped-flow NMR system details ........................................................................................ 194 xiii 4.5.2.1 General information .................................................................................................................. 194 4.5.2.2 Calibration of system’s peristaltic pump .................................................................................. 196 4.5.2.3 Determination of benchtop NMR flow system volume ........................................................... 197 4.5.3 Experimental procedures .................................................................................................................... 198 4.5.3.1 Determination of concentration conversion factors (CCF) ...................................................... 198 4.5.3.2 Multi-analyte CCF confirmation .............................................................................................. 199 4.5.3.3 Synthesis of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide .............................................. 199 4.5.4 Further relevant data .......................................................................................................................... 200 4.5.4.1.1 CCF determination with analytes in MeCN ........................................................................ 200 4.5.4.1.2 Robustness of CCF with multi-analyte test in DMSO-d6 .................................................... 204 4.5.4.2 Hydrolysis CDI ......................................................................................................................... 210 4.5.4.3 Calculation of CDI potency and initial solution concentration ................................................ 211 4.5.4.4 Nucleophilic capture of activated acyl imidazole .................................................................... 212 4.5.4.5 Variable temperature (VT) high-field NMR of amide 4.11 ..................................................... 214 4.5.4.6 Spin-lattice relaxation time (T1) estimations ............................................................................ 215 4.5.5 Product characterization ..................................................................................................................... 220 4.5.5.1.1 N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) ................................................... 220 Chapter 5: Reaction monitoring via benchtop NMR spectroscopy – a practical comparison of on-line stopped-flow and continuous-flow sampling methods ................................................. 222 5.1 Introduction ............................................................................................................................ 222 5.2 Reaction monitoring ............................................................................................................... 226 5.2.1 Homogenous imination reaction ........................................................................................................ 226 5.2.2 Heterogeneous (biphasic) carboxylic activation ................................................................................ 232 5.3 Conclusion ............................................................................................................................... 241 5.4 Experimental and further data ............................................................................................. 243 xiv 5.4.1 General ............................................................................................................................................... 243 5.4.1.1 Chemicals ................................................................................................................................. 243 5.4.1.2 NMR data collection, processing, and analysis ........................................................................ 243 5.4.1.3 Hazards and experimental precautions ..................................................................................... 244 5.4.2 Details on NMR flow systems ........................................................................................................... 244 5.4.2.1 Benchtop NMR flow system .................................................................................................... 244 5.4.2.1.1 General information ............................................................................................................. 244 5.4.2.1.2 Calibration of system’s peristaltic pump ............................................................................. 246 5.4.2.1.3 Determination of benchtop NMR flow system volume ....................................................... 246 5.4.2.2 High-field NMR flow system ................................................................................................... 248 5.4.2.2.1 General information ............................................................................................................. 248 5.4.2.2.2 Determination of the volume of the benchtop NMR system with integration of a high-field NMR……… ........................................................................................................................................... 250 5.4.3 Spin-lattice relaxation time (T1) estimations ...................................................................................... 251 5.4.3.1 Species relevant to imination reaction ...................................................................................... 252 5.4.3.2 Species relevant to carboxylic acid activation with PBSF ....................................................... 255 5.4.4 Reaction monitoring procedures ........................................................................................................ 257 5.4.4.1 Imination Reaction ................................................................................................................... 257 5.4.4.2 Activation of carboxylic acid with PBSF ................................................................................. 258 5.4.5 Further data relevant to imination reaction ........................................................................................ 260 5.4.5.1.1 Additional reaction profiles ................................................................................................. 260 5.4.5.1.2 Apparent rate constant determination .................................................................................. 261 5.4.5.1.3 Signal-to-noise ratio (SNR) determination .......................................................................... 263 5.4.6 Further data relevant to PBSF activation reaction ............................................................................. 263 5.4.6.1.1 Apparent reaction constant determination ........................................................................... 263 5.4.6.1.2 Mechanistic investigation .................................................................................................... 266 5.4.7 Product characterization ..................................................................................................................... 268 xv 5.4.7.1 N,1-bis(4-fluorophenyl)methanimine (5.3) .............................................................................. 268 5.4.7.2 4-fluorobenzoyl fluoride (5.10) ................................................................................................ 268 Chapter 6: Conclusion and future work ................................................................................... 270 6.1 Conclusion ............................................................................................................................... 270 6.2 Future work ............................................................................................................................ 276 6.3 Concluding remarks ............................................................................................................... 278 References .................................................................................................................................. 279 Appendices .................................................................................................................................. 296 Appendix A High-field NMR data for Chapter 3 ............................................................................. 296 A.1 4-fluorobenzoyl fluoride (3.11) .......................................................................................................... 296 A.2 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17) ............................................. 304 A.3 Reaction end point: all reagents for modified Curtius rearrangement added directly after one another to heated solution .............................................................................................................................................. 313 A.4 Reaction end point: full conversion to isocyanate 3.15 prior to alcohol 3.16 addition ...................... 320 Appendix B High-field NMR data for Chapter 4 ............................................................................. 328 B.1 N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) ................................................................. 328 Appendix C High-field NMR data for Chapter 5 ............................................................................. 339 C.1 N,1-bis(4-fluorophenyl)methanimine (5.3) ........................................................................................ 339 C.2 4-fluorobenzoyl fluoride (5.10) .......................................................................................................... 347 xvi List of Tables Table 1.1. Correlations between the atomic number and atomic mass number of a nucleus with its nuclear spin quantum number (I). Inspired by Ref 2 and 13. ......................................................... 5 Table 1.2. Summary of physical properties relevant to NMR spectroscopy, including NMR activity, for various nuclei. Data adapted from Ref 2, 57, and 84. ............................................... 35 Table 1.3. Chemical shift ranges of commonly studied nuclei via NMR spectroscopy. Data adapted from Ref 84. ..................................................................................................................... 37 Table 2.1. 1H NMR acquisition parameters utilized for SNR determination of 2.2 in MeCN. ... 77 Table 2.2. Results of filling and emptying analyses of NMR flow cell via 1H with various flow rates. These data were used to prepare the graph in Figure 2.5. .................................................. 93 Table 2.3. Flow dependent 1H NMR acquisition parameters used for inversion recovery experiments in T1 and T1* estimation for the aldehydic proton of 2.2 in MeCN (10.0 v/v% MeCN-d3). ................................................................................................................................................. 97 Table 2.4. Summary of T1 and T1* estimations (60 MHz, 0.24 M, 22.0 °C) for the 1H NMR resonance of the aldehyde proton of 2.2 in MeCN (10.0 v/v% MeCN-d3) using the inversion recovery experiment. ..................................................................................................................... 98 Table 2.5. Statistical analysis of 2.2 aldehyde SNR data (60 MHz, MeCN), with analyte at various concentrations and flow rates, and data collected as per slow acquisition parameters listed in Table 2.1................................................................................................................................................ 104 Table 2.6. Statistical analysis of 2.2 aldehyde SNR data (60 MHz, MeCN), with analyte at various concentrations and flow rates. Data collected as per fast acquisition parameters listed in Table 2.1...................................................................................................................................................... 105 xvii Table 2.7. Statistical analysis of 2.2 aldehyde SNR data (60 MHz, MeCN), with analyte at two flow rates and vial at various temperatures. Data collected as per slow acquisition parameters listed in Table 2.1. ................................................................................................................................ 107 Table 4.1. 1H NMR integration data used to determine CCF for 1H qNMR analyses with the benchtop NMR system. CCF was determined using the aromatic resonances of methyl 3,5-dinitrobenzoate (4.1, δH 9.2 ppm) in MeCN. .............................................................................. 201 Table 4.2. Summary of 1H NMR data used to determine CCF for 1H qNMR analyses with the benchtop NMR system. CCF was determined using the aromatic resonances of methyl 3,5-dinitrobenzoate (4.1, δH 9.2 ppm) in MeCN. .............................................................................. 202 Table 4.3. 19F NMR integration data used to determine CCF for 19F qNMR analyses with the benchtop NMR system. CCF was determined using the trifluoromethyl resonance of benzotrifluoride (4.2, δF -61.6 ppm) in MeCN. .......................................................................... 203 Table 4.4. Summary of 19F NMR data used to determine CCF for 19F qNMR analyses with the benchtop NMR system. CCF was determined using the trifluoromethyl resonance of benzotrifluoride (4.2, δF -61.6 ppm) in MeCN. .......................................................................... 204 Table 4.5. 1H NMR integration data used to confirm CCF for 1H qNMR analyses with the benchtop NMR system. CCF was determined with methyl 3,5-dinitrobenzoate (4.1) in DMSO-d6. ........ 205 Table 4.6. 1H NMR integration data used to confirm CCF for 1H qNMR analyses with the benchtop NMR system. CCF was determined with maleic acid (4.3) in DMSO-d6. ................................. 206 Table 4.7. 1H NMR integration data used to confirm CCF for 1H qNMR analyses with the benchtop NMR system. CCF was determined with dimethylmalonic acid (4.4) in DMSO-d6. ................. 207 Table 4.8. 1H NMR integration data used to confirm CCF for 1H qNMR analyses with the benchtop NMR system. CCF was determined with trimethoxybenzene (4.5) in DMSO-d6. ..................... 208 xviii Table 4.9. Summary of 1H NMR data used to confirm CCF for 1H qNMR analyses with the benchtop NMR system. CCF determined using multi-analytes, all in DMSO-d6. ..................... 209 Table 4.10. Summary of T1 estimations using the inversion recovery experiment for relevant species. For species with multiple resonances, see above figure for colour assignment. ........... 220 Table 5.1. Summary of apparent rate constants for each component/resonance for imination reaction monitored via benchtop 19F{1H} NMR and fitted to first-order exponential. .............. 261 Table 5.2. Summary of apparent rate constants for each component for carboxylic acid 5.4 activation with PBSF (5.6) monitored via benchtop 19F{1H} NMR and fitted to first-order exponential. ................................................................................................................................. 264 xix List of Figures Figure 1.1. Visual representation of a) what must be mathematically satisfied using a spectroscopic technique to observe the Plank-Einstein relation between two quantized energy levels and b) what is qualitatively observed when satisfied. Figure inspired by Ref 4. ................. 2 Figure 1.2. The electromagnetic spectrum with the different electromagnetic regions specified by wavelength (in meters), along with general trends in wavelength and energy denoted across the spectrum. ......................................................................................................................................... 2 Figure 1.3. Classic schematic depiction of a “spin !"” (I = !" ) NMR active nucleus (purple sphere) exposed to an external magnetic field (𝐵#, along +z-axis). This intrinsic angular momentum vector (𝑃) and magnetic moment (𝜇) precess about the direction of 𝐵# (red arrow) at the Larmor frequency (νL) of the nucleus. Inspired by Ref 34. .......................................................................................... 7 Figure 1.4. Schematic representations of magnetic moment vectors (purple arrows) projected onto the z-axis (𝜇%, red arrows) for both spin !" and 1 (I = !" and 1) nuclei. The directional quantum number (𝑚) for each of the𝜇% is additionally displayed. External magnetic field (𝐵#) is aligned on the +z-axis. .................................................................................................................................... 10 Figure 1.5. Visualization of moving from conceptualizing the magnetic moment vector of a single nucleus to the magnetic moment vectors of a simplified ensemble of spin !" nuclei. The Boltzmann distribution law (Equation 1.8) suggests for a given temperature, populations exist in both the 𝛼 and 𝛽 states, with an excess in the 𝛼 state. External magnetic field (𝐵#) is aligned on the +z-axis........................................................................................................................................................ 11 xx Figure 1.6. Considering the ensemble of nuclei for a spin !" nuclei, vector summation can be performed considering all x, y, and z components. The randomly distributed transverse (x-y plane) components cancel and only the bulk magnetization vector (𝑀#) along the +z-axis results of when performing a vector summation of the entire ensemble. This is a result of Boltzmann distribution law states that more nuclei will be orientated in the energy favourable 𝛼 state for a given temperature. External magnetic field (𝐵#) is aligned on the +z-axis. Inspired by Ref 34. ........... 13 Figure 1.7. Simple pulse sequence (single channel, no decoupling) for a 1D NMR experiment. This pulse sequence is annotated with a relaxation time (d1), pulse width (𝜏&), and acquisition time (AQ) resulting in acquisition of a free induction decay (FID). Important to note the pulse sequence is displayed with a time axis, to which elements in this theoretical pulse sequence are not drawn to scale. ......................................................................................................................................... 14 Figure 1.8. Schematic representing the perturbation of a bulk magnetization vector (𝑀#) with a RF pulse of 𝜃 degrees applied from an applied field (𝐵!) and transmitter coil. Only transverse (x’-y’) components (𝑀'"(") are observable by the receiver coil. Inspired by Ref 34. ................. 16 Figure 1.9. Annotated free induction decay (FID), highlighting decrease in observable signal over time due to relaxation processes. The FID is dominated by signal and noise in beginning and end of FID acquisition, respectively. ................................................................................................... 18 Figure 1.10. Experimentally acquired 1H NMR FIDs (60 MHz) of the same single component sample (water) with the same set of acquisition parameters other than offset frequency. a) When offset frequency (ν0) is equal to Larmor frequency of resonance (νL), the resonance is said to be on-resonance. b) When ν0 ≠ νL, resonance is said to be off-resonance (above, resonance is 77.4 Hz off-resonance). ......................................................................................................................... 19 xxi Figure 1.11. Experimentally acquired 19F NMR data (trifluorobenzene, 376 MHz) highlighting modulation of resonance intensity with pulse width (𝜏&), and directly proportional pulse angle (𝜃) in a simple 1D NMR experiment. ................................................................................................. 21 Figure 1.12. Expanded pulse sequence for a multi-scan (4 scan), signal-averaged experiment. Highlighted is the repetition time (𝜏*), which represents the total time between pulses (acquisition time (AQ) + relaxation time (d1)). Pulse sequence is displayed with a time axis, to which elements in this theoretical sequence are not drawn to scale. ...................................................................... 22 Figure 1.13. Experimentally acquired 1H NMR data measured for sample of Strychnine (CDCl3, 500 MHz). The acquired time-domain data (FID) undergoes a Fourier transform (FT) to produce the associated frequency-domain data (NMR spectrum). ............................................................. 23 Figure 1.14. Annotated 1H NMR spectrum of strychnine (CDCl3, 500 MHz) with common nomenclature used to compare relative chemical shifts of resonances in an NMR spectrum. ..... 25 Figure 1.15. a) Spin-lattice relaxation: recovery of relative longitudinal polarization (𝑀+) of the bulk magnetization (𝑀#) as a function of time (t) and spin-lattice relaxation time (T1) after a 90° pulse. b) Spin-spin relaxation: loss of transverse magnetization (𝑀'() as a function of t and spin-spin relaxation time (T2) after a 90° pulse. Figure inspired by Ref 34. ........................................ 26 Figure 1.16. Structures of some paramagnetic relaxation agents used for NMR spectroscopy. . 27 Figure 1.17. Schematic highlighting the process of spin-lattice (or longitudinal) relaxation in the rotating frame, considering an on-resonance bulk-magnetization vector (𝑀#) directly after a 90° pulse. As 𝑀# relaxes, longitudinal polarization (𝑀+,) accumulates, while transverse magnetization (𝑀',(, = 𝑀(,) decreases. Upon full relaxation, only longitudinal magnetization exists. Figure inspired by Ref 34. ........................................................................................................................ 28 xxii Figure 1.18. a) Pulse sequence for the inversion recovery experiment. b) Molecular structure of 2-(methoxymethyl)oxirane along with the estimated T1 values of 1H nuclei using the inversion recovery experiment. c) Experimental 1H NMR spectra (500 MHz, CDCl3) with increasing 𝜏 from bottom to top. d) Integration of each of the assigned resonances with various 𝜏 values, along with equation used to calculate the estimated T1 values. ...................................................................... 30 Figure 1.19. Schematic highlighting the process of spin-spin (or transverse) relaxation in the rotating frame, with the perspective of looking down on the transverse plane from the +z’-axis, starting with the bulk-magnetization vector (𝑀#) directly after a 90° pulse (𝑀',(, = 𝑀(,). As individual magnetic moment vectors start to fan out, net transverse magnetization decreases, until no transverse magnetization exists. Figure inspired by Ref 34. ................................................... 31 Figure 1.20. Experimentally acquired 1H NMR FID (60 MHz) of a single component sample (water), highlighting the practical relationship of observed spin-spin relaxation time (T2*) and linewidths in an NMR spectrum. .................................................................................................. 32 Figure 1.21. Schematic displaying the frequencies of nuclei commonly studied nuclei via NMR spectroscopy. Frequencies are displayed for a 11.7 T NMR instrument with a 500.1 MHz 1H Larmor frequency (νL). Data from Ref 84. ................................................................................... 36 Figure 1.22. Experimental 19F NMR (58 MHz) excitation profiles for pulse widths (𝜏&) of 75 𝜇s, 50 𝜇s, and 25 𝜇s, which correspond to 90°, 60°, and 30° pulse angles for the used spectrometer, respectively. .................................................................................................................................. 38 xxiii Figure 1.23. 13C and 13C{1H} NMR spectra of retapamulin (C6D6, 150 MHz). A “carbon NMR spectrum” generally refers to a 13C{1H} NMR spectrum as the spectrum is visually simplified and has a greater SNR due to consolidation of signal and enhancement of protonated carbons due to nuclear Overhauser effect (NOE). NMR data acquired and shared by Dr. David J. Russell (Genentech, Inc.). .......................................................................................................................... 41 Figure 1.24. Relationship between the relative energies of 𝛼 and 𝛽 states (𝑚 = + !" and − !", respectively) for a spin !" nucleus and the strength of the external magnetic field (𝐵0) supplied by the NMR instrument. Importantly, as strength of 𝐵# increases, so does the energy difference between 𝛼 and 𝛽 states (𝐵!&ΔE! < 𝐵"&ΔE"). Inspired by Ref 13. ............................................ 42 Figure 1.25. 1H NMR spectra of the same sample of strychnine (CDCl3) acquired with the same acquisition parameters on multiple NMR spectrometers with varying magnetic field strengths (60 – 850 MHz). NMR data were all processed the same and normalized to noise intensity. ..... 43 Figure 1.26. Annotated 1H NMR spectra zoomed into aromatic region (𝛿H 6.5 ppm – 8.5 ppm) of strychnine (CDCl3) acquired with multiple NMR spectrometers of varying magnetic field strengths (60 – 850 MHz). Signal dispersion increases with magnetic field strength, resulting in multiplets occupying less spectral space. ....................................................................................................... 44 Figure 1.27. 1H NMR spectra of the same sample of strychnine (CDCl3) acquired with the same acquisition parameters on multiple NMR spectrometers with varying magnetic field strengths (60 – 850 MHz). The horizonal scale has been changed from the typical parts-per-million (ppm) to kilohertz (kHz). Note that a spectrum of the same spectral width (in ppm) is composed of a larger frequency range as the strength of the external magnetic field strength of the instrument increases. ....................................................................................................................................... 45 xxiv Figure 1.28. 1H NMR spectra of the same sample of strychnine (CDCl3) acquired with the same acquisition parameters on multiple NMR spectrometers with varying magnetic field strengths (60 – 850 MHz). ............................................................................................................................ 46 Figure 1.29. Comparison of a) high-field 600 MHz NMR spectrometer (Bruker, located at Genentech Inc.) and b) benchtop NMR spectrometer designated with arrow (Nanalysis Scientific Corp., located at the University of British Columbia). ................................................................. 48 Figure 1.30. Schematic representation of an in-situ stopped-flow NMR system, shown to monitor hypothetical reaction “A + B”. These reagents are injected into the magnet, mixed, and NMR data are measured after the stop syringe is filled, stops the flow, and triggers data acquisition. ......... 52 Figure 1.31. Schematic representation of a rapid injection NMR system to monitor hypothetical reaction “A + B”. In this system as shown, reagent “B” is injected into a solution of reagent “A” that is already within the NMR spectrometer. .............................................................................. 53 Figure 1.32. Schematic representation of an in-situ continuous-flow NMR system, shown to monitor hypothetical reaction A + B. Solutions of each reagent are injected into the magnet, mixed, and continuously flowed through the NMR probe (as NMR data are measured) to some site of collection. ...................................................................................................................................... 55 Figure 1.33. Schematic representation of an on-line continuous-flow NMR system, shown to monitor a hypothetical batch reaction. Reaction solution is continuously pumped from the reaction vial, flowed through the NMR for data acquisition, and circulated back to the reaction occurring in batch conditions. Importantly, NMR data measurement is conducted on an actively flowing sample. .......................................................................................................................................... 56 xxv Figure 1.34. Schematic representation of an on-line stopped-flow NMR system, shown to monitor a hypothetical batch reaction. Reaction solution is pumped from the reaction vial, through the NMR, and circulated back to the reaction occurring in batch conditions. Prior to data acquisition, flow is halted (can be done by toggling “on”/“off” of pump, as shown above). After data acquisition, flow is reinitiated, and fresh reaction solution is flowed through the system. Importantly, NMR data measurement is conducted on a static sample. ....................................... 60 Figure 2.1. Schematic representation of the configuration and experimental flow benchtop NMR system utilized, with arrows signifying direction of analyte flow. The hardware components consist of a benchtop NMR spectrometer (NMReady-60PRO, Nanalysis Scientific Corp.) equipped with a flow cell, peristaltic pump (SF-10 reagent pump, Vapourtec Ltd.), and a vial with analyte in an EasyMax 402 Basic Synthesis Workstation (Mettler Toledo, not shown). ............. 65 Figure 2.2. Mixing and flowing behaviour within an NMR flow cell demonstrated by flowing water and red dye at various flow rates (a) 0.5 mL/min, b) 1.0 mL/min, and c) 3.2 mL/min). For a given flow rate, the left panel demonstrates the process of filling the cell, whereas the right panel demonstrates emptying the cell. .................................................................................................... 67 Figure 2.3. The relative presence of red dye in three ROIs of the flow cell (bottom, middle, and top) once the dye began to fill the flow cell for six flow rates (a) 0.5, b) 0.8, c) 1.0, d) 1.5, e) 2.2, and f) 3.2 mL/min). Importantly, the direction of flow is from bottom to top and connecting lines in graphs are for visual aid purposes only. ................................................................................... 69 xxvi Figure 2.4. a) Representative stacked 1H NMR (60 MHz) spectra demonstrating the growth of the methyl resonance of 2.1 during system filling with a flow rate of 0.8 mL/min. b) Normalized 1H NMR methyl resonance (𝛿H 3.3 ppm) integration of 2.1 as function of time when filling and emptying a flow cell at 0.8 mL/min. Connecting lines in graphs are for visual aid purposes only........................................................................................................................................................ 72 Figure 2.5. Time for methyl resonance of 2.1 (𝛿H 3.27 ppm) to reach maximum integration via 1H NMR with flow system initially primed with MeCN (filling) and time for 2.1 to be evacuated once MeCN was flowed back into the system (emptying) with various flow rates. Connecting lines in graphs are for visual aid purposes only. ........................................................................................ 73 Figure 2.6. a) True and apparent average spin-lattice relaxation times (T1 and T1*, respectively) for the aldehyde resonance of 2.2 (𝛿H 10.0 ppm, 60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) at various flow rates. b) Comparison of trends in estimated T1* and residence time of analyte in entire 1.20 mL flow cell at various flow rates. Connecting lines in graphs are for visual aid purposes only. ......................................................................................................................... 75 Figure 2.7. Average 1H NMR (60 MHz, MeCN) SNR of the aldehydic resonance of 2.2 (𝛿H 10.0 ppm) at 0.10, 0.24, and 0.48 M concentrations and various flow rates. Data were collected with a) slow and b) fast acquisition parameters, per Table 2.1. ............................................................... 79 Figure 2.8. Average 1H NMR (60 MHz, MeCN) SNR of the aldehyde signal of 2.2 (𝛿H 10.0 ppm) at a) 0.48 M, b) 0.24 M, and c) 0.10 M concentrations. Data were acquired with slow and fast acquisition parameters, as listed in Table 2.1. .............................................................................. 80 Figure 2.9. Average 1H NMR (60 MHz, MeCN) relative percent change in SNR for the aldehyde resonance of 2.2 (𝛿H 10.0 ppm) with analyte flow compared to static sample and data collected with a) slow and b) fast acquisition parameters, per Table 2.1. ................................................... 82 xxvii Figure 2.10. Linearity of average 1H NMR (60 MHz, MeCN) SNR of the aldehyde resonance of 2.2 (𝛿H 10.0 ppm) at various concentrations. R2 values are with respect to linear trendlines not shown, and connecting lines are for visual aide purposes only: a) slow acquisition at lower flow rates (0.0 – 0.8 mL/min), b) slow acquisition at higher flow rates (1.0 – 3.2 mL/min), c) fast acquisition at lower flow rates (0.0 – 0.8 mL/min), and d) fast acquisition at higher flow rates (1.0 – 3.2 mL/min). Acquisition parameters are listed in Table 2.1. ................................................... 83 Figure 2.11. a) Average 1H NMR (60 MHz, MeCN) SNR of the aldehyde proton of 2.2 (𝛿H 10.0 ppm, 0.10 M) with varied temperatures of the reaction vial at two flow rates (0.5 and 2.2 mL/min), and b) relative change in SNR for the same signal with reaction vial at room temperature. ....... 85 Figure 2.12. Zoomed in picture to the utilized flow cell, with reference to the specified ROIs used in the applied Python script to monitor relative red food dye intensity in “top”, “middle”, and “bottom” regions with time. .......................................................................................................... 90 Figure 2.13. Relative decrease in dye presence over time (at top, middle, and bottom of cell) while emptying the flow cell at different flow rates. Important to note, the inlet of the flow cell is at the bottom and output is located at the top. Evolution of air bubble can also be observed in trial for 1.0 mL/min. ......................................................................................................................................... 91 Figure 2.14. Normalized benchtop 1H NMR integration of methyl resonance of 2.1 (𝛿H 3.3 ppm) as a function of time for filling and emptying processes using a system of MeCN and a 50/50 2.1/MeCN solution at 0.5 mL/min. ............................................................................................... 94 Figure 2.15. Normalized benchtop 1H NMR integration of methyl resonance of 2.1 (𝛿H 3.3 ppm) as a function of time for filling and emptying processes using a system of MeCN and a 50/50 2.1/MeCN solution at 1.0 mL/min. ............................................................................................... 94 xxviii Figure 2.16. Normalized benchtop 1H NMR integration of methyl resonance of 2.1 (𝛿H 3.3 ppm) as a function of time for filling and emptying processes using a system of MeCN and a 50/50 2.1/MeCN solution at 1.5 mL/min. ............................................................................................... 95 Figure 2.17. Normalized benchtop 1H NMR integration of methyl resonance of 2.1 (𝛿H 3.3 ppm) as a function of time for filling and emptying processes using a system of MeCN and a 50/50 2.1/MeCN solution at 2.2 mL/min. ............................................................................................... 95 Figure 2.18. Normalized benchtop 1H NMR integration of methyl resonance of 2.1 (𝛿H 3.3 ppm) as a function of time for filling and emptying processes using a system of MeCN and a 50/50 2.1/MeCN solution at 3.2 mL/min. ............................................................................................... 96 Figure 2.19. Representative results of the inversion recovery experiment to estimate the T1 for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 0.0 mL/min flow. ....................................................................................... 99 Figure 2.20. Representative results of the inversion recovery experiment to estimate the T1* for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 0.5 mL/min flow. .............................................................................. 99 Figure 2.21. Representative results of the inversion recovery experiment to estimate the T1* for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 0.8 mL/min flow. ............................................................................ 100 Figure 2.22. Representative results of the inversion recovery experiment to estimate the T1* for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 1.0 mL/min flow. ............................................................................ 100 xxix Figure 2.23. Representative results of the inversion recovery experiment to estimate the T1* for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 1.5 mL/min flow. ............................................................................ 101 Figure 2.24. Representative results of the inversion recovery experiment to estimate the T1* for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 2.2 mL/min flow. ............................................................................ 101 Figure 2.25. Representative results of the inversion recovery experiment to estimate the T1* for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 3.2 mL/min flow. ............................................................................ 102 Figure 3.1. Schematic representation of the stopped-flow benchtop NMR system, with respect to flow paths in each of the valve positions. Arrows signify direction of analyte flow and coloured lines denote connecting segments of line. The hardware components consist of a benchtop NMR spectrometer (NMReady-60PRO, Nanalysis Scientific Corp.) equipped with a flow cell, peristaltic pump (SF-10 reagent pump, Vapourtec Ltd.), and six-port valve (C-10, Valco Instruments Co. Inc.). ............................................................................................................................................ 112 Figure 3.2. a) Stacked benchtop 19F NMR spectra (57 MHz) altering the off-resonance position (distance off resonance denoted in kHz) with the trifluoromethyl resonance of 3.1 (𝛿F -63.5 ppm) and b) the average absolute integration of this resonance with these spectral positions. ........... 117 Figure 3.3. a) Average benchtop 19F NMR (57 MHz) integration per nuclide of varying concentrations of 3.1 (𝛿F -63.5 ppm) used to determine the instrument's CCF for the applied data acquisition and processing. b) Verification of CCF by comparing 19F NMR determined concentrations of 3.2 (𝛿F -77.0 ppm) with the gravimetrically determined concentrations. ...... 118 xxx Figure 3.4. Schematic of stopped-flow benchtop NMR system as applied to monitor sulfuryl fluoride (SO2F2) processes. This includes a SO2F2 generator vial (vial 1) and capturing/reaction vial (vial 2), connected by PEEK tubing. ................................................................................... 121 Figure 3.5. a) Scheme corresponding to the for the capture (MeCN, 40 °C) and subsequent hydrolysis of SO2F2 (3.4, 0.08 M; 2.4 eq. H2O, 5.8 eq. DIPEA). b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired for the capture and hydrolysis of 3.4, with increasing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of benchtop NMR system. ......................................................................... 122 Figure 3.6. a) Reaction scheme for the activation 3.7 (0.67 M, MeCN, 40 °C) to the corresponding acyl fluoride 3.11 with DIPEA (2.5 eq.) and SO2F2 (3.4, theoretically 5.0 eq. synthesized). b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired for the activation, with increasing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of NMR system (internal standard, 3.1, not shown to simplify graph). .... 125 Figure 3.7. Determination of the dissolution constant of SO2F2 (3.4) to a first-order approximation (1.3 h-1 or 3.5 × 10-4 s-1). [SO2F2]dissol represents the remaining amount of 3.4 to either react or dissolve into the solution over the time course, determined retroactively. ................................. 126 Figure 3.8. a) Reaction scheme for the carbamate forming reaction of 3.7 (0.67 M, toluene) with TEA (1.1 eq.), DPPA (1.1 eq.), 3.16 (1.1 eq.) and heat (80 °C) added stepwise. b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired on the process, with increasing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of NMR system. ........................................................................................................... 130 xxxi Figure 3.9. Ratio of carbamate 3.17 to ester 3.18 concentrations as the result from the heated reaction solution (80 °C) of 3.14 (formed from reaction of 3.7 with DPPA) with 3.16. Time begins with the reaction solution exposed to heat. ................................................................................. 131 Figure 3.10. a) Reaction scheme for the carbamate forming reaction of 3.7 (0.67 M, toluene), TEA (1.1 eq.), DPPA (1.1 eq.), heat (80 °C) and 3.16 (1.1 eq.) added stepwise. b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired for the process, with increasing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of benchtop NMR system. .......................................................................................................... 133 Figure 3.11. a) Reaction scheme for the Mitsunobu type reaction between DPPA and 3.16, with reagents added stepwise, as indicated in corresponding graph. b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired for the process, with increasing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of NMR system. 19F NMR spectra zoomed into spectral region between 𝛿F -72 and -78 ppm. ............ 135 Figure 3.12. a) Reaction scheme and final benchtop 19F NMR (57 MHz) spectrum of monitoring the formation of carbamate 3.17 from 3.7 (0.67 M, toluene) with TEA (1.1 eq.), DPPA (1.1 eq.), heat (80 °C) and 3.16 (1.1 eq.). b) Reaction scheme and final benchtop 19F NMR (57 MHz) spectrum of monitoring reaction progress of Mitsunobu type reactivity between 3.16 (0.52 M) and DPPA (1.0 eq.) in a heated solution (toluene, 80 °C) with TEA (1.0 eq.). ................................. 136 Figure 3.13. Schematic representation of the on-line stopped-flow benchtop NMR system (shown in valve position “A”) with a Mettler Toledo ReactIR (702L) equipped with a Mettler Toledo DS Micro Flow Cell placed between the pump and valve, allowing for simultaneous monitoring of a reaction via NMR and IR spectroscopies. ................................................................................... 137 xxxii Figure 3.14. Comparison of some major reaction components monitored via ReactIR (coloured trends) and benchtop 19F NMR (greyed trends). This includes a) carboxylic acid starting material 3.7, b) acyl azide intermediate 3.14, c) isocyanate intermediate 3.15, and d) desired carbamate product 3.17. ............................................................................................................................... 139 Figure 3.15. Close up picture displaying the utilized 3D printed legs, allowing for instrument to be slightly lifted (advantageous for flow cell) and use of the instrument’s vibration dampening features. ....................................................................................................................................... 143 Figure 3.16. Colour designated identity (ETFE or PEEK) and associated lengths of tubing for each segment of stopped-flow benchtop NMR system. ...................................................................... 144 Figure 3.17. Annotated screenshot of the Python script allowing for convenient and centralized control of the stopped-flow benchtop NMR system, with important designations for analysis annotated. .................................................................................................................................... 146 Figure 3.18. Calibration of Vapourtec SF-10 reagent peristaltic pump used for stopped-flow benchtop NMR system. ............................................................................................................... 147 Figure 3.19.Verification of sufficient transfer and mixing of analyte with a 1.78 mL/min flow rate and 3.94 min. Determined via 19F NMR (57 MHz) monitoring the trifluoromethyl resonance of 3.1 (𝛿F -63.5 ppm), with the system initially primed with MeCN. ................................................... 151 Figure 3.20. Results from calibration of RF pulse for benchtop 19F NMR system (57 MHz). These results are shown a) qualitatively with the lithium bis(fluorosulfonyl)imide resonance (𝛿F 52.2 ppm, spectra normalized to noise) and b) graphically with the observed and expected relative 19F NMR integration. ........................................................................................................................ 152 xxxiii Figure 3.21. Results from application of the inversion recovery experiment for T1 estimation of the aryl fluoride peak of 3.7 (57 MHz, 32 °C). These results are shown a) qualitatively with the resonance of interest (normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values. ............................................................ 153 Figure 3.22. Results from application of the inversion recovery experiment for T1 estimation of some of the products of the activation reaction of interest using SO2F2 (3.4) activation reaction of interest (57 MHz, 32 °C). These results are shown a) qualitatively with the resonances of interest (decimated spectra, normalized to noise) and b) graphically with peak integrations of each of the resonance graphed with application of various 𝜏 values. ............................................................ 155 Figure 3.23. Results from application of the inversion recovery experiment for T1 estimation of the aryl fluoride peak of the acyl fluoride product (3.11, 57 MHz, 32 °C). These results are shown a) qualitatively with the resonance of interest (normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values. ............................... 156 Figure 3.24. Results from application of the inversion recovery experiment for T1 estimation of reaction species relevant to Curtius rearrangement work (57 MHz, 32 °C). A reaction mixture (reaction shown in Figure 3.10) well past its end point was used for analysis. These results are shown a) qualitatively with the resonances of interest (decimated spectra, note left and right spectra are of different intensities) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values. ................................................................................................... 157 Figure 3.25. Effect of change in ionic strength (by altering NaCl concentrations) on the average benchtop 19F NMR (57 MHz) integration of the resonance consistent with 3.2 (𝛿F -77.0 ppm)...................................................................................................................................................... 160 xxxiv Figure 3.26. Picture of the experimental setup to study the hydrolysis of SO2F2 (3.4). From left to right one can see the syringe pump dosing TFA (3.2), vial 1 (round-bottom flask) connected to vial 2 (scintillation vial), and the stopped-flow benchtop NMR system. Note of caution: this process involves the evolution and use of a toxic gas so special consideration to perform this work in a well-ventilated space must be done. Additionally, precautions to avoid over-pressurization of the system must be taken. ................................................................................................................. 162 Figure 3.27. Picture of the experimental setup (a) up-close and b) of the entire stopped-flow system) to study the activation 3.7 with SO2F2 (3.4). Note of caution: this process involves the evolution and use of a toxic gas so special consideration to perform this work in a well-ventilated space must be done. Additionally, precautions to avoid over-pressurization of the system must be taken. ........................................................................................................................................... 164 Figure 3.28. a) Reaction scheme for the carbamate forming modified Curtius rearrangement of 3.7 (0.68 M, toluene, 80 °C) with TEA (1.1 eq.) DPPA (1.1 eq.) and 3.16 (1.1 eq.) and reagents added sequentially, directly after one another. b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired on the process, with easing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of NMR system. .................. 167 Figure 3.29. a) Reaction scheme for the carbamate forming modified Curtius rearrangement of 3.7 (0.61 M, toluene) with TEA (1.1 eq.), DPPA (1.1 eq.), heat (80 °C) and 3.16 (1.1 eq.) added stepwise. b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired for the process, with increasing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of NMR system. ......................................................... 171 xxxv Figure 3.30. Full waterfall plots representing the ReactIR data acquired over the entire reaction course with a) allowing for better visualization of peaks with smaller wavenumbers and b) the same data but rotated to allow for better visualization of peaks with larger wavenumbers. ...... 172 Figure 4.1. Preparation of Concentration Conversion Factors (CCFs) for benchtop NMR system using Magritek flow cell for a) 1H NMR using aromatic resonances of methyl 3,5-dinitrobenzoate (4.1, δH 9.2 ppm) and b)19F NMR using trifluoromethyl resonance of benzotrifluoride (4.2, δF -61.6 ppm) in MeCN. ..................................................................................................... 181 Figure 4.2. Robustness of the qNMR method showcased by great agreement in absolute integration per nuclide versus concentration using multiple analytes: methyl 3,5-dinitrobenzoate (4.1, pink), maleic acid (4.3, green), dimethylmalonic acid (4.4, yellow), and trimethoxybenzene (4.5, blue) in DMSO-d6. Line of best fit determined using data from all analytes. .................... 182 Figure 4.3. a) Scheme for the hydrolysis of CDI (4.6, 0.20 M, δH 7.8 ppm) with residual water to form imidazole 4.7 (δH 11.0 ppm) in MeCN. b) Representative decimated stacked array of benchtop 1H NMR spectra. c) Quantitative reaction profile resultant from application of the NMR spectrometer’s CCF. ................................................................................................................... 185 Figure 4.4. a) Scheme for the activation of carboxylic acid 4.8 (0.28 M, δF -61.6 ppm) with CDI (4.6) to form the corresponding activated acyl imidazole 4.9 (δF -62.1 ppm) in MeCN. b) Representative decimated stacked array of benchtop 19F NMR spectra. c) Quantitative reaction profile resultant from application of the NMR spectrometer’s CCF. ......................................... 186 xxxvi Figure 4.5. a) Full reaction scheme for the activation of carboxylic acid 4.8 (0.28 M, δF -61.6 ppm) with CDI (4.6) to form acyl imidazole (4.9, δF -62.1 ppm) that was captured with 4-fluoroaniline (4.10, δF -128.5 ppm) to form the corresponding amide 4.11 (δF -61.6 ppm and -117.9 ppm) in MeCN. b) Decimated stacked array of benchtop 19F NMR spectra of the nucleophilic capture. c) Quantitative reaction profile resultant from application of the NMR spectrometer’s CCF. ...... 188 Figure 4.6. a) Scheme for the nucleophilic capture of prepared acyl imidazole (4.9) with 4-fluoroaniline (4.10) to form the corresponding amide 4.11 in MeCN. b) Annotated spectral regions of final benchtop 19F NMR spectrum, with trifluoromethyl resonances observable for both cis- and trans- amide conformations of 4.11. c) Quantitative reaction profiles; agreement between trifluoromethyl and aryl fluoride resonances observed only when trifluoromethyl resonances of both conformations are considered. ............................................................................................ 190 Figure 4.7. Expansion of the 1D 19F NMR VT overlay (565 MHz), focusing on the trifluoromethyl region of the spectra. Coalescence of the two trifluoromethyl resonances are consistent with these being from the cis- and trans- conformers of amide 4.11. .......................................................... 191 Figure 4.8. Schematic highlighting the stopped-flow system used in this study. ...................... 195 Figure 4.9. Calibration of peristaltic pump utilized with the on-line stopped-flow system. ..... 196 Figure 4.10. a) Expansion of lower concentration data points for multi-analyte CCF test. b) Results of linear regression without the two lowest concentration data points (0.10 M and 0.02 M with 14.5 and 12.6 % RSD, respectively) for methyl 3,5-dinitrobenzoate (pink). The determined CCF is the same if these points are either included or excluded, showcasing the robustness of the technique. Samples for this multi-analyte test include maleic acid (green), methyl 3,5-dinitrobenzoate (pink), dimethylmalonic acid (yellow), and trimethoxybenzene (blue) in DMSO-d6. ................................................................................................................................................ 210 xxxvii Figure 4.11. a) Reaction scheme for the hydrolysis of CDI (4.6) with residual water in MeCN. b) Reaction trend for monitoring resonance consistent with 4.6 (δH 7.8 ppm). .............................. 211 Figure 4.12. a) Reaction scheme for the nucleophilic capture of activated acyl imidazole 4.9 with 4-fluoroaniline (4.10) to prepare amide coupling product 4.11. Expansion of reaction profile for amide 4.11 formation when monitoring trifluoromethyl (δF -61.6 ppm) and aryl fluoride (δF -117.9 ppm) resonance b) at the final data points and c) near 50 % conversion to the amide product over the observed period. ............................................................................................... 213 Figure 4.13. a) Reaction scheme for the nucleophilic capture of activated acyl imidazole 4.9 with 4-fluoroaniline (4.10) to prepare amide coupling product 4.11. Determination of observed second order rate constant determined from b) acyl imidazole 4.9 (δF -62.1 ppm) and c) aniline 4.10 (δF -128.5 ppm) resonances, with time starting when nucleophile 4.10 was dosed into the reaction solution. ....................................................................................................................................... 214 Figure 4.14. Expansion of the 1D 19F NMR VT overlay (565 MHz), focusing on the zoomed aryl fluoride region. Intensity was increased to better visualize minor amide conformer. ................ 215 Figure 4.15. Results of the inversion recovery experiment for methyl 3,5-dinitrobenzoate a) spectrally and b) graphically. ...................................................................................................... 216 Figure 4.16. Results of the inversion recovery experiment for benzotrifluoride a) spectrally and b) graphically. ............................................................................................................................. 216 Figure 4.17. Results of the inversion recovery experiment for maleic acid a) spectrally and b) graphically. ............................................................................................................................. 217 Figure 4.18. Results of the inversion recovery experiment for dimethylmalonic acid a) spectrally and b) graphically. ...................................................................................................................... 217 xxxviii Figure 4.19. Results of the inversion recovery experiment for 1,3,5-trimethoxybenzene a) spectrally and b) graphically. ...................................................................................................... 218 Figure 4.20. Results of the inversion recovery experiment for 1,1’-carbonyldiimidazole (CDI) a) spectrally and b) graphically. ...................................................................................................... 218 Figure 4.21. Results of the inversion recovery experiment for 4-(trifluoromethyl)benzoic acid a) spectrally and b) graphically. ...................................................................................................... 219 Figure 4.22. Results of the inversion recovery experiment for 4-fluoroaniline a) spectrally and b) graphically. ............................................................................................................................. 219 Figure 5.1. Schematic of the on-line NMR flow systems compared in this study for a) stopped-flow analyses and b) continuous-flow analyses. ......................................................................... 225 Figure 5.2. a) Reaction scheme for coupling 5.1 (0.22 M, 1.0 eq., δF -105.0 ppm) and 5.2 (1.1 eq., δF -129.6 ppm) to form corresponding imine 5.3 (δF -110.0 and -118.9 ppm) in 1:1 MeCN:MeOH. b) Representative decimated stacked array of 19F{1H} NMR spectra (58 MHz) of the transformation when monitored via stopped-flow NMR. c) Reaction profile resulting from tracking each resonance with time. ........................................................................................................... 227 Figure 5.3. a) Reaction scheme for coupling 5.1 (0.22 M, δF -105.0 ppm) and 5.2 (1.1 eq., δF -129.6 ppm) to form the corresponding imine 5.3 (δF -110.0 and -118.9 ppm), along with estimated T1 values of each fluorine resonance. Observed reaction trends from 19F{1H} NMR spectra (58 MHz) for two representative reaction species monitored via stopped-flow (purple circle), continuous-flow (pink diamonds), and reaction performed in 5 mm NMR tube (grey cross): b) aldehyde starting material (5.1) and c) imine product (5.3). d) Apparent rate constants for each component/resonance when fitted to first-order exponential. ..................................................... 228 xxxix Figure 5.4. Superimposed NMR spectra (19F{1H}, 58 MHz, normalized to noise) for an imine product resonance (δF -118.9 ppm) from the same timepoint of the reaction. Spectra showcase the relative SNR differences for data acquired with the same acquisition parameters between 5 mm NMR tube analysis (orange), stopped-flow (green), and continuous-flow (purple) analyses. ... 230 Figure 5.5. a) Reaction scheme for the activation of 5.4 (0.30 M, 1.0 eq., δF -112.5 ppm) with 5.6 (1.1 eq.) to form the corresponding acyl fluoride 5.10 (δF -101.3 ppm) in MeCN with DIPEA (1.2 eq.). b) Representative zoomed decimated stacked array of 19F{1H} NMR spectra (58 MHz) of the transformation when monitored via stopped-flow NMR. c) Reaction profile resulting from tracking each resonance with time. ........................................................................................................... 234 Figure 5.6. a) Reaction scheme for the activation of 5.4 (0.30 M, 1.0 eq., δF -112.5 ppm) to form the corresponding acyl fluoride 5.10 (δF -101.3 ppm) using PBSF (5.6, 1.1 eq.), along with estimated T1 values for the two aryl fluoride resonances. Observed reaction trends from 19F{1H} NMR spectra (58 MHz) are compared for each component monitored via stopped-flow (purple circle), continuous-flow (pink diamonds), and reaction performed in 5 mm NMR tube (grey cross): b) carboxylic acid starting material 5.4 and c) aryl fluoride of acyl fluoride product 5.10. d) Apparent rate constants for each component/resonance when fitted to first-order exponential…..................................................................................................................................................... 235 Figure 5.7. a) Summation of reaction component concentrations used for uncorrected mass balance analysis. b) Results of uncorrected mass balance with line equation for linear line of best fit displayed (line not shown) for: b) 5 mm NMR tube, c) stopped-flow, and d) continuous-flow...................................................................................................................................................... 238 xl Figure 5.8. a) Reaction scheme for the activation of 5.4 (0.30 M, δF -112.5 ppm) with 5.6 (1.1 eq.) to form the corresponding acyl fluoride 5.10 (δF -101.3 ppm) in MeCN with DIPEA (1.2 eq.). b) Observed reaction trends resulting from tracking each 19F resonance (471 MHz) of interest, with the pump turned “off” part way through the reaction course. c) Relative normalized comparisons of last point with pump “on” and first point with pump “off”. d) Uncorrected mass balance analysis as result of tracking the sum of aryl fluoride components over time. ......................................... 240 Figure 5.9. Calibration of Vapourtec SF-10 reagent pump (with THF) for stopped-flow NMR system. ........................................................................................................................................ 246 Figure 5.10. Schematic highlighting the flow NMR system with both benchtop and high-field NMR spectrometers connected in series. For the majority of this work, the high-field NMR system was taken out of the loop and not used. ...................................................................................... 249 Figure 5.11. Picture highlighting the lab space with the complete high-field and benchtop flow NMR system. For the majority of this work, the high-field NMR system was taken out of the loop and not used. ............................................................................................................................... 250 Figure 5.12. Results from application of the inversion recovery experiment for T1 estimation of the aryl fluoride resonance of 5.1 (δF -105.0 ppm, 58 MHz, 26 °C). These results are shown a) qualitatively with the resonance of interest (decimated spectra, normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values...................................................................................................................................................... 252 xli Figure 5.13. Results from application of the inversion recovery experiment for T1 estimation of the aryl fluoride resonance of 5.2 (δF -129.6 ppm, 58 MHz, 26 °C). These results are shown a) qualitatively with the resonance of interest (decimated spectra, normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values...................................................................................................................................................... 254 Figure 5.14. Results from application of the inversion recovery experiment for T1 estimation of the two aryl fluoride resonances of 5.3 (δF -110.0 and -118.9 ppm, 58 MHz, 26 °C). These results are shown a) qualitatively with the resonance of interest (decimated spectra, normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values. ......................................................................................................................................... 255 Figure 5.15. Results from application of the inversion recovery experiment for T1 estimation of the aryl fluoride resonance of 5.4 (δF -112.5 ppm, 58 MHz, 26 °C). These results are shown a) qualitatively with the resonance of interest (decimated spectra, normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values...................................................................................................................................................... 256 Figure 5.16. Results from application of the inversion recovery experiment for T1 estimation of the aryl fluoride resonance of 5.10 (δF -101.3 ppm, 58 MHz, 26 °C). These results are shown a) qualitatively with the resonance of interest (decimated spectra, normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values...................................................................................................................................................... 257 xlii Figure 5.17. a) Reaction scheme for coupling 5.1 (0.22 M, δF -105.0 ppm) and 5.2 (1.1 eq., δF -129.6 ppm) to form corresponding imine 5.3 (δF -110.0 and -118.9 ppm), along with estimated T1 values of each fluorine resonance using the inversion recovery experiment. Observed reaction trends from benchtop 19F{1H} NMR spectra (58 MHz) monitored via stopped-flow (purple circle) and continuous-flow (pink diamonds) and with the reaction performed in 5 mm NMR tube (grey cross): b) aniline starting material (5.2) and imine product (5.3). .............................................. 260 Figure 5.18. Reaction profile for imination reaction performed in 5 mm NMR tube. 4-fluoroaldehyde (5.1, δF -105.0 ppm) is displayed in red, 4-fluoroaniline (5.2, δF -129.6 ppm) in blue, and imine product (5.3) is displayed in orange and green (for resonances δF -110.0 and -118.9 ppm, respectively). .......................................................................................................... 262 Figure 5.19. Reaction profile for imination reaction monitored via stopped-flow. 4-fluoroaldehyde (5.1, δF -105.0 ppm) is displayed in red, 4-fluoroaniline (5.2, δF -129.6 ppm) in blue, and imine product (5.3) is displayed in orange and green (for resonances δF -110.0 and -118.9 ppm, respectively). ............................................................................................................................... 262 Figure 5.20. Observed reaction profile for imination reaction monitored via continuous-flow. 4-fluoroaldehyde (5.1, δF -105.0 ppm) is displayed in red, 4-fluoroaniline (5.2, δF -129.6 ppm) in blue, and imine product (5.3) is displayed in orange and green (for resonances δF -110.0 and -118.9 ppm, respectively). .......................................................................................................... 263 Figure 5.21. Reaction profile for the carboxylic acid activation with PBSF performed in 5 mm NMR tube. 4-fluorobenzoic acid (5.4, δF -112.5 ppm) is displayed in red and acyl fluoride product (5.10, δF -101.3 ppm) is displayed in blue. ................................................................................. 264 xliii Figure 5.22. Reaction profile for the carboxylic acid activation with PBSF monitored via stopped-flow. 4-fluorobenzoic acid (5.4, δF -112.5 ppm) is displayed in red and acyl fluoride product (5.10, δF -101.3 ppm) is displayed in blue. ............................................................................................ 265 Figure 5.23. Observed reaction profile for the carboxylic acid activation with PBSF monitored via continuous-flow. 4-fluorobenzoic acid (5.4, δF -112.5 ppm) is displayed in red and acyl fluoride product (5.10, δF -101.3 ppm) is displayed in blue. .................................................................... 265 Figure 5.24. a) For mass balance confirmation and to aid in intermediate identification, two summations of concentrations existed depending on if the intermediate possessed one aryl fluoride (blue) or two symmetrical aryl fluorides (red). Uncorrected mass balance for these two schemes, along with line equation for line of best fit (actual line not shown for visual clarity) for: b) 5 mm NMR tube, c) stopped-flow, and d) continuous-flow. ................................................................ 267 Figure A.1. 1D 1H NMR spectrum (300 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). ................................................................................. 296 Figure A.2. 1D 13C{1H} NMR spectrum (75 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). ............................................................ 297 Figure A.3. 1D 19F NMR spectrum (282 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). ................................................................................. 298 Figure A.4. 2D 1H-1H COSY NMR spectrum (300 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). ............................................................ 299 Figure A.5. 2D 1H-13C HSQC NMR spectrum (300/75 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). .............................................. 300 xliv Figure A.6. Expansion of the 2D 1H-13C HSQC NMR spectrum (300/75 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). ..................... 301 Figure A.7. 2D 1H-13C HMBC NMR spectrum (300/75 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). .............................................. 302 Figure A.8. Expansion of 2D 1H-13C HMBC NMR spectrum (300/75 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). .................................. 303 Figure A.9. 1D 1H NMR spectrum (400 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). ................................................................................................. 304 Figure A.10. 1D 13C{1H} NMR spectrum (101 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). ......................................................................................... 305 Figure A.11. Expansion of 1D 13C{1H} NMR spectrum (101 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). ........................................................ 306 Figure A.12. 1D 19F NMR spectrum (282 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). ................................................................................................. 307 Figure A.13. 2D 1H-1H COSY NMR spectrum (400 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). ........................................................ 308 Figure A.14. 2D 1H-13C HSQC NMR spectrum (400/101 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). ........................................................ 309 Figure A.15. Expansion of 2D 1H-13C HSQC NMR spectrum (400/101 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). ..................................... 310 Figure A.16. 2D 1H-13C HMBC NMR spectrum (400/101 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). ........................................................ 311 xlv Figure A.17. Expansion of 2D 1H-13C HMBC NMR spectrum (400/101 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). ..................................... 312 Figure A.18. 1D 1H NMR spectrum (300 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. ..................................................... 313 Figure A.19. 1D 13C{1H} NMR spectrum (101 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. ........................................ 314 Figure A.20. 1D 19F NMR spectrum (282 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. ................................................ 315 Figure A.21. 1D 19F{1H} NMR spectrum (282 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. ........................................ 316 Figure A.22. 1D 31P{1H} NMR spectrum (162 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. ........................................ 317 Figure A.23. 2D 1H-13C HMBC NMR spectrum (400/101 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. Please excuse excessive t1 noise, necessary to zoom to this level to observe some key correlations (i.e., correlations consistent with ester byproduct). ............................................................................ 318 Figure A.24. Expansion of 2D 1H-13C HMBC NMR spectrum (300/282 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. .... 319 Figure A.25. 1D 1H NMR spectrum (300 MHz, CDCl3) of reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. ..................... 320 Figure A.26. 1D 1H NMR spectrum (300 MHz, CDCl3) of dried reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. .... 321 xlvi Figure A.27. 1D 13C{1H} NMR spectrum (75 MHz, CDCl3) of dried reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. .... 322 Figure A.28. 1D 19F NMR spectrum (282 MHz, CDCl3) of reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. ..................... 323 Figure A.29. 1D 19F{1H} NMR spectrum (282 MHz, CDCl3) of reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. .... 324 Figure A.30. 1D 31P NMR spectrum (121 MHz, CDCl3) of reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. ..................... 325 Figure A.31. 2D 1H-13C HMBC NMR spectrum (300/75 MHz, CDCl3) of dried reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16...................................................................................................................................................... 326 Figure A.32. 2D 1H-19F HMBC NMR spectrum (300/282 MHz, CDCl3) of dried reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16...................................................................................................................................................... 327 Figure B.1. 1D 1H NMR spectrum (500 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole (grey arrows). ............................... 328 Figure B.2. Expansion of the 1D 1H NMR spectrum (500 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole (grey arrows). ............................ 329 Figure B.3. 1D 13C{1H} NMR spectrum (126 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole (grey arrows). ............................... 330 xlvii Figure B.4. Expansion of 1D 13C{1H} NMR spectrum (126 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole (grey arrows)...................................................................................................................................................... 331 Figure B.5. 1D 19F NMR spectrum (471 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11). ............................................................................................ 332 Figure B.6. 2D 1H-13C HSQC NMR spectrum (500/126 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with some residual imidazole (grey boxes). .................... 333 Figure B.7. Expansion of 2D 1H-13C HSQC NMR spectrum (500/126 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with some residual imidazole (grey boxes). ......................................................................................................................................... 334 Figure B.8. 2D 1H-13C HMBC NMR spectrum (500/126 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole (grey boxes). ............................. 335 Figure B.9. Expansion of 2D 1H-13C HMBC NMR spectrum (500/126 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole (grey boxes)...................................................................................................................................................... 336 Figure B.10. 2D 1H-1H COSY NMR spectrum (500 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole. ...................................................... 337 Figure B.11. Expansion of 2D 1H-1H COSY NMR spectrum (500 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole. ................... 338 Figure C.1. 1D 1H NMR spectrum (400 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). ............................................................................................................................................ 339 xlviii Figure C.2. Expansion of 1D 1H NMR spectrum (400 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). ................................................................................ 340 Figure C.3. 1D 13C{1H} NMR spectrum (101 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). ................................................................................ 341 Figure C.4. 1D 19F NMR spectrum (282 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). ............................................................................................................................................ 342 Figure C.5. 2D 1H-13C HSQC NMR spectrum (400/101 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). ................................................................................ 343 Figure C.6. Expansion of 2D 1H-13C HSQC NMR spectrum (400/101 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). ................................................................................ 344 Figure C.7. 2D 1H-13C HMBC NMR spectrum (400/101 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). ................................................................................ 345 Figure C.8. Expansion of 2D 1H-13C HMBC NMR spectrum (400/101 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). ................................................................................ 346 Figure C.9. 1D 1H NMR spectrum (600 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). ....................................................................... 347 Figure C.10. D 13C{1H} NMR spectrum (151 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). ............................................................... 348 Figure C.11. Expansion of 1D 13C{1H} NMR spectrum (151 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). .......................................... 349 Figure C.12. 1D 19F NMR spectrum (377 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). ....................................................................... 350 xlix Figure C.13. 2D 1H-1H COSY NMR spectrum (600 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). ........................................................... 351 Figure C.14. Expansion of 2D 1H-1H COSY NMR spectrum (600 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). .................................... 352 Figure C.15. 2D 1H-13C HSQC NMR spectrum (600/151 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). .......................................... 353 Figure C.16. Expansion of 2D 1H-13C HSQC NMR spectrum (600/151 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). ........... 354 Figure C.17. 2D 1H-13C HMBC NMR spectrum (600/151 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). .......................................... 355 Figure C.18. Expansion of 2D 1H-13C HMBC NMR spectrum (600/151 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). ........... 356 l List of Symbols Symbol Meaning 𝐴𝐼 Absolute integration AQ Acquisition time 𝛼 Alpha 𝜔 Angular velocity T1* Apparent spin-lattice relaxation time 𝐵! Applied radio-frequency field 𝛽 Beta 𝑀# Bulk magnetization vector 𝑀( Bulk magnetization vector projected to y-axis 𝛿 Chemical shift R2 Coefficient of determination 𝐶 Concentration Δ Difference ΔE Difference in energy Δν Difference in Larmor frequencies DR Digital resolution DW Dwell time E! Energy state one E" Energy state two 𝛼- Ernst angle li 𝐵# External magnetic field or magnetic flux density 𝑓(𝜔) Frequency domain data ν Frequency of a photon 𝛾 Gyromagnetic ratio or magnetogyric ratio R Ideal gas constant (8.314 J ∙ 𝐾.! ∙ 𝑚𝑜𝑙.!) 𝐼 Integration ν# Irradiating frequency J Joule 𝐾 Kelvin ν/ Larmor frequency 𝜏stop Longest variable time delay used 𝑀+ Longitudinal magnetization 𝑚 Magnetic or directional quantum number 𝑆 Measured NMR signal 𝑁012 Natural abundance 𝜇 Nuclear magnetic moment 𝑃 Nuclear or intrinsic angular momentum I Nuclear spin or nuclear spin angular momentum quantum number TD Number of data points 𝑛 Number of non-equivalent nuclei 𝑁3 Number of nuclei in the 𝛼 state 𝑁4 Number of nuclei in the 𝛽 state lii 𝑁 Number of nuclei responsible for resonance NS Number of scans T2* Observed spin-spin relaxation time 𝜋 Pi (3.14159265359) ℎ Planck’s constant (6.626 × 10-34 J∙s) DE Pre-scan delay 𝑃+ Projection of angular momentum vector onto the z-axis 𝜇% Projection of nuclear magnetic moment vector onto the z-axis 𝑘 Proportionality constant 𝜃 Pulse angle 𝜏& Pulse width P Purity 𝑅5(𝑋) Receptivity of “X” nucleus relative to “A” ν6-7 Reference frequency % RSD Relative standard deviation d1 Relaxation time 𝜏* Repetition time 𝜏RD Residence time J Scalar coupling constant 𝜏start Smallest variable time delay used SW Spectral width 𝑐 Speed of light (3.0 × 108 m∙s-1) liii T1 Spin-lattice or longitudinal relaxation T2 Spin-spin or transverse relaxation 𝑇"(9:#) Spin-spin relaxation contributions from magnetic field inhomogeneity 𝑇 Temperature 𝑡 Time 𝑓(𝑡) Time domain data 𝑀'( Transverse magnetization 𝜏 Variable time delay 𝜏null Variable time delay with signal intensity of zero v/v% Volume percent λ Wavelength of radiation liv List of Abbreviations Abbreviation Meaning MeCN Acetonitrile ARTSI Amplitude-corrected referencing through signal injection br s Broad singlet CDI 1,1’-Carbonyldiimidazole CPMG Carr-Purcell-Meiboom-Gill Cr(acac)3 Chromium (III) acetylacetonate Cr(dpm)3 Chromium (III) tris(dipivaloylmethane) COM Communication CRAFT Complete reduction to amplitude frequency table CCF Concentration conversion factor COSY Correlated Spectroscopy DIPEA N,N-diisopropylethylamine DPPA Dipheylphosphoryl azide d Doublet dd Doublet of doublets EI Electron ionization ERETIC Electronic reference to access in vivo concentrations ESI Electrospray ionization ETFE Ethylene tetrafluoroethylene FLIPS Faster longitudinal relaxation investigated by progressive saturation lv FT Fourier transform FID Free induction decay Gd(DO3A) Gadolinium 1,4,7-triscarboxymethyl-1,4,7,10-tetraazacyclododecane Hz Hertz HMBC Heteronuclear multiple bond correlation HSQC Heteronuclear single quantum coherence HRMS High-resolution mass spectrometry IR Infrared I.D. Inner diameter IP Internet protocol LC-NMR Liquid chromatography NMR MS Mass spectrometry m/z Mass-to-charge ratio MHz Megahertz MNova MestReNova m Meter MeOH Methanol 𝜇L Microliter 𝜇m Micrometer 𝜇s Microseconds mL Milliliter mm Millimeter lvi mM Millimolar min Minute M Molar 𝑚𝑜𝑙 Mole m Multiplet nm Nanometer NMR Nuclear magnetic resonance NOE Nuclear Overhauser effect 1D One-dimensional O.D. Outer diameter PRA Paramagnetic relaxation agent ppm Parts-per-million PBSF Perfluorobutanesulfuryl fluoride PROJECT Periodic refocusing of J evolution by coherence transfer PEEK Poly ether ketone QUANTAS Quantification by artificial signal qNMR Quantitative nuclear magnetic resonance q Quartet RF Radio frequency ROIs Regions of interest rpm Revolutions per minute s Seconds lvii sep Septet SNR Signal-to-noise ratio s Singlet DSS Sodium 2,2-dimethyl-2-silapentane-5-sulfonate SDI 1,1’-Sulfonyldiimidazole SuFEx Sulfur VI fluoride exchange T Tesla THF Tetrahydrofuran TMS Tetramethylsilane 3D Three-dimensional TOCSY Total correlation spectroscopy TEA Triethylamine 2D Two-dimensional UV-vis Ultraviolet-visible USD United States dollar VT Variable temperature lviii Acknowledgements First and foremost, I must thank my Ph.D. supervisor and mentor Dr. Jason E. Hein for all the invaluable support, mentorship, and guidance through the journey that is graduate school. I am very fortunate to have an advisor who genuinely takes interest in, and provides the space for, allowing people to follow their academic passions. I forever thank you for being such a wonderful mentor and for all your insight you have provided over the years. Additionally, I must thank my supervisory committee: Dr. Martin E. Tanner, Dr. Parisa Mehrkhodavandi, and Dr. Raymond J. Andersen. Thank you for your dedicated time and for providing invaluable guidance through the Ph.D. process. I must also thank my “NMR mentor” Dr. David J. Russell. You were instrumental in planting the “NMR bug”. You have always been a rock-solid supporter (both professionally and personally), even in my endless times of my second guessing and over worrying. You have taught me so much about NMR, and I couldn’t emphasize your impact in my growth as a scientist and communicator enough. It cannot also not be forgotten to recognize another dear friend and mentor, Dr. Sarah J. Robinson. Sarah, you showcase what it truly means to not only be a great scientist, but also to support and lift-up people around you as both a scientist and a human being. I am so fortunate to have learned so much from you - I look up to and truly appreciate all that you do. I must also thank Dr. Rushia Turner - I would never have started pursuing anything related to chemistry if it were not for you. Thank you for taking a chance on me, providing mentorship in such an impressionable time of my life, and for being the amazing person you are. I additionally must thank all my coworkers from the Hein Lab, both past and present. From post-docs, research assistants, fellow graduate students, undergraduate students, and group staff - lix you have all made an impact on the journey and I wish there was room to thank everyone by name. Particularly, I must thank Dr. Lars P. E. Yunker and Veronica Lai who helped so much with all things related to coding and directly contributed to the success of the work reported in this thesis. I must also thank Dr. Andrew J. Kukor for being right there along the entire way, from the initial UBC chemistry recruiting day. Additionally, Dr. Joshua S. Derasp, Dr. Melodie Christensen, Dr. Maddie Deem, Dr. Yusuke Sato, Dr. Junliang (Leo) Liu, Yao (Kristy) Shi, and Jiayu Zhang thank you for all the help along the way - whether it be studying for the comprehensive exam, help with some organic chemistry in the lab, or help with Python code, you all made a huge difference. I also have to thank collaborators from Genentech Inc., and particularly a huge thank you is owed to Dr. José G. Napolitano for all the endless support and NMR mentorship. I have learned so much from you, and I could not be more thankful for all our discussions over the years. Further gratitude is owed to other Genentech colleagues, including but not limited to: Dr. Kenji L. Kurita, Dr. Thomas C. Malig, Dr. Chris M. Crittenden, Dr. Jessie Ochoa, Laly Garcia, and Breanna Conklin. Dr. Pete Yehl and Dr. Francis Gosselin, thank you for making opportunities available to further learn and grow as a scientist. From the UBC Chemistry department, thank you Dr. Maria B. Ezhova and Dr. Zhicheng (Paul) Xia for help and access with our department’s NMR spectrometers. Maria, you were incredibly helpful and I can’t thank you enough for all your help, especially when it came to learning all the Bruker “tips and tricks”. I also must thank Dr. Lawrence P. McIntosh and Dr. Marco A. Ciufolini for allowing me access to their NMR spectrometers, along with Dr. Mark Okon and Dr. Fariba Saadati for assistance with these spectrometers. I could not have survived through the graduate school process without the love and support of family and friends. I am forever grateful. I must thank my Dad (Reiner Maschmeyer), my sister lx (Reneé Mondragon), my brother-in-law (Raven Mondragon), and my Omi (Renate Schakat). You all were instrumental in this process. Our time spent laughing over FaceTime and adventuring around together during visits kept me going. I must also thank friends made in Vancouver for keeping me sane through the process, and for being like a family away from home: Gabby Lombardo, Sydney Estey, JD Leaño, Houston White, Parv Subramani, and Rand Lockwood. Lastly, and most importantly, I must thank my life partner and husband, Aiden Maschmeyer-Tombs. It takes a special person to be able to stand alongside someone when they are on this wild journey. If it was not for the foundation of your support, love, understanding, and laughter, I don’t know if I could have made it through. I forever thank you from the bottom of my heart. I must also not forget the love and endless support of our special chiweenie, Sammy. lxi Dedication To my husband, family, friends, and mentors lxii Epigraph “Much Betta!” - Baga Chipz 1 Chapter 1: Introduction Many different tools are accessible to a chemist in an academic or industrial setting to help decipher different physical/structural aspects of a particular molecule. One of these tools is spectroscopy, which broadly investigates how light interacts with matter.1 A spectroscopic signal is observed as a result of some transition between quantized energy levels, to which may be assigned to a certain structural characteristic of a particular molecule.2 The focus of this dissertation is to further the practical use of a type of spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, to monitor chemical reactions real-time and in a convenient manner. For a transition between energy levels to occur using spectroscopy, the sample must be irradiated with appropriate energy to induce such transition. Mathematically, this can be explained using the Plank-Einstein relation3, shown in Equation 1.1. Here the difference in energy between two states (ΔE), energy state two (E") and energy state one (E!), is related to Planck’s constant (ℎ, 6.626 × 10-34 J∙s) and the frequency of the photon that causes the transition (ν). This equation can further be broken down by applying the relationship of ν with the speed of light (𝑐, 3.0 × 108 m∙s-1) and the wavelength of the radiation (λ): ΔE = E2 − E! = ℎν = >?λ Equation 1.1 Importantly, the use of Equation 1.1 allows for the relationship between frequency of radiation (therefore wavelength of radiation) and the energy of transition to be understood. A visual representation of the Plank-Einstein relation, and its resulting qualitative spectroscopic observation, can be found in Figure 1.1. 2 Figure 1.1. Visual representation of a) what must be mathematically satisfied using a spectroscopic technique to observe the Plank-Einstein relation between two quantized energy levels and b) what is qualitatively observed when satisfied. Figure inspired by Ref 4. Every spectroscopic technique leverages a specific wavelength of electromagnetic radiation. A representation of the electromagnetic spectrum is shown in Figure 1.2, where the spectrum is displayed divided by wavelength of radiation, and the general trends between wavelength and energy of radiation are displayed. Importantly, wavelength and energy of radiation are inversely proportional. Figure 1.2. The electromagnetic spectrum with the different electromagnetic regions specified by wavelength (in meters), along with general trends in wavelength and energy denoted across the spectrum. As the application of different wavelengths of radiation leads to excitement of different energy levels, different spectroscopic techniques can be leveraged to illuminate certain structural X-Rays Ultraviolet(UV)Visible Infrared(IR)Microwaves Radiowaves10-8 4 x 10-7 7 x 10-7 10-3 10-110-11Gamma-Rayswavelength (𝜆, m)increasing wavelengthincreasing energy 3 or physical characteristics of molecules within a sample.2 For example, infrared (IR) spectroscopy probes vibrational bond energy states with electromagnetic radiation in the 25 to 2.5 𝜇m wavelength range. This energy allows for elucidation of functional groups present in a molecule.5–8 Additionally, ultraviolet-visible (UV-vis) spectroscopy leverages radiation in the 100 to 700 nm wavelength range to probe electronic transitions that can lend to the observation of chromophores and lead to insight into the extent of a molecule’s conjugation.9–12 As a final example, radio waves are used to probe nuclear spin transitions with NMR spectroscopy in the 0.5 to 75 m range (radio frequency or RF radiation).13 Chemical environments (along with atom connectivity) can be inferred for particular nuclei present in molecules within a sample investigated using NMR.14–17 These spectroscopic techniques are commonly utilized in tandem in the process of structure elucidation as the resultant data from multiple techniques may provide a more complete “picture” of the molecule or sample at hand.2,18–20 1.1 Nuclear magnetic resonance (NMR) spectroscopy The insightful structural information obtained using NMR spectroscopy is leveraged daily by organic chemists, a consequence of much work in the development of the spectroscopic technique. Nuclear magnetic moments were first measured by Rabi et al. in 1938.21 NMR resonances were then reported for 1H nuclei (“protons”) in both solids (paraffin)22 and liquids (water)23 in the years to follow (mid-1940’s). It was only in the next decade, Varian Associates sold the first commercially available NMR instrument, the 0.7 T HR-30 (30 megahertz (MHz) NMR instrument)24 and NMR analyses became more routine with the introduction of the 1.4 T Varian A-60 NMR spectrometer (60 MHz NMR instrument) in 1961.25 Since this time, NMR spectroscopy has been developed to be one of the most powerful structure elucidation tools available to an chemist, and the significance of the development and application of this technique 4 is demonstrated by the seven Nobel Prizes won regarding NMR or magnetic resonance imaging (MRI): Isidor Isaac Rabi (Physics, 1944), Edward Mills Purcell (Physics, 1952), Felix Bloch (Physics, 1952), Richard R. Ernst (Chemistry, 1991), Kurt Wüthrich (Chemistry, 2002), Sir Peter Mansfield (Medicine, 2003), and Paul C. Lauterbur (Medicine, 2003).26 1.1.1 The basics of NMR theory and the vector model As briefly highlighted above, NMR spectroscopy irradiates a sample with RF radiation and probes the amount of energy needed for a nuclear transition. For a particular nucleus to be observable via NMR (referred to as “NMR active”), the nucleus must have a non-zero nuclear spin quantum number (I, also referred to as nuclear spin or nuclear spin angular momentum quantum number). Allowable values for nuclear spin quantum numbers are integer multiples of !", starting at zero (I = 0, !" , 1, A" , 2, …). Dipolar nuclei possess an I = !". These nuclei are said to be “spin !"” and describe the most studied nuclei in NMR for drug development and bimolecular studies,27,28 including 1H, 13C, 15N, 19F and 31P. Nuclei which possess I ≥ 1 are said to be quadrupolar. Observation of many quadrupolar nuclei in not highly symmetrical chemical environments may be difficult as quick relaxation results in broad resonances and low sensitivity.29,30 While sometimes difficult, there are examples of successful detection of quadrupolar nuclei including 14N NMR for compound characterization and monitoring a selective nitration reaction,31 35Cl NMR to quantify chloride in active pharmaceutical ingredients (APIs),32 and leveraging 79Br NMR to monitor a Menschutkin reaction.33 Nuclei with a nuclear spin quantum number of zero (I = 0) are commonly referred to as “NMR inactive” and possess an even atomic mass number and even atom number. Examples of I = 0 nuclei are 12C, 16O, 28Si and 32S. Many of these NMR inactive nuclei unfortunately are 5 common in most organic compounds in a high natural abundance (𝑁012),34 which limits the number of nuclei that can be interrogated in these systems. In an effort to help quickly identify the NMR activity of a given nucleus, trends in the atomic number, atomic mass number, and nuclear spin quantum number have been reported in relevant textbooks.2,13 These trends are included in Table 1.1. Table 1.1. Correlations between the atomic number and atomic mass number of a nucleus with its nuclear spin quantum number (I). Inspired by Ref 2 and 13. Atomic number Atomic mass number Nuclear spin quantum number (I) Even Even Zero (NMR inactive, I = 0) Even or Odd Odd Half-integer value (NMR active, example I values: 12, 32, 52, …) Odd Even Integer value (NMR active, example I values: 1, 2, 3…) NMR active nuclei possess a non-zero nuclear or intrinsic angular momentum (𝑃), both quantized and a vector quantity (possesses direction and magnitude).35 Under ambient conditions, these vectors are degenerate, randomly distributed and oriented in space. However, when exposed to an external magnetic field (𝐵#), these vectors align according to 𝐵#. The intrinsic angular momentum can be mathematically explained by Equation 1.2, where I is the nuclear spin quantum number and ℎ is Planck’s constant, allowing one to rationalize why the nuclear spin quantum must not be zero for an NMR active nucleus (if I = 0, 𝑃 = 0). 6 𝑃 = bI (I+1) h2π Equation 1.2 Additionally, a nucleus that possesses a non-zero nuclear angular momentum also possess a directly proportional nuclear magnetic moment (𝜇), classically rationalized as a charge (i.e., a nucleus) moving through space. The proportionality constant that relates the nuclear magnetic moment to the nuclear angular momentum is termed the gyromagnetic ratio (or magnetogyric ratio, 𝛾) and in lay terms represents the “size” of the nuclear spin (or magnet).34 This is a constant value for a given nuclide (nucleus with specific number of protons and neutrons) and a key component dictating the sensitivity of a nucleus for NMR detection as sensitivity is proportional to 𝛾$%.36 Mathematically, the relationship between 𝜇 and 𝑃 with the proportionality constant 𝛾 is presented in Equation 1.3. 𝜇 = 𝛾𝑃 Equation 1.3 For an NMR active nucleus exposed to an external magnetic field, the magnetic moment of the nucleus experiences a torque - resulting in the magnetic moment precessing about the axis to which 𝐵# is applied (generally by convention along the +z-axis in the Cartesian coordinate system).34 The precessional rate is referred to as the Larmor frequency (ν/) and is directly proportional to both 𝛾 and 𝐵# as described mathematically in Equation 1.4. 7 ν/ = −𝛾𝐵#2𝜋 Equation 1.4 Crucially, the ν/ of a particular nucleus is incredibly sensitive to the surrounding chemical/electronic environment, resulting in a “chemical shift” in the observed frequency of the resonance, depending on a nuclide’s surroundings. This was first reported by Proctor and Yu in 1950 when two 14N resonances for NH4NO3 were observed dependent on the concentration of MnCl2 salt.37 Also in 1950, Dickinson observed different 19F resonances for different fluorine containing species.38 Arnold et al. additionally reported the first 1H chemical shifts, observed with protons of ethanol in 1951.39 Since these initial observations in the early 1950’s, chemical shifts of nuclei have been vital to organic structure elucidation. A schematic to aid in visualizing a classical depiction of a spin !" nucleus (simple sphere) in the presence of an external magnetic field can be found in Figure 1.3. Figure 1.3. Classic schematic depiction of a “spin &'” (I = &' ) NMR active nucleus (purple sphere) exposed to an external magnetic field (𝐵!, along +z-axis). This intrinsic angular momentum vector (𝑃) and magnetic moment (𝜇) precess about the direction of 𝐵! (red arrow) at the Larmor frequency (ν𝐿) of the nucleus. Inspired by Ref 34. 8 The external applied magnetic field of an NMR spectrometer is commonly referred to with megahertz (MHz) units, defined not by the strength of the magnet in tesla (T, SI units: kg·s -2·A-1), but instead the ν/ of a 1H nucleus.34 For example, an NMR spectrometer with a 11.7 T magnetic field results in a 1H ν/of 500.1 MHz and, therefore, this is referred to as a “500 MHz NMR spectrometer” in common vernacular, regardless of the nucleus to be detected. Furthermore, an instrument with a 1.4 T external magnetic field results in a 60 MHz proton ν/ and is commonly referred to as a “60 MHz NMR spectrometer”. Additionally, it is reasonable to combine both the Plank-Einstein relation (Equation 1.1) and the equation for Larmor frequency (Equation 1.4) to understand how a “resonance” or “peak” is observed using NMR spectroscopy (Equation 1.5). To observe a peak in an NMR spectrum, the equation below (i.e., “resonance”) must be satisfied. ΔE = E2 − E! = ℎν/ = ℎ −𝛾𝐵#2𝜋 Equation 1.5 NMR spectra were initially acquired either by holding the frequency of radiation the same and changing the strength of applied magnetic field (“field sweep”) or by varying the frequency and holding the strength of the applied magnetic field constant (“frequency sweep”).25 In 1966, Ernst and Anderson reported the use of Fourier transform (FT) pulse NMR allowing for faster spectral acquisition as all resonances are observable at once and spectra could be more efficiently signal-averaged.40 Later in the decade Bruker and Varian offered commercial instruments (HA-100 and WH-90, respectively) with FT NMR capabilities.25 For the remainder of this thesis, we 9 will be referring to “NMR” as pulse FT NMR. However, in order to discuss pulse NMR with a high degree of fluency, there are a few concepts that first must be discussed. For an NMR active nucleus in the presence of an applied external field, the magnetic moment vector may take orientations that are dictated by the magnetic or directional quantum number (𝑚).4,41 This value may possess the values of I, I-1, …, -I. Based on this, one can determine the number of energy states based on the equation listed below. total number of 𝑚 states = 2I + 1 Equation 1.6 For a spin !" nucleus, one can determine that two possible 𝑚 states are possible based on Equation 1.6. Based on the allowable values (I, I-1, …, -I), these two values would be + !" and − !". For a given directional quantum number state, the nuclear magnetic moment vector (𝜇) can be projected onto the z-axis (𝜇%), considering 𝐵# is again applied along the +z-axis. To do so, the following equation can be used, where 𝑃+ represents the projection of the angular momentum vector onto the z-axis: 𝜇+ = 𝑚𝛾𝑃+ = 𝑚𝛾 ℎ2𝜋 Equation 1.7 For the spin !" nucleus, the two possible energy states are commonly referred to as 𝛼 and 𝛽 states for 𝑚 = + !" and − !" states, respectively. The 𝛼 state represents the energetically favoured 10 state for this nucleus as 𝜇% is aligned with 𝐵#.2,34 An analogous type of analysis can be performed for a “spin 1” (I = 1) nucleus. This quadrupolar nucleus has three 𝑚 states (+1, 0, −1), of which the state where 𝜇% is aligned with 𝐵# (𝑚 = +1) is the more energetically favoured state. A schematic displaying 𝜇% of both spin !" and spin 1 nuclei can be found in Figure 1.4. Figure 1.4. Schematic representations of magnetic moment vectors (purple arrows) projected onto the z-axis (𝜇𝑍, red arrows) for both spin &' and 1 (I = &' and 1) nuclei. The directional quantum number (𝑚) for each of the 𝜇𝑍 is additionally displayed. External magnetic field (𝐵0) is aligned on the +z-axis. It is now important to consider the entire ensemble of nuclei in a given NMR sample instead of just a single nucleus alone, to which can be more adequately described with a Boltzmann distribution.42 For a nucleus of spin !" (e.g.,1H) the ratio between the number of nuclei in the energetically favourable 𝛼 state (𝑁3) and energy disfavoured state 𝛽 state (𝑁4) for a particular temperature (𝑇) can be determined with the Equation 1.8, with R being the ideal gas constant (8.314 J ∙ 𝐾.! ∙ 𝑚𝑜𝑙.!) and all other variables have been previously defined. z, !! " = + "# (%)" = − "# (')(z = − "# ) $#%(z = + "# ) $#%For I = "# nuclei z, !! " = + 1" = − 1(z = − ) $#%(z = + ) $#%(z = 0 " = 0For I = 1 nuclei(z = 0 11 G+G, = 𝑒9H/JK (ΔE = >L:#"M ) Equation 1.8 Based on the Boltzmann distribution for a spin !" nucleus (Equation 1.8), one can observe that populations of nuclei exist in both the 𝛼 and 𝛽 states for a given temperature, with an excess in the more stable 𝛼 state. Therefore, a very simplified schematic demonstrating this phenomenon can be found in Figure 1.5. The individual magnetic moment vectors precess at the same angle about the z-axis in both 𝛼 and 𝛽 states, making the surface of two spherical cones with apexes at the origin of the Cartesian system. Figure 1.5. Visualization of moving from conceptualizing the magnetic moment vector of a single nucleus to the magnetic moment vectors of a simplified ensemble of spin &' nuclei. The Boltzmann distribution law (Equation 1.8) suggests for a given temperature, populations exist in both the 𝛼 and 𝛽 states, with an excess in the 𝛼 state. External magnetic field (𝐵0) is aligned on the +z-axis. !x yz, "!!x yz, "!#magnetic moment from single nucleusmagnetic moments from ensemble of nuclei 12 With these magnetic moments existing in three-dimensional (3D) space, a vector summation can be performed on all the magnetic moment vectors in the ensemble. While the simplified schematic in Figure 1.5 only shows 12 magnetic moment vectors in the ensemble, it is important that in a more realistic NMR sample, this ensemble includes many, many more individual vectors. For instance, 9 × 1018 individual molecules exist in 600 𝜇L sample of a 25 millimolar (mM) sample. As all of these vectors (in both 𝛼 and 𝛽 states) are all randomly distributed along there respective spherical cones (precessing at their ν/), vector components in the transverse (x-y) plane all sum to zero. Then as the Boltzmann distribution law states that an excess will exist in the 𝛼 state (along +z-axis), the longitudinal components along +/- z-axis for 𝛼 and 𝛽 states, respectively, can be summed. A single vector results, pointed along the +z-axis. This resulting vector is commonly referred to as the bulk magnetization vector (𝑀#).2,34 As the 𝑀# is a simpler representation of the entire ensemble of nuclei, this vector is what is commonly discussed as the vector being perturbed during a pulse NMR experiment. 13 Figure 1.6. Considering the ensemble of nuclei for a spin &' nuclei, vector summation can be performed considering all x, y, and z components. The randomly distributed transverse (x-y plane) components cancel and only the bulk magnetization vector (𝑀!) along the +z-axis results of when performing a vector summation of the entire ensemble. This is a result of Boltzmann distribution law states that more nuclei will be orientated in the energy favourable 𝛼 state for a given temperature. External magnetic field (𝐵0) is aligned on the +z-axis. Inspired by Ref 34. 1.1.2 Pulse NMR spectroscopy With 𝑀# introduced, pulse NMR can be discussed. Elements of this section have been well discussed in multiple textbooks highlighting the fundamentals of FT pulse NMR.2,4,34,43 There are additionally numerous resources that now account for the now hundreds of one-dimensional (1D), two-dimensional (2D), and even 3D pulse NMR experiments that exist and are regularly used by scientists on a daily basis.44–46 Nonetheless, for ease of discussion in later chapters, a simple 1D pulse sequence (only single channel, no decoupling) will be reviewed here. While simple, this is a representative pulse sequence that results in a proton spectrum, something acquired by organic chemists on an almost daily basis. This pulse sequence mirrors 1D experiments commonly applied !x yz, "!#!x yz, "!#$"x yz, "!$"magnetic moments from ensemble of nucleimagnetic moments from ensemble of nuclei and associated bulk magnetization vector only bulk magnetization vector 14 with other nuclei, such as some 19F or 31P experiments. An annotated simple 1D pulse sequence is displayed in Figure 1.7. Figure 1.7. Simple pulse sequence (single channel, no decoupling) for a 1D NMR experiment. This pulse sequence is annotated with a relaxation time (d1), pulse width (𝜏-), and acquisition time (AQ) resulting in acquisition of a free induction decay (FID). Important to note the pulse sequence is displayed with a time axis, to which elements in this theoretical pulse sequence are not drawn to scale. First and foremost, it is important to note a pulse sequence is drawn with a time axis on the x-axis, in which time zero is at the start of the pulse sequence and the timings of the other pulse sequence elements are specified. In the first part of the pulse program showcased in Figure 1.7, a relaxation time (d1) is supplied. During this time nothing is physically being done to the sample. Rather this time allows for the magnetic moments to align with 𝐵#. In a future section (Section 1.1.3) “relaxation” will be discussed and the importance of this time will be highlighted. In short, when spins are exposed to an 𝐵# there is a certain time required for the spins to align with the magnetic field (referred to as a sample building-up magnetization or polarization). Additionally, !!d1AQtimefree induction decay (FID) 15 after an RF pulse is supplied to the sample there will be a time required for spins to relax back to their equilibrium state. This relaxation time (d1), therefore, allows for this necessary polarization to be accumulated prior to the pulse-acquire experiment.4,40,47 The next element of the generic pulse sequence shown in Figure 1.7 is the RF excitation pulse. This is generally displayed as a rectangular box along the time axis for a square pulse (could be another shape if a shaped pulse or gradient is applied). Prior to discussing the RF pulse further, it is best to transition from the laboratory frame to the rotating frame of reference. To this point, we have imagined our x, y, z coordinate system to be static, in an absolute sense (i.e., the laboratory frame). For the following discussion it will be easiest to introduce the rotating frame, in which this coordinate system is rotating at either the Larmor frequency (ν/) of some resonance or the irradiating frequency (ν#). When this transition to the rotating frame has been made the x, y, z coordinate system is denoted as the x’, y’, z’ coordinate system.34 In the rotating frame, we can now discuss the excitation pulse with a bit more detail. By convention the transmitter coil is placed on the x’-axis of the coordinate system, and it is through this coil that an applied RF field (𝐵!) is supplied. In the pulse program, this is applied for some duration of time, referred to as the pulse width (𝜏&), and is generally on the order of microseconds (𝜇s).48 When this pulse is applied for the specified duration as noted in the pulse sequence, 𝑀# will be perturbed from its equilibrium state (along the z’-axis) by some angle, which is referred to as the pulse angle (𝜃) in degrees. Importantly, the pulse width and pulse angle are directly proportional to one another (empirically observed later with Figure 1.11). Mathematically, these two are related by the nuclide’s 𝛾 and the strength applied field (𝐵!) with the RF pulse (Equation 1.9). 16 𝜃 = 𝛾𝐵!𝜏& Equation 1.9 While the transmitter coil is by convention on the x’-axis, a receiver coil is by convention placed on the y’-axis. The placement of this receiver results in only transverse (x’-y’) magnetization (i.e., only transverse components of the 𝑀# vector, 𝑀'() being detected during data acquisition of a pulse NMR experiment.34 A simplified schematic demonstrating the perturbation of 𝑀# with a RF pulse applied from the x’-axis (along with locations of transmitter/receiver coils) can be found in Figure 1.8. Figure 1.8. Schematic representing the perturbation of a bulk magnetization vector (𝑀!) with a RF pulse of 𝜃 degrees applied from an applied field (𝐵&) and transmitter coil. Only transverse (x’-y’) components (𝑀.!/!) are observable by the receiver coil. Inspired by Ref 34. After the applied pulse, a pre-scan delay (DE, usually order of several 𝜇s) allows for the electronics of the instrument such that early data points are not distorted in the FID.49 After the DE, the receiver records the free induction decay (FID).40 The time to which the receiver is on, x’ y’z’, !!transmitter coil""#receiver coil "#!$!!% 17 acquiring a number of data points (TD) to characterize the FID is referred to as the acquisition time (AQ, generally on the order of a seconds). The time between data points, called the dwell time (DW), can be multiplied by the total number of TD to calculate the AQ (Equation 1.10). The DW can additionally be determined based on the spectral width (SW) of the resulting NMR spectrum, in hertz.34 AQ = DW ⋅ TD = TD2 ⋅ SW (Hz) Equation 1.10 We have established that for an NMR signal to be observed with pulse NMR methods, 𝑀# must be perturbed from its equilibrium state, aligned with the external magnetic field along the +z’-axis. This perturbation from an applied RF pulse and transmitter coil creates transverse magnetization that is then observable with a receiver coil located on the +y’-axis. After the RF pulse, and during acquisition of the FID, however, transverse magnetization (i.e., NMR signal) is lost and longitudinal magnetization is re-established. While details on these relaxation processes will again be discussed later (Section 1.1.3), the loss of transverse magnetization is a function of spin-spin (T2) relaxation whereas the re-establishment of longitudinal relaxation is a result of spin-lattice (T1) relaxation.40 Important implications of these processes, include the dominance of NMR signal at the beginning of the FID (non-zero intensity data points) and dominance of noise at later parts (data points near zero).50 An annotated experimentally acquired FID, along with these observations, can be found in Figure 1.9. With this in mind, it is generally considered a best practice to acquire FID such that unnecessary noise isn’t acquired with too long of an AQ, but also 18 not too short such that truncation artifacts are observed in the frequency-domain spectra from the full decay of sinusoids to zero not achieved during the AQ. Additionally, the selected AQ determines the smallest measurable difference in frequencies, referred to as the digital resolution (DR), which is defined as the reciprocal of the AQ.34 Figure 1.9. Annotated free induction decay (FID), highlighting decrease in observable signal over time due to relaxation processes. The FID is dominated by signal and noise in beginning and end of FID acquisition, respectively. Based on the brief mention of relaxation processes, it could be understood why an FID displays an exponential decay behaviour and the next logical consideration is the sinusoidal behaviour of a typical FID. For a sample with many resonances for the observed nucleus, the complex nature of the FID stems from this overall decay function encompassing a sinusoid for each of the resonances (or components of resonance), resulting in a complex summation/superposition of these individual function for each resonance. For a simple single resonance sample, however, the sinusoidal behaviour can most easily be rationalized by comparing the ν# and ν/in the rotating frame. Let us consider a sample with a 0.5 1.0 1.5 2.0t1 (s)-15-10-5051015Amplitude (a.u.)signal decays with time, due to relaxationnoise dominates endsignal dominates beginning 19 single resonance to be analyzed via 1H NMR, such as a sample of pure water (H2O). If acquisition parameters are selected such that ν# = ν/, no sinusoidal behaviour is apparent and only the exponential decay during the relaxation of 𝑀# back to its equilibrium position is observed. On the other hand, if ν# ≠ ν/ for this sample, then the general exponential decay behaviour will be observable in the FID and the signal will oscillate as the transverse magnetization component of 𝑀# rotate about the transverse plane at a different frequency to that of ν#. Considering the receiver to be on the +y’-axis, the maximum (largest positive) signal will be achieved when the transverse components pass the +y’-axis and the minimum (largest negative) signal will be achieved when the transverse component passes the -y’-axis. Experimental FIDs acquired via 1H NMR on a sample of H2O can be found in Figure 1.10, acquired with exact same acquisition parameters but offset frequency. Figure 1.10. Experimentally acquired 1H NMR FIDs (60 MHz) of the same single component sample (water) with the same set of acquisition parameters other than offset frequency. a) When offset frequency (ν!) is equal to Larmor frequency of resonance (ν0), the resonance is said to be on-resonance. b) When ν! ≠ ν0, resonance is said to be off-resonance (above, resonance is 77.4 Hz off-resonance). 0.2 0.4 0.6 0.8 1.0t1 (s)-2000-1000010002000Amplitude (a.u.)0.2 0.4 0.6 0.8 1.0t1 (s)-2000-1000010002000Amplitude (a.u.)on-resonance off-resonancea) b) 20 Considering the behaviour of 𝑀# after an RF pulse in the rotating frame will next help us discuss the relationship between the relative signal intensity of a resonance and the relative 𝜏& (or pulse angle). With no applied RF pulse, the 𝑀# will remain aligned with 𝐵# (+z’-axis) and no transverse magnetization/NMR signal will result. If a 90° x’ pulse is applied, 𝑀# will be perturbed such that maximum positive transverse magnetization will result as 𝑀# will be aligned along the +y’-axis (no longitudinal magnetization). If the applied RF pulse is further increased to a 180° x’ pulse (𝜏& is doubled from a 90° pulse), 𝑀# will be perturbed such it aligns with the -z’-axis (only longitudinal magnetization). The lack of transverse magnetization results in no NMR signal to be observed. Further increasing the RF pulse to a 270° x’ pulse (𝜏& is triple that of a 90° pulse), perturbs 𝑀# such that it is aligned with the -y’-axis and a minimum NMR signal (maximum negative signal) is measured. A 360° +x’ pulse results in rotating 𝑀# back to its equilibrium position, along the +z’-axis with again only longitudinal magnetization existing (no transverse magnetization/signal). This results in a sinusoidal modulation of NMR signal with increasing applied RF pulse and the proper calibration is can be very important for success with some NMR experiments.51 An example array is shown in Figure 1.11. 21 Figure 1.11. Experimentally acquired 19F NMR data (trifluorobenzene, 376 MHz) highlighting modulation of resonance intensity with pulse width (𝜏-), and directly proportional pulse angle (𝜃) in a simple 1D NMR experiment. In effort to increase sensitivity of an NMR measurement and increase the signal-to-noise ratio (SNR) of a resonance, it is common to acquire signal averaged (multiple scan) data. When measuring signal-averaged data, the number of FIDs added together, or number of loops of a pulse sequence, are commonly referred to as the number of scans (NS). The relative SNR is said to increase with the √𝑁𝑆, so therefore a 4 scan experiment will have double the SNR relative to a single scan experiment.52 For a simple 1D signal-averaged experiment (say for pulse sequence displayed in Figure 1.7), the overall time between the end of a previous-pulse and the start of the next excitation pulse to be added to the previous FID is referred to as the repetition time (𝜏*).53 For our example pulse sequence, 𝜏* would include both the AQ and d1 periods and would represent the total time allowed for spins to relax between pulses (Figure 1.12). 0Pulse Width (!s)0°71421283542495663707784919810511212090°180°270°360°450°540°630°720°810°900°990°1080°1170°1260°1350°1440°1530°Pulse Angle (")Signal Intensity0 22 Figure 1.12. Expanded pulse sequence for a multi-scan (4 scan), signal-averaged experiment. Highlighted is the repetition time (𝜏1), which represents the total time between pulses (acquisition time (AQ) + relaxation time (d1)). Pulse sequence is displayed with a time axis, to which elements in this theoretical sequence are not drawn to scale. For signal averaged data, the Ernst angle (𝛼-) is used to describe the optimal pulse angle (or directly proportional 𝜏&) resulting in maximum SNR considering a specific resonance within a sample, with a particular spin-lattice relaxation time (T1), and a particular selected 𝜏*.40,54 Mathematically, the 𝛼- resulting in maximum SNR for a particular 𝜏& and T1 can be determined as per Equation 1.11: 𝛼- = 𝑐𝑜𝑠.!(𝑒.N2/K3) Equation 1.11 Once an FID is measured (and appropriate signal-averaging is complete, if desired), an FT is completed to mathematically convert the FID in the time-domain to the “NMR spectrum” in the frequency-domain. It was in 1957 that Low and Norberg suggested relationship of a spectrum resulting from an FT of an FID.55 In the following decade, Cooley and Tukey made strides to make the FT more efficient.56 The general form of the FT is displayed in Equation 1.12, with 𝑓(𝜔) 23 representing frequency-domain data, 𝑓(𝑡) representing time-domain data, 𝜔 is the angular velocity (ν ⋅ 2𝜋), and 𝑡 is time: 𝑓(𝜔) = t 𝑓(𝑡)𝑒OPQ𝑑𝑡RS.S Equation 1.12 Furthermore, an example of an experimentally acquired FID (time-domain data) and resulting NMR spectrum (frequency-domain data) after FT is shown in Figure 1.13. It is important to note that to the modern organic chemist, “NMR data” is synonymous with an NMR spectrum. Figure 1.13. Experimentally acquired 1H NMR data measured for sample of Strychnine (CDCl3, 500 MHz). The acquired time-domain data (FID) undergoes a Fourier transform (FT) to produce the associated frequency-domain data (NMR spectrum). While the output of the FT will inherently provide an NMR spectrum with frequency units (Hz or MHz) along the x-axis, the this is generally divided by a reference frequency (ν6-7) for the 0123456789f1 (1H / ppm)0100020003000Intensity (a.u.)0.5 1.0 1.5 2.0t1 (s)-10-5051015Amplitude (a.u.)0.0 . . 2.0t ( )-151015Intensity FTtime-domain data(FID)frequency-domain data(NMR spectrum) 24 particular nuclide being measured (e.g., 1H, 13C, 19F, 31P, etc.). This normalization (Equation 1.13) results in parts-per-million (ppm) units in the NMR spectrum and is referred to as the “chemical shift” (𝛿).57 𝛿 = (ν/ − ν6-7ν6-7 ) × 10T Equation 1.13 The importance of 𝛿 comes as this value is independent of magnet strength, something not the case if the absolute frequency value is reported. The specific frequency used as the reference frequency may be the operating frequency of the spectrometer or the frequency of a resonance from some specific reference compound, such as tetramethylsilane (TMS)58 or sodium 2,2-dimethyl-2-silapentane-5-sulfonate (DSS)59 for 1H NMR analyses. Over the decades, various nomenclature has been applied to compare relative chemical shifts of resonances in an NMR spectrum. These have generally been the product of different analysis techniques, such as the use of “high frequency” or “low frequency” with frequency sweep experiments60 or the use of “high field” and “low field” terms with field sweep experiments.61 Additionally, terms such as “downfield”/“upfield” and “deshielded”/“shielded” are used to make the same chemical shift comparisons.62 The wide use of terms used in these comparisons allow for easy confusion. Therefore, Figure 1.14 showcases an annotated 1H NMR spectrum of Strychnine (CDCl3, 500 MHz) with common nomenclature used to make these relative chemical shift comparisons. 25 Figure 1.14. Annotated 1H NMR spectrum of strychnine (CDCl3, 500 MHz) with common nomenclature used to compare relative chemical shifts of resonances in an NMR spectrum. Generally, for a particular resonance in an NMR spectrum, there are certain spectral attributes that are generally of highest interest to a chemist, including the chemical shift, integration, and linewidth. As an NMR spectrum originates from the directly measured FID, these attributes all have directly analogous time-domain attributes. The analogous features for chemical shift, integration, and linewidth in the frequency-domain include the frequency, amplitude (at time = 0), and decay rate, respectively, in the time-domain.63 While NMR data is most frequently analyzed in the frequency-domain, the access of this information directly in the time-domain (without subjective post-processing) has presented an interesting alternative in the recent years.64 1.1.3 Relaxation and NMR As previously mentioned, after excitation of spins with an RF pulse, the spins return (or relax) to their equilibrium energy state and orientation with the external magnetic field. Two types of relaxation exist, spin-lattice relaxation (also referred to as longitudinal or T1 relaxation) and 26 spin-spin relaxation (also referred to as transverse or T2 relaxation). These processes describe relaxation of polarization from the longitudinal and transverse perspectives, respectively. Generally, a relaxation time (units of s) is discussed to describe either the re-accumulation in longitudinal magnetization (𝑀+) for T1 relaxation or loss of transverse magnetization (𝑀'() for T2 relaxation after an RF pulse. Though, this can also be representative by relaxation rates (units of s-1) by taking the reciprocal of these values, resulting in the notations of R1 and R2 for T1 and T2 processes, respectively. In the 1940’s, Nobel Prize laureate Felix Bloch described the evolution of polarization as a function of time and these relaxation processes, referred to as the Bloch equations.23 As a result of a 90° RF pulse, the recovery of longitudinal polarization or loss of transverse polarization as a function of time in terms of T1 and T2 relaxation, respectively, is displayed in Figure 1.15. Figure 1.15. a) Spin-lattice relaxation: recovery of relative longitudinal polarization (𝑀4) of the bulk magnetization (𝑀!) as a function of time (t) and spin-lattice relaxation time (T1) after a 90° pulse. b) Spin-spin relaxation: loss of transverse magnetization (𝑀./) as a function of t and spin-spin relaxation time (T2) after a 90° pulse. Figure inspired by Ref 34. 00.20.40.60.810 1 2 3 4 5 6 7 8 9(! xy/ !0)Time (t / T2)00.20.40.60.810 1 2 3 4 5 6 7 8 9(! $/ !0)Time (t / T1)!!!" = # − %#t / T1 !$%!" = %#t / T2a) b) 27 Two practical considerations exist with these relaxation processes. For one, the relaxation times for a particular spin are specific to that spin and its specific chemical environment (i.e., T1 and/or T2 values of chemically different NMR active nuclei in a single molecule may differ). The second consideration is that T1 values are equal to or longer than T2 values.34 However, addition of paramagnetic relaxation agents (PRAs) to a sample may be leveraged to reduce relaxation times, with enhancement of relaxation due to dipolar interactions.65 Some examples of PRAs include chromium (III) acetylacetonate (Cr(acac)3),66 chromium (III) tris(dipivaloylmethane) (Cr(dpm)3),67 and gadolinium 1,4,7-triscarboxymethyl-1,4,7,10-tetraazacyclododecane (Gd(DO3A)).68 Structures for these three example PRAs can be found in Figure 1.16. Figure 1.16. Structures of some paramagnetic relaxation agents used for NMR spectroscopy. 1.1.3.1 Spin-lattice relaxation (T1) Spin-lattice relaxation, also known as longitudinal relaxation or T1, describes the relaxation or recovery of longitudinal polarization after transverse magnetization is generated with an RF pulse. A schematic illustrating this relaxation for an on-resonance spin is displayed in Figure 1.17. OOCrOOOOCr(acac)3OOCrOOOOCr(dpm)3Gd NNNNOOOOOOGd(DO3A) 28 Figure 1.17. Schematic highlighting the process of spin-lattice (or longitudinal) relaxation in the rotating frame, considering an on-resonance bulk-magnetization vector (𝑀!) directly after a 90° pulse. As 𝑀! relaxes, longitudinal polarization (𝑀45) accumulates, while transverse magnetization (𝑀.5/5 = 𝑀/5) decreases. Upon full relaxation, only longitudinal magnetization exists. Figure inspired by Ref 34. The importance of consideration of T1 values is particularly evident in quantitative NMR (qNMR) analyses, where the NMR response is assumed to be equal for all resonances of interest. For this to be true, not only is equal RF pulse excitation necessary (discussed in Section 1.1.4), sufficient time must be supplied for appropriate polarization accumulation both after spins have initially entered the 𝐵# and after an applied RF pulse, if measuring signal averaged data. If a time of 5 × T1 for a spin to exposed to 𝐵# or as a 𝜏* for signal averaged data, 99.3 % of polarization is assumed to be accumulated (Figure 1.15a) prior to RF pulse excitation. Based on this, a sample must be exposed to a 𝐵# and, if data are measured using signal averaging, a 𝜏* of 5 × T1 must be used considering the resonance with the longest T1 of interest to satisfy quantitative conditions.69,70 Many methods exist to estimate the T1 of resonances,71 and new methods continue to be published in effort to increase efficiency of such measurements, such as the Faster Longitudinal relaxation Investigated by Progressive Saturation (FLIPS) method reported by Wei et al. in 2021.72 The most common method, however, for estimating T1 values is the inversion recovery x’ y’z’, 𝐵0x’ y’z’, 𝐵0x’ y’z’, 𝐵0𝑴𝟎 𝑴𝒚′ = 𝑴𝟎𝑴𝟎𝑴𝟎𝑴𝟎 > 𝑴𝒚′ > 𝟎𝑴𝟎 > 𝑴𝒛′ > 𝟎 𝑴𝒛′ = 𝑴𝟎 𝑴𝒛′ = 𝟎 𝑴𝒚′ = 𝟎directly after a 90° pulse full longitudinal relaxation 29 experiment.73,74 The pulse sequence of this experiment (Figure 1.18a), which is generally included in the default pulse sequence library of most commercially available NMR spectrometers, leverages a 180° and 90° RF pulse, separated by a variable time delay, 𝜏. The initial 180° pulse inverts the polarization of spins along the -z-axis, the spins are allowed to relax for some time 𝜏, and then an FID is measured after a 90° pulse to sample the amount of longitudinal polarization after this time. This process is repeated, measuring FIDs with this pulse sequence with multiple 𝜏 values and ensuring that a long d1 is utilized to ensure relaxation of spins between measurement of the FID before and the next 180° pulse. After data have been acquired for multiple 𝜏 values, the signal intensity or integration for each resonance can be plotted and the T1 value can be determined based on Equation 1.14, where 𝜏null represents the 𝜏 value where signal intensity is zero. T1 = N6788UV(") Equation 1.14 The pulse sequence for the inversion recovery experiment, along with example application to estimate T1 values for the 1H NMR resonances of 2-(methoxymethyl)oxirane in a degassed sample, can be found Figure 1.18. Note the differing T1 values with each 1H resonance. 30 Figure 1.18. a) Pulse sequence for the inversion recovery experiment. b) Molecular structure of 2-(methoxymethyl)oxirane along with the estimated T1 values of 1H nuclei using the inversion recovery experiment. c) Experimental 1H NMR spectra (500 MHz, CDCl3) with increasing 𝜏 from bottom to top. d) Integration of each of the assigned resonances with various 𝜏 values, along with equation used to calculate the estimated T1 values. 1.1.3.2 Spin-spin relaxation (T2) Spin-spin relaxation, also known as transverse relaxation or T2, describes the relaxation or loss of transverse polarization after maximum transverse magnetization is generated from an RF pulse. To envision this type of relaxation properly, it is important to consider the many individual magnetic moment vectors that sum together to form the bulk magnetization vector. After a 90° pulse, these vectors are all in-phase along the +y’-axis. Then, as some vectors possess higher or lower frequencies depending on the local chemical environment experienced by each individual spin, these vectors begin to fan out over time. This fanning-out results in an overall loss in transverse magnetization.34 OOH3C H HH HH0 10 20 30 40 50 60 70 80Tau (s)-300000-200000-1000000100000200000300000Integration2.62.83.03.23.43.63.8f1 (ppm / 1H)!=30 "s !=2 s !=3.5 s !=4.5 s !=5.5 s !=6.5 s !=7.5 s !=8.5 s !=9.5 s !=10.5 s !=11.5 s !=12.5 s !=13.5 s !=14.5 s !=15.5 s !=25 s !=55 s !=95 s !=125 s !=155 s d1 !T1 = "null / ln(2) 8.0 s 8.2 s7.9 s10.4 s10.4 s19.3 s180° 90°a) b)c) d) 31 While this relaxation naturally occurs due to molecular interactions within a sample (T2), magnetic inhomogeneity introduced from the instrument contributes to this relaxation (𝑇"(9:#)). Therefore, the observed T2 (T2*) is comprised of dephasing of magnetic moment vectors with contributions from both the natural T2 and the 𝑇"(9:#) as per Equation 1.15. 1𝑇"∗ = 1𝑇" + 1𝑇"(9:#) Equation 1.15 A schematic illustrating relaxation of this transverse magnetization, considering an on-resonance NMR resonance is displayed in Figure 1.19. Figure 1.19. Schematic highlighting the process of spin-spin (or transverse) relaxation in the rotating frame, with the perspective of looking down on the transverse plane from the +z’-axis, starting with the bulk-magnetization vector (𝑀!) directly after a 90° pulse (𝑀.5/5 = 𝑀/5). As individual magnetic moment vectors start to fan out, net transverse magnetization decreases, until no transverse magnetization exists. Figure inspired by Ref 34. x’y’!!x’y’ !"!x’y’z’, ## !"! = !!!! > !"! > & !"! = &directly after a 90° pulse full transverse relaxation 32 While the impact of T1 relaxation times can be observed in signal intensities and/or integrals in the frequency-domain, the impact of T2* relaxation times is directly observable with the half-height linewidth (“linewidth”) of resonances in the frequency-domain. These two factors (T2* and linewidth) are inversely proportional, such that a resonance with a shorter T2* value is broader than a resonance with a longer T2* value. The Heisenberg uncertainty principle describes this phenomenon, as the transverse magnetization is what is directly measured with an FID.75 As an FID is a superposition of sinusoids for each line in the resulting NMR spectrum, it is easiest to visualize the relationship between T2* and linewidth with an FID and resulting NMR spectrum measured for a single component resulting in a single resonance. Therefore, Figure 1.20 visually highlights the delay in transverse magnetization (T2*) and the observed linewidth for a sample of water. Figure 1.20. Experimentally acquired 1H NMR FID (60 MHz) of a single component sample (water), highlighting the practical relationship of observed spin-spin relaxation time (T2*) and linewidths in an NMR spectrum. In effort to measure the natural T2 the contributions from magnetic field inhomogeneity must be removed. This is reasonably achieved using a spin-echo sequence, with a 180° pulse placed between the 90° pulse creating the transverse magnetization and the FID.34 The decay of 0.2 0.4 0.6 0.8 1.0 1.2t1 (s)-2000-1000010002000Amplitude (a.u.)4.604.654.704.754.804.85f1 (1H / ppm)Δ"! "# = 1% T2∗FTT2* 33 the resulting echos represents the natural T2 value for the resonance. This concept has been leveraged for the many sequences that are used to estimate T2 values, including the Carr-Purcell sequence,76 the Carr-Purcell-Meiboom-Gill (CPMG) sequence,77 and CPMG with periodic refocusing of J evolution by coherence transfer (PROJECT).78 1.1.4 Observation of different nuclei with NMR spectroscopy As previously established, an NMR active nucleus must possess nuclear spin (I ≠ 0). However, not all nuclei with nuclear spin are equally observable via NMR. Apart from the value of I, the practicality of observation is determined by both other physical properties, such as the natural abundance (𝑁012) and the gyromagnetic ratio of the nuclide.2,34 Since the early days of NMR, a linear relationship between the number of active spins in a sample and the resulting NMR response for a resonance has been understood.79,80 To enhance observation of a nucleus, therefore, the concentration of analyte can be manipulated by the experimenter themself, so long that material is available and fully soluble.81 However, there is some limitation as the number of active spins is directly influenced by 𝑁012 of a nucleus, at least in absence of isotopic enrichment. Additionally, the practicality of NMR observation for a given nucleus is dictated by 𝛾, which as previously mentioned, relates to the size of the “atomic magnetic”. The larger this ratio is (or the directly proportional 𝜇), the easier observation is of the nucleus via NMR. These physical parameters are often all considered to prepare a more holistic view on comparing the practicality of observation between two nuclei with NMR spectroscopy, with a ratio called relative receptivity.82 If the NMR receptivity of “X” nucleus is being compared to “A” an abbreviation of 𝑅5(𝑋) will be used. The equation to mathematically define this ratio is displayed in Equation 1.16, where all variables have been previously defined and the subscripts (either X or A) refer to the value for that particular nucleus. 34 𝑅5(𝑋) = v𝛾X𝛾5vA IX(IX + 1)I5(I5 + 1) 𝑁012,X𝑁012,5 Equation 1.16 Due to the relatively easy observation (high 𝑁012 and 𝛾) and presence in most organic molecules, measurement of a 1D 1H NMR spectrum is the most common NMR experiment.83 Therefore, it is common for receptivity values to be determined comparing observation of some nucleus to 1H. Additionally, as observed with Equation 1.16, when comparing nuclei with the same nuclear spin, the factor comparing values of I simplifies to one, and therefore the receptivity only depends on 𝑁012 and 𝛾. For example, when determining the receptivity of 13C relative to 1H, the 1.1 % natural abundance of 13C (compared to 99.98 % for 1H) and lower 𝛾 (L9L: = 0.25) results in a relative receptivity of 1.8 × 10-4. This low receptivity is consistent with the low sensitivity that is associated with 13C NMR relative to 1H NMR. A summary of physical parameters (including the I, 𝑁012, and 𝛾) for various nuclei likely relevant to an organic chemist are summarized in Table 1.2. 35 Table 1.2. Summary of physical properties relevant to NMR spectroscopy, including NMR activity, for various nuclei. Data adapted from Ref 2, 57, and 84. NMR active? Nuclear spin quantum number (I) Nucleus Natural abundance (𝑵𝒂𝒃𝒅, %) Resonance frequency at 2.35 T (MHz) Gyromagnetic ratio (𝜸, 107 rad s-1 T-1) Relative receptivity NMR INACTIVE 0 12C 98.9 - - - 16O 99.9 - - - 28Si 92.3 - - - 30Si 3.1 - - - 32S 94.8 - - - 34S 4.4 - - - NMR ACTIVE !" 1H 99.98 100.0 26.8 1.0 3H - 106.7 4.1 0.0 13C 1.1 25.1 6.7 1.7×10-4 15N 0.4 10.1 -2.7 3.8×10-6 19F 100.0 94.1 25.2 0.83 29Si 4.7 19.9 -5.3 3.7×10-4 31P 100.0 40.5 10.8 6.7×10-2 1 2H 0.01 15.4 4.1 1.1×10-6 14N 99.6 7.2 1.9 1.0×10-3 A" 11B 80.1 32.1 8.6 0.13 23Na 100.0 26.5 7.1 0.09 33S 0.8 7.7 2.1 1.7×10-5 35Cl 75.5 9.8 2.6 3.6 ×10-3 37Cl 24.5 8.2 2.2 6.6 ×10-4 79Br 50.5 25.1 6.7 0.04 81Br 49.5 27.0 7.2 0.05 Z" 17O 0.04 13.6 -3.6 1.1×10-5 127I 100.0 20.0 5.4 0.10 3 10B 19.9 10.7 2.9 4.0×10-3 Apart from physical properties that dictate the practicality of NMR observation with different nuclei, there are also experimental considerations, such as concentration of analyte as previously highlighted, that impact observation of certain nuclei with NMR spectroscopy. In a theory, and if modern hardware allowed, all nuclei could be observed simultaneously with a single NMR spectrum. This hypothetical spectrum would be spectrally large, with distinct spectral 36 regions for each of the NMR active nuclei in the sample (Figure 1.21). As this would be a very demanding for spectrometer’s electronics, this is in fact not possible with current capabilities. Instead, chemists leverage NMR spectrometers to probe specific frequency ranges that correlate to specific nuclei of interest. The potential nuclei that may be studied with a specific system are dictated by the electronics of the NMR probe and spectrometer system itself. Figure 1.21. Schematic displaying the frequencies of nuclei commonly studied nuclei via NMR spectroscopy. Frequencies are displayed for a 11.7 T NMR instrument with a 500.1 MHz 1H Larmor frequency (ν0). Data from Ref 84. While observation of specific frequency ranges for a given 𝐵# will result in observation of specific nuclei, the relative size of the frequency range will vary nuclei to nuclei. For instance, from practical and empirical observations, most organic chemists have learned that the chemical shift range of 1H nuclei is ~ 13 ppm while a chemical shift range of ~ 250 ppm exists for 13C NMR. This is primarily a result of the distance between the valence electrons and nucleus which has an impact on the paramagnetic contribution of magnetic shielding (or the screening constant).13,85,86 This contribution directly influences the effective magnetic field experienced by a nucleus at a given 𝐵#, therefore determining the Larmor frequency or chemical shift. Table 1.3 highlights the chemical shift ranges of some nuclei commonly studied via NMR spectroscopy. 37 Table 1.3. Chemical shift ranges of commonly studied nuclei via NMR spectroscopy. Data adapted from Ref 84. Nuclide 1H 19F 31P 13C 15N Chemical Shift Range (ppm) 13 400 430 250 1700 When measuring an NMR spectrum containing two or more resonances, considering excitation from the applied RF pulse is generally not necessary when observing nuclei with a smaller chemical shift range (e.g., 1H). However, this does become relevant when observing nuclei with a larger chemical shift range (e.g., 19F), especially for quantitative purposes. While we have seen that the absolute signal intensity of an on-resonance signal increases from a 0° pulse to a 90° pulse (Figure 1.11), the frequency (or spectral range) with maximum excitement decreases about the offset frequency. Figure 1.22 highlights this behaviour, with three pulse widths that are consistent with 90°, 60°, and 30° pulse angles. Importantly, the excitation profile for hard pulses (relatively short with larger excitation ranges) are described by a sinc(x), or sin(x)/x, function.87,88 38 Figure 1.22. Experimental 19F NMR (58 MHz) excitation profiles for pulse widths (𝜏-) of 75 𝜇s, 50 𝜇s, and 25 𝜇s, which correspond to 90°, 60°, and 30° pulse angles for the used spectrometer, respectively. Another factor influencing the observation of a resonance is the interaction through bonding electrons with nearby non-chemically or magnetically equivalent spins. This phenomenon was first reported in 1951, when the 121Sb resonance of NaSbF6 was observed to be split into several components due to the neighboring 19F nuclei.89 In that same year, mutual coupling between 19F and 31P nuclei were observed in several structures (POCl2F, POClF2 and CH3OPF2)90 and coupling of chemically inequivalent protons was reported.91 This scalar coupling, sometimes also called spin-spin or J-coupling, results of the dependency of the frequency of a spin on the state of the nearby coupling partner.92,93 The coupling partner importantly can exist in spin states as discussed with Equation 1.5 and Figure 1.4. The difference in frequencies depending on the coupling partner is denoted as the coupling constant (J) and is reported in Hz. Scalar coupling is a) 90° pulse (!! = 75 "s)-40-30-20-10010203040Distance off-resonance (kHz)02Intensity-40-30-20-10010203040Distance off-resonance (kHz)02Intensity-40-30-20-10010203040Distance off-resonance (kHz)02Intensityb) 60° pulse (!! = 50 "s)c) 30° pulse (!! = 25 "s)(a.u.)(a.u.)(a.u.) 39 commonly observed between chemically inequivalent spins separated by two or three bonds and is referred to geminal or vicinal coupling, respectively.94 Coupling constants are important to structure determination as they can further provide insight into conformation of structures (through angles of substituents or hyperconjugation)95–97 and has even been used to measure aromaticity.98 If the ratio of the difference in coupling partner Larmor frequencies (Δν) to coupling constant is 6 or greater (Δν/J ≥ 6), and if symmetry exists about the midpoint of the multiplet, the system is said to be “first-order”.99 If this is achieved, the multiplicity, or number of lines that a resonance is split to depending on the coupling partner, and relative intensity of each of the components can be easily predicted. The multiplicity can be predicted with Equation 1.17, where 𝑛 represents the number of non-equivalent nuclei and I represents the nuclear spin quantum number of the coupling nucleus: 𝑚𝑢𝑙𝑡𝑖𝑝𝑙𝑖𝑐𝑖𝑡𝑦 = 2𝑛I + 1 Equation 1.17 Additionally, Pascal’s triangle can be used to predict the relative intensities of the multiplet components for a nucleus coupled to a spin !" nucleus.100 As the ratio of Δν/J decreases just below 6 (still near 6) a coupling system is said to be “pseudo-first order”. Under these conditions the predictions highlighted above become less reliable.101,102 For example, if two doublet resonances (each resonance split to two lines) are under these conditions, the doublet components of each resonance closest to the doublet of the coupling partner may be of higher intensity than the other doublet component (not 1:1 as predicted with Pascal’s triangle). As Δν/J further decreases such that it is well below 6, coupling patterns become 40 inconsistent with the predictions highlighted above and second-order coupling effects are said to dominate.2 While the scalar coupling in 1D NMR spectra can provide valuable structural information regarding nearby nuclei, the importance of scalar coupling is further emphasized as it provides the foundation for pulse sequences of the most commonly utilized 2D NMR experiments for structure elucidation: heteronuclear single quantum coherence (HSQC),103 correlated spectroscopy (COSY),104 heteronuclear multiple bond correlation (HMBC),105 and total correlation spectroscopy (TOCSY).106 However, dispersion of signal into multiplet components may be detrimental if observing nuclei with low sensitivity nuclei or if analyzing a material limited sample. Additionally, scalar coupling may introduce additional complication if the NMR spectrum is spectrally complex, such as if the spectrum has many resonances or as if there is any resonance overlap. Therefore, it is common to employ decoupling techniques to consolidate signal into a single resonance, particularly for heteronuclear coupling. This results in increasing SNR, decreasing experimental time, and visually simplifying a spectrum. This is so common that a “13C NMR spectrum” is generally a 13C NMR spectrum with 1H decoupling (13C{1H} NMR spectrum).107,108 This is achieved by supplying a continuous RF pulse to the 1H nuclei, while acquiring the 13C NMR data. The saturation of 1H nuclei rids the Boltzmann distribution of nuclei in the 𝛼 and 𝛽 states, equaling populations of 1H spins, and results in a sensitivity enhanced (and simplified) 13C NMR spectrum. Additionally, if this decoupling pulse is supplied prior to measuring the 13C NMR FID, enhancement signal enhancement of protonated carbons due to the nuclear Overhauser effect (NOE) is achieved.109–111 An example of both 13C and 13C{1H} NMR spectra of retapamulin is displayed in Figure 1.23. 41 Figure 1.23. 13C and 13C{1H} NMR spectra of retapamulin (C6D6, 150 MHz). A “carbon NMR spectrum” generally refers to a 13C{1H} NMR spectrum as the spectrum is visually simplified and has a greater SNR due to consolidation of signal and enhancement of protonated carbons due to nuclear Overhauser effect (NOE). NMR data acquired and shared by Dr. David J. Russell (Genentech, Inc.). 1.1.5 Effect of external magnetic field strength (𝑩𝟎) on NMR spectra As previously discussed in Section 1.1.1, NMR spectroscopy relies on an 𝐵# as individual magnetic moments of nuclei are otherwise randomly orientated in space. Additionally, when an NMR active nucleus is exposed to an 𝐵#, the ν/ of a nucleus is directly proportional to the 𝐵# (Equation 1.4). We have also established that the energy difference (ΔE) between energy states, to which a nucleus needs to be excited to for observation via NMR, is directly proportional to ν/ (Equation 1.5). Therefore, there is a direct relationship between the 𝐵# and ΔE. For the continuing discussion, let us again consider a spin !" nucleus. With the direct proportionality of 𝐵# and ΔE, one can suggest that as the strength of 𝐵# increases, so does the ΔE between states. Furthermore, this suggests as the stronger the 𝐵#, the more energetically favourable 42 the 𝛼 state (𝑚 = + !") and the more energy disfavourable the 𝛽 state (𝑚 = − !").2,13 Figure 1.24 graphically highlights this relationship between the 𝐵# and ΔE of 𝛼 and 𝛽 states. Figure 1.24. Relationship between the relative energies of 𝛼 and 𝛽 states (𝑚 = + &' and − &', respectively) for a spin &' nucleus and the strength of the external magnetic field (𝐵!) supplied by the NMR instrument. Importantly, as strength of 𝐵! increases, so does the energy difference between 𝛼 and 𝛽 states (𝐵&&ΔE& < 𝐵'&ΔE'). Inspired by Ref 13. It is next important to consider the impact on the Boltzmann distribution of spins (Equation 1.8) as the ΔE of energy states changes with 𝐵#. Practically speaking, as the 𝛼 becomes more energetically favourable with increasing 𝐵#, a larger number of nuclei exist in this state and are available to be excited with the RF pulse.112 Overall, this results in an increase in sensitivity with an increase in 𝐵#. Figure 1.25 highlights this relationship of sensitivity and 𝐵# experimentally, with 1H NMR spectra of the same sample of strychnine but measured at different magnetic fields, from 1.4 – 20.0 T (60 – 850 MHz). ! = − !" (#)! = + !" (&)E = 0 ΔE!+#ΔE"+! +"E 43 Figure 1.25. 1H NMR spectra of the same sample of strychnine (CDCl3) acquired with the same acquisition parameters on multiple NMR spectrometers with varying magnetic field strengths (60 – 850 MHz). NMR data were all processed the same and normalized to noise intensity. If one were to zoom into the aromatic spectral region (𝛿H 6.5 – 8.5 ppm) in the same 1H NMR spectra displayed above, another result of varying magnetic field strength becomes apparent when spectra are no longer normalized to noise (Figure 1.26). The multiplets for resonances appear to sharpen and occupy less spectral space as the magnetic field strength increases. This is a result of the greater signal dispersion as the applied magnetic field increases.112 44 Figure 1.26. Annotated 1H NMR spectra zoomed into aromatic region (𝛿H 6.5 ppm – 8.5 ppm) of strychnine (CDCl3) acquired with multiple NMR spectrometers of varying magnetic field strengths (60 – 850 MHz). Signal dispersion increases with magnetic field strength, resulting in multiplets occupying less spectral space. Another way to visualize these signal dispersion differences is to change the units of the horizontal axis of the NMR spectra from the typical normalized frequency (in ppm) to absolute frequency (in either Hz or kHz). Despite the same acquisition parameters, and same relative spectral width (in ppm), the absolute frequency range observed when increasing external magnetic field strength also increases. In other words, a ppm is comprised of more frequencies as the instrument’s field strength increases. To this point, the same 1H NMR spectra, but with kHz units, is displayed in Figure 1.27. 45 Figure 1.27. 1H NMR spectra of the same sample of strychnine (CDCl3) acquired with the same acquisition parameters on multiple NMR spectrometers with varying magnetic field strengths (60 – 850 MHz). The horizonal scale has been changed from the typical parts-per-million (ppm) to kilohertz (kHz). Note that a spectrum of the same spectral width (in ppm) is composed of a larger frequency range as the strength of the external magnetic field strength of the instrument increases. Lastly, for a more holistic and practical view, Figure 1.28 showcases the entire spectral width (in ppm) for each of the 1H NMR spectra of strychnine measured at different magnetic fields. These data again highlight the signal dispersion differences. 0246810f1 (1H / kHz)850 MHz300 MHz400 MHz500 MHz600 MHz60 MHzNOOHHHHN 46 Figure 1.28. 1H NMR spectra of the same sample of strychnine (CDCl3) acquired with the same acquisition parameters on multiple NMR spectrometers with varying magnetic field strengths (60 – 850 MHz). The increase in both sensitivity and signal dispersion with an increase in magnetic field strength prompted steady attention in growing the capabilities of the field. While the first commercially available NMR spectrometers were equipped with electromagnets, in the early 1960’s Varian introduced the first commercially available NMR spectrometer with a high-field superconducting magnet, the HR-220 (operating frequency of 220 MHz).25 High-field superconducting magnets allowed for larger, more stable magnetic fields to be achieved.34 Since this time, a steady and continuous increase in magnetic field strength further persisted: 270 MHz spectrometer introduced in 1970 by Bruker; 360 MHz spectrometer introduced in 1973 by Bruker; 500 MHz spectrometer introduced in 1979 by Bruker; 600 MHz spectrometer introduced in 1987 0123456789f1 (1H / ppm)850 MHz300 MHz400 MHz500 MHz600 MHz60 MHzNOOHHHHN 47 by Bruker, Varian, Oxford Instruments; 750 MHz spectrometer introduced in 1992 by Bruker, Varian, Oxford Instruments; and 950 MHz spectrometer introduced in 2006 by Bruker.113 In the late 2010’s, NMR spectrometers with operating frequencies in the gigahertz (GHz) range were commercially developed by Bruker.112,114 Numerous subdisciplines in chemistry have benefited from the enhanced sensitivity and signal dispersion of NMR spectrometers that operate with higher operating frequencies (≥600 MHz), with examples of natural product quantification and characterization,115 the study of an intrinsically disordered protein (𝛼-synuclein) in-cell,116 and the observation of an inherently insensitive nuclide (17O) in a metal-organic framework via solid-state NMR.117 Starting in the 2000’s, development of low-field permanent magnet benchtop NMR systems (<100 MHz) allowed for instruments with a smaller physical footprint and significant cheaper associated costs (purchase and maintenance).118 However, the smaller magnetic fields of these systems results in a decrease in both sensitivity and signal dispersion, consistent with observations made in this section. Pictures displaying the size difference between a high-field 600 MHz system (Bruker) and a low-field benchtop NMR system (Nanalysis Scientific Corp.) can be found in Figure 1.29. In the picture note how the high-field system is large such that an experimenter must travel up steps to enter a sample for analysis while the benchtop NMR system can be conveniently placed on a benchtop near active chemistry. 48 Figure 1.29. Comparison of a) high-field 600 MHz NMR spectrometer (Bruker, located at Genentech Inc.) and b) benchtop NMR spectrometer designated with arrow (Nanalysis Scientific Corp., located at the University of British Columbia). While benchtop NMR may not allow for significant signal dispersion and sensitivity for some applications, such as complex natural product structure elucidation,119 these systems do allow for NMR analyses to be readily conducted in non-traditional settings in a cost-effective manner. For instance, in academic settings benchtop NMR systems can allow for undergraduate students to accumulate in-lab experience with NMR and J-coupling,120 organic synthesis,121 and quantitation of components from mixtures.122 The benefits of benchtop NMR have further been leveraged in the field of forensics science, where these systems have been shown to be suitable to differentiate fentanyl analogous123 and identify active ingredients from illegal drugs.124 Additionally, these systems have been shown to be attractive in industrial settings, with applications to reaction monitoring (allowing for insight into air sensitive reactions125 and reaction mechanism126), along with identification testing.127 a) b) 49 1.1.6 Monitoring reactions with NMR spectroscopy Monitoring the formation and consumption of chemical species through the evolution of a reaction can provide mechanistic insight that can illuminate paths to enhance safety,128–130 sustainability,131,132 and process optimization.133–135 Many spectroscopic techniques (such as UV spectroscopy applied with a chromatographic technique136,137 or IR spectroscopy134) are commonly applied. As each spectroscopic technique leverage different physical properties of analytes for detection, inherent benefits and limitations are associated with each technique.138,139 NMR spectroscopy is an attractive tool for reaction monitoring as it is nondestructive, inherently quantitative, and provides great insight into chemical structure.140 Application of NMR spectroscopy as a means of reaction monitoring can be found back in the late 1960’s, with an early example of Parker and Das Gupta monitoring the methylation of 4,4’-bipyridal (1.1) with methyl chloride (Scheme 1.1).141 Observation of the intermediate mono-methylated species (1.2) and formation the bis-methylated product (1.3) was successful via 1H NMR at 60 MHz. Since this time, methods for reaction monitoring with NMR spectroscopy has greatly developed, allowing for insight into diverse reaction systems.140 Scheme 1.1. Methylation reaction monitored by Parker and Das Gupta141 in the early history of NMR spectroscopy leveraged as a reaction monitoring tool. N NCH3Cl N N CH3CH3Cl N N CH3H3C+ Cl + 2Cl1.1 1.2 1.3 50 1.1.6.1 Reactions monitored in a standard NMR tube Arguably, the most accessible reaction monitoring technique using NMR for chemists is to monitor a reaction in-situ by adding all reagents into an NMR tube, placing the NMR tube with all reagents in the spectrometer, and periodically measuring NMR spectra.142,143 The success in reaction monitoring with this method is shown with examples of identification of reaction intermediates,144 preparation kinetic models,145 and optimization of reaction conditions.146 This technique may be particularly attractive to a chemist as the analysis is straightforward as no special hardware configuration is needed and the analyses can be conducted in regular NMR tubes, readily available in most synthetic organic chemistry lab spaces. Additionally, minimal material is needed to monitor the reactions, as typically only ~550 𝜇L of sample is needed for analyses in a typical 5 mm NMR tube. The convenience comes at a cost, however, as Foley et al. highlighted how the inherent lack of mixing with this method may not accurately represent mass transfer under “regular” synthetic conditions with stirring.143 To enhance the representative nature of the reaction trends determined via NMR with a reaction in a 5 mm NMR tube, the NMR tube may be physically removed from the spectrometer by the experimenter and physically inverted to mix. To a certain extent, this was shown to enhance the representative nature of reaction trends for heterogeneous reactions, such as the self-condensation of propionaldehyde catalyzed by L-Proline.143 Another method that may be adopted to monitor a reaction off-line with an NMR tub exists where an aliquot of some reaction in a reaction flask is periodically sampled, transferred to an NMR tube, and physically transported to an NMR for analysis. As an example, this method was applied to monitor the sulfonation of triphenylphosphine propionaldehyde via 1H and 31P{1H} NMR, to which the sample reaction was quenched prior to analysis.147 While not requiring any specialized hardware for the above analysis 51 methods, each of these methods do require human intervention which may limit the practical nature of such analyses. 1.1.6.2 In-situ stopped-flow NMR While the aforementioned techniques involve NMR analysis of a static sample in an NMR tube, in-situ flow NMR techniques for reaction monitoring also exist. In the 1970’s “stopped-flow” techniques were introduced, where reagents are injected into the NMR, travel through a mixing chamber, and enter the NMR probe. Then spectral measurement is completed on a static solution once flow is halted. After analysis, reaction solutions are not re-circulated, rather collected in a stop syringe or some waste stream. Figure 1.30 highlights a schematic example of an in-situ stopped-flow NMR system. This was first described by Sudmeier and Pesek who leveraged 35Cl NMR to monitor the reaction of mercury(II) bovine serum albumin with various ligands.148 Shortly thereafter, Grimaldi et al. applied a stopped-flow NMR system to monitor the displacement of ammonia (NH3) ligand in Ni(NH3)(H2O)52+ with water in acidic conditions.149 Since the initial reports, further development of these in-situ stopped-flow systems have resulted, allowing for variable temperature control,150 systems under high-pressure to be investigated,151 and variable ratios of reagents to be used.152 This technique, while requiring the specialized hardware (NMR probes, syringes, pumps, etc.), has advantages of allowing observation of relatively fast reactions with half-lives of ~ 0.05 s or greater.140 Recent examples of the technique in the last few years include a report by García-Domínguez et al. on the kinetics of sodium iodide mediated alkene difluorocycloproponation using trifluoromethyltrimethylsilane153 and an investigation by Wei et al. on the base catalyzed protodeboronation of pentafluorophenyl boronic acid.152 52 Figure 1.30. Schematic representation of an in-situ stopped-flow NMR system, shown to monitor hypothetical reaction “A + B”. These reagents are injected into the magnet, mixed, and NMR data are measured after the stop syringe is filled, stops the flow, and triggers data acquisition. 1.1.6.3 Rapid injection NMR While, in-situ stopped-flow techniques inject solutions of reagents into an NMR, travel through a mixing chamber, and then enter the NMR probe for analysis, rapid injection NMR directly injects a reagent to a solution of reagent(s) already in the NMR probe for in-situ analysis.154 Advantages to this technique include the ability to add reagent to an ongoing reaction and analyze reactions at a large range of temperatures.140 As an example, Jones et al. applied this technique to study the difference in reactivity between aggregates of n-butyl lithium at low temperatures (-135 °C).155 Apart from the apparatus required for such analyses, limitations arise in that only one reagent can be injected and the apparatus must be removed from the NMR between analyses to replenish fresh reagent solution in the NMR probe to which reagent will be inject NMRMIXERPROBESTOP(TRIGGERS ACQUISITION)SYRINGE WITH “A”SYRINGE WITH “B”“STOP” SYRINGE 53 into.140 A simple schematic of a rapid injection NMR system for reaction monitoring is shown in Figure 1.31. Figure 1.31. Schematic representation of a rapid injection NMR system to monitor hypothetical reaction “A + B”. In this system as shown, reagent “B” is injected into a solution of reagent “A” that is already within the NMR spectrometer. 1.1.6.4 In-situ continuous-flow NMR Despite the first report of measuring NMR spectra on actively flowing solutions in 1951,156 it wasn’t until 1973 that Fyfe et al. first reported measuring collecting in-situ NMR data on an actively flowing reaction mixture.157 This initial study observed the nucleophilic attack of methoxide to 3,5-dinitrocyanobenzene (1.4) to prepare the corresponding Meisenheimer complex via 1H NMR. This process was monitored by mixing the reagents and directly flowing the solution to the NMR for analysis. Therefore, influence of the change in the flow rate, and therefore the time between mixing reagents and observation, on the distribution of thermodynamic (1.5) and kinetic NMRBPROBE“A” (in NMR)SYRINGE WITH “B” 54 (1.6) products was observed. The reaction scheme for the early reaction study can be found in Scheme 1.2. Scheme 1.2. First example of monitoring a reaction under continuous-flow conditions, by Fyfe et al. in 1973.157 In 1976, Fyfe et al. further introduced an apparatus to conduct in-situ flow NMR reaction monitoring, based on the same principle as in-situ stopped-flow systems, with injecting of reagents through a mixing chamber and flowing the mixture to the NMR for analysis.158 Also similar to in-situ stopped-flow systems mentioned above, the reaction solution is not recirculated, but collected into waste. Several applications were soon reported in the literature leveraging such a system, including the addition of hydroxylamine to acetaldehyde159 and the reaction of bromine with 2,6-disubstituted phenols.160 Application of flow NMR in either instance allowed for kinetics to be studied, along with the identification and characterization of intermediates. While using such an in-situ continuous-flow system allowed for observation of chemical species with a short lifetime, the large quantity of solution needed for such an analysis remained the primary disadvantage of the technique.161 Figure 1.32 showcases an example in-situ continuous-flow NMR system. 1.4 1.5 1.6O2N NO2CNO2N NO2CNO2N NO2CNOCH3ORH3CO HOCH3H 55 Figure 1.32. Schematic representation of an in-situ continuous-flow NMR system, shown to monitor hypothetical reaction A + B. Solutions of each reagent are injected into the magnet, mixed, and continuously flowed through the NMR probe (as NMR data are measured) to some site of collection. 1.1.6.5 On-line continuous-flow NMR Use of on-line flow NMR for various applications, including reaction monitoring, benefited from the attention and developments of liquid chromatography NMR (LC-NMR).162–164 For the context of reaction monitoring, on-line flow NMR involves sampling a portion of a nearby reaction in some reaction flask. Importantly, this solution can be returned to the reaction after analysis which both leverages the non-destructive nature of NMR and decreases the material needed for analysis in comparison to the analogous in-situ continuous-flow NMR method. Furthermore, a reaction is allowed to proceed under “normal” synthetic conditions (stirring, heating or cooling, addition of reagents, etc.) enhancing the representative nature of resultant reaction trends. A schematic of an example on-line continuous-flow system is displayed in Figure 1.33. NMRCOLLECTIONMIXERPROBESYRINGE WITH “A”SYRINGE WITH “B” 56 Flow cells and systems have been reported for this purpose, with recent examples compatible with most modern high-field NMR spectrometers and probes.165,166 Additionally, commercially available flow systems from instrument vendors exist on the market for both high-field (Bruker)167 and benchtop (Bruker, Magritek, and Nanalysis Scientific Corp.)167–169 NMR spectrometers. Furthermore, Saib et al. outlined important engineering considerations when designing such a flow system, including selection of materials used for transfer lines and pump to move solution.170 Figure 1.33. Schematic representation of an on-line continuous-flow NMR system, shown to monitor a hypothetical batch reaction. Reaction solution is continuously pumped from the reaction vial, flowed through the NMR for data acquisition, and circulated back to the reaction occurring in batch conditions. Importantly, NMR data measurement is conducted on an actively flowing sample. NMRPROBEREACTIONPUMP“ON”MOVING SOLUTION 57 On-line continuous-flow NMR has successfully been applied to monitor many different batch reactions with high-field NMR instrumentation, including the conversion of 𝛼-thioamides to 𝛼-thio-𝛽-chloroacrylamides with N-chlorosuccinamide171 and the study of 3-methylpentanoic acid with 2,2-dimethyl-1,3-dioxane-4,6-dione (Meldrum’s acid).172 Both studies resulted in enhanced mechanistic understanding with observation of transient intermediates and the former example was also monitored via IR spectroscopy, highlighting the ability of monitoring with multiple orthogonal techniques with such a system. As an additional example, an on-line continuous-flow was successfully applied to monitor the dissolution of hydrogen gas.173 These batch continuous-flow systems have additionally been applied with smaller magnetic field NMR spectrometers, with an example of Nordon et al. observing the esterification of crotonic acid with 2-butanol at 29 MHz.174 With the success of this technique, however, comes with the need to consider how an actively flowing a reaction sample impacts NMR data measurement. To this effect, numerous reports have documented these key considerations, with specific application to reaction monitoring.174–180 An important consideration is the impact of flow on the polarization of spins. As previously discussed (Section 1.1.3.1), spins must be in the presence of an external magnetic field for polarization to be achieved, with a time of 5 × T1 considered necessary for complete (99.3 %) polarization of spins for a resonance. Therefore, as a spin is flowed into the NMR for analysis, the spin may not exist in the magnetic field for adequate polarization to be achieved prior to measurement of the NMR spectrum.174–177,180 This is called the “in-flow” effect and is particularly the case if the T1 of the resonance is long or if the residence time of the spin within the magnetic field is short (i.e., higher flow rate is used). For reaction monitoring this is of high interest as 58 insufficient polarization will lend to underestimation of a chemical species. However, the impact of this in-flow effect can be minimized if lower flow rates are used,181 a pre-magnetization region is incorporated into the flow system,174 a paramagnetic relaxation agent is spiked into the sample,182 or a correction factor is used to compensate for such underestimations.180 It should be further noted that these effects are directly influenced by the properties of the magnet utilized by the NMR instrument, dictating the orientation and extent of a stray field that can polarize incoming spins.180,183 Furthermore, the introduction of flow to a reaction mixture being analyzed via NMR introduces “out-flow” effects, where an apparent reduction of T1 values is observed from polarized spins exiting and being constantly replenished with new spins. The apparent reduction of T1 values can allow for faster measurement of signal averaged data, and has been leveraged to more efficiently acquire NMR data on slowly relaxing nuclei.184,185 While the true T1 is physically unchanged, the apparent T1 (T1*) becomes dependent on the analyte's residence time (𝜏RD), as per Equation 1.18.186 1T1* = 1T1 + 1𝜏RD Equation 1.18 Additionally, the impact of the flow cell geometry and the utilized flow rate must be considered, as these factors directly impact the behaviour and residence time of analyte in the flow cell, influencing polarization and efficiency of the replenishment of spins.179,180 Dalitz et al. analyzed the effects using various flow rates with a cell similar to what is commonly employed with benchtop NMR systems, and observed formation of vortices at higher flow rates (above 2 59 mL/min) depending on the geometry of the flow cell.179 Hall et. al. observed mixing behaviour using an InsightMR flow system, a typical type flow design used with high-field NMR instrumentation, and observed non-plug flow behaviour visually when dye was flowed through the flow cell outside the spectrometer at a rate of 4 mL/min.180 Efficient transfer of reaction mixture both to and from the NMR for analysis is critical for robust reaction monitoring analyses, and can influence both in-flow and out-flow effects of a resonance. 1.1.6.6 On-line stopped-flow NMR An on-line stopped-flow NMR system allows for the benefits of an on-line continuous-flow system (convenient transfer of reaction solution from reaction underway under “normal” reaction conditions), but with data measurement under no flow, static conditions. This is completed by flushing fresh reaction solution into the flow cell of the NMR, halting the flow, collecting NMR data, and then restarting the flow such that the flow cell is replenished with fresh reaction solution prior to the process repeating. Flow may be started/halted by simply toggling the pump “on”/“off” or by use of hardware to halt flow within the spectrometer (e.g., a valve). Importantly, this application of this type of workflow avoids introduction of potential complications arising from measurement of NMR spectra on a moving sample (e.g., in-flow and out-flow effects, influences of eddying behaviour from flow cell geometry, etc.). A schematic representation of an on-line stopped-flow system is shown in Figure 1.34. 60 Figure 1.34. Schematic representation of an on-line stopped-flow NMR system, shown to monitor a hypothetical batch reaction. Reaction solution is pumped from the reaction vial, through the NMR, and circulated back to the reaction occurring in batch conditions. Prior to data acquisition, flow is halted (can be done by toggling “on”/“off” of pump, as shown above). After data acquisition, flow is reinitiated, and fresh reaction solution is flowed through the system. Importantly, NMR data measurement is conducted on a static sample. This was type of system, along with 31P NMR, allowed for insight into optimization of the final step of the process for the synthesis of retinoic acid, a Wittig reaction.187 Further, an on-line stopped-flow system using a benchtop NMR was leveraged to monitor the distillation of methanol, resulting in an aldehyde compound used for the synthesis of a compound under industrial development.125 While stopped-flow systems have the benefit of circumventing the impacts of flow on NMR measurements, however, the flow system must be configured in such a way to allow for analyte flow to be halted in the NMR instrument which may require additional hardware (such a valve) or some kind of scripted control (with software such as Python).125 NMRPROBEREACTIONPUMP“ON”TOGGLE PUMP “ON”/”OFF”NMRPROBEREACTIONPUMP“OFF”MOVING SOLUTIONSTATIC SOLUTION 61 1.2 Overview of thesis Traditionally using high-field NMR instrumentation, spectrometers are fixed in a dedicated lab space. Therefore, if a reaction is desired to be monitored via NMR, the reaction needs to be brought to the NMR spectrometer for analysis, where reaction conditions may need be changed to accommodate for the change and to both practically and safely allow for analysis. The smaller size of benchtop NMR instruments allow for these reaction monitoring analyses to be conducted such that the NMR spectrometer can be brought to the chemistry, having the potential to increase the practicality and representative nature of resulting data on processes ongoing in their “normal” conditions. This thesis, therefore, focuses on the use of modern benchtop NMR spectrometers for the application of reaction monitoring. Chapter 2 explores the use of on-line continuous-flow conditions with a benchtop NMR spectrometer. Particularly, the effects of flow analyte on the mixing/filling behaviours of solutions and on data acquisition parameter selection is highlighted. Chapter 3 showcases the convenient utilization of an on-line stopped-flow system with a benchtop NMR instrument for quantitative reaction monitoring. This work includes the necessary considerations for qNMR measurements and successful application in monitoring two challenging reactions via benchtop 19F NMR. Chapter 4 highlights an external referencing qNMR technique that is highly relevant for reaction monitoring analyses with benchtop NMR instrumentation. After discussion of the technique, this chapter includes practical application of the technique to a highly relevant series of transformations in the pharmaceutical industry. Finally, Chapter 5 is a study that directly compares the application of both on-line continuous- and stopped-flow monitoring techniques using a benchtop NMR and two model reaction systems. 62 Chapter 2: On-line continuous-flow benchtop NMR, exploration of acquisition parameters and considerations for reaction monitoring 2.1 Introduction The use of NMR spectroscopy for real-time reaction monitoring has the potential to address fundamental mechanistic questions and optimization challenges, particularly of relevance to the pharmaceutical industry.142 The ability to address complex structure elucidation problems in a nondestructive way is a central advantage of this technique. These factors have led to the development of flow cells and benchtop NMR systems that allow for data acquisition under conditions that are representative of a reaction vial. However, due to the smaller external magnetic fields of these systems, lower sensitivity and signal dispersion lend some chemists to consider the resultant spectra to be “lower-quality” data compared to data collected on their high-field counterparts. Data is further impacted in continuous-flow systems, where the analyte is in motion during data acquisition. For these reasons, selecting appropriate data acquisition parameters is crucial to optimizing data integrity. This study elucidates the effect of flow rate selection on mixing/filling behaviour and acquisition parameter selection on spectrum quality. Thereby, this work provides a roadmap to advancing on-line continuous-flow benchtop NMR analyses. Modern high-field NMR spectrometers are equipped with large superconducting magnets that can generate magnetic field strengths over 14 T and 1H Larmor frequencies exceeding 600 MHz. These large magnetic fields enable acquisition of spectra with well dispersed resonances and with relatively high sensitivity, even from reasonably dilute samples (see Section 1.1.5). The development and application of cryogenically cooled probes have further enhanced the sensitivity of these instruments.188,189 Another advantage is the compatibility of most modern day 63 spectrometers with nondeuterated (proteo) solvents, eliminating the requirement of deuterated solvents.190 These high-field instruments, however, incur a high purchase price (potentially over $1 million USD, depending on magnet strength and vendor), occupy a significant amount of physical lab space (roughly 3.6 m × 3.3 m minimum for a 300 MHz Varian instrument and console),191 and require costly cryogenic liquids to cool the superconducting magnet (liquid helium refills can cost over $2,000 USD and be necessary every few months, depending on the spectrometer). Limitations also arise in the context of reaction monitoring, where data acquisition is time sensitive and the reaction vial is generally in a different physical space than the NMR spectrometer. Therefore, the reaction may be performed directly inside an NMR tube, or aliquots of the reaction mixture can be taken at desired time intervals, quenched, and then analyzed. In either case, the acquired data may not be representative of actual reaction conditions as they neglect the real-time effects of heating, stirring, and/or chemistry that occurs prior to quenching.143 One approach to circumvent the limitation regarding transportation of reaction solution to an NMR spectrometer for analysis is the use of a flow cell system to flow reaction mixtures through an NMR probe while acquiring spectra.143,165,171–174,177,193 Such systems can reveal otherwise undetectable reaction intermediates and generally produce data that are representative of reaction progress. It should be noted, however, that physical parameters such as flow cell design and flow rate must be finely tuned to maintain data integrity.179,180 For instance, inconsistent mixing behaviour has been reported to cause peak tailing in spectra,139 and any alteration in magnetic field homogeneity across the sample compromises the resonance line shape.194 Along with flow cells, benchtop NMR instruments have emerged as especially versatile tools for rapid compound characterization and reaction monitoring.125,126,195–199 These instruments incorporate smaller permanent magnets, generally with magnetic fields under 2.35 T (100 MHz 64 1H Larmor frequency). Benchtop NMR spectrometers are more affordable than high-field instruments, do not require cryogenic liquids, and are easily implemented in spaces attractive for pharmaceutical industry, such as laboratory benchtop or in a fumehood.125,195 As with high-field instruments, some benchtop NMR spectrometers can be equipped with static NMR tubes or flow cells. Furthermore, in addition to traditional deuterated solvent systems, some are capable of measuring data in proteo solvent systems,199 both reducing the cost of analysis and enabling reaction monitoring under more realistic reaction conditions. We note that benchtop NMR systems in synthetic laboratories are subject to environmental factors such as nearby magnetic fields, temperature fluctuations, and sources of vibration that can adversely affect data acquisition. Furthermore, more significant limitations of these systems are an overall decrease in sensitivity and signal dispersion arising from the use of smaller external magnetic fields. These limitations reduce the practicality of benchtop NMR as a structure elucidation tool for highly complex organic molecules, however, the instruments can be a powerful reaction monitoring tool when tracking well-resolved, diagnostic resonances. The motivation of this study is to increase the utility of benchtop NMR for on-line continuous-flow reaction monitoring analyses. This was particularly of interest as the effects of flow are documented to be dependent on the instrument’s magnet configuration and stray magnetic field.183 Therefore, we sought to determine the effects of physical analyte conditions and NMR data acquisition on data acquisition using a modern commercially available benchtop spectrometer (NMReady-60PRO, Nanalysis Scientific Corp.) equipped with a flow cell from the instrument’s manufacturer (1.20 mL total volume, 0.575 mL within reading frame), operating under practical organic synthesis laboratory conditions (Figure 2.1). Six flow rates ranging from 0.5 – 3.2 mL/min were selected to assess the effect of flow on the acquired signal. Where appropriate, the results 65 were contrasted with static sample conditions (0.0 mL/min). This specific flow rate range is representative of practical rates for reaction monitoring, and flow rates exceeding 3.2 mL/min generate high pressures that are incompatible with our system and were therefore excluded from study. If necessary, higher rates could be accommodated by high-pressure flow systems or by redesigning the flow system with a larger dead volume to alleviate pressure. Figure 2.1. Schematic representation of the configuration and experimental flow benchtop NMR system utilized, with arrows signifying direction of analyte flow. The hardware components consist of a benchtop NMR spectrometer (NMReady-60PRO, Nanalysis Scientific Corp.) equipped with a flow cell, peristaltic pump (SF-10 reagent pump, Vapourtec Ltd.), and a vial with analyte in an EasyMax 402 Basic Synthesis Workstation (Mettler Toledo, not shown). We first studied the flow and mixing behaviour of the on-line continuous-flow system by visually observing a solution of red dye being pumped from a reaction vial through a flow cell at the selected flow rates. This configuration is analogous to the setup in Figure 2.1, but these studies were conducted outside the spectrometer. Complementary to these visual observations, a solution of proteo methanol (MeOH, 2.1) in proteo acetonitrile (MeCN) was flowed through the flow system with a spectrometer. We monitored the time required for the methyl signal of 2.1 to appear when filling the flow cell and disappear when emptying at the various flow rates. Furthermore, we VialPumpBenchtop NMR 66 tracked changes in the apparent spin-lattice relaxation time (T1*) of the aldehydic proton resonance of benzaldehyde (2.2) in MeCN under various flow rates. Lastly, the sensitivity of the instrument was determined by calculating the SNR of the same signal (i.e., the aldehyde resonance of 2.2 in MeCN) and monitored for different analyte concentrations, analyte flow rates, and reaction vial temperatures. It is important to note that the work reported herein involved the use of a single benchtop spectrometer, flow cell, and flow system configuration. This limitation must be considered, as use of a different benchtop NMR system, flow cell (presumably with different geometry) or flow system (different lines and/or line diameter) may result in different observations, especially in terms of residence times and analyte homogeneity. NMR data acquisition parameters themselves should be translatable across NMR instruments (contingent on the instrument's hardware itself), but one should be cognizant of expected differences with use of instruments with different magnetic field strengths. 2.2 Investigation into continuous-flow conditions 2.2.1 Direct visual observation of flow/mixing behaviour To better understand the effect of flow rate on mixing behaviour of analyte in the flow cell for on-line continuous-flow analyses, a series of qualitative tests were conducted using a red dye solution and 0.5, 0.8, 1.0, 1.5, 2.2, and 3.2 mL/min flow rates. For these tests, a flow system similar to that in Figure 2.1 was configured, but without the NMR spectrometer and with the sample flowing to a waste container rather than being returned to the original vial in a closed loop system. The system was initially primed with water. Red dye was then added to the reaction vial to observe as it filled the cell (“filling”). After the system was equilibrated with the red dye solution, the input was switched to clear water and similarly observed (“emptying”). Pictures of the flow cell at 67 various filling and empty times, and various flow rates, can be found in Figure 2.2. Note the direction of flow (solution entered the bottom of the flow cell and exited the top) and the formation of local concentration gradients with flow. Figure 2.2. Mixing and flowing behaviour within an NMR flow cell demonstrated by flowing water and red dye at various flow rates (a) 0.5 mL/min, b) 1.0 mL/min, and c) 3.2 mL/min). For a given flow rate, the left panel demonstrates the process of filling the cell, whereas the right panel demonstrates emptying the cell. Direction of FlowFilling Emptying 68 Videos of the flow cell during these processes were collected. A Python script, developed by colleague Veronica Lai, was used to analyze these videos. Use of the script allowed for reported normalized pixel colour at three different regions of interest (ROIs) to be reported: near the point of sample entry to the cell (“bottom”), the center of the spectrometer coil (“middle”), and at the restriction as the sample exits (“top”). Figure 2.3 displays the filling behaviour of the red dye in these three regions for all flow rates, with time beginning as the dye entered the cell. For clarity, only the filling behaviour is discussed here; however, corresponding graphs of emptying behaviour can be found in Section 2.4.2.1.2. Filling with a flow rate of 1.5 mL/min resulted in the highest efficiency as the difference in time between dye observed at the bottom and top of the flow cell was only ~ 30 s, and the time to reach equilibrium within the cell was ~ 60 s. This flow rate exhibited behaviour similar to ideal plug flow behaviour with the relative dye concentrations in each region resulting in sharp step changes during the filling process (Figure 2.3d). 69 Figure 2.3. The relative presence of red dye in three ROIs of the flow cell (bottom, middle, and top) once the dye began to fill the flow cell for six flow rates (a) 0.5, b) 0.8, c) 1.0, d) 1.5, e) 2.2, and f) 3.2 mL/min). Importantly, the direction of flow is from bottom to top and connecting lines in graphs are for visual aid purposes only. With low flow rates, which result in the greatest SNR in subsequent analyses, the largest time differences were observed for dye to fill (or empty) each of the three regions of interest. 00.20.40.60.811.20 0.2 0.4 0.6 0.8Relative Dye IntensityTime (min)MiddleFlow Rate: 2.2 mL/minTopBottom00.20.40.60.811.20 0.2 0.4 0.6 0.8 1Relative Dye IntensityTime (min)MiddleFlow Rate: 1.5 mL/minTopBottom00.20.40.60.811.20 1 2 3Relative Dye IntensityTime (min)MiddleFlow Rate: 1.0 mL/minTopBottoma) b)c) d)00.20.40.60.811.20 1 2 3 4 5Relative Dye IntensityTime (min)BottomMiddleFlow Rate: 0.5 mL/minTop00.20.40.60.811.20 1 2 3 4Relative Dye IntensityTime (min)MiddleTopBottomFlow Rate: 0.8 mL/mine) f)00.20.40.60.811.20 0.2 0.4 0.6 0.8 1Relative Dye IntensityTime (min)MiddleFlow Rate: 3.2 mL/minTopBottom 70 Alone, 2.5 minutes were required just for the bottom of the flow cell to reach a constant dye concentration with a 0.5 mL/min flow rate. While the longer residence time may enhance polarization of spins while in the spectrometer’s reading frame, resulting in an enhanced SNR and decreasing the in-flow effects of flow NMR, these long observed long cell equilibration times may not be appropriate for reaction monitoring. These slow flow rates may be too slow to transfer short-lived reaction intermediates or products to the flow cell for analysis, suggesting NMR measurements may not truly represent contents of a reaction vial for these applications. Additionally, the concentration gradients evidenced by the nonuniformity of dye inside the cell (Figure 2.2 and Figure 2.3) could have detrimental effects on the accuracy of qNMR measurements. Although increasing the flow rate shortens the time delay between the reaction vial and spectrometer, rapid flow also promotes strong eddies and formation of local concentration gradients across the cell. This effect is best demonstrated with the 3.2 mL/min trial. As shown in both Figure 2.2 and Figure 2.3, the fastest transition is seen in the middle region of the flow cell and the slowest transition at the bottom. When measuring NMR data in these conditions, eddies and accumulated analyte at the inlet affect the total number of individual molecules and atoms within the reading frame of the instrument, therefore reduce the acquired NMR signal relative to when the cell is completely homogeneous in the solution of incoming analyte. In addition, magnetic inhomogeneity may arise from the mixing, compromising resonance lineshape and sensitivity. This eddying behaviour implies that concentration gradients in the flow cell are likely to evolve at higher flow rates, and longer equilibration times of the analyte solution may be required. These observations are consistent with vertices reported by Dalitz et al. with higher flow rates and similar flow cells.179 71 An additional source of concentration gradients and magnetic inhomogeneity are air or gas bubbles, which may be introduced when transferring the intake line from one vial to another, stirring rapidly, or if a gaseous product is formed during a chemical reaction. The effect of an air bubble on the relative concentration of dye can be observed with the 1.0 mL/min emptying trial in Section 2.4.2.1.2, Figure 2.13c. Altogether, these simple flow cell filling and emptying studies provide insight into the fluid dynamics for the specific flow cell utilized for the on-line continuous-flow system. Deeper study, similar to the report by Dalitz et al.,179 may inform how flow cell geometries compatible with the specific benchtop NMR used may be optimized to decrease turbulence for high flow rates. 2.2.2 Observation of flow behaviour via 1H NMR A key factor in the operation of flow benchtop NMR for reaction monitoring is the relationship between flow rate, analyte residence time, and flow cell filling/emptying times. To monitor the flow cell filling time, we primed the system with MeCN and observed the appearance and equilibration of the methyl proton resonance (𝛿H 3.3 ppm) of MeOH (2.1) as a 50/50 mixture of 2.1/MeCN flowed through the spectrometer. This system differed from the closed-loop setup in Figure 2.1 as the solution flowed from the reaction vial, through the spectrometer, and was collected in a separate waste container. Once the 2.1/MeCN mixture reached equilibration in the system, MeCN was flowed through the system, and the disappearance of the proton methyl resonance of 2.1 was monitored (again, with the solution collected in a separate container). In both cases, 1H NMR spectra were measured at regular time intervals after the pump was started and the 2.1/MeCN mixture (“filling”) or pure MeCN solution (“emptying”) began to flow. Representative 1H NMR spectra collected from the 0.8 mL/min filling trial, along with a plot of the relative methyl 72 resonance integration as a function of time for both filling and emptying processes, are shown in Figure 2.4. Individual graphs for all other flow rates can be found in Section 2.4.2.2.2. Figure 2.4. a) Representative stacked 1H NMR (60 MHz) spectra demonstrating the growth of the methyl resonance of 2.1 during system filling with a flow rate of 0.8 mL/min. b) Normalized 1H NMR methyl resonance (𝛿H 3.3 ppm) integration of 2.1 as function of time when filling and emptying a flow cell at 0.8 mL/min. Connecting lines in graphs are for visual aid purposes only. The fastest time for the proton methyl resonance of 2.1 to reach both a maximum and minimum relative intensity was observed at a flow rate of 3.2 mL/min (requiring 1.0 and 1.5 minutes, respectively). While this was partially surprising due to the previous visual observations of eddying and mixing behaviours at this high flow rate, it is speculated that eddies may have formed and remained constant during the experiment time, resulting in an apparent “equilibrium” resonance integration to be observed. Conversely, a 0.5 mL/min flow rate resulted in the longest times: the methyl resonance of 2.1 required 11.5 minutes to reach maximum intensity during filling and 13.6 minutes to disappear during emptying. The corresponding times for the remainder of the H OHHH2.1a) b)012345678f1 (1H / ppm)00.20.40.60.810 5 10 15 20Relative Methyl Resonance IntegrationTime (min)FillingEmptyingt=0.0 mint=7.2 minIncreasing Time≈ 73 analyzed flow rates lay between those two extremes in an exponential decay and are displayed in Figure 2.5. Figure 2.5. Time for methyl resonance of 2.1 (𝛿H 3.27 ppm) to reach maximum integration via 1H NMR with flow system initially primed with MeCN (filling) and time for 2.1 to be evacuated once MeCN was flowed back into the system (emptying) with various flow rates. Connecting lines in graphs are for visual aid purposes only. The number of variables impacting the quality of acquired spectra suggests that one single flow rate will not be ideal for all monitored reaction systems. There is an inherent trade-off between the rapid transfer of the analyte from the reaction vial to the spectrometer at high flow rates, and a reduced residence time of analyte in flow cell, which decreases accumulation of polarization of spins (i.e., increases in-flow effect174–177,180 of flow) and therefore the sensitivity of measurements. Higher flow rates also increase the potential for unpredictable mixing behaviour in the flow cell. For example, when increasing the flow rate from 1.5 mL/min to 2.2 mL/min, the time needed to fill the cell increased by 0.6 min and the time needed to empty the cell remined constant. This is contrast to the expected decrease in times needed for both filling and emptying processes when increasing the flow rate. Although this observation would not immediately be expected, it is consistent with the previous visual analysis of the eddying and mixing behaviour of 024681012140 1 2 3 4Time (min)Flow Rate (mL/min)FillingEmptying 74 the red dye. We contend that local concentration gradients are produced within the cell and that due to eddying behaviour, faster flow rates are not conducive to rapidly evacuating the higher concentration areas of a flow cell. Additionally with our 2.1/MeCN system, the time required for equilibration of the observed resonance more than doubled when the flow rate decreased from 0.8 mL/min (5.1 min) to 0.5 mL/min (11.5 min). This trend was reflected during emptying, where 6.7 min and 13.6 min were needed for the signal to disappear at 0.8 mL/min and 0.5 mL/min, respectively (Figure 2.5). This demonstrates how small changes in flow rates can therefore significantly affect the time required for analytes to reach the spectrometer. Although, when making such changes an analyst must assess whether this time frame is appropriate to monitor the reaction of interest and observe potentially short-lived reaction intermediates. 2.2.3 Determination of spin-lattice relaxation time (T1) and observed spin-lattice relaxation time (T1*) with flow The spin-lattice relaxation time (or longitudinal relaxation time) is a critical physical parameter of an NMR active nucleus as it provides insight into the time required for nuclei to become initially polarized in the presence of an applied magnetic field along with the time required for relaxation as polarization is reestablished after pulse excitation. It is important to note the dependency of T1 values on physical conditions such as analyte concentration, temperature, and strength of the external magnetic field.200,201 The true average spin-lattice relaxation time (T1) for the 1H NMR resonance of the aldehyde proton of benzaldehyde (2.2, 𝛿H 10.0 ppm) in MeCN was estimated using the inversion recovery experiment.73,74 Under our experimental conditions (0.24 M, 22.0 °C, and 60 MHz), we estimated an average T1 value of 26.3 s for this resonance. When analyte was actively flowing through the spectrometer, we determined the apparent spin-lattice 75 relaxation time (T1*) using the same method for each of the six flow rates (from 0.5 to 3.2 mL/min). The minimum T1* (0.95 s) was observed at the highest flow rate tested (3.2 mL/min). All measurements were conducted in triplicate. Representative results of the inversion recovery experiment with each flow condition are included in Section 2.4.2.3.2. Figure 2.6. a) True and apparent average spin-lattice relaxation times (T1 and T1*, respectively) for the aldehyde resonance of 2.2 (𝛿H 10.0 ppm, 60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) at various flow rates. b) Comparison of trends in estimated T1* and residence time of analyte in entire 1.20 mL flow cell at various flow rates. Connecting lines in graphs are for visual aid purposes only. Based on the decreased residence time of analyte with increased flow, it is unsurprising that the T1 of the aldehyde proton was observed to be greater than any T1* value. This can be expected, as faster flow would suggest faster loss of polarized and pulsed spins, along with faster replenishment with at least partially polarized spins. These out-flow effects180,186 have long been understood and these results are further consistent with the timings in the previous filling and emptying observations, as the T1* decreased exponentially as the flow rate of the analyte increased. In the early 1980s, Haw et al.186 elaborated on the effects of flow on an analyte's T1* and discussed HO2.2a) b)0510152025300 1 2 3 4Estimated T1or T1* (s)Flow Rate (mL/min)True T1Apparent T1 (T1*)04080120160024680 1 2 3 4Residence Time (s)EstimatedT 1*(s)Flow Rate (mL/min)Residence TimeT1* 76 on how flow may be interpreted as a relaxation mechanism. Our data (Figure 2.6b) are consistent with a correlation between an analyte's residence time and T1*. An understanding of T1 values (or T1* values, with flow) is crucial to obtaining high-quality data for qNMR studies such as reaction profiling. Per the Boltzmann distribution, quantitative data are obtained with a relaxation time of 5 × T1 (or T1*) for 99.3 % of the protons to re-equilibrate and align with the external magnetic field. With the aldehydic proton of 2.2 under static flow conditions in our system, and the estimated T1 value, this would suggest a relaxation time of 131.5 s necessary for qNMR. This relatively long time period becomes increasingly impractical under realistic reaction conditions, if signal averaging is necessary to achieve sufficient enough sensitivity for quantitative purposes (SNR of ≥150 is required to decrease uncertainty below 1 %).202 Utilizing continuous-flow with these instruments, however, resulted in lower T1* values and therefore decreased necessary relaxation times. For example, increasing the flow to 0.5 mL/min from static conditions reduces the T1* value to 5.5 s. This value translates to a quantitative relaxation time of only 27.3 s, cutting down the experimental time by approximately five times. It should be emphasized that, for a simple single channel 1D NMR experiment (such as measuring a simple 1H NMR spectrum), the time available for relaxation for signal averaged data includes both the acquisition time (AQ) and relaxation delay (d1), which are collectively known as the repetition time (𝜏*). The 𝜏* becomes increasingly more relevant to discuss than solely the d1, as smaller d1 are utilized in experiments. Additionally, it is important to note that the T1 of an analyte can also be decreased with the addition of paramagnetic relaxation agents (PRAs) to the analyte solution,65–68,182 but for the application of reaction monitoring, this may be less practical, as the addition of an additional species to the reaction vial may not allow for accurate snapshots of the reaction progress without such species. However, Bara-Estaún et al. evaluated the use of 77 different PRAs specifically for on-line continuous-flow reaction monitoring analyses and successfully applied a PRA to monitor a rhodium catalyzed hydroformylation reaction.182 2.2.4 Signal-to-noise ratio (SNR) determination with various flow rates The aldehydic proton signal (𝛿H 10.0 ppm) of 2.2 in MeCN was further monitored to determine SNR at various concentrations (0.48, 0.24, and 0.10 M) and flow rates (0.0, 0.5, 0.8, 1.0, 1.5, 2.2, and 3.2 mL/min) to better understand the overall impact of continuous-flow conditions on resultant data. To do so, benchtop 1H NMR spectra were acquired in triplicate for each concentration and flow rate combination, with two different sets of acquisition parameters (Table 2.1). One set of parameters (“slow” acquisition parameters) utilized a larger repetition time and pulse angle, whereas the other (“fast” acquisition parameters) utilized a smaller repetition time and pulse angle. It was assumed that the primary changes in observed SNR of the resonance of interest, measured with same data acquisition parameters but different flow conditions, would be a result of the differing T1* and mixing/flow behaviour of the solution inside the flow cell. Table 2.1. 1H NMR acquisition parameters utilized for SNR determination of 2.2 in MeCN. Slow acquisition parameters Fast acquisition parameters Number of transients 4 4 Acquisition time (AQ) 9.4 s 2.4 s Repetition time (𝜏*) 12.9 s 3.6 s Pulse angle 90° 60° In the absence of analyte flow (0.0 mL/min), the average SNRs achieved with slow acquisition were 81.4, 36.2, and 13.9 for 0.48, 0.24, and 0.10 M solutions, respectively. The same 78 solutions with fast acquisition and static conditions displayed average SNRs of 45.5, 22.0, and 8.19, respectively. Maximum average SNRs with slow acquisition were observed at 0.5 mL/min flow rates for all concentrations (103.6, 52.8, and 21.1 for 0.48, 0.24, and 0.10 M solutions, respectively), but with fast acquisition, this was achieved with a 0.8 mL/min flow rate for 0.48 and 0.10 M solutions (85.7 and 17.6, respectively) and 1.5 mL/min for the 0.24 M solution (42.1). The minimum average SNR value with slow acquisition was observed at 3.2 mL/min for all solutions (39.1, 21.2, and 9.18 for 0.48, 0.24, and 0.10 M solutions, respectively), and the same was observed for the 0.48 (36.8) and 0.24 M (19.7) solutions with fast acquisition. The only solution that had a differing minimum was the 0.10 M solution (8.19) with fast acquisition and that was observed with static conditions. Considering data acquired with slow and fast acquisition, the 0.48 M solution displayed the largest range between maximum and minimum values in average SNR across all flow rates (Δ64.5 and Δ48.9 for slow and fast, respectively). The 0.10 M solution displayed the smallest difference between maximum and minimum average SNR values with both slow and fast data acquisition (Δ12.0 and Δ9.38, respectively). These results in a graphical and more detailed format can be found in Figure 2.7. 79 Figure 2.7. Average 1H NMR (60 MHz, MeCN) SNR of the aldehydic resonance of 2.2 (𝛿H 10.0 ppm) at 0.10, 0.24, and 0.48 M concentrations and various flow rates. Data were collected with a) slow and b) fast acquisition parameters, per Table 2.1. Across all concentrations and flow rates analyzed, the aldehyde proton resonance of 2.2 was consistently higher in spectra acquired with slow than those of the same concentration and flow rate acquired with fast parameters. Graphs demonstrating the differences in average SNR between the two sets of acquisition parameters, for each concentration, are found in Figure 2.8. Note that these are the same data but with different graphical representation than Figure 2.7. The largest differences appeared at lower flow rates (0.0 – 0.8 mL/min), whereas at higher flow rates, the difference appeared to be less significant between the set of acquisition parameters. This suggests that a longer 𝜏* can be especially beneficial at lower flow rates and less beneficial at higher flow rates. a) b)0204060801001200 1 2 3 4Average SNRFlow Rate (mL/min)0.24 M0.10 M 0.48 M “Fast” Acquisition0204060801001200 1 2 3 4Average SNRFlow Rate (mL/min)0.48 M 0.24 M 0.10 M “Slow” Acquisition 80 Figure 2.8. Average 1H NMR (60 MHz, MeCN) SNR of the aldehyde signal of 2.2 (𝛿H 10.0 ppm) at a) 0.48 M, b) 0.24 M, and c) 0.10 M concentrations. Data were acquired with slow and fast acquisition parameters, as listed in Table 2.1. Given that higher flow rates can cause inhomogeneity across the flow cell due to the geometry of cell, it could be expected that sensitivity would be maximized under static conditions, where homogeneity and time for spins to become initially polarized is maximized. This expectation is contradicted by data across all concentrations and both sets of acquisition parameters. We contend that the combination of a large T1 (26.3 s) and comparatively short 𝜏* (12.9 s and 3.6 s for slow and fast parameters, respectively) negatively impacts SNR under static conditions. Despite the long residence time and homogeneous conditions within the flow cell, the 0204060801001200 1 2 3 4Average SNRFlow Rate (mL/min)“Slow” “Fast” a) b)0204060801001200 1 2 3 4Average SNRFlow Rate (mL/min)“Slow” “Fast” Analyte Concentration: 0.48 M05101520250 1 2 3 4Average SNRFlow Rate (mL/min)“Slow” “Fast”c)Analyte Concentration: 0.24 MAnalyte Concentration: 0.10 M 81 relatively short 𝜏* in comparison with the determined T1 value prevents the aldehyde proton magnetic moment vectors from equilibrating with the external magnetic field before being pulsed again in the signal averaged experiments. When the flow is introduced from 0.0 mL/min to a low to medium flow rate (0.5 – 1.0 mL/min), the discrepancy between the 𝜏* and T1* is reduced (T1* at 1.0 mL/min is 2.95 s, smaller than the 𝜏* for both slow and fast). At these rates, a reasonable SNR can be achieved even if the sample flow introduces some inhomogeneity. At faster flow rates (1.5 – 3.2 mL/min), the T1* value further decreases, and the analyte may not reside within the reading frame long enough to establish polarization, resulting in a lower signal. SNR therefore depends on a balance between analyte residence time, T1*, and sample homogeneity impacted by flow rate, along with the 𝜏* dictated by experimental acquisition parameters. To better visualize and analyze these results in a relative sense, Figure 2.9 displays the same previous SNR data (as in Figure 2.7 and Figure 2.8) but as a percent change in average SNR with an actively flowed sample relative to the SNR observed with static conditions. This visualization allows one to observe an increase in SNR with introduction of slow flow rates across both sets of acquisition parameters. Acquisition parameters with a slower 𝜏*, however, result in a larger relative increase in SNR at these lower flow rates. Furthermore, acquisition parameters that promote a slower 𝜏* have a greater propensity for a negative influence of flow on SNR with fast analyte flow. 82 Figure 2.9. Average 1H NMR (60 MHz, MeCN) relative percent change in SNR for the aldehyde resonance of 2.2 (𝛿H 10.0 ppm) with analyte flow compared to static sample and data collected with a) slow and b) fast acquisition parameters, per Table 2.1. Lastly, we analyzed the linearity between analyte concentration and observed SNR under the selected flow rates (Figure 2.10), though both acquisition parameter sets (slow and fast) are acknowledged not to be quantitative. However, the necessity of linearity across reasonable concentrations is imperative for NMR instruments to be utilized for qNMR.203,204 This is especially the case of qNMR analyses performed with external referencing techniques, which do not require an internal standard.204 By plotting the observed average SNR against the concentration of 2.2, we established excellent linearity with data collected with both sets of acquisition parameters at conditions of no flow and for four of the six flow rates. The coefficient of determination (R2) for the line of best fit was greater than 0.99 for 0.0, 0.5, 0.8, 1.0, and 3.2 mL/min flow rates, suggesting great linearity. For slow acquisition, however, the R2 for 1.5 and 2.2 mL/min flow rates were 0.9218 and 0.9885, respectively, and for fast acquisition the R2 values were 0.9453 and 0.9686, respectively. The poor linearity with these two flow rates, with both acquisition parameter sets, is consistent with the dye a) b)-60-40-200204060800.0 1.0 2.0 3.0 4.0Relative SNR Chenge (%) Flow Rate (mL/min)0.48 M 0.24 M 0.10 M “Slow” Acquisition-40040801201600.0 1.0 2.0 3.0 4.0Relative SNR Change (%) Flow Rate (mL/min)0.48 M 0.24 M 0.10 M “Fast” Acquisition 83 experiments displaying concentration inhomogeneity at faster rates. It is therefore surprising that linearity was achieved at our highest flow rate, 3.2 mL/min. We suggest that local gradients and eddies formed at this flow rate in the flow cell may have been constant within the data acquisition time frame, leading to an overall linear relationship between flow rate and observed SNR. Figure 2.10. Linearity of average 1H NMR (60 MHz, MeCN) SNR of the aldehyde resonance of 2.2 (𝛿H 10.0 ppm) at various concentrations. R2 values are with respect to linear trendlines not shown, and connecting lines are for visual aide purposes only: a) slow acquisition at lower flow rates (0.0 – 0.8 mL/min), b) slow acquisition at higher flow rates (1.0 – 3.2 mL/min), c) fast acquisition at lower flow rates (0.0 – 0.8 mL/min), and d) fast acquisition at higher flow rates (1.0 – 3.2 mL/min). Acquisition parameters are listed in Table 2.1. a) b)c) d)0204060801000 0.2 0.4 0.6Average SNRConcentration (M)“Slow” Acquisition1.0 - 3.2 mL/min 0204060801000 0.2 0.4 0.6Average SNRConcentration (M)“Slow” Acquisition0.0 - 0.8 mL/min 0204060800 0.2 0.4 0.6Average SNRConcentration (M)“Fast” Acquisition1.0 - 3.2 mL/min 0204060800 0.2 0.4 0.6Average SNRConcentration (M)“Fast” Acquisition0.0 - 0.8 mL/min 1.0 mL/minR² = 0.99961.5 mL/minR² = 0.92182.2 mL/minR² = 0.98853.2 mL/minR² = 0.99860.8 mL/minR² = 0.99520.5 mL/minR² = 0.99970.0 mL/minR² = 0.99820.5 mL/minR² = 0.99960.8 mL/minR² = 0.99920.0 mL/minR² = 1.00001.0 mL/minR² = 0.99881.5 mL/minR² = 0.94532.2 mL/minR² = 0.96863.2 mL/minR² = 0.9986 84 2.2.5 Signal-to-noise ratio (SNR) determination with various reaction vial temperatures The temperature of the utilized benchtop NMR’s permanent magnet is maintained at a specific and constant temperature to maintain field homogeneity, common due to the configuration of utilized magnets with majority of benchtop NMR spectrometers.205 Therefore, the sample temperature can not be manipulated. As the temperature of the magnet (32 °C) of the used benchtop NMR system was above ambient temperature, it was hypothesized that raising the analyte temperature to this level could reduce temperature gradients in the sample and thereby increasing homogeneity across the sample, leading to increased sensitivity. As with the previous SNR and flow rate analysis, the SNR was determined by monitoring aldehydic proton resonance (𝛿H 10.0 ppm) of 2.2 in MeCN (0.10 M). This concentration was particularly utilized as the previous SNR study highlighted this solution displayed the largest potential for improvement and this concentration is further representative of a realistic concentration in synthetic organic laboratories. Two flow rates (0.5 and 2.2 mL/min) allowing for relative slow and fast analyte transfer and five different reaction vial temperatures (5.0, 20.0, 35.0, 50.0, and 65.0 °C) were selected to monitor the impact of analyte temperature in the reaction vial on the observed SNR in measured NMR spectra. At each temperature and flow rate combination, benchtop 1H NMR spectra were measured in triplicate using the slow acquisition parameters (Table 2.1). The results can be found in Figure 2.11. 85 Figure 2.11. a) Average 1H NMR (60 MHz, MeCN) SNR of the aldehyde proton of 2.2 (𝛿H 10.0 ppm, 0.10 M) with varied temperatures of the reaction vial at two flow rates (0.5 and 2.2 mL/min), and b) relative change in SNR for the same signal with reaction vial at room temperature. Across all temperatures tested, the absolute average SNR was higher for samples flowing at 0.5 mL/min than those at 2.2 mL/min, although at 35.0 °C the difference in SNR between the two flow rates was small and within a standard deviation. However, larger deviations from measurement of NMR data with the reaction vial at room temperature was observed with the higher flow rate. At both high and low flow rates, a higher SNR was observed with the temperature of reaction vial between 5.0 °C and 20.0 °C. Additionally, the SNR tended to decrease as the vial temperature was elevated above the temperature of the permanent magnet (35.0, 50.0, and 65.0 °C). With the concentration of analyte, flow rates, and the experimental flow system used for this temperature based analysis, some improvements in SNR can be observed by altering the temperature of the reaction vial. Figure 2.11b displays these results as a relative percent change in average SNR with altering the reaction vial temperature, relative to the room temperature study presented previously. When the sample was flowed at 0.5 mL/min, an improved SNR was a) b)0510152025300 20 40 60 80Average SNRSample Flask Temperature (°C)0.5 mL/min2.2 mL/minObserved SNR Values-60-1040901400 20 40 60 80Relative SNR Change (%) Sample Flask Temperature (°C)0.5 mL/min2.2 mL/minRelative Change (%) in SNR 86 observed with the reaction vial at 5.0 °C (24.2) when compared with the vial at room temperature in the previous room temperature analysis (21.1). At this flow rate, the average SNR was comparable with the previous value with the reaction vial at 20.0 °C (21.1) and was lower when the reaction vial was at higher temperatures (11.4, 12.4, and 10.8 for 35.0, 50.0, and 65.0 °C, respectively). When the sample was flowed through the system at 2.2 mL/min, an increased average SNR was observed with the reaction vial at 5.0, 20.0, and 35 °C (SNR values of 18.3, 18.4, and 11.4, respectively) relative to the same average SNR analysis at room temperature (9.25). A decreased average SNR was observed with this rate and temperatures 50 °C and 65 °C (6.82 and 7.23, respectively). SNRs corresponding to temperatures below ambient (22 °C) are slightly larger than SNRs in the room temperature studies above, suggesting that the sample equilibrated to the surroundings before reaching the NMR instrument. We posit that some equilibration to the ambient temperature of the surroundings were also evident with the higher temperature solutions. However, the higher-temperature solutions resulted in lower SNRs than ambient measurements. This is likely due to elevated oxidation of 2.2 and residual temperature gradients across the sample, leading to sample inhomogeneity in the reading frame of the instrument during data acquisition. This is consistent with observations of Saib et al. who reported full equilibration of heated/cooled solutions with ambient temperature when flowing through 2 – 4 meters of tubing.170 By decreasing the length of travel between the reaction vial and the instrument, insulating the sample transfer line, or by controlling the temperature of the analyte immediately prior to entering the flow cell, a more direct observation of the effect of temperature on SNR could be made. We also note that the T1 relaxation time, discussed above, is also temperature dependent and further influences the observed SNR for a given sample. 87 2.3 Conclusion This work provides a foundational exploration of physical processes and data acquisition relevant to utilizing on-line continuous-flow conditions with a modern benchtop NMR spectrometer. Benchtop NMR spectroscopy can provide rich structural data for reaction monitoring in a representative, cost effective, and convenient way relative to conventional high-field NMR instruments. Due to the lower magnetic fields attainable in benchtop systems, however, acquisition parameters require special consideration. These factors become increasingly important in the application of real-time reaction monitoring, where short lifetimes and low concentrations of reaction intermediates tend to produce less intense NMR signals. This work highlights no adequate “one-size-fits-all” approach to acquiring the best and most useful data set for reaction or structural analysis with on-line continuous-flow benchtop NMR: flow cell geometry, flow rate, analyte concentration, temperature, and observed spin-lattice relaxation time (T1*) all affect data quality and are critical to consider. Consistent with the literature,179 the results presented in this study demonstrate how the geometry of a flow cell has the potential to lead to inhomogeneity across the reading frame of the instrument with the production of local concentration gradients, particularly at high flow rates. Furthermore, our results further demonstrate how T1 values can be manipulated with the use of continuous-flow such that a lower T1* may be observed. This decrease in T1* naturally impacts the quality and quantitative nature of acquired data and was consistent with the observation of higher SNRs with low to medium flow rates (0.5 – 1.0 mL/min). In addition, spectra acquired with acquisition parameters with a longer 𝜏* resulted in higher SNRs relative to those acquired with a shorter 𝜏* (especially with static and low flow conditions, both parameter sets non- 88 quantitative), and an overall loss in linearity with respect to analyte concentration was observed with higher flow rates. Contrary to expectation, significant improvement of SNR was not observed by altering the temperature of the analyte's reaction vial, likely due to equilibration of the solution with the ambient environment and production of temperature gradients across the instrument's reading frame. It is still believed, however, that accurately altering the analyte temperature to closely resemble the temperature of the permanent magnet would lead to optimal data acquisition for a given set of acquisition parameters and flow conditions as homogeneity across the sample could be increased. These results can easily be applied and considered to the application of reaction monitoring. For instance, as previously discussed, low flow rates (0.5 – 1.0 mL/min) and parameters that led to an overall longer experimental time resulted in the highest SNR. These flow rates and acquisition parameters may not be fast enough to transport and potentially observe a short-lived reaction intermediate, however. A higher flow rate might alleviate the transport problem and better suite acquisition parameters with a shorter 𝜏* and reduction of T1* but also further promotes solution heterogeneity within the flow cell itself. This introduced heterogeneity has the potential to decrease the overall recovered signal and also decrease the linearity of the instrument with respect to concentration. With prior knowledge of the analyte and utilized flow system, however, one can consider these competing parameters. Altogether, the results reported herein offer visibility into areas in which consideration must be provided for optimal reaction analysis with an on-line continuous-flow benchtop NMR system. It is with an investment in NMR acquisition parameters, and 89 knowledge of analyte behaviour in the flow system itself, that one can optimize the insight into a reaction system that this technique may provide. 2.4 Experimental and further data 2.4.1 General 2.4.1.1 Chemicals Acetonitrile (MeCN), methanol (2.1), and benzaldehyde (2.2) were purchased from Sigma-Aldrich. All reagents and solvents were used as received, unless otherwise stated. 2.4.1.2 NMR data collection, processing, and analysis All NMR data were collected at 60.49 MHz with a NMReady-60PRO (Nanalysis Scientific Corp.) benchtop NMR spectrometer. The instrument was equipped with a glass flow cell (Nanalysis Scientific Corp.), with a total internal volume of approximately 1.20 mL and volume of about 0.575 mL within the reading frame of the instrument. Unless otherwise stated, solutions were flowed through the flow system and spectrometer with a peristaltic pump (SF-10 reagent pump, Vapourtec Ltd.). The temperature of the reaction vial was controlled and monitored using an EasyMax 402 Basic Synthesis Workstation (Mettler Toledo). 1H NMR spectra were measured all with the same receiver gain value (11.8 dB) and all chemical shifts are reported with spectra referenced to the acetonitrile solvent peak (𝛿H 1.9 ppm). All NMR data were processed and analyzed with Mestrelab’s MestReNova (Mnova) software. Each spectrum was processed with an applied 0.5 Hz exponential apodization, manual phase correction, and zeroth order polynomial fit baseline correction. 90 2.4.2 Experimental procedures and further relevant data 2.4.2.1 Direct visual observation of flow and mixing behaviour 2.4.2.1.1 Experimental procedure A flow cell was configured on a ring stand outside of the NMR instrument, equipped with a Tacmina pump (Smoothflow, Q Series). With the flow cell and system primed with water, the flow/mixing behaviour was observed as a solution of red food dye in water was pumped through the flow cell at six flow rates (0.5, 0.8, 1.0, 1.5, 2.2, and 3.2 mL/min). Once the cell was completely full of red dye solution, water was then pumped through the cell to monitor flushing behaviour at the same flow rate used to fill the system. The entire process was filmed with a video camera, where the mixing/filling behaviour was observed and the time to fill/empty was monitored. The videos were processed using a Python script (developed by Veronica Lai) allowing for relative dye presence to be monitored over time in three different regions of the flow cell (Figure 2.12). Figure 2.12. Zoomed in picture to the utilized flow cell, with reference to the specified ROIs used in the applied Python script to monitor relative red food dye intensity in “top”, “middle”, and “bottom” regions with time. Reference of ROIsDirection of Flow 91 2.4.2.1.2 Further data relevant to section Data further relevant to the observation of emptying and mixing behaviour with red food dye within the utilized NMR flow cell with various flow rates can be found below (Figure 2.13). Figure 2.13. Relative decrease in dye presence over time (at top, middle, and bottom of cell) while emptying the flow cell at different flow rates. Important to note, the inlet of the flow cell is at the bottom and output is located at the top. Evolution of air bubble can also be observed in trial for 1.0 mL/min. a) b)c) d)e) f)00.20.40.60.811.20 1 2 3 4Relative Dye IntensityTime (min)Flow Rate: 0.5 mL/minTopBottom Middle00.20.40.60.811.20 1 2 3 4Relative Dye IntensityTime (min)MiddleTopBottomFlow Rate: 0.8 mL/min00.20.40.60.811.20 0.5 1 1.5Relative Dye IntensityTime (min)MiddleFlow Rate: 1.0 mL/minTopBottom00.20.40.60.811.20 0.4 0.8 1.2Relative Dye IntensityTime (min)MiddleFlow Rate: 1.5 mL/minTopBottom00.20.40.60.811.20 0.2 0.4 0.6 0.8Relative Dye IntensityTime (min)MiddleFlow Rate: 2.2 mL/minTopBottom00.20.40.60.811.20 0.5 1 1.5 2 2.5Relative Dye IntensityTime (min)MiddleFlow Rate: 3.2 mL/minTopBottom 92 2.4.2.2 Observation of flow behaviour via 1H NMR 2.4.2.2.1 Experimental procedure With the flow system primed with MeCN, a 50 v/v% sample of 2.1 in MeCN was flowed through the system and collected in a waste container. As soon as the pump started flowing with the 50/50 2.1/MeCN solution, 1H NMR spectra were measured at regular time intervals until equilibrium with this solution was reached within the flow cell. When equilibrium was well established, spectral acquisition was halted, the pump was stopped, and the intake line was transferred to a vial of 100 % MeCN. The pump was restarted, and spectral measurement was immediately started again at regular time intervals until an equilibrium had been reached with the 100 % MeCN solution, suggesting that the flow cell had been completely evacuated of the 2.1/MeCN solution. Data were collected with the same acquisition parameters for all six flow rates ranging from 0.5 to 3.2 mL/min (0.5, 0.8, 1.0, 1.5, 2.5, and 3.2 mL/min), but double the acquisition time for the 0.5 mL/min trial was used in comparison to the other flow rates. Each spectrum was measured with a 90° pulse, 4 scans, no dummy scans, and 3 s time between each spectrum. Data with a 0.5 mL/min flow rate were acquired with a 4.7 s AQ, 3,125 Hz (51.7 ppm) SW, 6.0 ppm spectral offset, and 8.0 s 𝜏*. Spectra for all other flow rates (0.8, 1.0, 1.5, 2.2, and 3.2 mL/min) were measured with a 2.3 s AQ, 3,125 Hz (51.7 ppm) SW, 6.0 ppm spectral offset, and 5.5 s 𝜏* in order to better characterize trends with higher degree of data density. Once processed, these data were analyzed by integrating the resonance corresponding to the methyl of 2.1 (𝛿H 3.3 ppm). The integration values were plotted against the time in which the spectrum was acquired after the pump was turned on with the solution of interest (either 50/50 93 2.1/MeCN for filling or 100 % MeCN for emptying). Data for each flow rate, other than the one shown above in Figure 2.4 for 0.8 mL/min, can be found in Figure 2.14 - Figure 2.18, below. 2.4.2.2.2 Further data relevant to section The results of the filling and emptying trials for all studied flow rates have been summarized in Table 2.2 below. These data were used to prepare the graph displayed in Figure 2.5 of the main text above. Table 2.2. Results of filling and emptying analyses of NMR flow cell via 1H with various flow rates. These data were used to prepare the graph in Figure 2.5. Flow rate Time to fill Time to empty 0.5 mL/min 11.5 min 13.6 min 0.8 mL/min 5.1 min 6.7 min 1.0 mL/min 3.6 min 4.1 min 1.5 mL/min 1.5 min 2.6 min 2.2 mL/min 2.1 min 2.6 min 3.2 mL/min 1.0 min 1.5 min Filling and emptying trends using a 50/50 2.1/MeCN and various flow rates (0.5, 1.0, 1.5, 2.2, and 3.2 mL/min) used to describe filling behaviour can be found in Figure 2.14 - Figure 2.18, below. The filling and emptying trends using a 1.8 mL/min flow rate can be found in the main text above (Section 2.2.2, Figure 2.4). 94 Figure 2.14. Normalized benchtop 1H NMR integration of methyl resonance of 2.1 (𝛿H 3.3 ppm) as a function of time for filling and emptying processes using a system of MeCN and a 50/50 2.1/MeCN solution at 0.5 mL/min. Figure 2.15. Normalized benchtop 1H NMR integration of methyl resonance of 2.1 (𝛿H 3.3 ppm) as a function of time for filling and emptying processes using a system of MeCN and a 50/50 2.1/MeCN solution at 1.0 mL/min. 00.20.40.60.810 10 20 30 40Relative Methyl Resonance IntegrationTime (min)FillingEmptying00.20.40.60.810 5 10 15Relative Methyl Resonance IntegrationTime (min)FillingEmptying 95 Figure 2.16. Normalized benchtop 1H NMR integration of methyl resonance of 2.1 (𝛿H 3.3 ppm) as a function of time for filling and emptying processes using a system of MeCN and a 50/50 2.1/MeCN solution at 1.5 mL/min. Figure 2.17. Normalized benchtop 1H NMR integration of methyl resonance of 2.1 (𝛿H 3.3 ppm) as a function of time for filling and emptying processes using a system of MeCN and a 50/50 2.1/MeCN solution at 2.2 mL/min. 00.20.40.60.810 2 4 6 8 10Relative Methyl Resonance IntegrationTime (min)FillingEmptying00.20.40.60.810 2 4 6 8 10Relative Methyl Resonance IntegrationTime (min)FillingEmptying 96 Figure 2.18. Normalized benchtop 1H NMR integration of methyl resonance of 2.1 (𝛿H 3.3 ppm) as a function of time for filling and emptying processes using a system of MeCN and a 50/50 2.1/MeCN solution at 3.2 mL/min. 2.4.2.3 Determination of spin-lattice relaxation time (T1) and observed spin-lattice relaxation time (T1*) with flow 2.4.2.3.1 Experimental procedure A solution of 0.24 M 2.2 (865 𝜇L) was prepared in MeCN-d3 (3.49 mL) and MeCN (30.52 mL). The 10.0 v/v% deuterated solution insured that the instrument was able to hold and maintain a lock during data acquisition with the inversion recovery experiment. Data to estimate the T1 and T1* of the aldehyde proton of 2.2 were collected using the inversion recovery experiment under static conditions (0.0 mL/min) and with analyte flow (0.5, 0.8, 1.0, 1.5, 2.2, and 3.2 mL/min). All analyses in this section were completed in triplicate. Benchtop 1H NMR spectra were measured with 4 scans, no dummy scans, 5.2 s AQ, 3,125 Hz (51.7 ppm) SW, and 6.0 ppm spectral offset. The variable time (𝜏) between the 180° and 90° RF pulses was varied in 24 linearly spaced increments between 𝜏start and 𝜏stop. Some experimental parameters, such as the applied d1, 𝜏start, and 𝜏stop values, varied depending on flow rate (Table 2.3). 00.20.40.60.810 2 4 6 8Relative Methyl Resonance IntegrationTime (min)FillingEmptying 97 Table 2.3. Flow dependent 1H NMR acquisition parameters used for inversion recovery experiments in T1 and T1* estimation for the aldehydic proton of 2.2 in MeCN (10.0 v/v% MeCN-d3). Flow rate Relaxation delay (d1) 𝜏start 𝜏stop 0.0 mL/min 176.0 s 10.0 ms 100,000.0 ms 0.5 mL/min 81.0 s 10.0 ms 30,000.0 ms 0.8 mL/min 41.0 s 1.0 ms 16,000.0 ms 1.0 mL/min 31.0 s 1.0 ms 15,000.0 ms 1.5 mL/min 21.0 s 1.0 ms 9,000.0 ms 2.2 mL/min 21.0 s 0.10 ms 7,000.0 ms 3.2 mL/min 11.0 s 0.10 ms 5,000.0 ms Once processed, these data were analyzed by integrating the signal corresponding to the aldehyde proton of 2.2 (𝛿H 10.0 ppm) and plotting this value against the variable time delay, 𝜏. These data were fitted to a “Three Parameter Exponential Fit” in Mnova, and a 𝜏null (𝜏 where signal integration/intensity was equal to zero) point was calculated. If the data were acquired with the sample flowed at some rate, the T1* (or T1, if static conditions) was determined by dividing the determined 𝜏null by ln(2). 2.4.2.3.2 Further data relevant to section The results of T1 and T1* estimations for all studied flow rates have been summarized in Table 2.4. 98 Table 2.4. Summary of T1 and T1* estimations (60 MHz, 0.24 M, 22.0 °C) for the 1H NMR resonance of the aldehyde proton of 2.2 in MeCN (10.0 v/v% MeCN-d3) using the inversion recovery experiment. Flow rate Average estimated T1 Standard deviation % RSD 0.0 mL/min 26.33 s 0.067 s 0.253 % 0.5 mL/min 5.46 s 0.403 s 7.387 % 0.8 mL/min 3.64 s 0.045 s 1.245 % 1.0 mL/min 2.95 s 0.095 s 3.223 % 1.5 mL/min 1.75 s 0.074 s 4.223 % 2.2 mL/min 1.30 s 0.037 s 2.841 % 3.2 mL/min 0.95 s 0.026 s 2.770 % Representative data for each flow rate from the inversion recovery experiment used to estimate the T1 value, or T1* with flow, for the aldehyde proton resonance of 2.2 using the inversion recovery experiment can be found in Figure 2.19 - Figure 2.25. 99 Figure 2.19. Representative results of the inversion recovery experiment to estimate the T1 for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 0.0 mL/min flow. Figure 2.20. Representative results of the inversion recovery experiment to estimate the T1* for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 0.5 mL/min flow. HO2.26.57.07.58.08.59.09.510.010.5f1 (ppm / 1H)0 20 40 60 80 100Tau (s)-1.0-0.50.00.51.01.52.0Integration Y' = B+F*exp(-Tau *G)B=2.223; F=-3.747; G=0.02865;Error: 0.001115a) b)Increasing !0 10000 20000 30000Tau (ms)-0.50.00.51.01.5Integration78910f1 (ppm / 1H)Y' = B+F*exp(-X*G)B=1.678; F=-2.907; G=0.0001413;Error: 0.00001039a) b)Increasing !HO2.2 100 Figure 2.21. Representative results of the inversion recovery experiment to estimate the T1* for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 0.8 mL/min flow. Figure 2.22. Representative results of the inversion recovery experiment to estimate the T1* for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 1.0 mL/min flow. 67891011f1 (ppm / 1H)0 4000 8000 12000 16000Tau (ms)-0.50.00.51.0Integration Y' = B+F*exp(-X*G)B=1.260; F=-2.514; G=0.0002746;Error: 0.00001719a) b)Increasing !HO2.267891011f1 (ppm / 1H)0 4000 8000 12000Tau (ms)-0.50.00.51.0Integration Y' = B+F*exp(-X*G)B=1.012; F=-1.962; G=0.0003361;Error: 0.00002109a) b)Increasing !HO2.2 101 Figure 2.23. Representative results of the inversion recovery experiment to estimate the T1* for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 1.5 mL/min flow. Figure 2.24. Representative results of the inversion recovery experiment to estimate the T1* for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 2.2 mL/min flow. 67891011f1 (ppm / 1H)0 2000 4000 6000 8000Tau (ms)-0.4-0.20.00.20.40.60.8Integration Y' = B+F*exp(-X*G)B=0.7732; F=-1.400; G=0.0004780;Error: 0.00003419a) b)Increasing !HO2.20 2000 4000 6000Tau (ms)-0.4-0.20.00.20.40.6Integration67891011f1 (ppm / 1H)Y' = B+F*exp(-X*G)B=0.5308; F=-1.118; G=0.0008309;Error: 0.00004674a) b)Increasing !HO2.2 102 Figure 2.25. Representative results of the inversion recovery experiment to estimate the T1* for the 1H NMR resonance of the aldehyde resonance of 2.2 (60 MHz, 0.24 M, 22.0 °C) in MeCN (10.0 v/v% MeCN-d3) with 3.2 mL/min flow. 2.4.2.4 Signal-to-noise ratio (SNR) determination with various flow rates 2.4.2.4.1 Experimental procedure Solutions of 2.2 were prepared in MeCN (0.48 M: 1.734 mL 2.2 in 34.0 mL MeCN; 0.24 M: 864 𝜇L 2.2 in 34.0 mL MeCN; 0.10 M: 340 𝜇L 2.2 in 34.0 mL MeCN). Benchtop 1H NMR spectra were measured with each of these solutions under static conditions (0.0 mL/min) and at various flow rates (0.5, 0.8, 1.0, 1.5, 2.2, and 3.2 mL/min). Each flow rate and concentration combination was analyzed in triplicate with two sets of acquisition parameters (slow and fast, Table 2.1). For slow, data were measured with a 90° pulse, 4 scans, no dummy scans, 9.4 s AQ, 3,125 Hz (51.7 ppm) SW, 6.0 ppm spectral offset, and 12.9 s 𝜏*. For fast, data were measured with a 60° pulse, 4 scans, no dummy scans, 2.4 s AQ, 3,125 Hz (51.7 ppm) SW, 6.0 ppm spectral offset, and 3.6 s 𝜏*. 0 1000 2000 3000 4000 5000Tau (ms)-0.4-0.20.00.20.4Integration67891011f1 (ppm / 1H)Y' = B+F*exp(-X*G)B=0.5246; F=-1.053; G=0.001034;Error: 0.00004663a) b)Increasing !HO2.2 103 After applying appropriate processing, the SNR was determined using the SNR script embedded in Mnova (“SNR Calculation ...”) on the aldehyde signal of 2.2 (𝛿H 10.0 ppm). For this script's purpose, a range of 𝛿H 9.8 – 8.5 ppm was used for the spectral noise region, and a range of 𝛿H 10.1 – 9.9 ppm was used for the signal region. 2.4.2.4.2 Further data relevant to the section Summaries of the resultant data from monitoring the benchtop 1H NMR SNR of the aldehyde resonance of 2.2 with various flow rates, and different acquisition parameters, can be found below: SNR data measured with slow data acquisition parameters are summarized in Table 2.5 and the data measured with fast data acquisition parameters are summarized in Table 2.6. 104 Table 2.5. Statistical analysis of 2.2 aldehyde SNR data (60 MHz, MeCN), with analyte at various concentrations and flow rates, and data collected as per slow acquisition parameters listed in Table 2.1. Concentration Flow Rate Average SNR Standard Deviation % RSD 0.48 M 0.0 mL/min 81.42 3.58 4.40 % 0.5 mL/min 103.60 9.37 9.05 % 0.8 mL/min 96.26 14.38 14.94 % 1.0 mL/min 91.59 5.75 6.28 % 1.5 mL/min 63.89 3.99 6.24 % 2.2 mL/min 62.72 6.61 10.54 % 3.2 mL/min 39.06 7.21 18.45 % 0.24 M 0.0 mL/min 36.21 4.55 12.55 % 0.5 mL/min 52.76 5.56 10.53 % 0.8 mL/min 52.43 6.44 12.28 % 1.0 mL/min 46.08 3.89 8.45 % 1.5 mL/min 45.56 2.99 6.56 % 2.2 mL/min 34.02 1.86 5.47 % 3.2 mL/min 21.19 2.08 9.84 % 0.10 M 0.0 mL/min 13.89 0.75 5.37 % 0.5 mL/min 21.13 2.39 11.31 % 0.8 mL/min 19.35 1.71 8.85 % 1.0 mL/min 17.49 2.65 15.12 % 1.5 mL/min 16.31 1.16 7.14 % 2.2 mL/min 9.25 0.53 5.67 % 3.2 mL/min 9.18 0.27 2.96 % 105 Table 2.6. Statistical analysis of 2.2 aldehyde SNR data (60 MHz, MeCN), with analyte at various concentrations and flow rates. Data collected as per fast acquisition parameters listed in Table 2.1. Concentration Flow Rate Average SNR Standard Deviation % RSD 0.48 M 0.0 mL/min 45.49 4.50 9.90 % 0.5 mL/min 85.30 7.02 8.23 % 0.8 mL/min 85.72 11.13 12.98 % 1.0 mL/min 82.22 16.06 19.54 % 1.5 mL/min 63.06 2.31 3.66 % 2.2 mL/min 52.77 9.09 17.22 % 3.2 mL/min 36.80 1.22 3.31 % 0.24 M 0.0 mL/min 21.97 2.80 12.76 % 0.5 mL/min 39.01 5.30 13.60 % 0.8 mL/min 41.03 2.09 5.10 % 1.0 mL/min 42.02 3.90 9.29 % 1.5 mL/min 42.10 3.62 8.60 % 2.2 mL/min 31.59 2.09 6.62 % 3.2 mL/min 19.67 2.04 10.37 % 0.10 M 0.0 mL/min 8.19 1.37 16.76 % 0.5 mL/min 14.12 1.06 7.53 % 0.8 mL/min 17.56 0.41 2.35 % 1.0 mL/min 15.30 2.46 16.07 % 1.5 mL/min 13.82 0.98 7.06 % 2.2 mL/min 8.29 0.93 11.21 % 3.2 mL/min 8.24 0.76 9.17 % 106 2.4.2.5 Signal-to-noise ratio (SNR) determination with various reaction vial temperatures 2.4.2.5.1 Experimental procedure A solution of 0.10 M 2.2 (340 𝜇L) in MeCN (34.0 mL) was prepared and the vial with the solution was equipped with a magnetic stir bar. Benchtop 1H NMR spectra were measured with this solution with flow (0.5 and 2.2 mL/min) at various temperatures of the solution in the solution vial (5.0 C, 20.0 C, 35.0 C, 50.0 C, and 65.0 °C). Each flow rate and temperature combination was measured in triplicate, each with a 90° pulse, 4 scans, no dummy scans, 9.4 s AQ, 3,125 Hz (51.7 ppm) SW, 6.0 ppm spectral offset, and 12.9 s 𝜏* The SNR was determined using the SNR script embedded in Mnova (“SNR Calculation ...”) using the aldehyde signal of 2.2 (𝛿H 10.0 ppm). For this script's purpose, a range of 𝛿H 9.8 – 8.5 ppm was used for the spectral noise region, and a range of 𝛿H 10.1 – 9.9 ppm was used for the signal region. 2.4.2.5.2 Further data relevant to the section The data for monitoring the benchtop 1H NMR SNR of the aldehyde resonance of 2.2 with two flow rates, and different temperatures of reaction vial, have been summarized in Table 2.7 below. 107 Table 2.7. Statistical analysis of 2.2 aldehyde SNR data (60 MHz, MeCN), with analyte at two flow rates and vial at various temperatures. Data collected as per slow acquisition parameters listed in Table 2.1. Flow Rate Temperature Average SNR Standard Deviation % RSD 0.5 mL/min 5.0 °C 24.16 1.35 5.58 % 20.0 °C 21.05 2.22 10.55 % 35.0 °C 11.40 0.98 8.59 % 50.0 °C 12.37 0.98 7.93 % 65.0 °C 10.76 1.73 16.03 % 2.2 mL/min 5.0 °C 18.32 2.25 12.30 % 20.0 °C 18.37 1.19 6.48 % 35.0 °C 11.36 1.03 9.05 % 50.0 °C 6.82 0.24 3.46 % 65.0 °C 7.23 0.59 8.16 % 108 Chapter 3: Quantitative and convenient real-time reaction monitoring using on-line stopped-flow benchtop NMR 3.1 Introduction Reaction monitoring can provide mechanistic insight, in turn highlighting pathways for process optimization and/or enhanced process safety. Various analytical tools may be employed for this purpose - each with a unique set of benefits and limitations based on the physical characteristics necessary for analyte detection.138,139 Solution state NMR spectroscopy is non-destructive, quantitative, and arguably the strongest structure elucidation tool at a chemist's disposal. Despite this, NMR is not a widely applied tool for reaction monitoring in synthetic laboratories, despite the growth of available benchtop NMR and flow systems – primarily due to complexity in the ease of quantitative flow analyses. Herein, we present a simple on-line stopped-flow benchtop NMR system, composed of a physically small, commercially available spectrometer that allows for quantitative information to be acquired under static conditions. Benchtop NMR spectrometers have gained attention in the recent years for education,120,206 forensic,124,207 and environmental208,209 sectors. Particularly, keen interest has developed in the application of these spectrometers as a reaction monitoring tool.178,198 This is primarily a result of the significant decrease in purchase price, maintenance cost, and physical footprint (can operate in/at a fumehood125,195) generally associated with NMR spectrometers. These benefits are a result from the non-cryogenically cooled permanent magnets used by these systems, which result in 1H Larmor frequencies typically ≤100 MHz. Despite these significant advantages, however, come disadvantages observable in the resultant NMR spectra - notably a decrease in both signal dispersion and sensitivity (as per Section 1.1.5). 109 While the limitation of sensitivity with benchtop NMR spectrometers can be lessened by increasing the concentration of analyte210 or through hyperpolarization techniques,211,212 signal dispersion remains a complication and only increases the likelihood of resonance overlap. Some commercially available benchtop NMR systems (including some offered from Nanalysis Scientific Corp.,213 Magritek,214 and Oxford Instruments215) offer multinuclear capabilities, lending the ability to observe nuclei other than 1H, including 13C, 19F, 31P, and even 7Li. Through observation of nuclei with a large chemical shift range (such as 19F) the limitation due to a decrease in signal dispersion can be minimized with benchtop NMR instruments. In addition to the benefits of benchtop NMR listed above, the inherently quantitative nature of the technique makes this universal detector an attractive reaction monitoring tool. Particularly unique to NMR is that the response factor for an NMR active nucleus is constant for a particular instrument and set of acquisition parameters (contingent on equal excitation and appropriate relaxation),216 irrespective of its chemical environment. Quantitative NMR (qNMR) can be achieved through various methods. These methods include the addition of an internal standard,217 electronic referencing (such as Electronic REference To access In vivo Concentrations (ERETIC),218 Amplitude-corrected Referencing Through Signal Injection (ARTSI),219 QUANTification by Artificial Signal (QUANTAS)220), and the use of the absolute intensity method.203 Though the internal standard method has shown a slight increase in accuracy over electronic reference methods,221 the internal standard method relies on the necessity of an additional species to the analyte solution which may introduce complications in terms of resonance overlap, solubility, and introduction of additional reactivity with the analyte. The electronic referencing method and the absolute intensity method have been reported to result in similar levels of accuracy,221 though some electronic referencing techniques require non-standard 110 hardware. In any case, it cannot be understated that special attention to both data acquisition and processing must be paid to preserve the quantitative nature of any NMR data.202 While the cost, size, and inherently quantitative nature of benchtop NMR instruments makes for an attractive reaction monitoring tool, NMR samples are traditionally analyzed in NMR tubes. This inherently presents a challenge for reaction monitoring as a reaction must either be completed in an NMR tube or an aliquot must be physically transported from some reaction vessel to the spectrometer for analysis. While the former is most easily implemented, it may not fully represent the native reaction as mass transfer complications arise from a lack of mixing during reaction progress.143 Therefore, a sample can be physically transported from the reaction vessel to the NMR spectrometer (in let's say an NMR tube), but this is often labour and time intensive for the experimenter. Therefore, a flow system (such as those described by Khajeh et al.165 and Foley et al.166 applied with high-field systems) can help circulate a reaction mixture between the reaction vessel and the NMR spectrometer, alleviating these sample transport and mass transport problems. Despite a flow system allowing for more representative and convenient reaction monitoring data to be acquired, complications arise if the solution is analyzed under continuous-flow conditions. Literature reports179,180 have highlighted elements such as flow cell geometry, analyte residence time, and analyte pre-magnetization that dictate the quality of resultant data. Particularly with benchtop NMR and flowing systems, analyte relaxation times and analyte homogeneity across the flow cell introduce potential challenges in terms of the robustness of qNMR measurements. Relevant impacts of flow using a potential reaction monitoring system with an on-line continuous-flow benchtop NMR system are discussed in Chapter 2. Though it should be noted that with special considerations, quantitative data may be achievable with flowing systems.177 111 We therefore sought to utilize a flow system that efficiently transferred reaction solution to a benchtop NMR spectrometer for analysis, but with spectral acquisition under static, no-flow, conditions - allowing for quantitative data to be acquired and interpreted with significant ease. Herein, we present this on-line stopped-flow benchtop NMR system for reaction monitoring, composed of commercially and easily obtainable components. These hardware elements are centrally controlled by a single Python script, allowing for convenient NMR data to be obtained. Quantitative data acquisition using the absolute intensity method203 (for reasons previously highlighted) are carefully considered prior to the application of the system to monitor complex model reactions. 3.2 Designing an on-line stopped-flow benchtop NMR system 3.2.1 System hardware and remote control The stopped-flow benchtop NMR system (Figure 3.1) consists of three hardware components: a benchtop NMR spectrometer (NMReady-60PRO, Nanalysis Scientific Corp.), a peristaltic pump (SF-10 reagent pump, Vapourtec Ltd.), and a six-port valve (Vici C2, Valco Instruments Co. Inc.). These components are connected by either ethylene tetrafluoroethylene (ETFE, 1/16” outer diameter (O.D.), 0.02” inner diameter (I.D.)) or polyether ether ketone (PEEK, 1/16” O.D., 0.01” I.D.) tubing. The segments of the smaller I.D. PEEK tubing (placed between the pump/valve and valve/NMR) are necessary to generate appropriate backpressure to eliminate solvent cavitation when using organic solvents, such as MeCN. 112 Figure 3.1. Schematic representation of the stopped-flow benchtop NMR system, with respect to flow paths in each of the valve positions. Arrows signify direction of analyte flow and coloured lines denote connecting segments of line. The hardware components consist of a benchtop NMR spectrometer (NMReady-60PRO, Nanalysis Scientific Corp.) equipped with a flow cell, peristaltic pump (SF-10 reagent pump, Vapourtec Ltd.), and six-port valve (C-10, Valco Instruments Co. Inc.). In addition to the hardware components listed above, an NMR glass flow cell (∼1.2 mL volume, Nanalysis Scientific Corp.) is used where the analyte solution enters from the bottom of the instrument and exits the top. The volume of this system, with used lengths of ETFE/PEEK tubing and the flow cell, was determined by 19F NMR to be 1.78 mL (see Section 3.5.2.1, Figure 3.16 for line lengths and Section 3.5.2.4 for description of volume determination). A Python script (developed by Dr. Lars P. E. Yunker) allows for efficient transfer of analyte to the spectrometer, but with data acquisition to be completed under static conditions. This is possible with use of a six-port valve (two ports plugged) placed between the pump/NMR and NMR/vial (Figure 3.1). In general, reaction solution is pumped from the vial through the valve and NMR flow cell, returning to the vial (valve position “A”). Then at a pre-determined timepoint, the valve position is switched (position “B”) resulting in the reaction solution being pumped from the reaction vial to the valve and returning to the vial, without entering the flow cell. Crucially, Switch valve position6-Port Valve Position: “B”6-Port Valve Position: “A”flowing staticVialPumpBenchtopNMR 113 this results in the solution within the NMR flow cell static for analysis, overall eliminating quantitative complications associated with continuous-flow NMR analyses. Using a valve and switching its position was selected as the method to halt analyte solution in the NMR for analysis, in lieu of stopping pump operation, as this allowed the reaction solution in the stopped-flow system but not NMR flow cell to re-enter the main reaction vial during spectral acquisition. This crucially re-exposed this volume of reaction solution to the overall reaction conditions, generally involving heat and mixing. Further, this method results in a smaller overall volume needed to replenish the NMR flow cell with fresh reaction solution. It should be noted that no temperature control of the reaction solution volume in the stopped-flow system is obtained. The permanent magnet of the used benchtop NMR spectrometer is very sensitive to any temperature fluctuation and is therefore internally held to a constant temperature (32 °C). While this is a limitation of the stopped-flow system as the reaction profile may look slightly different if all the reaction solution is maintained a constant temperature, analyzing approximately room temperature solution was important to maintain the spectrometer's shimming and lock. To assess this potential limitation, a heated model reaction (80 °C) was monitored via flow IR spectroscopy (ReactIR) and on-line stopped-flow 19F benchtop NMR. The agreement in reaction trends between these orthogonal techniques validates the representative nature of resultant 19F NMR trends despite the lack of thermal insulation within the stopped-flow benchtop NMR system (Section 3.3.4). Nonetheless, this shall be taken into consideration with acquired reaction profiles, as appropriate. 3.2.2 Benchtop 19F NMR data processing and analysis With an increase in active pharmaceutical ingredients possessing at least one fluorine atom,222 19F has become a popular nucleus to detect via NMR in pharmaceutical settings. 114 Additionally, 19F has a relatively high NMR receptivity (0.83 relative to 1H) due to its gyromagnetic ratio and 100 % natural abundance. Further, 19F has a nuclear spin of !" and therefore follows splitting and relaxation patterns generally assumed with other spin !" nuclei, such as 1H and 13C. With benchtop NMR instrumentation, the large chemical shift range (>200 ppm) of 19F additionally increases its applicability as resonances are less likely to overlap. For reaction monitoring in particular, the utilization of non-deuterated solvents is particularly of interest to decrease cost and eliminate potential isotopic effects. Importantly, the absence of residual solvent signals (as most common solvents are non-fluorinated) increases the utility of 19F NMR as resonances can be better digitized without the introduction of dynamic range complications. All NMR data were processed offline with MestReNova (Mnova). A script derived from the manufacturer of the NMR spectrometer (Nanalysis Scientific Corp.) automatically uploaded the acquired NMR data to a file accessible with a network connected computer, even with the spectrometer in “remote” mode. The data files, once transferred to Mnova, were then processed with the application of a 2.0 Hz exponential apodization, 0th order baseline correction, and an automatic phase correction. An automatic phase correction was always attempted first in effort to reduce subjectivity of the applied phase correction, but if further phase correction was still deemed necessary, this was applied manually. 3.2.3 Benchtop 19F NMR data acquisition parameter selection To preserve the quantitative nature of resultant NMR data, data acquisition must be carefully considered. With our primary focus on 19F NMR (for above highlighted reasons), we determined a set of “go-to” acquisition parameters appropriate for quantitative analyses with our system. Robinson and coworkers204 have highlighted important considerations concerning 19F 115 qNMR data acquisition, providing a roadmap of crucial factors to consider with our benchtop NMR system. Therefore, we carefully considered the SW, receiver gain, RF pulse angle, number of transients, d1, and resonance excitation. For most reaction systems of interest for our group, a 12,500 Hz (219.6 ppm) spectral width, with appropriately selected spectral offset, was deemed sufficient to encompass resonances of interest. Our NMReady-60PRO benchtop NMR spectrometer has a hardware limitation of collecting 65,536 complex data points per acquisition, therefore limiting the maximum achievable AQ for a particular SW. We therefore elected to collect our 19F benchtop NMR data with a 2.79 s AQ (34,816 complex data points and 220 ppm SW). With a determined SW and AQ, an appropriate pulse angle and receiver gain was selected. We anticipated a relatively long 𝜏* to ensure quantitative conditions, therefore a calibrated 90° pulse (see Section 3.5.3.1) was selected to recover maximum signal per transient. Furthermore, a sample of benzotrifluoride (3.1, 0.67 M) in MeCN was used to determine a set receiver gain value, as this sample roughly represented relevant reaction concentrations. While data collected with various receiver gain and other acquisition parameters (pulse angle, number scans, etc.) can be compensated for in concentration calculations,223,224 we sought to seek data with a fixed receiver gain value to minimize calculation complexity and propensity for quantitative error. The receiver gain value was therefore determined by acquiring a 19F NMR spectrum with the instrument's “autogain” option. A few units were subtracted from the autogain determined value (arriving at 44 dB), ensuring the receiver would not experience oversaturation in later analyses. With the decreased sensitivity intrinsic to benchtop NMR, we acknowledged that signal averaged data would need be acquired, even with a 90° pulse and relatively concentrated reaction solutions (∼0.3 – 0.5 M). Therefore, spectra were collected with four scans to increase SNR 116 without increasing experimental time such that spectra were no longer representative of reaction progress. With the application of signal averaging, however, it was clear that sufficient time needed to be supplied for relaxation of spins prior to subsequent pulse excitation. We therefore estimated the spin-lattice relaxation time (T1) of starting material and product resonances using the inversion recovery experiment73,74 at appropriate reaction concentrations (Section 3.5.3.2). As discussed in Section 1.1.3.1 of this thesis, the repetition time need be at least 5 × T1 for qNMR measurements. Based on our longest estimated T1, a d1 of 61.5 s or less (depending on specific reaction system) was selected to satisfy this quantitative condition. In addition to properly digitizing resonances and supplying sufficient relaxation time, it is imperative for qNMR measurements that nuclei be equally excited across the spectral region of interest. Observation of nuclei with a smaller chemical shift range (such as 1H) and with modern NMR instruments results in this generally being the case. However, with more disperse nuclei such as 19F, this becomes increasingly more difficult as a significantly larger spectral area must be uniformly excited. 204 To explore the 90° (11.8 𝜇s) RF pulse excitation profile of our spectrometer over our desired 12,500 Hz (220 ppm) SW, we monitored the absolute integration of the trifluoromethyl resonance (𝛿F -63.5 ppm) of 3.1 in MeCN (0.63 M) while changing the spectral offset such that the monitored resonance changed its distance off-resonance (all other acquisition parameters held constant). The results of the triplicate analysis suggest uniform excitation across the entire 12,500 Hz (220 ppm) spectral region with a 90° pulse (Figure 3.2). 117 Figure 3.2. a) Stacked benchtop 19F NMR spectra (57 MHz) altering the off-resonance position (distance off resonance denoted in kHz) with the trifluoromethyl resonance of 3.1 (𝛿F -63.5 ppm) and b) the average absolute integration of this resonance with these spectral positions. 3.2.4 Quantitative method development and verification In effort to perform absolute qNMR measurements, we sought to determine a 19F NMR response factor (referred to as a Concentration Conversion Factor or CCF) for our system utilizing the previously discussed acquisition parameters. Seven concentrations (0.01 – 0.67 M) of 3.1 in MeCN were analyzed in duplicate and the absolute resonance integration per nuclide was fit to a linear trend against the gravimetrically determined molar concentrations (Figure 3.3a). The reciprocal of the resulting slope represents the CCF for our system (with this set of data acquisition and processing). The CCF can then be applied to determine the concentration of a component by multiplying this response factor by the absolute integration and dividing this by the number of nuclide responsible for the resonance. Once determined, we next verified this experimentally determined CCF by comparing the calculated concentration via qNMR of trifluoroacetic acid (TFA, 3.2, 𝛿F -77.0 ppm) in MeCN with the gravimetrically determined concentrations (0.05 – 0.38 M). Not only was the relationship linear -250-200-150-100-50050100f1 (19F / ppm)a) b)5.6 KHz0.00.20.40.60.81.0-6 -4 -2 0 2 4 6AverageRelative IntegrationDistance off resonance (kHz)5.0 KHz3.8 KHz2.5 KHz1.3 KHz0 KHz-1.3 KHz-2.5 KHz-3.8 KHz-5.0 KHz-5.06 KHzF3.1F F 118 (as expected) but we also observed great agreement (R2 > 0.999) between the qNMR and gravimetrically determined concentrations (Figure 3.3b). Figure 3.3. a) Average benchtop 19F NMR (57 MHz) integration per nuclide of varying concentrations of 3.1 (𝛿F -63.5 ppm) used to determine the instrument's CCF for the applied data acquisition and processing. b) Verification of CCF by comparing 19F NMR determined concentrations of 3.2 (𝛿F -77.0 ppm) with the gravimetrically determined concentrations. In effort to maintain the highest degree of quantitative integrity, a CCF (determined in triplicate via single-point analysis) was independently determined with standard solution of 3.1 prior to each reaction monitoring trial. Further, this CCF was determined with the reaction solvent (either MeCN or toluene) of later analyses. Additionally, it is a well-documented that a change in a sample's ionic strength (i.e., change in sample's conductance) can change the NMR response,225 resulting in a change in absolute resonance integration. For reaction monitoring, this is particularly of consideration as the total number of ions in solution during a reaction may change as the reaction progresses. As the absolute intensity method directly correlates absolute integration to analyte concentration, an artificial a) b)y = 506.83x + 0.9719R² = 0.999901002003004000 0.2 0.4 0.6 0.819F Absolute Integration per NuclideGravimetric Concentration (M)y = 1.0213x + 0.008R² = 0.999300.10.20.30.40.50 0.1 0.2 0.3 0.4 0.5Concentration via19F NMRGravimetric Concentration (M)F3.1F F3.2OHFOFF 119 change in concentration of a species may result. To better understand this with our system, we monitored the absolute integration of the resonance consistent with 3.2 in water, while differing the sodium chloride (NaCl) concentration. We observed a decrease in 2.8 % resonance integration (and therefore 2.8 % decrease in observed concentration) with an increase in 1.0 M ionic strength (Section 3.5.3.5). We consider this within error associated with our system for qNMR purposes and, therefore, no correction factor is applied in the subsequent reaction monitoring analyses. 3.3 Application of on-line stopped-flow benchtop NMR system to reaction monitoring The previously described stopped-flow system was applied to quantitatively monitor two general reaction systems via 19F NMR - both of which are complex, multiple component processes that would be challenging to observe traditionally with NMR. Our first investigation involves the generation, hydrolysis, and synthetic use of sulfuryl fluoride (SO2F2, 3.4), an electrophilic toxic gas. The second involves isocyanate chemistry via Curtius rearrangement of an acyl azide (3.14) produced with 4-fluorobenzoic acid (3.7) and diphenylphosphoryl azide (DPPA). This process inherently involves high temperatures, nitrogen gas (N2) evolution, and hazardous azide handling. Importantly, all chemistry was conducted in a fumehood and the reaction solution was conveniently flowed to the benchtop NMR on an adjacent lab bench for analysis, highlighting the utility of such system under practical synthetic laboratory settings. Note, all concentrations to follow are determined based on the CCF of the spectrometer and number of fluorine nuclei responsible for each resonance of interest. 3.3.1 Sulfuryl fluoride (SO2F2) generation and hydrolysis SO2F2 (3.4, known as the commercially available fumigant Vikane®)226 has proven synthetic utility in sulfur VI fluoride exchange (SuFEx) chemistry and has been applied to a vast number of synthetic transformations,227 including deoxygenations,228,229 nucleophilic acyl 120 substitutions (NAS),230,231 synthesis of polysulfates,232,233 and synthesis of arylfluorosulfates.234 In 2017, Veryser et al. reported an elegant two-chamber reactor system, where SO2F2 was formed ex-situ in one chamber and would migrate to a second chamber to be consumed in a fluorosulfonation reaction with a phenol.235 Using an analogous type of two-chamber system, we first aimed to apply our on-line stopped-flow benchtop NMR system to monitor the simple ex-situ formation, capture and hydrolysis of this synthetically relevant, but toxic, electrophilic gas via 19F benchtop NMR. Generation of SO2F2 (3.4) was completed with 1,1’-sulfonyldiimidazole (SDI, 3.3), potassium fluoride (KF), and water in a septum sealed vial (“vial 1”). Gas formation was initiated by dosing acid TFA (3.2) into this vial over 10 minutes and vial 1 was connected to a secondary septum sealed vial (“vial 2”) via PEEK tubing (49 cm, 1/16′′ O.D., 0.04′′ I.D.). In vial 2 was MeCN (with 3.1 as an internal standard) to capture the gas upon generation and migration. This vial was further heated to 40 °C in a water bath and fitted with a balloon such that over pressurization did not occur. Important to note, the solution of vial 2 was monitored via 19F NMR and the on-line stopped-flow benchtop NMR system (Figure 3.4). 121 Figure 3.4. Schematic of stopped-flow benchtop NMR system as applied to monitor sulfuryl fluoride (SO2F2) processes. This includes a SO2F2 generator vial (vial 1) and capturing/reaction vial (vial 2), connected by PEEK tubing. Spectra (with previously discussed acquisition parameters) were acquired at regular intervals once TFA (3.2) began to be dosed into vial 1 (Figure 3.5). Based on monitoring the resonance consistent with SO2F2 (3.4, 𝛿F 33.5 ppm), a saturation concentration of ∼0.1 M was achieved in MeCN at 40 °C with a ∼90 mL headspace. For decades, it has been understood that hydrolysis of SO2F2 (3.4) readily occurs under basic conditions.236 Therefore, to this same solution, we injected water (2.4 eq.) and base (N,N-diisopropylethylamine, DIPEA, 5.8 eq.) into vial 2 sequentially, once the steady-state concentration of SO2F2 (3.4) had been maintained. 122 Figure 3.5. a) Scheme corresponding to the for the capture (MeCN, 40 °C) and subsequent hydrolysis of SO2F2 (3.4, 0.08 M; 2.4 eq. H2O, 5.8 eq. DIPEA). b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired for the capture and hydrolysis of 3.4, with increasing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of benchtop NMR system. Upon injection of water and base, a decrease in the concentration of 3.1 was observed -expected and consistent based on additional volume added to the reaction vial. Additionally, the disappearance of the resonance consistent with SO2F2 (3.4), along with the appearance of new chemical species, was observed. These two new species were observed with chemical shifts of 𝛿F 37.2 ppm and 𝛿F -106.0 ppm, assigned to hydrolysis products fluorosulfate (FSO3-, 3.5) and fluoride (F-, 3.6), respectively (Figure 3.5). The application of the stopped-flow benchtop NMR system allowed for quick, reliable, and real-time quantitative information regarding the !" life of SO2F2 (3.4) in these hydrolysis conditions 3.1N S NN NKFTFAH2OF S FO OH2ODIPEAMeCN FS OO OF+3.3 3.4 3.5 3.6internal standard:O O-150-100-50050f1 (19F / ppm)a)c)≈t=0.0 ht=1.4 hIncreasing Time00.10.20.30 1 2 3 4Concentration (M)Time (h)add H2O and baseb)3.13.63.53.4 123 (4.8 min). Further, these data highlight how this system could be used as a method to observe/verify when this electrophilic gas has fully been destroyed. Additionally, interesting information regarding the relative presence of SO2F2 (3.4) was highlighted as most of the gas appeared to be in solution rather than the headspace of the vial, demonstrated by about an equimolar amount of either hydrolysis product than SO2F2 (3.4) originally in solution. While the formation of hydrolysis products (3.5 and 3.6) was expected based on the literature,236 adequate observation of such species was not necessarily guaranteed with benchtop 19F NMR. To our delight, sufficient signal dispersion resulted to visually observe the resonance consistent with 3.5 fully spectrally resolved from that of the resonance consistent with SO2F2 (3.4). Additionally, fluoride (3.6) can be an analytically challenging species to track and observe, especially in terms of a non-destructive method with a neat reaction mixture.237 Despite this, a resonance consistent with fluoride (3.6) was non-destructively observed and quantified. It is important to note that, while fluoride (3.6) was observed, the very broad nature of the signal results in additional noise being incorporated into the absolute integration. Therefore, the trend for this species appeared relatively noisy compared to the other resonances observed. Nonetheless, the general concentration trend follows that of fluorosulfate 3.5 and corroborates the ability of this system to observe (and quantify) an otherwise analytically challenging species. 3.3.2 Activation of a carboxylic acid with sulfuryl fluoride (SO2F2) One process that is particularly of interest is the activation of a carboxylic acid using SO2F2 and subsequent nucleophilic acyl substitution with an amine to form the corresponding amide.230 This process presents a method to prepare amides in a one-pot sequential process, resulting from reacting an amine to an activated carboxylic acid (identified as an acyl fluoride),238 resulting from the transformation between carboxylate and SO2F2 (3.4). This reaction system was recently 124 investigated via IR spectroscopy (ReactIR) in a Sammis and Hein lab collaboration,238 with particular focus on how this process can be accelerated by use of tetrabutylammonium chloride and tetrabutylammonium bromide. Therefore, we aimed to monitor this carboxylic acid activation process (without halide accelerant) using our on-line stopped-flow benchtop NMR system. The experimental setup again mirrored that of Figure 3.4, with SO2F2 (3.4) generated in vial 1 (theoretically 5.0 eq. prepared with same method previously described) and transferred to a heated (40 °C) and balloon fitted vial 2 by a segment of PEEK tubing. In vial 2, in addition to MeCN, DIPEA, and 3.1, was a fluorinated benzoic acid species (3.7). Monitoring the process once again began as gas formation was initiated by slowly dosing acid TFA (3.2) into vial 1 (10 min). The process was overall successfully monitored (Figure 3.6), where the consumption of 3.7 (𝛿F -114.2 ppm) could be observed along with the growth and consumption of a resonance consistent with an intermediate (3.10, 𝛿F -104.3 ppm). To our delight, great agreement in acyl fluoride product (3.11) concentrations was observed whether calculated from the acyl (𝛿F 16.8 ppm) or aryl fluoride (𝛿F -102.6 ppm) resonance. 125 Figure 3.6. a) Reaction scheme for the activation 3.7 (0.67 M, MeCN, 40 °C) to the corresponding acyl fluoride 3.11 with DIPEA (2.5 eq.) and SO2F2 (3.4, theoretically 5.0 eq. synthesized). b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired for the activation, with increasing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of NMR system (internal standard, 3.1, not shown to simplify graph). Additionally, we carefully monitored the behaviour of SO2F2 (3.4), which appeared to be consumed faster than initially produced, until it reached and roughly maintained a steady state concentration (∼0.1 M, consistent with the previous analysis). This was expected as SO2F2 (3.4) was produced in great excess and the reaction solution in vial 2 was kept under positive pressure of the gas. Therefore, we suggest dissolution of the gas was faster than the reaction between the deprotonated 3.7 and SO2F2 (3.4) as the steady state solution concentration was roughly maintained throughout the reaction course. 3.1DIPEAMeCNF S FO O3.7 3.4internal standard:OHOF+ OOF FOF S OO O3.5F+3.63.10 3.11FOF-120-100-80-601020304050f1 (19F / ppm)a)c)t=0.0 ht=4.8 hIncreasing Timeb)00.20.40.60.80 1 2 3 4Concentration (M)Time (h)3.113.63.53.43.73.10 126 Assuming the S–F bond as an indicator of all sulfur containing compounds within the solution, we additionally propose the dissolution constant of SO2F2 (3.4) for this system can be estimated with these data. The sum at each time point of both the concentrations consistent with unreacted and reacted SO2F2 (via concentration of SO2F2 (3.4) and fluorosulfate 3.5, respectively) must represent the total SO2F2 that must have migrated to the solution phase from the headspace at each timepoint. To apply first principles, however, a consumption plot is needed. This was obtained by subtracting each sum data point from the maximum of these values (where each data point now represents the concentration of SO2F2 (3.4) still to go into solution within the analyzed period, [SO2F2]dissol). Per these data and the first two hours of the reaction course, the dissolution of SO2F2 (3.4) fits a first-order approximation, with the observed rate constant for the dissolution process of 3.5 × 10-4 s-1 or 1.3 h-1 (Figure 3.7). Figure 3.7. Determination of the dissolution constant of SO2F2 (3.4) to a first-order approximation (1.3 h-1 or 3.5 × 10-4 s-1). [SO2F2]dissol represents the remaining amount of 3.4 to either react or dissolve into the solution over the time course, determined retroactively. y = -1.2665x - 0.3408R² = 0.9791-3-2-100 0.5 1 1.5 2 2.5ln( [SO2F2] dissol) Time (h) 127 Furthermore, Foth et al.238 observed and identified a reaction intermediate via ReactIR when investigating the activation of an analogous carboxylic acid with SO2F2 (3.4). Their work identified this species as the symmetric anhydride and a reaction intermediate with a chemical shift consistent with such species (𝛿F -104.3 ppm) was observed in our work. Additionally, analysis of the mass balance of our aryl fluoride resonances supports this intermediate having two symmetrical fluorine nuclei. This intermediate (3.10) reached a maximum concentration at 9.2 % relative to the initial fluorinated benzoic acid starting material concentration, consistent with the maximum percent previously observed with ReactIR.238 This overall highlights how use of benchtop NMR can result in data corroborating those acquired with orthogonal techniques, such as ReactIR. Additionally, this further underscores the clean nature of this reaction, as intermediate 3.10 was only observed at lower concentration levels, despite the many potential species that could be formed depending on the reaction pathway(s) lending to acyl fluoride 3.11 formation (Scheme 3.1). 128 Scheme 3.1. Potential reaction pathways and reaction mechanism for the activation of carboxylic acid 3.7 using sulfuryl fluoride (3.4) in the presence of base. Lastly, a resonance consistent with analytically challenging fluoride (3.6) could be quantified over the course of the reaction. This resonance was observed to shift through the reaction, overall following the species concentration profile. First a higher frequency shift was observed as the concentration increased (∼5 ppm in 2 hours), followed by a minor lower frequency shift (∼1 ppm) from the concentration maximum. Based on these trends we conclude that formation of fluoride (3.6) was faster in the early in the reaction, until a maximum concentration was observed at ∼51 min. Then a steady concentration decrease followed, suggesting consumption faster than formation and allowing for formation of desired product 3.11. 3.3.3 Modified Curtius rearrangement with diphenylphosphoryl azide (DPPA) In the early 1970's, Shioiri et al. reported the ability to form an acyl azide with a carboxylic acid and DPPA,239 which can thermally undergo Curtius rearrangement and form carbamates when reacted with an alcohol.239,240 This strategy has been applied to a wide range of processes, from steps towards natural products241,242 to chemical indicators.243 We therefore aimed to apply our on-OOHOOOO SFOOOSFOOF S FOOOOOOO SOOFNNH3.7F F3.83.4F3.83.83.93.8OFF3.113.53.83.5FFF 3.10OOFO SOOOOF3.123.133.133.63.63.63.63.6 129 line stopped-flow benchtop NMR system to gain a better understanding of this system that is otherwise difficult to monitor as it involves both N2 gas evolution and azide handling. As a first attempt, we hoped to monitor this process stepwise, monitoring the reaction solution between each addition of reagents or change in condition (Figure 3.8). Therefore, NMR data acquisition started with 3.7 (0.67 M, 1 eq.) in a solution of triethylamine (TEA, 1.1 eq.) and toluene. To this solution, we added DPPA (1.1 eq.) ∼26 minutes after observation of this solution via benchtop 19F NMR. Then, after observing significant formation of the corresponding acyl azide (3.14), hexafluoroisopropanol (3.16, 1.1 eq.) was added. Approximately 2 hours after addition of 3.16, the reaction solution was brought to 80 °C with a preheated oil bath (alleviation of N2 gas visually observed). Overall, the process was monitored over 20 hours total and this vial was vented with a needle though a septum-filled cap such that over pressurization did not occur. The stopped-flow benchtop NMR system otherwise directly mirrored that shown in Figure 3.1. Additionally, it is important to note, that while formation of gas was observed in the reaction vial itself during heat exposure, no bubbles were observed entering nor exiting the NMR flow cell, overall withholding the integrity of acquired benchtop 19F NMR spectra. Application of our on-line stopped-flow system successfully resulted in the observation and quantification (Figure 3.8) of the full consumption of 3.7 (𝛿F -110.4 ppm), partial consumption of 3.16 (𝛿F -75.4 ppm), along with the formation and consumption of the acyl azide intermediate 3.14 (𝛿F -103.6 ppm). Resonances consistent with the desired carbamate product (3.17) were unfortunately overlapped with nearby resonances resultant from species formed from competitive reaction pathways (trifluoromethyl resonance of 3.17 overlapped with trifluoromethyl of the ester and aryl fluoride of 3.17 overlapped with an aryl fluoride of an unidentified species). Despite the complication arising from the signal dispersion limitation of benchtop NMR systems, 130 the concentration of the carbamate product could still be deciphered by subtracting the ester 3.18 concentration (determined from ester's aryl fluoride resonance, 𝛿F -102.3 ppm) from the overlapping trifluoromethyl resonances resulting from both 3.17 and 3.18 (Figure 3.8c). Figure 3.8. a) Reaction scheme for the carbamate forming reaction of 3.7 (0.67 M, toluene) with TEA (1.1 eq.), DPPA (1.1 eq.), 3.16 (1.1 eq.) and heat (80 °C) added stepwise. b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired on the process, with increasing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of NMR system. Further based on these data, observations on the initial transformation of 3.7 to corresponding 3.14 can be made. For one, we observed this process to be relatively quick, with near full conversion in ∼1 h. The maximum concentration reached (∼0.54 M) is below that of the DPPATEAToluene3.7OHOFN3OF3.14Δ3.15FN2 (g)3.17HNF3.16HO CF3CF3OOCF3CF3ΔHN33.18OOFCF3CF33.16NCO-130-120-110-100-90-80-70f1 (19F / ppm)3.14b)00.20.40.60 5 10 15 20Concentration (M)Time (h)a)c)t=0.0 ht=20.0 hIncreasing Timeadd DPPAadd 3.16Δ(80° C)3.163.173.183.7 131 initial carboxylic acid concentration (∼0.67 M) as DPPA is a liquid and therefore adds volume to the reaction vial upon injection. Additionally, this transformation was clean as no fluorinated side-products were observed during this period. Upon addition of 3.16, no products with the aryl fluoride moiety were directly formed. Instead, products with the aryl fluoride moiety were initiated upon addition of heat (80 °C) to the reaction solution. This included the desired carbamate 3.17 (formed through modified Curtius rearrangement of acyl azide 3.14), and the corresponding ester 3.18 (formed through the competitive nucleophilic acyl substitution of the acyl azide with 3.16). Desired carbamate 3.17 did achieve a higher end concentration (0.21 M) than ester 3.18 (0.08 M), but by monitoring the concentration ratio of these two species with time, we interestingly gained insight into the preferred reaction pathway as a function of time that the reaction solution is exposed to heat (Figure 3.9). Figure 3.9. Ratio of carbamate 3.17 to ester 3.18 concentrations as the result from the heated reaction solution (80 °C) of 3.14 (formed from reaction of 3.7 with DPPA) with 3.16. Time begins with the reaction solution exposed to heat. 00.511.522.530 5 10 15Ratio (Carbamate : Ester) Time Exposed to Heat (h)ester formation favouredcarbamate formation favoured 132 These ratio data (Figure 3.9) suggest formation of ester 3.18 is favoured during the first hour of the heat exposure, with carbamate 3.17 formation dominating the remainder of the reaction. This is consistent with the competitive mechanistic nature of these two nucleophilic capturing pathways of the acyl azide 3.14, as ester formation is favoured and faster when concentration of acyl azide (3.14) is high in the presence of 3.16. Then as the acyl azide 3.14 competitively rearranges to the associated isocyanate 3.15, and quickly consumed to form 3.17, there is less opportunity for ester 3.18 formation. This simple example highlights the potential mechanistic insight that an on-line stopped-flow benchtop NMR system can provide. It should be noted that a reaction with both DPPA and 3.14 added sequentially (directly after one another) to a heated solution of 3.7 in toluene with TEA was also completed at the same scale (15.5 mL) and similar concentration (0.68 M). We observed similar formation of both the desired carbamate 3.17 and ester 3.18 via benchtop 19F NMR to the above discussed reaction (see Section 3.5.4.2.2). While it is well reported that the reaction of carboxylate and DPPA results in an acyl azide that undergoes a Curtius rearrangement upon heat exposure, the corresponding isocyanate (3.15) was not directly observed with our initial benchtop NMR studies. While this mechanistically was the logical precursor to desired carbamate product 3.17, it was hypothesized the reaction of 3.15 with alcohol 3.16 was too fast to visualize on our time-scale. To test this hypothesis, and minimize ester product formation, this reaction was performed with reversing the order of 3.16 addition and exposure to heat than our initial studies above. Therefore, our next reaction was again performed stepwise, with the same scale and concentrations as the previous reaction. DPPA (1.1 eq.) was added to a solution of 3.7 (0.67 M, 1 eq.) in solution of TEA (1.1 eq.) and toluene after 34 minutes of NMR data acquisition. The 133 formation of the corresponding 3.14 was monitored to reach an equilibrium concentration prior to heat exposure (80 °C). Upon heating successful Curtius rearrangement (along with alleviation of N2 gas) was observed, allowing for build-up of isocyanate 3.15 (𝛿F -116.1 ppm) in solution. Then, after 3.15 reached an equilibrium concentration, 3.16 (1.1 eq.) was added. Similar to the previous trial, the reaction vial was vented with a needle through the septum filled cap and no bubbles were observed entering or exciting the NMR flow cell. Additionally, our benchtop NMR system resulted in significant signal dispersion to both observe and quantify all resonances of interest (Figure 3.10). Figure 3.10. a) Reaction scheme for the carbamate forming reaction of 3.7 (0.67 M, toluene), TEA (1.1 eq.), DPPA (1.1 eq.), heat (80 °C) and 3.16 (1.1 eq.) added stepwise. b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired for the process, with increasing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of benchtop NMR system. DPPATEAToluene3.7OHOFN3OF3.14Δ3.15NFN2 (g)3.17HNFHO CF3CF3OOCF3CF33.16CO00.20.40.60 5 10 15 20Concentration (M)Time (h)-130-120-110-100-90-80-70f1 (19F / ppm)3.14b)a)c)t=0.0 ht=18.0 hIncreasing Timeadd DPPAadd 3.16Δ(80° C)3.163.173.153.7≈≈ 134 Upon addition of heat to the reaction solution with accumulated 3.14, we observed successful Curtius rearrangement, resulting in the formation of N2 gas and corresponding 3.15. The rearrangement was significantly slower (14.5 h) in reaching maximum concentration of this species (0.41 M), compared to the preparation of the acyl azide 3.14 precursor. This process additionally appeared to be less clean as several low-level side-products with an aryl fluoride moiety appeared to form - all with low SNR in the resulting benchtop 19F NMR spectra. The formation of these unidentified side-products help explain isocyanate 3.15 not reaching the same maximum concentration as acyl azide 3.14 (0.54 M). Nonetheless, upon addition of 3.16 to this reaction mixture predominately composed of isocyanate 3.15, the reaction produced the desired 3.17 rapidly. Conversion appeared complete after the acquisition of the first benchtop 19F NMR spectrum upon addition of 3.16 (∼8.5 minutes after injection). This observation was further consistent with our previous hypothesis and offered an explanation to why isocyanate 3.15 was not observed in the previous trial. Further, the concentration determination of this species using both trifluoromethyl moiety (𝛿F -73.4 ppm) and aryl fluoride (𝛿F -119.6 ppm) resonances appeared to be in great agreement (both 0.30 M) - with no nearby resonances spectrally overlapped. Additionally, formation of ester 3.18 was avoided and not observed with this sequence of reaction conditions. In both highlighted trials, irrespective of the order of 3.16 and heat addition, a doublet side-product resonance (𝛿F -74.2 ppm) appeared at low levels (maximum concentration ∼0.06 M if 3.16 added then heat, ∼0.02 M if heat then 3.16). This resonance is observable between the trifluoromethyl product resonance of carbamate 3.17 and that of alcohol 3.16 in Figure 3.8b and Figure 3.10b (between pink and green arrowed resonances). Given the chemical shift, multiplicity, and timing of resonance, we predicted this species encompassed and originated from the 135 trifluoromethyl moiety of 3.16. In the late 1970's, Bose and coworkers described Mitsunobu type reactivity with the use of DPPA for converting of alcohols to their corresponding azides.244 This, therefore, became our hypothesized origin of the observed side-product. To test this hypothesis, we performed a reaction with all components, other than carboxylic acid 3.7. Therefore, DPPA (1 eq.) was added to a solution of toluene and TEA (1 eq.) at the same concentrations and scale as the previous reactions. This solution was heated in an oil bath (80 °C) and then 3.16 (1 eq.) was subsequently added. This reaction was successfully monitored, and a product was observed to be formed (Figure 3.11). Figure 3.11. a) Reaction scheme for the Mitsunobu type reaction between DPPA and 3.16, with reagents added stepwise, as indicated in corresponding graph. b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired for the process, with increasing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of NMR system. 19F NMR spectra zoomed into spectral region between 𝛿F -72 and -78 ppm. DPPATEATolueneHO CF3CF33.16ΔN3 CF3CF33.19-78-77-76-75-74-73-72f1 (19F / ppm)00.10.20.30.40.50 2 4 6 8Concentration (M)Time (h)b)a)c)t=0.0 ht=7.8 hIncreasing Timeadd DPPAadd 3.16Δ(80° C)3.163.19 136 Upon further inspection of the acquired 19F NMR data, the product of the reaction with consistent chemical shift and multiplicity as the observed side-product in previous reactions (Figure 3.12). Therefore, we hypothesize this side-product is the corresponding azide (3.19) of alcohol 3.16. Due to this species being a suspected volatile azide, further isolation and characterization was not sought. Figure 3.12. a) Reaction scheme and final benchtop 19F NMR (57 MHz) spectrum of monitoring the formation of carbamate 3.17 from 3.7 (0.67 M, toluene) with TEA (1.1 eq.), DPPA (1.1 eq.), heat (80 °C) and 3.16 (1.1 eq.). b) Reaction scheme and final benchtop 19F NMR (57 MHz) spectrum of monitoring reaction progress of Mitsunobu type reactivity between 3.16 (0.52 M) and DPPA (1.0 eq.) in a heated solution (toluene, 80 °C) with TEA (1.0 eq.). 3.3.4 Simultaneous reaction monitoring via stopped-flow benchtop NMR and ReactIR - comparison of orthogonal monitoring techniques With no thermal insulation of the lines of the stopped-flow NMR system, it is logical to question how representative NMR data acquired with this system are of a reaction that is heated well above ambient temperature (such as the studied Curtius rearrangement in this report). Therefore, a Curtius rearrangement reaction was monitored with conditions of heat prior to 3.16 DPPATEATolueneHO CF3CF33.16ΔN3 CF3CF33.193.17HNFOOCF3CF3DPPATEAToluene3.7OHOFΔN2 (g)HO CF3CF33.16b)a)-77-76-75-74-73-72-71f1 (19F / ppm)Reaction in Figure 3.11Reaction in Figure 3.10 137 addition (analogous to reaction described in Figure 3.10) simultaneously via benchtop 19F NMR and ReactIR. The ReactIR was a Mettler Toledo ReactIR (702L) equipped with a Mettler Toledo DS Micro Flow Cell, placed between the pump and valve in the flow system. This was completed with the same stopped-flow benchtop NMR system as displayed in Figure 3.1, but with the PEEK line exiting the pump connected to the “in” port of the flow ReactIR and a 29 cm segment of PEEK tubing (1/16” O.D., 0.01” I.D.) placed to connect the “out” of the flow React IR to the valve (Figure 3.13). Applying the same procedure to determine the volume of the flow system without the ReactIR was also applied to determine the volume of the new system. The volume of this system was determined to be 1.89 mL. Figure 3.13. Schematic representation of the on-line stopped-flow benchtop NMR system (shown in valve position “A”) with a Mettler Toledo ReactIR (702L) equipped with a Mettler Toledo DS Micro Flow Cell placed between the pump and valve, allowing for simultaneous monitoring of a reaction via NMR and IR spectroscopies. Monitoring the described process via benchtop 19F NMR was again successful (Section 3.5.4.2.5, Figure 3.29) and resulted in reaction trends previously observed under these conditions (see Figure 3.10). Monitoring the reaction via ReactIR (Section 3.5.4.2.5, Figure 3.30), resulted 6-Port Valve Position: “A”flowingPumpBenchtopNMRFlow ReactIR 138 in successful observation of some of the major reaction species. This includes the carboxylic acid starting material 3.7 (trended with peak at 1120 cm-1), acyl azide intermediate 3.14 (trended with peak at 1696 cm-1), isocyanate intermediate 3.15 (trended with peak at 2272 cm-1), and desired carbamate product 3.17 (trended with peak at 1759 cm-1). Data analysis was performed in the iC IR software (Mettler Toledo) on the double derivative of the resultant IR spectra to assist in deconvolution of IR peaks. Monitoring the previously denoted reaction species (3.7, 3.14, 3.15, and 3.17) by either orthogonal technique generally resulted in similar trends, directly compared in Figure 3.14. The agreement provides evidence for the representative nature of the resulting 19F NMR trends, even despite the non-insulated lines of the stopped-flow benchtop NMR system when monitoring a heated process. The IR trend consistent with the intermediate isocyanate species 3.15 highlights the complex nature of IR data processing, as tracking the 19F NMR resonance consistent with this species via benchtop NMR resulted in a cleaner and arguably more reasonable/representative trend. Additionally, the quantitative nature of the 19F NMR trends further promotes the utility of benchtop NMR in such circumstance. Nonetheless, the general agreement of reaction trends (whether from ReactIR or benchtop NMR) provides validation of the representative nature of the discussed 19F NMR trends with this stopped-flow benchtop NMR system, even despite the lack of thermal insulation with the flow system. Additionally, this work highlights the flexibility of the stopped-flow benchtop NMR system, as other process analytical technologies can easily be appended to the system to offer additional orthogonal information on the reaction system. 139 Figure 3.14. Comparison of some major reaction components monitored via ReactIR (coloured trends) and benchtop 19F NMR (greyed trends). This includes a) carboxylic acid starting material 3.7, b) acyl azide intermediate 3.14, c) isocyanate intermediate 3.15, and d) desired carbamate product 3.17. 3.4 Conclusion We present an on-line stopped-flow benchtop NMR system that helps further the utility of benchtop NMR spectrometers in a synthetic laboratory or pharmaceutical setting. By monitoring relatively concentrated reaction solutions and observing 19F NMR, we were able to circumvent sensitivity and signal dispersion limitations intrinsic to benchtop NMR. It should be noted, however, that while we observed 19F with our model reaction systems, this stopped-flow benchtop NMR system could be carried out with observation of other nuclei that the spectrometer is capable 00.20.40.60.810 5 10 15 20Relative peak height (IR) or integral (NMR) Time (h)00.20.40.60.810 5 10 15 20Relative peak height (IR) or integral (NMR) Time (h)b)a)00.20.40.60.810 5 10 15 20Relative peak height (IR) or integral (NMR) Time (h)00.20.40.60.810 5 10 15 20Relative peak height (IR) or integral (NMR) Time (h)d)c)IR: 1120 cm-119F NMR: -110.4 ppmIR: 1696 cm-119F NMR -> -103.6 ppmIR -> 2272 cm-119F NMR -> -116.1 ppmIR -> 1759 cm-119F NMR -> -119.6 ppm 140 of observing (e.g., 1H or 31P, with or without deuterated solvents). Further, this system could be applied to monitor heterogeneous reactions with the addition of an in-line filter to the “in” line of the system. Special consideration and selection of such filter must be completed, however, to avoid fowling the filter surface over the reaction course. Additionally, careful consideration of our 19F NMR data acquisition allowed for qNMR to be reliably and consistently achieved using a set of acquisition parameters and the absolute intensity method. Application of our stopped-flow benchtop NMR system allows for flow analyses to be completed with the associated convenience and representative nature, but overall circumventing quantitative complications that arise under continuous-flow conditions. To highlight the utility of this stopped-flow benchtop NMR system, we monitored two model systems that would prove difficult with traditional NMR analyses, as each involves hazardous reagents and gas evolution. Applying this system to monitor the capture and hydrolysis of SO2F2 (3.4) allowed for an equilibrium concentration of this gas to be quantified, along with the half-life to be determined under hydrolysis conditions. This is particularly of interest for ridding this electrophilic and toxic gas of a system. We were also able to observe and quantify fluoride (3.6), a difficult species to non-destructively monitor with other analytical techniques. This system was further applied to successfully monitor the activation of a carboxylic acid (3.7) to an acyl fluoride (3.11), resulting in the quantification of the anhydride intermediate (3.10) and the dissolution constant of SO2F2 (3.4) to be discerned for this reaction system. Additionally, we applied this stopped-flow benchtop NMR system to monitor the carbamate (3.17) formation following a Curtius rearrangement of an acyl azide (3.14) formed with a 3.7 and DPPA. This allowed for elucidation of conditions resulting in an increase in 3.17 - heating the reaction solution to maximum isocyanate (3.15) conversion, prior to alcohol (3.16) addition. 141 Additionally, by heating (again, until maximum isocyanate conversion) prior to 3.16 addition, the formation of the competitive ester side-product (3.18) was avoided. Lastly, the application of this system led to the identification of an observed side-product with this Curtius rearrangement work - the conversion of alcohol 3.14 to its corresponding azide (3.19) with DPPA. While this system has helped informed synthetically relevant decisions for our lab, analyses of these acquired data with currently non-traditional tools, such as Complete Reduction to Amplitude Frequency Table (CRAFT),63,64 provides the opportunity to increase the robustness and accuracy of these quantitative results. Nonetheless, our work and the accompanying on-line stopped-flow system serves to further the utility of benchtop NMR spectrometers as a reliable, convenient, and quantitative reaction monitoring tool. 3.5 Experimental and further data 3.5.1 General 3.5.1.1 Chemicals Benzotrifluoride (3.1), trifluoroacetic acid (3.2), diisopropylethylamine (DIPEA), triethylamine (TEA), acetonitrile (MeCN), and methanol (MeOH) were purchased from Sigma-Aldrich. 1,1’-Sulfonyldiimidazole (3.3), 4-fluorobenzoic acid (3.7), and potassium fluoride (KF) were purchased from AK Scientific. Diphenylphosphoryl azide (DPPA) and hexafluoro-2-propanol (3.16) were purchased from Oakwood Chemicals. Lastly, toluene was purchased from Fischer Chemical. All reagents and solvents were used as received, unless otherwise stated. Silica was sourced from Silicycle (F60 60 Å, 230-400 mesh). 3.5.1.2 NMR data collection, processing, and analysis Chemical shifts (𝛿) are reported in parts-per-million (ppm) and all NMR data were processed and analyzed with MestReNova (Mnova) software. The following abbreviations were 142 used to describe multiplicities of resonances: s = singlet, d = doublet, q = quartet, sep = septet, br s = broad singlet, dd = doublet of doublets, m = multiplet. Additionally, all coupling constants (J) are provided in hertz (Hz). Benchtop 19F NMR data were processed with baseline correction (zeroth-order polynomial fit) and auto phase correction (manual phase correction applied if additional correction necessary). Additionally, data were processed with applied exponential apodization of 2.0 Hz. Benchtop NMR data were collected with a Nanalysis Scientific Corp. NMReady-60PRO spectrometer (1H 60.49 MHz and 19F 56.91 MHz). All offline high-field NMR data for structure elucidation were collected with a Bruker Avance 300 spectrometer (1H 300.13 MHz, 13C 75.48 MHz, 19F 282.40 MHz, 31P 121.49 MHz) and/or a Bruker Avance 400 spectrometer (1H 400.13 MHz, 13C 100.62 MHz, 31P 161.97 MHz). 3.5.1.3 Hazards and experimental precautions Reactions included in this work include hazardous material that must be taken under special consideration. Sulfuryl fluoride (SO2F2, 3.4) is a toxic, electrophilic gas and must only be worked with in well ventilated conditions. The included reactions involving 3.4 additionally may result in the formation of hydrofluoric acid, highly corrosive and dangerous. The Curtius rearrangement work involves both gas formation and hazardous azide handling. Consideration to avoid over pressurization with either reaction system (venting and/or balloon) must be taken. 3.5.2 Stopped-flow benchtop NMR system details 3.5.2.1 General physical description For a schematic of the stopped-flow benchtop NMR system, please see Figure 3.1 above. To facilitate stopped-flow benchtop NMR measurements, the NMR spectrometer was equipped with a glass flow cell (Nanalysis Scientific Corp.), with a total internal volume of approximately 143 1.20 mL (~ 0.575 mL within the reading frame of the instrument). The internal diameter of the flow cell within the reading frame is the same as a 5 mm NMR tube as the flow cell is initially made from a 5 mm NMR tube. The NMR instrument was additionally placed on internally designed and 3D printed legs (Figure 3.15). These legs allowed for the vibration dampening feet, while also allowing for additional clearance for the flow cell between the bottom of the flow cell and the lab bench. Figure 3.15. Close up picture displaying the utilized 3D printed legs, allowing for instrument to be slightly lifted (advantageous for flow cell) and use of the instrument’s vibration dampening features. To physically move solutions within the flow system, a peristaltic pump (SF-10 reagent pump, Vapourtec Ltd.) was used within the system. Solutions were directed either to the spectrometer or back to the vial determined by the position of Vici six-port valve (Figure 3.1). The hardware components of the flow system (pump, spectrometer, and valve) were connected by either ETFE tubing (1/16” O.D., 0.02” inner diameter I.D.) or PEEK tubing (1/16” O.D., 0.01” I.D.). The identity and lengths of each segment of line is designated in Figure 3.16. In our 144 experience the segments of smaller I.D. tubing were necessary to eliminate solvent cavitation, resulting from insufficient generation of backpressure. Further, the temperature of the reaction vial was further controlled using an oil bath on a hot plate, where appropriate and indicated. No temperature control is allowable with the NMR spectrometer itself (magnet internally controlled at constant 32 °C) and the segments of ETFE and PEEK tubing were not thermally insulated. Figure 3.16. Colour designated identity (ETFE or PEEK) and associated lengths of tubing for each segment of stopped-flow benchtop NMR system. 3.5.2.2 Description of workflow with Python script and stopped-flow NMR system As described previously, the stopped-flow benchtop NMR system’s hardware components are controlled remotely by a Python script developed by Dr. Lars P. E. Yunker. Prior to analysis, our work generally began by performing an autoshim protocol with the NMR spectrometer. This was performed on the reaction solvent (preferably on solution with starting material) until a linewidth ≤ 1.8 Hz was achieved. This was generally the case after a “Medium” or “Full” autoshim procedure. Then the workflow began with designating the observed nucleus (“19F” for our 19F NMR work), lock nucleus (“1H” for our work in non-deuterated, proteo solvents), the solvent (either “Acetonitrile” or “Toluene” in our included work), and the experiment (“1D” for our trials). ETFE 1/16” O.D., 0.02” I.D.PEEK 1/16” O.D., 0.01” I.D.45.4 cm 26.6 cm82.8 cm82.5 cm58.2 cm 145 By selecting “Experiment Settings”, the relevant acquisition parameters can be selected on the spectrometer (number scans, number dummy scans, pulse angle, AQ, SW, spectral offset, TD, d1, and receiver gain), which thereby determined the overall NMR experimental time. Then in the Python script (screenshot in Figure 3.17), the pre-magnetization time, pump flow rate, whether a spectrum at time zero (t=0 s) was desired, total number of spectra, and desired total time between spectra are denoted. This is considering that the spectrometer’s internet protocol (IP) address, communication (COM) port connected to valve, and valve serial number (turquoise arrows in Figure 3.17) are already inputted to script. This only needs to be done once considering these values don’t change. Further, we noticed that unless the pulse angle and fixed receiver gain is explicitly fixed in the script itself, these values may default to another spectrometer determined value. These can be denoted where designated with dark blue arrows in Figure 3.17. Once the reaction of interest is ready to be initiated, the “NMReady-CONNECT” feature on the spectrometer must be enabled to allow remote calls (done by going to “Setup” -> “System” -> “Network” -> “Remote” -> check box to enable “NMReady-CONNECT”). At this point, the script is ready to be started. Our reaction monitoring work generally began with acquiring a spectrum at t=0 s. Considering the valve in position “A” (our default position), once the script is started in PyCharm, the pump starts (at determined flow rate), and the valve instantly switches to position “B”. Therefore, at this point the reaction solution is static in the flow cell (note, no new solution enters the flow cell once the script is initiated with these conditions). After waiting the designated pre-magnetization time allowing for sufficient polarization of the spins in the static sample prior to application of RF pulse, NMR data is acquired per the acquisition parameters denoted on the spectrometer (pulse angle/receiver gain denoted in script). After data acquisition, the valve 146 switches position (position “A”) and fresh solution flows through the NMR flow cell for the remainder of the denoted time between spectra. The process is then repeated until the desired number of spectra are acquired, with the pump turning off after the final NMR spectrum is acquired. Figure 3.17. Annotated screenshot of the Python script allowing for convenient and centralized control of the stopped-flow benchtop NMR system, with important designations for analysis annotated. 147 3.5.2.3 Calibration of system’s peristaltic pump The used peristaltic pump (SF-10 reagent pump) was gravimetrically calibrated with the use of MeOH and five flow rates (later determined to be 0.7, 1.3, 2.2, 2.6, and 3.2 mL/min), with each flow rate analyzed in triplicate. To do so, three scintillation vials per flow rate were pre-weighed using an analytical balance. With the stopped-flow NMR system primed with MeOH and valve in position “A” (Figure 3.1), MeOH was pumped through the flow system and collected into one of the pre-weighed scintillation vials at a single set flow rate (1.0, 2.0, 3.3, 4.0, and 5.0 mL/min flow set flow rates analyzed) for 2 minutes. The mass of MeOH pumped in this time interval was converted to a volume using the density of MeOH - allowing for the actual flow rate to be determined. Within the flow rate range analyzed, these data suggested a conversion factor of 0.6495 to determine the actual flow rate (Figure 3.18) Figure 3.18. Calibration of Vapourtec SF-10 reagent peristaltic pump used for stopped-flow benchtop NMR system. y = 0.6495x + 0.0111R² = 0.9996012340 1 2 3 4 5 6Actual Flow Rate (mL/min)Set Flow Rate (mL/min) 148 3.5.2.4 Volume determination of benchtop NMR stopped-flow system With no thermal control of reaction solution in the lines of the stopped-flow benchtop NMR system, nor of the solution in the NMR spectrometer, it was of keen interest to understand the volume of the stopped-flow benchtop NMR system. This information was of interest as this fraction of the solution is not necessarily exposed to conditions (such as mixing or temperature) of the remainder of the reaction solution at any given point of time. To measure this volume, a 0.32 M solution of 3.1 was prepared using a microsyringe, brought to 25.00 mL with MeCN in a volumetric flask, and thoroughly mixed. Using a volumetric pipet, 5.00 mL of this solution was transferred to a scintillation vial, equipped with a magnetic stir bar and fitted with a septum filled cap. About 19 mL of the remainder solution in the volumetric flask was flowed through the stopped-flow benchtop NMR system (2.14 mL/min per previous calibration, valve in position “A” per Figure 3.1) and collected into a waste container, ensuring this solution was purely within the reading frame of the instrument. The pump was stopped and three 19F NMR spectra (“pre” spectra) were measured on the solution, each with the same acquisition parameters: 90° pulse, 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -50.0 ppm spectral offset, and 64.0 s 𝜏*. Post data acquisition, the solution in the flow system was evacuated and fresh MeCN was flowed into the system (again, collecting into waste at 2.14 mL/min with valve in position “A”) for ~ 20 minutes. With the system primed with fresh MeCN, the inlet and outlet lines of the system were transferred to the scintillation vial with the 5.00 mL of the 3.1 standard solution. On a magnetic stir plate, the solution in the vial was stirred (500 rpm) and the inlet line was placed well below the liquid level. The pump was then turned on (2.14 mL/min) and the solution was able to circulate and reach an equilibrium concentration over 20 minutes. After this time, the pump was 149 turned off and three 19F NMR spectra (“post” spectra) were measured on the solution with the same acquisition parameters previously described for the “pre” spectra. The above procedure was completed in duplicate (six total spectra for “pre” conditions and six total spectra for “post conditions”). Once spectra were imported and processed in Mnova, the absolute integration of the trifluoromethyl resonance (𝛿F -63.5 ppm) of 3.1 was determined. The average “pre” integration (587.9545, 1.48 % RSD) and average “post” integration (433.7993, 2.81 %) were used to determine the volume of the system based on a 5.00 mL “pre” volume. Therefore, the system’s volume (calculated 1.78 mL) was equal to the “post” volume minus the “pre” volume. The “post” volume was determined as per Equation 3.1 below. "𝑝𝑜𝑠𝑡" 𝑣𝑜𝑙𝑢𝑚𝑒 = "𝑝𝑟𝑒" 𝑁𝑀𝑅 𝑖𝑛𝑡𝑒𝑔𝑟𝑎𝑡𝑖𝑜𝑛 × "𝑝𝑟𝑒" 𝑣𝑜𝑙𝑢𝑚𝑒 "𝑝𝑜𝑠𝑡" 𝑁𝑀𝑅 𝑖𝑛𝑡𝑒𝑔𝑟𝑎𝑡𝑖𝑜𝑛 Equation 3.1 3.5.2.5 Determination of flow rate for subsequent analyses with benchtop NMR stopped-flow system Using too high of a flow rate (> 2.2 mL/min) with the utilized flow cell has shown eddying and mixing behaviours that are less than optimal for efficient emptying/filling with the flow system (as observed in Chapter 2). Therefore, we desired to use a medium flow rate to transfer reaction solution to the flow cell for analysis within a reasonable amount of time, without the introduction of behaviours that might be counterproductive for efficient filling/emptying. Considering some factors that would fix the time that analyte solution is static in the valve and NMR loop (such as the pre-magnetization time just prior to data acquisition and the NMR data acquisition time itself), we desired to flow fresh solution at a rate of the system’s volume per 150 minute, for no more than four minutes. This was in effort to decrease time between subsequent data points without jeopardizing the integrity and representative nature of acquired qNMR data. To verify this timing scheme resulted in both sufficient mixing and a representative sample for analysis, a solution of 3.1 in MeCN was once again used. A 0.24 M solution of 3.1 was prepared in a 10.00 mL volumetric flask, using a microsyringe to measure and transfer 3.1. This was then brought to 10.00 mL with fresh MeCN. Using a volumetric pipet, 5.00 mL was transferred to a scintillation vial that was configured with a magnetic stir bar and septum filled cap. The NMR flow system was cleaned and primed with fresh MeCN (valve in position “A” per Figure 3.1). With the spectrometer, 19F NMR data acquisition parameters were designated: 90° pulse, 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -50.0 ppm spectral offset, and 64.0 s 𝜏*. Relevant parameters were also designated in the Python script: collect spectrum at t=0, 15 s pre-magnetization time, 11 total time points after t=0, spectrum every 510 s, and a 1.78 mL/min pump flow rate. Then, with the inlet line placed well below the liquid level in the scintillation vial, stirring was initiated (500 rpm), and the spectrometer in “Remote” mode, the script was initiated. Once spectra were imported and processed in Mnova, the absolute integration of the trifluoromethyl resonance (𝛿F -63.5 ppm) of 3.1 was monitored as a function of time. To our delight, this timing scheme (3.94 minutes of analyte flow between time points with a 1.78 mL/min flow rate) appeared to result in efficient transfer of analyte (Figure 3.19). This was concluded based on the first data point with 3.1 observed at the second overall timepoint, and the concentration of 3.1 remained constant over the duration of analysis. No oscillation in 3.1 concentration was observed until an equilibrium concentration was achieved, expected if either the flow rate or time of flow needed to be adjusted to allow. Therefore, for all following stopped-flow 151 NMR analyses, this flow rate (1.78 mL/min) and time period of flow (3.94 min) to replenish solution in the NMR was used. Figure 3.19.Verification of sufficient transfer and mixing of analyte with a 1.78 mL/min flow rate and 3.94 min. Determined via 19F NMR (57 MHz) monitoring the trifluoromethyl resonance of 3.1 (𝛿F -63.5 ppm), with the system initially primed with MeCN. 3.5.3 19F NMR data acquisition parameter selection 3.5.3.1 Radiofrequency (RF) pulse calibration To verify pulse excitation, a sample of lithium bis(fluorosulfonyl)imide was gravimetrically prepared in a 50/50 mixture of H2O/D2O (0.26 M). Benchtop 19F NMR spectra were measured (in triplicate) with 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -60.0 ppm spectral offset, and 64.0 s 𝜏*. 16 pulse angles were analyzed from 0° to 372.5° (0.00°, 23.3°, 45.0°, 66.7°, 90.0°, 116.9°, 146.2°, 174.0°, 198.0°, 219.9°, 241.5°, 264.2°, 290.1°, 319.2°, 347.7°, and 372.5°) by changing the proportional pulse width (0, 2.9, 5.9, 8.8, 11.8, 14.7, 17.7, 20.6, 23.5, 26.5, 29.4, 32.4, 35.3, 38.3, 41.2, and 44.1 𝜇s respectively). Once these data were acquired and processed, the integral area for the symmetrical sulfonyl fluoride resonance (𝛿F 52.2 00.10.20.30 1 2 3 4Concentration (M)Time (h)F3.1F F 152 ppm) was monitored and plotted against anticipated pulse angle values. These data were compared expected sine function behaviour of relative resonance integration based on varying pulse angles (Figure 3.20). Figure 3.20. Results from calibration of RF pulse for benchtop 19F NMR system (57 MHz). These results are shown a) qualitatively with the lithium bis(fluorosulfonyl)imide resonance (𝛿F 52.2 ppm, spectra normalized to noise) and b) graphically with the observed and expected relative 19F NMR integration. 3.5.3.2 Spin-lattice relaxation time (T1) estimations In effort to allow for sufficient relaxation (at least five times the longest T1) between subsequent RF excitation to ensure quantitative NMR (qNMR) conditions, T1 values for each of the major chemical species were estimated in effort to determine the longest T1. To do so, the inversion recovery experiment73,74 was used. To determine the T1 of chemical species relevant to the sulfuryl fluoride work, a sample was prepared of carboxylic acid starting material 3.7 (0.09 M) in a 5 mL volumetric flask. An aliquot of this was transferred to a 5 mm NMR tube and 19F spectra were measured with 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -20.0 ppm spectral offset, and 103.8 s -1-0.6-0.20.20.610 90 180 270 360Relative 19F NMR IntegrationPulse Angle (°)a) b)ExperimentalTheroretical Pulse Width (!s)023°Pulse Angle 2.9 5.9 8.8 11.814.7 17.7 20.626.5 29.4 32.4 35.3 38.3 41.244.10°45°67°90°117°146°174°198°220°242° 264°290°319°373°348°23.5 153 𝜏*. The time between the 180° and 90° pulses (𝜏) was varied in 16 linearly spaced increments between 𝜏start (0.10 s) and 𝜏stop (16.0 s). Once processed in Mnova, these data were analyzed by integrating the signal corresponding to the aryl fluoride peak (𝛿F -107.9 ppm) and plotting this integration against 𝜏. These data were fitted to a line of best fit in Mnova, and a 𝜏null (𝜏 where signal integration/intensity was equal to zero) was calculated (Figure 3.21). Figure 3.21. Results from application of the inversion recovery experiment for T1 estimation of the aryl fluoride peak of 3.7 (57 MHz, 32 °C). These results are shown a) qualitatively with the resonance of interest (normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values. To determine the approximate T1 of observed products of the activation reaction with SO2F2 (3.4), an aliquot of a reaction mixture was analyzed. For this reaction, prior to the reaction commencing, a round-bottom flask (“vial 1”) was equipped with a magnetic stir bar, KF (7.32 g, 126 mmol), 3.3 (8.92 g, 45.0 mmol), and water (10 mL). This vial was connected to another round-bottom flask (“vial 2”) via a small segment of tubing. Vial 2 was equipped with an empty balloon, and 3.7 (1.26 g, 9.00 mmol), DIPEA (4.70 mL, 27.0 mmol), and MeCN were added. 3.1 (368 uL, 0 2 4 6 8 10 12 14 16Tau (s)-1012Integration-120-115-110-105-100f1 (19F / ppm)3.7OHOFY' = B+F*exp(-Tau *G)B=2.468; F=-4.329; G=0.2561;Error: 0.005568a) b)Increasing ! 154 3.00 mmol) was also added to vial 2 as an internal standard. While 3.1 was not used to calculated concentrations of species, the system’s CCF was leveraged to do so, it was used for validation of the qNMR method. The reaction was initiated by SO2F2 formation, initiated by slowly dosing TFA (3.2, 306 mmol, 23.4 mL) into vial 1 (over 10 minutes with the use of a New Era NE-1000 syringe pump). After ~ 8 hours of reaction progress, an aliquot was transferred to a 5 mm NMR tube and the inversion recovery experiment was used. First, T1 estimates for fluorosulfate (FSO3-, 3.5, 𝛿F 37.3 ppm), acyl fluoride resonance of product 3.11 (𝛿F 16.5 ppm), and 3.1 (𝛿F -63.5 ppm) were calculated. This was achieved by measuring 19F spectra with 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -10.0 ppm spectral offset, and 53.8 s 𝜏*. The time between the 180° and 90° pulses (𝜏) was varied in 35 linearly spaced increments between 𝜏start (0.01 s) and 𝜏stop (15.0 s). These data were fit to a trend and T1 values were calculated consistent with previous analyses. The resonance consistent with SO2F2 (3.4, 𝛿F 33.6 ppm) appeared to have a T1 less than the acyl fluoride resonance of 3.11, and as this resonance did not have the longest T1, it was not calculated. These results were additionally insightful and considered for the SO2F2 hydrolysis work (Figure 3.22). 155 Figure 3.22. Results from application of the inversion recovery experiment for T1 estimation of some of the products of the activation reaction of interest using SO2F2 (3.4) activation reaction of interest (57 MHz, 32 °C). These results are shown a) qualitatively with the resonances of interest (decimated spectra, normalized to noise) and b) graphically with peak integrations of each of the resonance graphed with application of various 𝜏 values. While this experiment was adequate to properly characterize the recovery of magnetization for the aforementioned product resonances with the used 𝜏 and d1 values, it appeared inadequate to properly characterize the z-magnetization recovery for the aryl fluoride resonance of 3.11. Therefore, 19F spectra were measured with 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -20.0 ppm spectral offset, and 104.8 s 𝜏*. The time between the 180° and 90° pulses (𝜏) was varied in 16 linearly spaced increments between 𝜏start (0.01 s) and 𝜏stop (90.0 s). These acquisition parameters allowed for the data to be fit to a trendline and a T1 value was adequately estimated for the aryl fluoride resonance of 3.11 (Figure 3.23). 3.11FOF0 2 4 6 8 10 12 14Tau (s)-5-3-1135Integrationa) b)Increasing !F S FO O3.4F S OO O3.5 F3.1F FY' = B+F*exp(-Tau *G)B=5.288; F=-10.35; G=0.4853;Y2' = B+F*exp(-Tau *G)B=2.554; F=-4.795; G=0.3752;Y1' = B+F*exp(-Tau *G)B=2.288; F=-4.525; G=0.1797;-65-6015203540f1 (19F / ppm) 156 Figure 3.23. Results from application of the inversion recovery experiment for T1 estimation of the aryl fluoride peak of the acyl fluoride product (3.11, 57 MHz, 32 °C). These results are shown a) qualitatively with the resonance of interest (normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values. To determine the approximate T1 of relevant components of the Curtius rearrangement work, an aliquot of a reaction mixture was analyzed. The reaction mixture used for this analysis was the same solution that was analyzed overtime and showcased in Figure 3.10. This sample, however, was analyzed after the time course data was acquired. The 19F spectra were measured with 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -85.0 ppm spectral offset, and 63.8 s 𝜏*. The time between the 180° and 90° pulses (𝜏) was varied in 16 linearly spaced increments between 𝜏start (0.001 s) and 𝜏stop (20.0 s). These acquisition parameters allowed for the data to be fit to a trendline and T1 values were calculated consistent with previous analyses. The estimated T1 values of each compound of interest were all short (less than 1.2 s) and, therefore, the resulting curves could be better characterized at lower 𝜏 values than the utilized experimental 3.11FOF0 10 20 30 40 50 60 70 80 90Tau (s)-2-10123Integration-107-106-105-104-103-102-101-100-99f1 (19F / ppm)Y' = B+F*exp(-X*G)B=2.942; F=-4.970; G=0.05974;a) b)Increasing ! 157 parameters. Nonetheless, these data provided confirmation that our utilized d1 for reaction monitoring fulfilled quantitative requirements (Figure 3.24). Figure 3.24. Results from application of the inversion recovery experiment for T1 estimation of reaction species relevant to Curtius rearrangement work (57 MHz, 32 °C). A reaction mixture (reaction shown in Figure 3.10) well past its end point was used for analysis. These results are shown a) qualitatively with the resonances of interest (decimated spectra, note left and right spectra are of different intensities) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values. 3.5.3.3 Radiofrequency (RF) pulse excitation over 220 ppm spectral range To observe uniform resonance excitation over the desired SW 220 ppm for our benchtop 19F NMR analyses, a sample of 3.1 (0.63 M) was prepared by bringing 3.1 to 2 mL with MeCN in a volumetric flask. Once an aliquot was transferred to a 5 mm NMR tube, 19F spectra were measured in triplicate with a 90° pulse, 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, and 32.8 s 𝜏*. Spectral offsets were changed such that the resonance consistent with 3.1 (𝛿F -63.5 ppm) changed its relative off resonance position (± 5.6 kHz) and the following spectral offsets were selected: -162.0, -151.0, -129.0, -107.0, -85.0, -63.0, -41.0, -19.0, 3.0, 25.0, and 36.0 ppm. Once the spectra were transferred and processed in Mnova, the average absolute integration 3.15NFCO0 2 4 6 8 10 12 14 16 18 20Tau (s)-80-4004080Integrationa) b)Increasing !Y1' = B+F*exp(-Time *G)B=83.33; F=-159.9; G=0.7836;Y' = B+F*exp(-Time *G)B=62.47; F=-119.9; G=1.165;Y3' = B+F*exp(-Time *G)B=10.09; F=-17.88; G=0.7276;Y2' = B+F*exp(-Time *G)B=1.734; F=-2.982; G=0.9052;-78-76-74-72f1 (19F / ppm)-120-110f1 (19F / ppm)-120-100-80-601020304050f1 (19F / ppm)HO CF3CF33.163.17HNFOOCF3CF3 158 per resonance position was determined. The average integrations were normalized and these were plotted against spectral position (Figure 3.2). 3.5.3.4 19F NMR concentration conversion factor (CCF) determination and verification To determine a CCF, 3.1 (0.67 M) was gravimetrically measured and brought to 5 mL in MeCN. The purity of 3.1 (99 %) was considered for determining an accurate CCF. This stock solution was used in a 1:1 serial dilution with MeCN to prepare seven total samples. These samples were then analyzed via benchtop 19F NMR, as spectra were measured in triplicate with 90° pulse, 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -60.0 ppm spectral offset, and 64.8 s 𝜏*. These spectra were processed and the singlet resonance consistent with the trifluoromethyl substituent of 3.1 (𝛿F -63.5 ppm) was integrated. The absolute integration was plotted against the concentrations. The inverse of this slope was divided by 3 (the number of 19F nuclei responsible for the resonance) and this represented the CCF per nuclide for a given resonance (Figure 3.3a). This CCF was verified by preparing a stock solution of TFA (3.2) in MeCN (0.38 M) gravimetrically and bringing this to 5 mL with MeCN. The purity of TFA (3.2, 99 %) was also considered into account to accurately determine concentration of solution. This stock solution was used in a 1:1 serial dilution with MeCN to prepare four total samples with varying concentrations of TFA (3.2). These samples were then analyzed via benchtop 19F NMR, as spectra were measured in triplicate with a 90° pulse, 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -60.0 ppm spectral offset, and 64.8 s 𝜏*. These spectra were processed and the singlet resonance consistent with TFA (3.2, 𝛿F -77.0 ppm) was integrated. The absolute integration and previously determined CCF were used to calculated concentrations. These concentrations calculated via 19F qNMR were then graphed against the gravimetrically determined concentrations (Figure 3.3b). 159 3.5.3.5 Monitoring change in NMR response with differing ionic strength A 0.20 M solution of TFA (3.2) was prepared by transferring the species via microsyringe to a volumetric flask and bringing to 25.00 mL with H2O. After mixing this solution, 10.00 mL was transferred (via volumetric pipet) to a scintillation vial equipped with a septum filled cap and magnetic stir bar. This solution was then flowed through the stopped-flow benchtop NMR system (cleaned and dried). Once the system was well primed, this solution was analyzed via benchtop 19F NMR, as spectra were measured in triplicate with a 90° pulse, 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -60.0 ppm spectral offset, and 64.8 s 𝜏*. The system was evacuated of the solution, NaCl was added (0.3065 g) to prepare a 0.52 M solution and the solution was allowed to circulate through the system (~ 15 minutes). The pump was then halted, leaving the analyte static in the NMR for analysis. Benchtop 19F NMR spectra (in triplicate) were measured with the same acquisition parameters as previously listed. This process was repeated by adding 0.3208 g, 0.3062 g, 0.3248 g, and 0.3196 g NaCl sequentially, preparing 1.0 M, 1.6 M, 2.1 M, and 2.7 M solutions, respectively. Once completed, these spectra were processed and analyzed with Mnova. The singlet resonance consistent with the trifluoromethyl substituent of TFA (3.2, 𝛿F -77.0 ppm) was integrated. The average of the absolute integration was plotted against NaCl concentrations where a decrease in 2.8 % integral area can be expected per 1.0 M increase in ionic strength (Figure 3.25). 160 Figure 3.25. Effect of change in ionic strength (by altering NaCl concentrations) on the average benchtop 19F NMR (57 MHz) integration of the resonance consistent with 3.2 (𝛿F -77.0 ppm). 3.5.4 Reaction monitoring and further relevant data 3.5.4.1 Reactions involving sulfuryl fluoride (SO2F2) 3.5.4.1.1 Capture and hydrolysis of sulfuryl fluoride (SO2F2) Prior to the hydrolysis reaction commencing, a standard solution with 3.1 (0.19 M) was created in a volumetric flask, brought 25.00 mL with MeCN. After mixing this solution, 10.00 mL was transferred to a scintillation vial (“vial 2”) equipped with a magnetic stir bar and septum filled cap. The remainder was used to prime the stopped-flow system with this standard solution. When ~ 1 mL remained in the volumetric flask, the inlet and outlet lines of the stopped-flow system were transferred to vial 2, ultimately increasing the volume of vial 2 by 1.78 mL by adding the system’s volume. Next, a round-bottom flask (“vial 1”) was equipped with a magnetic stir bar, KF (2.5350 g, 44.1 mmol), 3.3 (3.5350 g, 17.6 mmol), and H2O (11.5 mL). Vial 1 was additionally fitted with a septum and connected to vial 2 via PEEK tubing (~ 49 cm). Vial 2 was then placed in y = -0.0279x + 1.004300.20.40.60.810 1 2 3Relative 19F NMR Absolute Inetgration NaCl Concentration (M)3.2OHFOFF 161 a heated water bath (40 °C), fitted with a balloon, and stirring was applied to each vial. Once TFA (3.2, 8.5 mL) was measured, a syringe pump (New Era NE-1000) was prepared to dose this reagent over 10 min into vial 1. After the NMR spectrometer and Python script were configured with experimental parameters, the script was started. Immediately following, a small segment of PEEK tubing attached to the syringe to allow for TFA (3.2) dosing was connected to vial 1 and the syringe pump was started. After the 7th benchtop 19F NMR spectrum was acquired, an equilibrium concentration of SO2F2 (3.4, ~ 0.1 M, 1 eq.) appeared to be reached. Therefore, once the 8th spectrum started to be acquired, the connecting line between vial 1 and vial 2 was removed (vial 2 was still septum capped) and both H2O (0.08 mL, 2.4 eq.) and DIPEA (1.4 mL, 5.8 eq.) were dosed into vial 2. Observation of this reaction mixture continued for the remainder of time points. For this trial, benchtop 19F NMR spectra were measured with a 90° pulse, 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -50.0 ppm spectral offset, and 28.8 s 𝜏*. In the Python script, 44 timepoints were collected every 366 s, with a 15 s pause time, 1.78 mL/min calibrated pump rate, and an additional t=0 s spectrum collected. Results from this reaction can be found summarized in Figure 3.5. Additionally, a picture highlighting this system for this reaction monitoring procedure can be found in Figure 3.26. 162 Figure 3.26. Picture of the experimental setup to study the hydrolysis of SO2F2 (3.4). From left to right one can see the syringe pump dosing TFA (3.2), vial 1 (round-bottom flask) connected to vial 2 (scintillation vial), and the stopped-flow benchtop NMR system. Note of caution: this process involves the evolution and use of a toxic gas so special consideration to perform this work in a well-ventilated space must be done. Additionally, precautions to avoid over-pressurization of the system must be taken. 3.5.4.1.2 Activation if a carboxylic acid with sulfuryl fluoride (SO2F2) To a round-bottom flask (“vial 1”) a magnetic stir bar, KF (5.1239 g, 87.7 mmol), 3.3 (7.0250 g, 35.09 mmol), and H2O (24.0 mL), were added. Next, a standard solution was prepared by transferring DIPEA (6.30 mL, 35.8 mmol) and 3.1 (0.60 mL, 4.84 mmol) to a volumetric flask, and this was brought to 25.00 mL with MeCN. A portion of this solution (10.00 mL) was transferred to a scintillation vial (“vial 2”) with 3.7 (7.0250 g, 7.03 mmol, 1 eq.), a magnetic stir bar, and fitted with a septum filled cap. The stopped-flow benchtop NMR system was cleaned and primed with MeCN, after which the inlet and outlet lines were connected to vial 2 (inlet line below liquid level, system’s volume 163 added to the overall total volume in vial 2, 11.78 mL total). Additionally, vial 2 was connected to vial 1 by a small segment of PEEK tubing (~ 49 cm), fitted with a balloon, and was lowered into a 40 °C heated oil bath. TFA (3.2, 17.0 mL) was then measured, and a syringe pump (New Era NE-1000) was prepared to dose this reagent over 10 min into vial 1. After the NMR spectrometer and Python script were configured with experimental parameters, the script was started. Immediately following, a small segment of PEEK tubing attached to the syringe to allow for dosing TFA (3.2) was connected to vial 1 and the syringe pump was started. Observation of this reaction mixture continued for the remainder of time points. For this trial, benchtop 19F NMR spectra were measured with a 90° pulse, 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -40.0 ppm spectral offset, and 63.8 s 𝜏*. In the Python script, 33 timepoints were collected every 510 s, with a 15 s pause time, 1.78 mL/min calibrated pump rate, and an additional t=0 s spectrum collected. Results from this reaction can be found summarized in Figure 3.6. Pictures of the experimental configuration can be found in Figure 3.27. 164 Figure 3.27. Picture of the experimental setup (a) up-close and b) of the entire stopped-flow system) to study the activation 3.7 with SO2F2 (3.4). Note of caution: this process involves the evolution and use of a toxic gas so special consideration to perform this work in a well-ventilated space must be done. Additionally, precautions to avoid over-pressurization of the system must be taken. 3.5.4.2 Reactions relevant to Modified Curtius rearrangement 3.5.4.2.1 Stepwise Curtius rearrangement and carbamate formation - hexafluoroisopropyl alcohol (3.16) addition prior to heat To a scintillation vial, 3.7 (1.0383 g, 7.34 mmol, 1 eq.), 10.00 mL toluene, TEA (1.1 mL, 1.1 eq.), and a magnetic stir bar were added prior to being fitted with a septum filled cap and venting needle. The stopped-flow benchtop NMR system was cleaned and primed with toluene, after which the inlet and outlet lines were connected to the vial (inlet line below liquid level). Therefore, the system’s volume was added to the overall total volume of toluene in the vial (now 11.78 mL). After the NMR spectrometer and Python script were configured with experimental parameters, the script was started. 165 Once the 4th benchtop 19F NMR spectrum started acquisition, DPPA (1.8 mL, 1.1 eq.) was added. Then, 3.16 (0.84 mL, 1.1 eq.) was added to the reaction solution once the 12th spectrum started to be acquired as significant conversion from 3.7 to the corresponding acyl azide (3.14) was observed. This reaction solution remained untouched until after the 26th spectrum was acquired, when the reaction solution was lowered to a pre-heated oil bath (80 °C). The reaction was then monitored for the remaining time points as denoted with the script. For this trial, benchtop 19F NMR spectra were measured with a 90° pulse, 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -90.0 ppm spectral offset, and 63.8 s 𝜏*. In the Python script, 174 timepoints were collected every 510 s, with a 15 s pause time, 1.78 mL/min calibrated pump rate, and an additional t=0 s spectrum collected. Results from this reaction can be found summarized in Figure 3.8 in the chapter above. 3.5.4.2.2 Modified Curtius rearrangement and carbamate formation - reagents added directly after one another to a heated solution To a scintillation vial, 3.7 (1.0335 g, 7.30 mmol, 1 eq.), 10.00 mL toluene, TEA (1.1 mL, 1.1 eq.), and a magnetic stir bar were added prior to being fitted with a septum filled cap and venting needle. The stopped-flow benchtop NMR system was cleaned and primed with toluene, after which the inlet and outlet lines were connected to the vial (inlet line below liquid level). Therefore, the system’s volume was added to the overall total volume of toluene in the vial (now 11.78 mL). The vial was now lowered into a pre-heated oil bath (80 °C). After the NMR spectrometer and Python script were configured with experimental parameters, the script was started. Once the Python script was started, DPPA (1.8 mL, 1.1 eq.) and 3.16 (0.84 mL, 1.1 eq.) were added sequentially. The reaction was then monitored for the remaining time points as denoted with the script. 166 Note: the pump halted operation after the spectrum at the 5.24 h timepoint being acquired. Spectra were still collected, but of the halted reaction mixture in the instrument. Despite losing insight into the reaction system between 5.24 and 8.39 h, pump operation was restored remotely allowing for the remainder of time points to be accurately acquired. For this trial, benchtop 19F NMR spectra were measured with a 90° pulse, 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -90.0 ppm spectral offset, and 63.8 s 𝜏*. In the Python script, 144 timepoints were collected every 510 s, with a 15 s pause time, 1.78 mL/min calibrated pump rate, and an additional t=0 s spectrum collected. Results from this reaction can be found summarized in Figure 3.28 below. 167 Figure 3.28. a) Reaction scheme for the carbamate forming modified Curtius rearrangement of 3.7 (0.68 M, toluene, 80 °C) with TEA (1.1 eq.) DPPA (1.1 eq.) and 3.16 (1.1 eq.) and reagents added sequentially, directly after one another. b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired on the process, with easing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of NMR system. 3.5.4.2.3 Stepwise Curtius rearrangement and carbamate formation - heat prior to hexafluoroisopropyl alcohol (3.16) addition To a scintillation vial, 3.7 (1.0363 g, 7.34 mmol, 1 eq.), 10.00 mL toluene, TEA (1.1 mL, 1.1 eq.), and a magnetic stir bar were added prior to being fitted with a septum filled cap and venting needle. The stopped-flow benchtop NMR system was cleaned and primed with toluene, after which the inlet and outlet lines were connected to the vial (inlet line below liquid level). Therefore, the system’s volume was added to the overall total volume of toluene in the vial (now DPPATEAToluene3.7OHOFN3OF3.14Δ3.15FN2 (g)3.17HNF3.16HO CF3CF3OOCF3CF3ΔHN33.18OOFCF3CF33.16NCO00.20.40.60.80 5 10 15 20Concentration (M)Time (h)-120-110-100-90-80-70f1 (19F / ppm)3.14b)a)c)t=0.0 ht=20.4 hIncreasing Time3.163.173.183.7≈≈ 168 11.78 mL). After the NMR spectrometer and Python script were configured with experimental parameters, the script was started. Once the 5th benchtop 19F NMR spectrum started acquisition, DPPA (1.8 mL, 1.1 eq.) was added. Then, once the 14th spectrum started to be acquired, the reaction solution was lowered to a pre-heated oil bath (80 °C) as significant conversion of 3.7 to the corresponding 3.14 was observed. 3.16 (0.84 mL, 1.1 eq.) was added to the reaction solution once the 116th spectrum started to be acquired as significant conversion from the 3.14 to the corresponding isocyanate 3.15 was observed. The reaction was then monitored for the remaining time points as denoted with the script. For this trial, benchtop 19F NMR spectra were measured with a 90° pulse, 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -90.0 ppm spectral offset, and 63.8 s 𝜏*. In the Python script, 136 timepoints were collected every 510 s, with a 15 s pause time, 1.78 mL/min calibrated pump rate, and an additional t=0 s spectrum collected. Results from this reaction can be found summarized in Figure 3.10. 3.5.4.2.4 Mitsunobu type reaction between diphenylphosphoryl azide (DPPA) and hexafluoroisopropyl alcohol (3.16) To a scintillation vial, 10.00 mL toluene, TEA (1.1 mL, 7.83 mmol, 1.0 eq.), and a magnetic stir bar were added prior to being fitted with a septum filled cap and venting needle. The stopped-flow benchtop NMR system was cleaned and primed with toluene, after which the inlet and outlet lines were connected to the vial (inlet line below liquid level). Therefore, the system’s volume was added to the overall total volume of toluene in the vial (now 11.78 mL). After the NMR spectrometer and Python script were configured with experimental parameters, the script was started. 169 Once the 2nd benchtop 19F NMR spectrum started acquisition, DPPA (1.8 mL, 1.0 eq.) was added. Then, once the 4th spectrum started to be acquired, the reaction solution was lowered to a pre-heated oil bath (80 °C). 3.16 (0.84 mL, 1.0 eq.) was added to the reaction solution once the 7th spectrum started to be acquired. The reaction was then monitored for the remaining time points as denoted with the script. For this trial, benchtop 19F NMR spectra were measured with a 90° pulse, 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -90.0 ppm spectral offset, and 63.8 s 𝜏*. In the Python script, 55 timepoints were collected every 510 s, with a 15 s pause time, 1.78 mL/min calibrated pump rate, and an additional t=0 s spectrum collected. Results from this reaction can be found summarized in Figure 3.11. 3.5.4.2.5 Simultaneous reaction monitoring via stopped-flow benchtop NMR and ReactIR - comparison of orthogonal monitoring techniques The stopped-flow benchtop NMR system equipped with a ReactIR was tested with the Curtius rearrangement process previously highlighted and with conditions analogously described above. Therefore, 10.00 mL of toluene was added to a scintillation vial equipped with a magnetic stir bar and septum filled cap (with venting needle). With the stopped-flow benchtop NMR system pumping fresh toluene (collecting into waste), the ReactIR was blanked on toluene and these “in” and “out” lines were connected to the scintillation vial (adding 1.89 mL toluene to overall volume). Next, TEA (1.1 mL, 1.0 eq.) was added to the vial and allowed to circulate. With the “in” line pulled out of solution, 3.7 (1.0361 g, 7.32 mmol, 1 eq.) was added. Once the solution appeared homogeneous, the “in” line was again placed well below the liquid level. After, the NMR spectrometer and Python script were configured with experimental parameters, the stopped-flow 170 script was started, and IR spectra began to be collected every minute using the iC IR software (Mettler Toledo). Once the 5th benchtop 19F NMR spectrum started acquisition, DPPA (1.8 mL, 1.1 eq.) was added. Then, once the 15th spectrum started to be acquired, the reaction solution was lowered to a pre-heated oil bath (80 °C) as significant conversion of 3.7 to the corresponding 3.14 was observed. 3.16 (0.84 mL, 1.1 eq.) was added to the reaction solution once the 135th spectrum started to be acquired as significant conversion from 3.14 to the corresponding isocyanate 3.15 was observed. The reaction was then monitored for the remaining time points as denoted with the script. For this trial, benchtop 19F NMR spectra were measured with a 90° pulse, 4 scans, no dummy scans, 2.79 s AQ, 12,500 Hz (219.6 ppm) SW, -90.0 ppm spectral offset, and 63.8 s 𝜏*. In the Python script, 170 timepoints were collected every 510 s, with a 15 s pause time, 1.78 mL/min calibrated pump rate, and an additional t=0 s spectrum collected. Results from this reaction, monitored by both benchtop 19F NMR and ReactIR can be found separately below in Figure 3.29 and Figure 3.30, respectively. Additionally, NMR and IR trends are directly compared for components in Figure 3.14. 171 Figure 3.29. a) Reaction scheme for the carbamate forming modified Curtius rearrangement of 3.7 (0.61 M, toluene) with TEA (1.1 eq.), DPPA (1.1 eq.), heat (80 °C) and 3.16 (1.1 eq.) added stepwise. b) Decimated stacked array of benchtop 19F NMR spectra (57 MHz) acquired for the process, with increasing time from bottom to top. c) Concentration trends determined using resonance absolute integration and CCF of NMR system. DPPATEAToluene3.7OHOFN3OF3.14Δ3.15NFN2 (g)3.17HNFHO CF3CF3OOCF3CF33.16CO-140-130-120-110-100-90-80-70f1 (19F / ppm)3.14b)a)c)t=0.0 ht=19.1 hIncreasing Timeadd DPPAadd 3.16Δ(80° C)3.163.173.153.7≈≈00.20.40.60 5 10 15 20Concentration (M)Time (h) 172 Figure 3.30. Full waterfall plots representing the ReactIR data acquired over the entire reaction course with a) allowing for better visualization of peaks with smaller wavenumbers and b) the same data but rotated to allow for better visualization of peaks with larger wavenumbers. 3.5.5 Product Characterization 3.5.5.1 4-fluorobenzoyl fluoride (3.11) 3.11 was synthesized from 3.7 and 3.4, per Section 3.5.4.1.2. Isolation of this product was attempted to be isolated via silica gel column chromatography but was unsuccessful. This is consistent with literature reports of the compound being to be slightly unstable to silica gel.245 Nonetheless, characterization was successful on the DMSO soluble components of the reaction mixture - resulting in data consistent with previously reported data.245,246 173 1H NMR (300 MHz, DMSO-d6) 𝛿H 8.13 (m, 2H), 7.47 (m, 2H); 13C{1H} NMR (100 MHz, MeCN with 10 v/v% MeCN-d3) 𝛿C 166.70 (d, J = 255.5 Hz), 156.15 (d, J = 342.4), 134.54 (dd, J = 10.3, 3.9 Hz), 120.78 (dd, J = 62.2 Hz, 2.8 Hz), 116.83 (dd, J = 22.9, 1.0 Hz); 19F NMR (282 MHz, DMSO-d6) 𝛿F 17.28 (s), -102.62 (m); MS-EI (m/z) 142.18 [M]+ (Calculated for C7H4F2O, 142.02). 3.5.5.2 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl)carbamate (3.17) 3.17 was synthesized from 3.7 using DPPA and 3.16, per protocols listed in Section 3.5.4.2.1 - Section 3.5.4.2.5 (in varying yields depending on conditions). For successful isolation, reaction solution was extracted with hexanes (2 × 15 mL). Once combined, these hexanes layers were dried down via rotary evaporation and isolation was successful by silica gel column chromatography using hexanes. Product was obtained as white crystals. 1H NMR (400 MHz, CD2Cl2) 𝛿H 7.40 (m, 2H), 7.13 (br s, 2H), 7.08 (m, 2H), 5.83 (sep, 1H); 13C{1H} NMR (100 MHz, CD2Cl2) 𝛿C 160.23 (d, J = 244.0 Hz), 150.28, 132.78, 121.64 (d, J = 8.1 Hz), 121.01 (q, J = 281.8 Hz), 68.02 (sep, J = 281.8 Hz); 19F NMR (282 MHz, CD2Cl2) 𝛿F -73.94 (d, J = 6.2 Hz), -102.74 (m); MS-EI (m/z) 305.06 [M]+ (Calculated for C10H6F7NO2, 305.03). 3.11FOF3.17HNFOOCF3CF3 174 Chapter 4: A reliable external calibration method for reaction monitoring with benchtop NMR 4.1 Introduction Nuclear magnetic resonance (NMR) spectroscopy provides structural information about species in the test sample and its inherent quantitative nature has been understood since the early 1960’s.79,80 Importantly, quantitative information can be obtained with NMR spectroscopy non-destructively, relatively quickly, and with minimal or no sample preparation. Additionally, this information is acquired non-specifically, allowing quantitative information to be obtained and assigned to all individual components in the test sample at once. To many chemists, quantitative NMR (qNMR) is still associated with high-field NMR spectrometers. In recent years, however, the availability of benchtop NMR instruments has enabled the acquisition of structurally-rich, quantitative data in settings where chemistry is taking place, such as laboratory fumehoods, pilot plants, and manufacturing facilities.125,195,247 While notable limitations with benchtop NMR systems do exist (decrease in both sensitivity and signal dispersion), the benefits include a smaller physical size and a reduced cost (both to purchase and maintain). As the access to benchtop NMR systems increases the ability of analysts to perform NMR measurements in a variety of non-traditional settings, special consideration must still be given to two important phenomena: polarization and excitation.205 Upon fulfilment of the needed requirements of these key considerations allows for NMR to be quantitative. Equation 4.1 describes the quantitative nature of NMR with 𝑆 representing the measured NMR signal (resonance integration or intensity in the frequency-domain), 𝑘 representing a proportionality 175 constant (for NMR spectrometer, probe, acquisition parameters, temperature, sample, etc.), and 𝑁 representing the number of nuclei responsible for resonance.202,216 𝑆 = 𝑘 ∙ 𝑁 Equation 4.1 For Equation 4.1 to be applicable for qNMR, irrespective of the quantitative technique applied, full equilibrium of polarization must be achieved for all nuclei desired to be quantified (as discussed in Chapter 1, Section 1.1.3.1). Generally, to fulfill this requirement, the sample must be exposed to the external magnetic field of the instrument and the NMR experiment must have a repetition time (if signal averaged) at least five times the longest spin-lattice relaxation time (T1) with an applied 90° pulse. Using a repetition time of ≥ 5 × T1 ensures over 99 % of polarization is recovered prior to the 90° RF pulse. The T1 of nuclei can be estimated using an inversion recovery experiment73,74 or other techniques such as FLIPS (Faster Longitudinal relaxation Investigated by Progressive Saturation).72 The importance of considering polarization and T1 values is only underscored with the use of flow NMR systems, where in-flow and out-flow effects may be observed with an actively flowing analyte.174–177,180 As per the excitation requirement for qNMR, resonances to be compared must be equally excited. In the case of 1H NMR, the small chemical shift range (~12 ppm) generally results in easy satisfaction of this requirement. However, when monitoring nuclei with a larger chemical shift ranges, such as 19F, particular attention is due as the pulse width is inversely proportional to the spectral range with equal excitation.204 This can be mathematically determined using the pulse width (excluding effects of digital filter) or empirically determined by monitoring changes in 176 signal intensity with varying offset values. Importantly, assuming the same pulse width is used, benchtop NMR systems will yield a larger spectral region (in ppm) of equal excitation than high-field NMR instruments. With the physical requirements for qNMR in mind, many quantitation techniques exist. Using internal calibration202 is arguably the most applied technique, where a calibrant is spiked directly into the sample to be analyzed. This allows the integrals of analyte resonances to be compared to the integrals of calibrant resonance to determine quantity. Equation 4.2 highlights how the concentration of analyte (𝐶5) can be determined with the integration of analyte and internal standard resonances (𝐼5 and 𝐼\], respectively), considering the number of nuclei responsible for integrated resonances (𝑁5 and 𝑁\] for analyte and internal standard, respectively) and the concentration and purity of internal standard (𝐶\] and P\], respectively). 𝐶5 = 𝐼5𝑁5 × 𝑁\]𝐼\] × 𝐶\] × P\] Equation 4.2 While using an internal calibrant results in only a single NMR spectrum needed for qNMR analysis, it also introduces potential complications in relation to the calibrant’s solubility, reactivity, and likelihood of resonance overlap. With a decrease in signal dispersion inherent to data measured with a benchtop NMR spectrometer, the likelihood of overlap between analyte and calibrant resonances only increases. Therefore, external referencing techniques for qNMR with a benchtop NMR system are highly attractive. 177 External referencing techniques such as ERETIC,218 ARTSI,219 or QUANTAS220 may be applied in some NMR systems, where an artificial reference signal is used to calibrate analyte resonances for quantification. While this method enables qNMR analysis without the introduction of an internal calibrant, some of these methods mentioned above possess specific hardware requirements; therefore, some techniques are not applicable/practical with benchtop NMR systems, depending on the hardware of the system itself. Another external reference qNMR method, which is applicable to all benchtop NMR systems, relies on the acquisition and analysis of NMR spectra for a reference sample containing the calibrant and the test sample containing the analyte to be quantified.203 NMR experiments are commonly collected using the same acquisition parameters (same instrument, probe, number scans, dummy scans, acquisition time, repetition time, spectral width, receiver gain, volume of analyte, etc.). However, mathematical corrections can be used to quantify components with spectra acquired with differing acquisition parameters.223,224 Fundamentally, this technique leverages a Concentration Conversion Factor (or CCF), determined with the external reference sample and the known number of nuclei responsible for the resonance (or resonances, if applicable). The CCF value correlates absolute integration (per nuclide) for a particular spectral acquisition and processing scheme. Then with the experimental analyte sample, the absolute integration of a spectrally resolved analyte resonance (𝐴𝐼5) and number of nuclei responsible for resonance (𝑁5) can be used with the conjunction of this CCF to determine the molar concentration of the analyte using Equation 4.3. 178 𝐶5 = CCF × 𝐴𝐼5𝑁5 Equation 4.3 This quantitative technique is attractive for benchtop NMR systems particularly as no additional resonances, other than the analyte desired to be quantified, are needed in the NMR spectrum. As this absolute quantitation technique critically relies on the CCF for quantitative analysis, it is easy to understand how it plays a vital factor in achieving accurate results. The work reported herein highlights a method to determine a more robust CCF with use of single- and multi-analyte linear regression models instead of a single point calibration using the absolute qNMR method. To highlight the applicability of this approach, the CCF values are then applied to quantitatively monitor an industrially relevant model reaction system - activation of a carboxylic acid using 1,1’-carbonyldiimidazole (CDI, 4.6) and subsequent nucleophilic capture to prepare an amide. 4.2 Preparing a concentration conversion factor (CCF) A CCF is commonly and easily determined via single point analysis. This involves carefully weighing/measuring the external standard, bringing to an accurate volume, and transferring to the NMR for analysis. Then, with a pre-determined set of acquisition parameters, an NMR spectrum is measured. After processing the reference spectrum in the analyst's designated software package, the resonance(s) of the external standard compound are integrated. Equation 4.4 highlights how the CCF is calculated as a function of the absolute integration of external standard 179 resonance (𝐴𝐼-]), number of nuclei responsible for resonance (𝑁-]), concentration of external standard (𝐶-]), and purity of external standard (P-]). 𝐶𝐶𝐹 = 𝑁-] 𝐴𝐼-] × 𝐶-] × P-] Equation 4.4 It is important to note that the CCF is sensitive to acquisition parameters and choice of applied processing - therefore it is essential to use the same parameters in each of these cases, unless one uses an appropriate mathematical correction factor. Additionally, it is also important to consider how sometimes less obvious hardware attributes (such as tuning, receiver gain, and pulse calibration) of the benchtop NMR spectrometer may influence data measurement and the determined CCF. For the used spectrometer in this study, the tuning of the probe was factory set, and both the receiver gain and the pulse widths (corresponding to particular pulse angles) were unable to be changed. Therefore, all data were acquired with pre-defined settings. However, on systems where flexibility exists (probe is actively tuned, receiver gain can be changed, flexibility of pulse widths, etc.) a significant level of consideration shall be applied to maintain consistent data measurement. While use of a single concentration and sample allows for a rapid determination of a CCF, the intrinsic error associated from this single point measurement (and therefore all quantitative measurements to follow) can be decreased by performing replicate measurements and using multiple concentrations of analyte. This both minimizes variability and also allows confirmation of the CCF over a range of different SNRs of an analyte. 180 Additionally, not only is the resulting CCF more robust when replicates and varied analyte concentrations are used, but the general data work-up and analysis is simple and straightforward. Upon data acquisition and applying appropriate processing, the resonance (or resonances, if multiple are used) are integrated. If the absolute integration per nuclide is plotted against the concentration, the inverse of the slope for the resulting line of best fit represents the CCF. For the utilized benchtop NMR spectrometer (Spinsolve 60, Magritek) and set of acquisition/processing parameters, a CCF was determined with the above described method for both 1H and 19F nuclei using methyl 3,5-dinitrobenzoate (4.1) and benzotrifluoride (4.2), respectively (Figure 4.1). Importantly, these CCF values were determined with a commercially available Magritek flow cell. As volume of analyte (and therefore number of NMR active spins within the active volume) is directly correlated to the recovered signal, it was vital to determine these values under conditions (i.e., NMR tube, flow cell with flow, flow cell without flow, etc.) that are representative of later analyses. As the reaction monitoring to follow was conducted with an on-line stopped-flow NMR system, with reaction mixture analyzed while static in an NMR flow cell, static solutions of both standards used to determine CCF values were analyzed in the same NMR flow cell. Additionally, the CCF values were determined with analytes in the same solvent as later reaction monitoring analyses. 181 Figure 4.1. Preparation of Concentration Conversion Factors (CCFs) for benchtop NMR system using Magritek flow cell for a) 1H NMR using aromatic resonances of methyl 3,5-dinitrobenzoate (4.1, δH 9.2 ppm) and b)19F NMR using trifluoromethyl resonance of benzotrifluoride (4.2, δF -61.6 ppm) in MeCN. The CCFs for 1H and 19F nuclei and the used system were determined to be 0.0040 M/absolute integration per nuclide and 0.0234 M/absolute integration per nuclide, respectively. With either nucleus detected, the line of best fit was observed to be linear (R2 values of 0.9995 and 0.9992 for 1H and 19F, respectively). If one compares the 1H NMR CCF determined with the above method with a CCF determined with just a single point at any one of the concentrations analyzed, on average a 7.8 % difference in CCF was observed. On the other hand, if just a triplicate analysis was used at any of the concentrations analyzed to determine a CCF, an average 7.9 % difference resulted. Similar results were additionally observed for 19F NMR CCF determination as, on average, a 6.8 % difference was observed if a single point was used and a 6.6 % difference for a triplicate analysis at any single concentration. These relative differences are consistent with measured variability between analysts using an external referencing qNMR with a benchtop NMR.225 y = 42.627x - 0.2151R² = 0.9992024680.00 0.05 0.10 0.15 0.20Absolute Integration per 19FConcentration (M)y = 249.28x + 2.0311R² = 0.9995040801200.00 0.20 0.40 0.60Absolute Integration per 1 HConcentration (M)a) b)OONOONOO4.1HH H4.2FF F 182 To highlight the robustness of this qNMR technique, 1H NMR spectra were measured on independent solutions of four analytes: methyl 3,5-dinitrobenzoate (4.1), maleic acid (4.3), dimethylmalonic acid (4.4), and trimethoxybenzene (4.5). NMR data were measured in triplicate at a range of various concentrations (0.01 – 0.79 M). The absolute integration per 1H for all analytes and concentrations were plotted and the resultant graph with line of best fit can be found in Figure 4.2. Additionally, it should be noted that data from this multicomponent experiment were collected on the same system as the previous analysis but by collaborator Dr. José G. Napolitano (Genentech Inc.). Figure 4.2. Robustness of the qNMR method showcased by great agreement in absolute integration per nuclide versus concentration using multiple analytes: methyl 3,5-dinitrobenzoate (4.1, pink), maleic acid (4.3, green), dimethylmalonic acid (4.4, yellow), and trimethoxybenzene (4.5, blue) in DMSO-d6. Line of best fit determined using data from all analytes. The CCF determined with multiple analytes (0.0043 M/absolute integration per nuclide) was in great agreement to the previously determined CCF for the observed nucleus (1H) and y = 235.08x + 0.3948R² = 0.99940501001502000.00 0.25 0.50 0.75 1.00Absolute Integration per 1 HConcentration (M)4.3HOOOHOOONOONOO4.14.4HOOOHO4.5OO O 183 benchtop NMR spectrometer, underscoring robustness of the qNMR method with general applicability with a wide range of analytes. Additionally, robustness is highlighted as these data were determined with a different analyst (Dr. José G. Napolitano), from physically preparing analyte solutions, measuring benchtop 1H NMR data, processing NMR data, and analyzing NMR data. Furthermore, these data were measured with a different solvent (DMSO-d6) than the initial data (proteo MeCN), showcasing robustness of the qNMR technique with different analyte conditions. Lastly, these data were generated approximately one year after the initial CCF data were collected and display only 7.2 % difference with the previously determined value. Therefore, these data highlight the long-term stability of a CCF for a given NMR instrument and set of conditions. It is further worth noting the linearity of data measured on lower concentration samples (< 60 mM). An expansion of the data shown in Figure 4.2 at this lower concentration range is displayed in the Section 4.5.4.1.2 (Figure 4.10). While relatively high variability was observed with NMR data measured with 10 mM and 20 mM samples of methyl 3,5-dinitrobenzoate (14.5 and 12.6 % RSD, respectively), the robustness of the technique is again displayed as the same CCF is determined if these data points are excluded. Therefore, as the CCF is determined using a wide range of analyte concentrations, and in triplicate, a more accurate conversion factor for external calibration qNMR is obtainable with this technique over single point measurements conducted with either one or three replicates. This method also allows for additional precautions to be applied to further increase the accuracy of the determined CCF for quantitative analyses. For reaction monitoring instances, where analyte concentrations are inherently changing with time, this may include analyzing a range of relevant analyte concentrations for later reactions. Naturally, a concentration regime 184 where only spectra that do not saturate the receiver, considering a particular receiver gain value, shall be used. Additionally, the ionic strength of a sample (and therefore sample’s conductivity) can influence an instrument’s response. We have previously observed a ~ 3 % decrease in integration, or apparent concentration if using an external qNMR method, with a 1.0 M increase in ionic strength with a similar benchtop NMR system (Chapter 3, Section 3.5.3.5). 4.3 Application to reaction monitoring: CDI mediated activation Amides are an important moiety in numerous active pharmaceutical ingredients.248 A preferred method for forming amide bonds between a carboxylic acid and an amine is 1,1’-carbonyldiimidazole (CDI) mediated amidation.249,250 This is an attractive method as CDI is cost efficient and the by-products are non-toxic and easily purged. While it is possible to measure the potency (i.e., percent purity) of CDI through established methods, the quality of the solid may vary and the material is moisture sensitive. Therefore, it is often difficult to precisely dose. Benchtop 1H qNMR can be used to measure the concentration of dosed CDI using the external calibration method obviating the use of deuterated solvents and an internal standard. As a model system, CDI (4.6) was used to activate 4-(trifluoromethyl)benzoic acid (4.8). Upon full activation to the carbonyl imidazole (4.9), the activated acid was reacted with 4-fluoroaniline (4.10) to prepare corresponding amide 4.11. Prior to the activation of carboxylic acid 4.8, CDI (4.6) was charged into the reaction solvent (MeCN) to measure potency and to observe stability in the presence of residual water (Figure 4.3). Benchtop 1H NMR provides sufficient signal dispersion to observe CDI in solution quantitatively without the use of an internal standard (using the CCF method highlighted above). These benchtop 1H qNMR data allowed for a real 53 % potency value to be determined using a spectrally resolved resonance consistent with CDI (δH 7.8 ppm) and the system’s CCF for the nucleus. The calculation for determining the potency 185 of CDI, along with real initial concentration (0.19 M) with these experimentally determined values is included in Section 4.5.4.3 below. Additionally, the CDI remained relatively stable over the observed as 0.17 M, 89 % of the initial CDI concentration, remained in solution by the end of the 70 minute observation period. Additionally, a 2.7 × 10-4 s-1 observed rate constant was determined for the hydrolysis process with residual water in the solvent when the data are fit to a first-order exponential. This potency value is highly relevant and of interest to process chemists, yet this information is not always readily accessible despite the huge impacts on the overall success of the amidation process. Figure 4.3. a) Scheme for the hydrolysis of CDI (4.6, 0.20 M, δH 7.8 ppm) with residual water to form imidazole 4.7 (δH 11.0 ppm) in MeCN. b) Representative decimated stacked array of benchtop 1H NMR spectra. c) Quantitative reaction profile resultant from application of the NMR spectrometer’s CCF. After maintaining a consistent CDI solution concentration, determined by monitoring both the concentrations of CDI and achieving a constant chemical shift for the amine imidazole proton MeCNN NONNHN N CO2+2xH H2O4.6 4.7024681012f1 (1H / ppm)a)t=6.5 mint=69.5 minIncreasing Timeb) c)00.10.20.30 20 40 60Concentration (M)Time (min)4.6 186 (δH 11.0 ppm, a well-established pH indicator),251 carboxylic acid 4.8 was dosed into solution to produce the corresponding activated carbonyl imidazole (4.9). The presence of fluorine atoms in both 4.8 and 4.9 allowed the activation to be monitored via benchtop 19F NMR (Figure 4.4). Leveraging 19F benchtop NMR was beneficial as the larger chemical shift range of 19F simplifies the resulting spectra (no solvent resonance, less overlap) and therefore simplified the following analysis. Additionally, the increasing presence of 19F nuclei in active pharmaceutical ingredients,222 the practicality of benchtop NMR and the applied qNMR method in pharmaceutical settings is further increased. Figure 4.4. a) Scheme for the activation of carboxylic acid 4.8 (0.28 M, δF -61.6 ppm) with CDI (4.6) to form the corresponding activated acyl imidazole 4.9 (δF -62.1 ppm) in MeCN. b) Representative decimated stacked array of benchtop 19F NMR spectra. c) Quantitative reaction profile resultant from application of the NMR spectrometer’s CCF. -65-64-63-62-61-60f1 (19F / ppm)4.84.6 4.94.7OHF3COMeCN+N NONNHN NOF3CN N CO2+ +a)t=0.1 ht=3.5 hIncreasing Timeb) c)Add4.6Add 4.6Add 4.8 to 4.600.10.20.30 1 2 3Concentration (M)Time (h)≈4.94.8 187 A single charge of 4.8 (δF -61.6 ppm) resulted in incomplete activation to the corresponding acyl imidazole 4.9 (δF -62.1 ppm), consistent with the 53 % CDI potency determined with the 1H qNMR measurement. Therefore, it was necessary to add more CDI. Importantly, due to the previous CDI potency determination, this could be completed with a single addition of the activating reagent. However, in effort to showcase the real-time chemical information obtainable with this system, this was completed with two additional charges. Noticeably, incomplete activation could be observed after the second charge, prompting the need for a third addition to achieve complete activation. It should be noted, the two trifluoromethyl resonances of both 4.8 and 4.9 could unambiguously be assigned and monitored with time, despite the chemistry occurring on a carbon six bonds away. Nonetheless, adding only the appropriate amount of CDI allows for full conversion of 4.8 while minimizing any additional activating reagent left in solution. The remaining CDI in solution could otherwise contribute to side-product formation upon nucleophile addition, where the nitrogen nucleophile could add to the CDI, forming urea side-products. Additionally, this could result in an overall decreased yield in the desired amide product as nucleophile is consumed through an unproductive pathway. After full conversion of the carboxylic acid 4.8 to the activated acyl imidazole 4.9, 4-fluoroaniline (4.10, δF -128.5 ppm) was added to prepare the corresponding amide 4.11 (Figure 4.5). This step was additionally quantitatively monitored by 19F NMR spectroscopy. Upon addition of the nucleophile, great agreement in reaction profiles was observed when tracking the formation of desired amide 4.11 with either the trifluoromethyl or aryl fluoride 19F NMR resonance (δF -61.6 ppm and -117.9 ppm for trifluoromethyl and aryl fluoride resonances, respectively). This agreement is apparent by comparing the reaction trends qualitatively (Figure 4.5c) and the time 188 required to reach 50 % conversion (~ 3 h). Further, the observed second order rate constant for consumption of both electrophile 4.9 and nucleophile 4.10 (3 × 10-4 M-1 s-1). Figure 4.5. a) Full reaction scheme for the activation of carboxylic acid 4.8 (0.28 M, δF -61.6 ppm) with CDI (4.6) to form acyl imidazole (4.9, δF -62.1 ppm) that was captured with 4-fluoroaniline (4.10, δF -128.5 ppm) to form the corresponding amide 4.11 (δF -61.6 ppm and -117.9 ppm) in MeCN. b) Decimated stacked array of benchtop 19F NMR spectra of the nucleophilic capture. c) Quantitative reaction profile resultant from application of the NMR spectrometer’s CCF. Notably, despite the general agreement between the trends for amide 4.11, one can qualitatively decipher a large difference in relative noise between the two trends. Not only is there intrinsically less signal for the aryl fluoride (1 × 19F per molecule) compared to the trifluoromethyl resonance (3 × 9F per molecule), but it additionally is coupled to nearby aromatic protons, further dispersing the signal. Nonetheless, the consistent nature of the quantitative results further validates OHF3COMeCN+N NONNHN NOF3CN N CO2+ +H2NONHHN N +FFF3C4.84.6 4.94.7 4.114.104.7-135-125-115f1 (19F / ppm)-65-63-61f1 (19F / ppm)a)t=3.6 ht=20.7 hIncreasing Timeb) c)Add 4.6Add 4.10=00.10.20.30 5 10 15 20Concentration (M)Time (h)4.114.94.10 189 the robustness of the quantitative method, even despite the trifluoromethyl resonance encompassing six times the SNR. It should be further noted that in this final step excess aniline 4.10 was initially added relative to acyl imidazole 4.9. This was to ensure that sufficient nucleophile remained in the case that 4.10 reacted with CO2 in solution (side product from CDI activation) to form the corresponding formate by-product or if the reaction solution possessed any remaining unreacted CDI in solution. However, both unreacted aniline and acyl imidazole was present in solution upon the end of the observation period. We hypothesize that the pH of the reaction could have changed through the reaction course, allowing for the reaction to stall. As this model reaction was conducted without the addition of base, the pH could decrease, increasing the population of protonated aniline 4.10 and decreasing the nucleophilicity. Nonetheless, the power of benchtop 19F NMR is further displayed with the observation of two trifluoromethyl resonances for amide 4.11, consistent with both cis- and trans- amide conformers (Figure 4.6). This was initially noted when comparing reaction trends of the trifluoromethyl resonance of the major conformer and the aryl fluoride resonance of 4.11, where unexpected disagreement was observed. Then, when the integral region of the minor trifluoromethyl resonance was additionally incorporated, great agreement between the trends resulted. 190 Figure 4.6. a) Scheme for the nucleophilic capture of prepared acyl imidazole (4.9) with 4-fluoroaniline (4.10) to form the corresponding amide 4.11 in MeCN. b) Annotated spectral regions of final benchtop 19F NMR spectrum, with trifluoromethyl resonances observable for both cis- and trans- amide conformations of 4.11. c) Quantitative reaction profiles; agreement between trifluoromethyl and aryl fluoride resonances observed only when trifluoromethyl resonances of both conformations are considered. As no temperature control of the sample is possible with the benchtop NMR used in this study, variable temperature (VT) 19F NMR data were measured on a high-field system (at 565 MHz). Prior to analysis, the reaction solution was dried under air and resuspended in DMSO-d6. This was necessary as the increased boiling point of DMSO-d6 allowed for access to warmer temperatures in the VT NMR experiment, if necessary. Coalescence was observed of the two trifluoromethyl resonances (at 70 °C) as the temperature of the sample was increased (Figure 4.7). Therefore, these data are consistent and support our hypothesis that both cis- and trans- amide conformations of 4.11 were present in the reaction mixture at room temperature. Altogether, these -122-119-116f1 (19F / ppm)ONHFF3CONHF3CFtrans-cis-OF3CN NH2NHN N +F+4.9 4.114.104.74.11-62.5-61.5-60.5f1 (19F / ppm)a)b) c) Add Aniline=00.10.20.30 5 10 15 20Concentration (M)Time (h)4.114.114.114.9 4.11 191 VT NMR data, though collected on a high-field instrument, validate the valuable information that may be obtainable on with a benchtop NMR instrument. Figure 4.7. Expansion of the 1D 19F NMR VT overlay (565 MHz), focusing on the trifluoromethyl region of the spectra. Coalescence of the two trifluoromethyl resonances are consistent with these being from the cis- and trans- conformers of amide 4.11. -62.1-62.0-61.9-61.8-61.7-61.6-61.5-61.4-61.3-61.2f1 (19F / ppm)T = 23.0 dCT = 35.0 dCT = 50.0 dCT = 65.0 dCT = 80.0 dCT = 75.0 dCT = 70.0 dCT = 65.0 dCT = 60.0 dCT = 55.0 dCT = 50.0 dCT = 45.0 dCT = 40.0 dCT = 35.0 dCT = 23.0 dCheatcoolONHFF3CONHF3CFtrans-cis-4.114.11≈ 192 4.4 Conclusion The influx in commercially available benchtop NMR spectrometers has allowed for NMR analyses to be conducted in spaces otherwise inaccessible with high-field NMR instruments. This is particularly of interest for reaction monitoring and the pharmaceutical industry, as these instruments allow for the ability to quantitatively monitor a reaction under native reaction settings/conditions. This is further enhanced with the use of an external reference method for qNMR measurements, as an additional species as a quantitative standard is not introduced into the interrogated reaction mixture. The work reported herein describes a method resulting in more robust qNMR analyses using the external referencing technique. The quantitative method discussed in this work can be applied to qNMR analyses conducted with either benchtop or high-field NMR spectrometers. Determining a CCF with multiple concentrations of analyte, and in triplicate at a given concentration, allows for a more robust response factor to be achieved for a particular NMR instrument, set of acquisition parameters, and active volume of spins. Additionally, the method is widely accessible as the CCF is simply the slope of the best linear model fit when plotting the concentration of analyte versus the (average) absolute integration per nuclide. Application of this qNMR technique was demonstrated by monitoring a chemical transformation highly relevant to pharmaceutical settings. Combining benchtop NMR and qNMR allows critical process knowledge such as reagent potency and reaction rates to be determined with minimal experimentation. Overall, this model system displays the practicality of this qNMR technique, and benchtop NMR, to a pharmaceutical environment as critical process relevant information can readily be achieved. 193 4.5 Experimental and further data 4.5.1 General 4.5.1.1 Chemicals All materials were obtained from commercial sources and used as received. Acetonitrile (MeCN), benzotrifluoride (4.2), 1,1’-carbonyldiimidazole (4.6, CDI), 4-(trifluoromethyl)benzoic acid (4.8), and 4-fluoroaniline (4.10), were sourced from Sigma-Aldrich. Certified reference materials for qNMR (namely, methyl 3,5-dinitrobenzoate (4.1), maleic acid (4.3), dimethylmalonic acid (4.4), and 1,3,5-trimethoxybenzene(4.5)) were acquired from MilliporeSigma. 4.5.1.2 NMR data collection, processing and analysis Chemical shifts (δ) are reported in parts-per-million (ppm) and coupling constants (J) are provided in hertz (Hz). All NMR datasets were processed and analyzed with Mestrelab’s Mnova software. The following abbreviations were used to describe multiplicities of resonances in the characterization data: s = singlet, d = doublet, q = quartet, m = multiplet. NMR measurements for reaction monitoring were carried out on a 1.46 T Magritek Spinsolve 60 benchtop NMR system, with operating resonance frequencies of 61.88 and 58.22 MHz for 1H and 19F, respectively. A glass flow cell provided by the instrument manufacturer was used to transfer the test solutions into the benchtop NMR spectrometer without the need for standard NMR tubes. NMR measurements were carried out using standard pulse sequences available in the instrument library. Single-pulse 1D 1H NMR experiments were measured using the benchtop NMR instrument with the following acquisition parameters: 90º pulse, 1 scan, no dummy scans, 3.2 s AQ, 5,000 Hz (80.8 ppm) SW, 5.0 ppm spectral offset, and 42.4 s 194 𝜏*. All 1H NMR spectra were processed with an applied 1 Hz exponential apodization, 3rd order polynomial baseline correction, automatic phase correction (manual corrections applied as needed), and zero-filling to 65,536 data points. Single pulse 1D 19F NMR experiments were measured using the benchtop NMR instrument using the following acquisition parameters: 90º pulse, 1 scan, no dummy scans, 6.5 s AQ, 20,000 Hz (343.5 ppm) SW, -63.0 ppm spectral offset, and a 20.5 s 𝜏*. All 19F NMR spectra were processed with an applied 2 Hz exponential apodization, 3rd order polynomial baseline correction, automatic phase correction (manual corrections applied as needed), and zero-filling to 262,144 data points. Offline high-field NMR data, including VT and 2D NMR experiments for structure characterization, were carried out on either a JEOL JNM-ECZ600R spectrometer equipped with a room-temperature Royal HFX probe (resonance frequencies of 600 and 565 MHz for 1H and 19F, respectively) or an 11.74 T Bruker AVANCE III HD spectrometer equipped with a nitrogen-cooled Prodigy broadband probe (resonance frequencies of 500, 471, and 126 MHz for 1H, 19F, and 13C, respectively). 4.5.1.3 Hazards and experimental precautions Reaction solutions with consumption of CDI involve the alleviation of carbon dioxide gas. Precautions must be taken to not over pressurize reaction vessels with gas evolution. 4.5.2 On-line stopped-flow NMR system details 4.5.2.1 General information A prototype on-line stopped-flow reaction monitoring system, directly analogous to system discussed in Chapter 3 but with a different NMR spectrometer, was utilized to enable periodic static sampling of batch reactors via 1H and/or 19F NMR spectroscopy. To do so, an analogous 195 Python script was utilized to control a Vapourtec SF-10 peristaltic pump, a Vici six-port valve, and the benchtop NMR spectrometer. For reaction monitoring, measurement of NMR spectra was triggered using the Python script. All of the actions with the system were controlled with a Python script. In brief, once the script was started, the reaction solution flowed through the system (valve position “A”) from some vial with analyte at the designated flow rate for the time designated by the analyst in the code. At a pre-determined time point, the valve toggled positions (position “A” to position “B”), leaving an aliquot of the reaction solution static within the NMR instrument for data measurement. This allowed for the representative nature of flow analysis to be leveraged, but for NMR data to be measured on the static sample, circumventing the need for quantitative corrections needed with analyses under continuous-flow conditions. Once NMR data acquisition was complete, the valve again toggled positions (from position “B” to position “A”), allowing for a fresh reaction solution to replenish the NMR flow cell. The loop continued, until the number of spectra designated by the analysts is acquired. A schematic of this system is shown in Figure 4.8, highlighting configurations with each valve position. Figure 4.8. Schematic highlighting the stopped-flow system used in this study. Reaction Vial in EasyMaxPumpBenchtop NMRValve60 MHzFLOWINGFLOWING60 MHzSTATICFLOWINGSwitch Valve PositionData acquisition while solution is static in NMRReplenish NMR with “fresh” reaction solutionValve Position: “A” Valve Position: “B” 196 With this Python script and benchtop NMR system, the user designates the overall time between measurement of NMR spectra, the flow rate, a pause time (time between the toggling of valve position and data measurement), and the designated NMR experiments (with associated acquisition parameters). The sum of the pause time and time for all designated NMR experiments indirectly determines the total time to which the solution remains static (valve position “B”) in the NMR spectrometer. 4.5.2.2 Calibration of system’s peristaltic pump The Vapourtec SF-10 reagent pump was gravimetrically calibrated with tetrahydrofuran (THF). Four flow rates were used, later determined to be 1.8, 2.4, 3.0 and 3.7 mL/min. THF was pumped through the flow system and collected into pre-weighed scintillation vials for two minutes at each of the flow rates. Using the density of THF at room temperature, the mass of THF pumped in this time was converted to a volume. Within the flow rate range analyzed, these data suggested a conversion factor of 0.6202 to determine the actual flow rate (Figure 4.9). Figure 4.9. Calibration of peristaltic pump utilized with the on-line stopped-flow system. y = 0.6202x - 0.0667R² = 1012340 2 4 6 8Real Flow Rate (mL/min)Set Flow Rate (mL/min) 197 4.5.2.3 Determination of benchtop NMR flow system volume To measure the volume of this system, a stock solution of benzotrifluoride (4.2) at a molar concentration of 0.36 M was prepared in MeCN. Using a volumetric pipet, 3.00 mL of this solution was transferred to a scintillation vial, equipped with a magnetic stir bar, and fitted with a septum filled cap. Some of the remainder of the stock solution was pumped through the flow system (valve position “A”, Figure 4.8) at 3.0 mL/min and collected into a waste container, ensuring this solution was purely left within the reading frame of the instrument when the flow was halted. Then three 19F NMR spectra (“pre” spectra) were measured on the solution, with the same acquisition parameters: 90º pulse, 1 scan, no dummy scans, 3.28 s AQ, 20,000 Hz (343.5 ppm) SW, δF -40.0 ppm spectral offset, and 17.3 s 𝜏*. After data collection was completed, the solution in the flow system was evacuated and fresh MeCN was pumped into the system (again, collecting into waste at 3.0 mL/min, valve in position “A”). With the system primed with fresh MeCN, the inlet and outlet lines of the system were transferred to the scintillation vial with the 3.00 mL of the 0.36 M 4.2 solution standard solution. On a magnetic stir plate, the solution in the vial was stirred (300 rpm) and the inlet line was placed well below the liquid level. The pump was then turned on (3.00 mL/min) and the solution was able to circulate and reach an equilibrium concentration over 20 minutes. After this time, the pump was turned off and three 19F NMR spectra (“post” spectra) were acquired on the solution with the same acquisition parameters described above, with the exception of the spectral offset changed to δF -55.0 ppm. Once spectra were imported and processed in Mnova, the absolute integration of the trifluoromethyl resonance (δ F -63.3 ppm) of 4.2 was determined. The average “pre” integration 198 (17.27, 1.33 % RSD) and average “post” integration (10.89, 0.65 % RSD) were used to determine the volume of the system based on a 3.00 mL “pre” volume. Therefore, the system’s volume (calculated 1.76 mL) was equal to the “post” volume minus the “pre” volume. The “post” volume was calculated using Equation 3.1 in Chapter 3. 4.5.3 Experimental procedures 4.5.3.1 Determination of concentration conversion factors (CCF) To prepare a CCF to be used for 1H qNMR analyses, methyl 3,5-dinitrobenzoate (4.1, 570.61 mg, 99.7 %, TraceCERT) was used to prepare a 0.50 M stock solution by bringing to 5.00 mL with MeCN. After the solution was flowed into the NMR with a closed loop flow system, the flow was halted and 1H NMR spectra were measured in triplicate. After data acquisition, the sample was diluted with additional MeCN to prepare a 0.25 M solution. The solution was mixed well and flushed through the closed loop flow system. On the sample static in the NMR, 1H NMR spectra were collected in triplicate. This process was repeated upon further diluting the solution to 0.17, 0.10, 0.06, and 0.02 M and measuring 1H NMR in triplicate. Overlapping aromatic resonances (δH = ~ 9.2 ppm, 3 × 1H) were integrated in each spectrum and the absolute integration per nuclide versus concentration was plotted. The inverse of the slope for the line of best fit represented the CCF for this nucleus, set of acquisition parameters, and set of processing parameters. To prepare a CCF for 19F qNMR analyses, benzotrifluoride (4.2, 0.700 mL, 99 %) was used to prepare a 0.16 M stock solution by bringing to 35.00 mL with MeCN. The solution was pumped into the closed-loop NMR flow system, flow was halted, and 19F NMR spectra were measured in triplicate. The sample was diluted with MeCN to prepare 0.14, 0.12, 0.08, 0.06, and 0.04 M solutions. Each solution was mixed well, flowed through the closed loop flow system and analyzed 199 in triplicate using the previously noted acquisition parameters. The trifluoromethyl resonance (δF = -61.6 ppm, 3 × 19F) was integrated in each spectrum. The absolute integration per nuclide versus concentration was plotted. The inverse of the slope for the line of best fit represented the CCF for this nucleus, set of acquisition parameters, and set of processing parameters. 4.5.3.2 Multi-analyte CCF confirmation Individual solutions of various concentrations of 4.1 (0.01, 0.02, 0.04, 0.16, and 0.32 M), 4.3 (0.09, 0.19, 0.37, and 0.74 M), 4.4 (0.02, 0.05, 0.10, 0.20, 0.40, and 0.79 M), and 4.5 (0.02, 0.03, 0.06, 0.13, 0.25, and 0.51 M) were analyzed via 1H NMR. The data were measured with solutions in a flow cell using the same acquisition parameters listed above. Additionally, data were processed and analyzed the same. All of these solutions were prepared and data were measured, processed, and analyzed by Dr. José G. Napolitano (Genentech Inc.). 4.5.3.3 Synthesis of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide The benchtop NMR flow system was primed with MeCN and connected to a septum-capped scintillation vial containing 6 mL MeCN and a vent needle. The vial was equipped with a magnetic stir bar and kept at a controlled temperature of 26 °C using a Mettler Toledo EasyMax synthesis workstation. This is the same internal temperature of the magnet of the used benchtop NMR spectrometer. With the pump set to off, 445 mg (1.2 eq.) of CDI (4.6) was charged into the vial as a solid and the resulting solution was stirred at 500 rpm. The Python script was started which turned the pump on with a flow of 2.7 mL/min and facilitated analyte transfer to the benchtop NMR. Altogether, 20 1H NMR spectra were acquired starting 3 minutes after the CDI solids were dosed. Spectra were measured 3.5 minutes apart with a 10 s pre-magnetization time prior to initiation of the next NMR experiment. 200 Upon reaching a consistent CDI concentration in solution, as evidenced by an unchanging NMR integration value, the pump was halted, and 442 mg (1 eq.) of 4-(trifluoromethyl)benzoic acid (4.8) was added to the vial. The activation was monitored via benchtop 19F NMR starting 3 minutes after addition of the carboxylic acid. Incomplete activation was observed after acquisition of the first 34 19F NMR spectra. An additional 127 mg (0.3 eq.) of CDI were added to the vial. Likewise, more CDI (127 mg, 0.3 eq.) was added after the acquisition of the 41st 19F NMR spectrum, resulting in full activation of the carboxylic acid. The process was monitored for 3.5 hours until 60 total 19F NMR spectra total were acquired. After full activation of the carboxylic acid, 0.25 mL (1.1 eq.) of 4-fluoroaniline (4.10) was added to the reaction. The reaction mixture was monitored by 19F NMR. In total, 206 additional 19F NMR spectra were measured with 10 s pre-magnetization time and a 5 minute delay between acquisitions. 4.5.4 Further relevant data 4.5.4.1.1 CCF determination with analytes in MeCN The CCF was determined using the Magritek Spinsolve 60 MHz system for both 1H and 19F nuclei, using acquisition and processing parameters noted in Section 4.5.1.2. The CCF was determined with solutions of analyte in the NMR flow cell later used for the reaction monitoring model application. The data to determine the 1H NMR CCF using the aromatic resonances of methyl 3,5-dinitrobenzoate (4.1, δH 9.2 ppm) can be found in Table 4.1 below. A summary of these CCF data, along with standard deviation and error (% RSD), for each concentration analyzed can be found in Table 4.2. 201 Table 4.1. 1H NMR integration data used to determine CCF for 1H qNMR analyses with the benchtop NMR system. CCF was determined using the aromatic resonances of methyl 3,5-dinitrobenzoate (4.1, δH 9.2 ppm) in MeCN. Concentration (M) Integral (11.043325,7.139533) Integration per 1H CCF (Concentration per integration/nuclide) 0.50 382.96 127.65 0.003917 375.95 125.32 0.003990 379.95 126.65 0.003948 0.25 196.41 65.47 0.003819 199.60 66.53 0.003758 199.78 66.59 0.003754 0.17 134.35 44.78 0.003796 131.73 43.91 0.003871 137.03 45.68 0.003722 0.10 80.67 26.89 0.003719 81.48 27.16 0.003682 81.56 27.19 0.003678 0.06 48.45 16.15 0.003715 46.39 15.46 0.003881 42.57 14.19 0.004229 0.02 19.76 6.59 0.003037 18.86 6.29 0.003182 19.46 6.49 0.003083 202 Table 4.2. Summary of 1H NMR data used to determine CCF for 1H qNMR analyses with the benchtop NMR system. CCF was determined using the aromatic resonances of methyl 3,5-dinitrobenzoate (4.1, δH 9.2 ppm) in MeCN. Conc. (M) Average integration per 1H Standard deviation % RSD 0.50 126.540 1.173 0.927 0.25 66.199 0.633 0.956 0.17 44.790 0.883 1.971 0.10 27.0783 0.164 0.605 0.06 15.267 0.994 6.513 0.02 6.452 0.153 2.373 The data to determine the 19F NMR CCF using the trifluoromethyl resonance of benzotrifluoride (4.2, δF -61.6 ppm) can be found in Table 4.3 below. A summary of these CCF data, along with standard deviation and error (% RSD), for each concentration analyzed can be found in Table 4.4. 203 Table 4.3. 19F NMR integration data used to determine CCF for 19F qNMR analyses with the benchtop NMR system. CCF was determined using the trifluoromethyl resonance of benzotrifluoride (4.2, δF -61.6 ppm) in MeCN. Concentration (M) Integral (-60.368802,-62.729124) Integration per 19F CCF (Concentration per integration/nuclide) 0.16 20.11 6.70 0.023874 20.52 6.84 0.023387 19.88 6.63 0.024148 0.14 17.34 5.78 0.024226 17.29 5.76 0.024289 16.38 5.46 0.025649 0.12 14.47 4.82 0.024878 14.39 4.80 0.025024 14.21 4.74 0.025341 0.08 10.23 3.41 0.023468 9.54 3.18 0.025154 10.22 3.41 0.023493 0.06 7.60 2.53 0.023679 6.26 2.09 0.028742 7.24 2.41 0.024878 0.04 5.39 1.80 0.022283 4.78 1.59 0.025114 5.13 1.71 0.023371 204 Table 4.4. Summary of 19F NMR data used to determine CCF for 19F qNMR analyses with the benchtop NMR system. CCF was determined using the trifluoromethyl resonance of benzotrifluoride (4.2, δF -61.6 ppm) in MeCN. Conc. (M) Average integration per 19F Standard deviation % RSD 0.16 6.723 0.109 1.623 0.14 5.667 0.181 3.192 0.12 4.785 0.045 0.942 0.08 3.331 0.130 3.927 0.06 2.344 0.231 9.840 0.04 1.700 0.102 5.982 4.5.4.1.2 Robustness of CCF with multi-analyte test in DMSO-d6 The data to determine the 1H NMR CCF value using resonances from 3,5-dinitrobenzoate (4.1), maleic acid (4.3), dimethylmalonic acid (4.4), and trimethoxybenzene (4.5) can be found in Table 4.5, Table 4.6, Table 4.7, and Table 4.8, respectively. A summary of these CCF data, along with standard deviation and error (% RSD), for each concentration analyzed can be found in Table 4.9. 205 Table 4.5. 1H NMR integration data used to confirm CCF for 1H qNMR analyses with the benchtop NMR system. CCF was determined with methyl 3,5-dinitrobenzoate (4.1) in DMSO-d6. Conc. (M) Integral (9.781,7.699) Integration per 1H CCF (conc. per integration/nuclide) Integral (4.463,3.398) Integration per 1H CCF (conc. per integration/nuclide) 0.32 218.98 72.99 0.004351 224.15 74.72 0.004251 219.07 73.02 0.004350 223.37 74.46 0.004266 219.05 73.02 0.004350 222.72 74.24 0.004278 0.16 109.75 36.58 0.004341 112.91 37.64 0.004220 107.98 35.99 0.004412 111.74 37.25 0.004264 108.39 36.13 0.004395 112.12 37.37 0.004249 0.04 26.60 8.87 0.004478 29.04 9.68 0.004101 25.77 8.59 0.004622 24.71 8.24 0.004820 27.10 9.03 0.004395 29.78 9.93 0.003999 0.02 12.94 4.31 0.004602 15.88 5.29 0.003751 12.65 4.22 0.004708 11.10 3.70 0.005367 14.69 4.90 0.004054 14.49 4.83 0.004110 0.01 7.65 2.55 0.003894 8.44 2.81 0.003528 7.47 2.49 0.003986 8.45 2.82 0.003523 6.46 2.15 0.004613 9.92 3.31 0.003001 206 Table 4.6. 1H NMR integration data used to confirm CCF for 1H qNMR analyses with the benchtop NMR system. CCF was determined with maleic acid (4.3) in DMSO-d6. Concentration (M) Integral (6.952,5.000) Integration per 1H CCF (conc. per integration/nuclide) 0.74 357.532 178.77 0.004152 353.282 176.64 0.004201 354.526 177.26 0.004187 0.37 176.856 88.43 0.004196 178.289 89.14 0.004163 176.261 88.13 0.004211 0.19 89.924 44.96 0.004127 89.021 44.51 0.004168 87.73 43.87 0.004230 0.09 49.932 24.97 0.003716 46.968 23.48 0.003950 52.246 26.12 0.003551 207 Table 4.7. 1H NMR integration data used to confirm CCF for 1H qNMR analyses with the benchtop NMR system. CCF was determined with dimethylmalonic acid (4.4) in DMSO-d6. Concentration (M) Integral (1.896,0.306) Integration per 1H CCF (conc. per integration/nuclide) 0.79 1106.63 184.44 0.004306 1107.06 184.51 0.004305 1106.29 184.38 0.004308 0.40 550.48 91.75 0.004328 550.79 91.80 0.004326 551.03 91.84 0.004324 0.20 276.84 46.14 0.004303 277.98 46.33 0.004286 275.86 45.98 0.004319 0.10 138.05 23.01 0.004315 139.36 23.23 0.004274 139.41 23.24 0.004273 0.05 74.59 12.43 0.003993 73.58 12.26 0.004048 73.06 12.18 0.004077 0.02 34.67 5.78 0.004295 37.93 6.32 0.003926 35.63 5.94 0.004179 208 Table 4.8. 1H NMR integration data used to confirm CCF for 1H qNMR analyses with the benchtop NMR system. CCF was determined with trimethoxybenzene (4.5) in DMSO-d6. Concentration (M) Integral (6.874,5.156) Integration per 1H CCF (conc. per integration/nuclide) 0.51 364.41 121.47 0.004191 365.42 121.81 0.004180 368.06 122.69 0.004150 0.25 179.56 59.85 0.004253 181.19 60.40 0.004215 180.78 60.26 0.004224 0.13 93.20 31.07 0.004097 94.39 31.46 0.004045 91.45 30.48 0.004175 0.06 44.71 14.90 0.004270 45.27 15.09 0.004217 46.62 15.54 0.004095 0.03 24.65 8.22 0.003873 25.06 8.35 0.003809 25.18 8.39 0.003790 0.02 10.97 3.66 0.004351 13.91 4.64 0.003432 12.58 4.19 0.003794 209 Table 4.9. Summary of 1H NMR data used to confirm CCF for 1H qNMR analyses with the benchtop NMR system. CCF determined using multi-analytes, all in DMSO-d6. Analyte Concentration (M) Average integration per 1H Standard deviation % RSD Methyl 3,5-dinitrobenzoate (4.1) 0.318 73.74 0.814 1.10 0.159 36.83 0.688 1.87 0.040 9.06 0.644 7.11 0.020 4.54 0.573 12.62 0.010 2.69 0.391 14.53 Maleic acid (4.3) 0.742 177.56 0.728 0.41 0.371 88.57 0.347 0.39 0.186 44.45 0.368 0.83 0.093 24.86 1.323 5.32 Dimethylmalonic acid (4.4) 0.794 184.44 0.064 0.03 0.397 91.79 0.045 0.05 0.199 46.15 0.177 0.38 0.099 23.16 0.129 0.56 0.050 12.29 0.129 1.05 0.025 6.01 0.279 4.64 Trimethoxybenzene (4.5) 0.509 121.99 0.629 0.52 0.255 60.17 0.283 0.47 0.127 31.00 0.494 1.59 0.064 15.18 0.328 2.16 0.032 8.32 0.093 1.12 0.016 4.16 0.490 11.78 An expansion of the multi-analyte CCF trial (shown in Figure 4.2 of the manuscript) focusing on the lower-level concentration data points are displayed in Figure 4.10 below. 210 Importantly, these data highlight the linearity of NMR response even with low concentrations of analytes. Additionally, in Figure 4.10 the linear regression using the multi-analyte data was performed, but without the lowest concentration (0.10 M and 0.02 M) of methyl 3,5-dinitrobenzoate which displayed relatively high variations in reproducibility (14.5 and 12.6 % RSD, respectively). The results of the linear regression highlight the robustness of the technique as the same CCF results. Figure 4.10. a) Expansion of lower concentration data points for multi-analyte CCF test. b) Results of linear regression without the two lowest concentration data points (0.10 M and 0.02 M with 14.5 and 12.6 % RSD, respectively) for methyl 3,5-dinitrobenzoate (pink). The determined CCF is the same if these points are either included or excluded, showcasing the robustness of the technique. Samples for this multi-analyte test include maleic acid (green), methyl 3,5-dinitrobenzoate (pink), dimethylmalonic acid (yellow), and trimethoxybenzene (blue) in DMSO-d6. 4.5.4.2 Hydrolysis CDI The reaction scheme, corresponding decimated stacked array of 1H NMR data, and time profile for monitoring the hydrolysis trends of CDI (4.6) are displayed in the main text of the chapter (Figure 4.3). Additionally, with these same data, a concentration versus time profile was HOOOHOHOOOHOOO OOONOONOOy = 235.08x + 0.3948R² = 0.9994051015200.00 0.02 0.04 0.06Absolute Integration per 1 HConcentration (M)y = 235.08x + 0.3948R² = 0.99940501001502000.0 0.5 1.0Absolute Integration per 1 HConcentration (M)a) b) 211 prepared in Mnova. Then using a “Three Parameter Exponential Fit”, the data were fit where the resulting equation was used to determine the apparent rate constant to first-order approximation. Figure 4.11. a) Reaction scheme for the hydrolysis of CDI (4.6) with residual water in MeCN. b) Reaction trend for monitoring resonance consistent with 4.6 (δH 7.8 ppm). 4.5.4.3 Calculation of CDI potency and initial solution concentration Based on the line-of-best fit above (Y’ = B + F * exp(-Time * G); B = 0.1598, F = 0.02683, G = 0.01646), the concentration of CDI (Y’) at the time the solids entered the solution (Time = 0) can be calculated: Y’ = B + F * exp(-Time * G) Y’ = B + F * exp(0) Y’ = B + F * 1 = 0.1598 + 0.02683 = 0.1866 M => initial CDI concentration 10 20 30 40 50 60 70Time (min)0.000.050.100.150.20Concentration (M)Y' = B+F*exp(-Time *G)B=0.1598; F=0.02683; G=0.01646;Error: 0.009498MeCNN NONNHN N CO2+2xH H2O4.6 4.7a)b) 212 Based on this calculated value and the known reaction solution volume (7.76 mL), the total amount of CDI dosed into solution can be determined (first in terms of number of moles, then in mg): 0.187 mol/L * (1 L / 1000 mL) = 0.001448 mol 0.001448 mol * (162.15 g / 1 mol) * (1000 mL / 1 L) = 234.834 mg CDI actually used The calculated actual amount of CDI can then be divided by the amount of material weighed from the CDI stock bottle to determine the potency: (234.834 mg / 445.061 mg) * 100 % = 52.8 % => 53 % potency 4.5.4.4 Nucleophilic capture of activated acyl imidazole The reaction scheme, corresponding decimated stacked array of 19F NMR data, and time profile for monitoring the nucleophilic capture of activated acyl imidazole are displayed in the main text (Figure 4.5). Additionally, with these same data, a concentration versus time profile was prepared in Mnova, by monitoring amide 4.11 formation from both the trifluoromethyl (δF -61.6 ppm) and aryl fluoride (δF -117.9 ppm) resonance. Then using a “Three Parameter Exponential Fit”, the data were fit where the resulting equation was used to determine the apparent rate constant to first-order approximation. 213 Figure 4.12. a) Reaction scheme for the nucleophilic capture of activated acyl imidazole 4.9 with 4-fluoroaniline (4.10) to prepare amide coupling product 4.11. Expansion of reaction profile for amide 4.11 formation when monitoring trifluoromethyl (δF -61.6 ppm) and aryl fluoride (δF -117.9 ppm) resonance b) at the final data points and c) near 50 % conversion to the amide product over the observed period. Additionally, the observed second order rate constant was determined using concentration data derived from the 19F NMR resonances of acyl imidazole 4.9 and aniline 4.10. The inverse of the concentrations was plotted against time and agreement between the rate constants determined with either resonance (3 × 10-4 M-1 s-1) can be observed (Figure 4.13). OF3CN N CO2+H2NONHHN N +FFF3C4.9 4.114.104.7a)b)17.0 17.2Time (h)0.050.100.150.20Concentration (M)2.8 3.0 3.2Time (h)0.050.100.150.20Concentration (M)0.11 Mc) 214 Figure 4.13. a) Reaction scheme for the nucleophilic capture of activated acyl imidazole 4.9 with 4-fluoroaniline (4.10) to prepare amide coupling product 4.11. Determination of observed second order rate constant determined from b) acyl imidazole 4.9 (δF -62.1 ppm) and c) aniline 4.10 (δF -128.5 ppm) resonances, with time starting when nucleophile 4.10 was dosed into the reaction solution. 4.5.4.5 Variable temperature (VT) high-field NMR of amide 4.11 Two trifluoromethyl resonances were observed to be consistent with amide 4.11, when monitoring the formation at 58 MHz and at 26 °C. With no variable temperature (VT) control of the sample inside the benchtop NMR instrument, variable temperature 19F NMR spectra were acquired at high-field (565 MHz). Additionally, the reaction mixture (in MeCN) was dried down under air and resuspended in DMSO-d6. The higher boiling point of DMSO-d6 allowed for a larger temperature range in the VT experiment to be explored. 19F NMR spectra were measured from 23 °C to 80 °C in 5 °C steps after 35 °C. After measuring a spectrum at 80 °C, the temperature was returned to 23 °C. Upon analysis of the VT NMR spectra, the two resonances (δF -61.5 ppm and -61.6 ppm) of interest were observed to OF3CN NH2NONHHN N +FFF3C4.9 4.114.104.7a)b) c)y = 0.0003x + 4.5491010200 10000 20000 300001/[Concentration (M)] Time (s)y = 0.0003x + 3.4127010200 10000 20000 300001/[Concentration (M)] Time (s) 215 coalesce with heat. This is consistent with cis- and trans- amide conformers and is further consistent with both our hypothesis and initial analysis of reaction trends (Figure 4.7). Below (Figure 4.14) are the same VT high-field 19F NMR data zoomed out such that the highest intensity conformer resonance isn’t clipped. Figure 4.14. Expansion of the 1D 19F NMR VT overlay (565 MHz), focusing on the zoomed aryl fluoride region. Intensity was increased to better visualize minor amide conformer. 4.5.4.6 Spin-lattice relaxation time (T1) estimations The spin-lattice relaxation time (T1) values of relevant resonances were estimated using the inversion-recovery method,73,74 an experiment accessible in the default pulse sequence library of the benchtop NMR instrument. Samples of individual components were analyzed, with results for -62.1-62.0-61.9-61.8-61.7-61.6-61.5-61.4-61.3-61.2f1 (19F / ppm)T = 23.0 dCT = 35.0 dCT = 50.0 dCT = 65.0 dCT = 80.0 dCT = 75.0 dCT = 70.0 dCT = 65.0 dCT = 60.0 dCT = 55.0 dCT = 50.0 dCT = 45.0 dCT = 40.0 dCT = 35.0 dCT = 23.0 dCheatcoolONHFF3CONHF3CFtrans-cis-4.114.11 216 each species included in Figure 4.15 - Figure 4.22. The results are summarized in Table 4.10 below. Figure 4.15. Results of the inversion recovery experiment for methyl 3,5-dinitrobenzoate a) spectrally and b) graphically. Figure 4.16. Results of the inversion recovery experiment for benzotrifluoride a) spectrally and b) graphically. 0 5 10 15 20 25 30Tau (s)-50050Intensity (au)Y' = B+F*exp(-time *G)B=31.48365484; F=-62.22648672; G=0.1482645253;Error: 0.000000000Y1' = B+F*exp(-time *G)B=58.85023769; F=-115.1622249; G=0.1577513707;Error: 0.000000000Y2' = B+F*exp(-time *G)B=88.72966757; F=-176.5751157; G=0.6557354360;Error: 0.000000000489f1 (1H / ppm)a) b)OONOONOO0 1 2 3 4 5 6 7 8 9 10Tau (s)-40-20020406080Intensity (au)Y' = B+F*exp(-time *G)B=87.54799378; F=-150.1862720; G=0.5620994266;Error: 0.000000000-65-63-61-59f1 (19F / ppm)a) b)F3C 217 Figure 4.17. Results of the inversion recovery experiment for maleic acid a) spectrally and b) graphically. Figure 4.18. Results of the inversion recovery experiment for dimethylmalonic acid a) spectrally and b) graphically. 4.55.56.5f1 (1H / ppm)0 5 10 15 20 25 30Tau (s)-200-1000100200Intensity (au)Y' = B+F*exp(-time *G)B=220.3745230; F=-428.5886166; G=0.5074007502;Error: 0.000000000a) b)HOOOHOHOOOHO0.51.01.52.02.5f1 (1H / ppm)0 5 10 15 20 25 30Tau (s)-400-2000200400Intensity (au)Y' = B+F*exp(-time *G)B=455.1119640; F=-873.9723737; G=1.359562273;Error: 0.000000000a) b) 218 Figure 4.19. Results of the inversion recovery experiment for 1,3,5-trimethoxybenzene a) spectrally and b) graphically. Figure 4.20. Results of the inversion recovery experiment for 1,1’-carbonyldiimidazole (CDI) a) spectrally and b) graphically. 3.54.55.5f1 (1H / ppm)0 5 10 15 20 25 30Tau (s)-800-4000400800Intensity (au)Y' = B+F*exp(-time *G)B=278.7184912; F=-548.8185956; G=0.3625340034;Error: 0.000000000Y1' = B+F*exp(-time *G)B=838.6579426; F=-1650.895289; G=0.7727610797;Error: 0.000000000a) b)OO O0 5 10 15 20 25 30Tau (s)-50050Intensity (au)Y' = B+F*exp(-time *G)B=76.60099492; F=-151.9046607; G=0.2120843540;Error: 0.000000000Y1' = B+F*exp(-time *G)B=91.55951046; F=-180.2852678; G=0.2353761410;Error: 0.000000000Y2' = B+F*exp(-time *G)B=81.42632952; F=-160.2082934; G=0.2403997882;Error: 0.0000000006.57.07.58.0f1 (1H / ppm)a) b)N NONN 219 Figure 4.21. Results of the inversion recovery experiment for 4-(trifluoromethyl)benzoic acid a) spectrally and b) graphically. Figure 4.22. Results of the inversion recovery experiment for 4-fluoroaniline a) spectrally and b) graphically. 0 1 2 3 4 5 6 7 8 9 10Tau (s)-50510Intensity (au)Y' = B+F*exp(-time *G)B=11.44922389; F=-19.34693222; G=0.5657091806;Error: 0.000000000-63.5-62.5-61.5-60.5f1 (19F / ppm)a) b)OHF3CO0 5 10 15 20 25Tau (s)-20-100102030Intensity (au)Y' = B+F*exp(-time *G)B=39.92699030; F=-68.57549832; G=0.2423435632;Error: 0.000000000-133-130-127f1 (19F / ppm)a) b)H2NF 220 Table 4.10. Summary of T1 estimations using the inversion recovery experiment for relevant species. For species with multiple resonances, see above figure for colour assignment. G (s-1) T1 (s) methyl 3,5-dinitrobenzoate 0.1483 6.74 0.1578 6.34 0.6557 1.53 benzotrifluoride 0.5621 1.78 maleic acid 0.5074 1.97 dimethylmalonic acid 1.3596 0.74 1,3,5-trimethoxybenzene 0.3625 2.76 0.7728 1.29 CDI 0.2121 4.72 0.2354 4.25 0.2404 4.16 4-(trifluoromethyl)benzoic acid 0.5657 1.77 4-fluoroaniline 0.2423 4.13 4.5.5 Product characterization 4.5.5.1.1 N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) 4.11 was synthesized from activation of 4.8 with 4.6 and subsequent capture with 4.10 in MeCN, per Section 4.5.3.3 above. Upon completion of the reaction, the mixture was dried down to successfully obtain the desired amide product as a powder. The isolated solid was dissolved in DMSO-d6 for high-field NMR analysis. The NMR data are consistent with previous literature.252 221 1H NMR (500.13 MHz, DMSO-d6) δ H 8.15 (d, J = 8.2 Hz, 2H), 7.91 (d, J = 8.2 Hz, 2H), 7.80 (m, 2H), 7.21 (m, 2H); 13C{1H} NMR (125.77 MHz, DMSO-d6) δC 164.32, 158.50 (d, J = 240.7 Hz), 138.61 (q, J = 1.3 Hz), 135.20 (d, J = 2.6 Hz), 131.41 (q, J = 32.1 Hz), 128.59, 125.42 (q, J = 3.9 Hz), 123.93 (q, J = 272.1 Hz), 122.34 (d, J = 8.0 Hz), 115.29 (d, J = 23.0 Hz); 19F NMR (470.56 MHz, DMSO-d6) δF -61.34 (s, 3F), -118.39 (m, 1F); HRMS-ESI (m/z) 284.0693 [M+H]+ (Calculated for C14H9F4NO, 284.0693). 4.11ONHFF3C 222 Chapter 5: Reaction monitoring via benchtop NMR spectroscopy – a practical comparison of on-line stopped-flow and continuous-flow sampling methods 5.1 Introduction NMR spectroscopy is a well-known analytical technique with the ability to provide structurally rich in-formation in a non-destructive and in an inherently quantitative manner.202 These features are highly valuable assets for reaction monitoring in the pharmaceutical industry, as knowledge of consumption and/or formation of chemical species can help inform critical decisions related to a chemical process. While NMR is generally associated with physically large and expensive superconducting high-field systems, benchtop NMR instruments are providing a viable alternative for certain applications. Benchtop NMR spectrometers are significantly smaller and cheaper to purchase and maintain. The smaller physical footprint of these systems allow for the structural insights associated with NMR to enter the synthetic laboratory.125,195 This is not without tradeoffs, however, as the application of smaller external applied magnetic field strength results in an overall decrease in sensitivity and signal dispersion.253 While benchtop NMR may not be a viable option for complex structure elucidation problems due to the limitations highlighted above, reaction monitoring generally entails tracking key resonances so the impact of these limitations can be minimized. To address the decrease in sensitivity, hyperpolarization techniques211,212 may be employed or one can simply monitor a more concentrated reaction solution.210 In order to decrease the likelihood of resonance overlap, and enhance signal dispersion, one can additionally monitor a nucleus with a large chemical shift range (such as 19F or 31P).210,254 If greater signal dispersion cannot be achieved, non-traditional data 223 processing methods, such as Complete Reduction to Amplitude Frequency Table (CRAFT),63,64 may be leveraged. It should be noted that, while benchtop NMR allows for NMR data to be conveniently acquired in a synthetic laboratory, the sample (i.e., reaction solution in this case) must physically be transported to the instrument for analysis. For a reaction ongoing in batch this implies three primary options: i. the reaction can be performed on small-scale in an NMR tube itself (monitored in-situ), ii. the reaction can be periodically sampled and aliquot transferred to NMR tube for analysis (monitored off-line), or iii. a flow system can be devised such that a portion of the reaction solution is transferred to the NMR magnet for analysis (monitored on-line). In the interest of decreasing the human power needed to perform a reaction monitoring analysis, only i. and iii. will further be considered. In 2016, Foley et al. demonstrated the significant differences in measured reaction rates when observing processes in an NMR tube versus on-line continuous-flow conditions using high-field NMR.143 Differences were particularly evident in heterogeneous systems where stirring allowed for more representative mass transfer under “regular” synthetic conditions. It should not be understated that much work has been completed in effort to understand the effect of flow on NMR data acquisition; even at the start of this century, a review was written including relevant work on the subject to that point, and even with the application to process monitoring.175 Investigations, however, have continued to enhance our understanding on the subject. For example, Nordon et al. showcased how incorporating a pre-magnetization region can assist in increasing the polarization of spins in continuous-flow analyses174 and Dalitz et al. highlighted quantitative reaction monitoring with continuous-flow conditions with consideration of the impacts of flow.255 Additionally, the impact of flow rate and flow cell geometry on flow 224 behaviour has been studied179 and the necessary hardware considerations one must make when designing a flow NMR system (such as choice of pump and resultant pulsation of analyte) has more recently been reported.170 Recent investigations of continuous-flow conditions for NMR measurements with a modern high-field NMR system180 and a modern benchtop NMR system (Chapter 2) have been conducted with application to reaction monitoring in mind. Recently, we have demonstrated the utility of an on-line stopped-flow benchtop NMR system where we quantitatively monitored reaction systems (Chapter 3) and demonstrated an external referencing qNMR method using such a system (Chapter 4). This stopped-flow system is analogous type to an on-line stopped-flow system applied as far back as the 1980’s for reaction monitoring187 and different than the in-situ stopped-flow systems employed for monitoring rapid reactions, where fundamentally those systems are used to minimize the time between initiation of the reaction and data acquisition.150–153 This on-line stopped-flow system is a closed-loop flow batch system, as solution circulates through the NMR instrument and reactor, but the solution is halted in the magnet just prior and during NMR data collection (Figure 5.1). After data acquisition the solution returns to continuous circulation until the next data acquisition event. Using this method, NMR measurements are conducted under static conditions so irregularities of hardware that can be detrimental to NMR measurements, such as pump pulsation, are a non-issue so long that sufficient time for analyte to stabilize is provided prior to data acquisition. 225 Figure 5.1. Schematic of the on-line NMR flow systems compared in this study for a) stopped-flow analyses and b) continuous-flow analyses. In this chapter, reaction profiles are acquired with both stopped-flow and continuous-flow sampling conditions with a modern, commercially available benchtop NMR instrument and accompanied on-line flow system. Acquired data and reaction trends are directly compared, with the desire to reduce complexity of data analysis and allow for approachable reaction monitoring analyses for a non-NMR specialist. This was of particular interest as the extent of flow effects are known to be specific to magnet configurations,180 therefore these empirical observations may be of interest for users of similar systems. Two reactions were monitored in this effort: a homogeneous imination reaction between 4-fluorobenzaldehyde (5.1) and 4-fluoroaniline (5.2) and a biphasic activation reaction of 4-fluorobenzoic acid (5.4) with perfluorobutanesulfonyl fluoride (PBSF, 5.6) to the corresponding acyl fluoride (5.10). In either case, reactions were additionally performed in a 5 mm NMR tube as a benchmark measurement. 60 MHzReaction Vial in EasyMaxPumpBenchtop NMRFLOWINGFLOWINGValve60 MHzFLOWINGFLOWING60 MHzSTATICFLOWINGSwitch Valve Positiona) Stopped-flowb) Continuous-flowContinuously replenishing NMR with “fresh” reaction solutionData acquisition while solution flows through NMRData acquisition while solution is static in NMRReplenish NMR with “fresh” reaction solutionValve Position: “A” Valve Position: “B”Valve Position: “A” 226 5.2 Reaction monitoring 5.2.1 Homogenous imination reaction The coupling of 4-fluorobenzaldehyde (5.1) and 4-fluoroaniline (5.2) to prepare the corresponding imine (5.3) was performed in batch and monitored by both stopped-flow and continuous-flow techniques. Additionally, this reaction was performed and monitored in a 5 mm NMR tube. This system was selected as it represented a homogeneous reaction system similar to the reaction analyzed by Foley et al. in 2016 where trends resulting from the reaction performed in a 5 mm tube (with and without periodic inversion) and under continuous-flow conditions were directly compared.143 This reaction system (along with activation reaction to follow) was monitored via 19F{1H} NMR. This was the desired method as there was no solvent signal in the resulting spectra and the greater signal dispersion helped with accurately quantifying resonances without the need of advanced spectral processing and analysis. Furthermore, the 1H decoupling consolidated each of the aryl fluoride signals to a singlet, resulting in better digitization of resonances and overall reducing the impact of the sensitivity limitation associated with benchtop NMR. For this reaction and all monitoring techniques (stopped-flow, continuous-flow, or 5 mm NMR tube), resonances consistent with each species were readily observed. The consumption of 5.1 and 5.2 could be monitored with the disappearance of resonances with chemical shifts of 𝛿F -105.0 ppm and -129.6 ppm, respectively. Additionally, the appearance of two fluorine resonances with chemical shifts of 𝛿F -110.0 ppm and -118.9 ppm were consistent with the formation of the desired imine product 5.3. Representative data for this transformation for the stopped-flow monitoring trial can be found in Figure 5.2. 227 Figure 5.2. a) Reaction scheme for coupling 5.1 (0.22 M, 1.0 eq., δF -105.0 ppm) and 5.2 (1.1 eq., δF -129.6 ppm) to form corresponding imine 5.3 (δF -110.0 and -118.9 ppm) in 1:1 MeCN:MeOH. b) Representative decimated stacked array of 19F{1H} NMR spectra (58 MHz) of the transformation when monitored via stopped-flow NMR. c) Reaction profile resulting from tracking each resonance with time. The reaction profiles tracking each component, with each analysis method, were directly compared (Figure 5.3 and Section 5.4.5.1.1). With this homogeneous reaction system, excellent agreement in reaction rates when tracking each of the components with stopped-flow and continuous-flow analysis methods was observed. This can be seen both qualitatively in the reaction trends and quantitatively by monitoring the apparent rate constants when fitting the reaction trends to a first-order exponential. Additionally, no difference in reaction trends resulted when comparing each of the flow methods (stopped- and continuous-flow) and the reaction conducted in a 5 mm NMR tube. Though some deviation existed in the aniline reaction profile and apparent rate constant for the reaction conducted inside a 5 mm NMR tube. This is hypothesized to be a result of experimental error resulting from measuring such a small volume of the aniline in preparation of FN1:1 MeCN:MeOHFHO FH2O+ +H2NF5.1 5.2 5.3-130-125-120-115-110-105f1 (19F / ppm)a)t=0.1 ht=1.8 h00.10.20.0 0.5 1.0 1.5 2.0Concentration (M)Time (h)Increasing Timeb) c)5.25.35.1 228 the reaction solution. Overall, this suggests that the reaction solution in the 5 mm NMR tube was well mixed and the reaction was not diffusion limited. Figure 5.3. a) Reaction scheme for coupling 5.1 (0.22 M, δF -105.0 ppm) and 5.2 (1.1 eq., δF -129.6 ppm) to form the corresponding imine 5.3 (δF -110.0 and -118.9 ppm), along with estimated T1 values of each fluorine resonance. Observed reaction trends from 19F{1H} NMR spectra (58 MHz) for two representative reaction species monitored via stopped-flow (purple circle), continuous-flow (pink diamonds), and reaction performed in 5 mm NMR tube (grey cross): b) aldehyde starting material (5.1) and c) imine product (5.3). d) Apparent rate constants for each component/resonance when fitted to first-order exponential. It should be mentioned that the spin-lattice relaxation time (T1) dictates the time needed for adequate polarization of spins prior to application of an RF pulse when a sample is both introduced into an instrument’s external applied magnetic field and after application of RF pulse (as discussed in Chapter 1, Section 1.1.3.1 of this thesis). This constant can be estimated using methods such as FLIPS72 or the inversion recovery experiment.73,74 FN1:1 MeCN:MeOHFHO FH2O+ +H2NF5.1 5.2 5.300.10.20.0 0.5 1.0 1.5 2.0Time (h)a)b) d)00.10.20.0 0.5 1.0 1.5 2.0Apparent Concentration (M)Time (h)c)5 mm NMR tube Continuous-flowStopped-flowaldehyde starting material (5.1) imine product (5.3)T1 = 3.6 sT1 = 3.8 s T1 = 4.1 sT1 = 3.4 s6.0Component / ResonanceApparent Rate Constant (h-1 ) 2.04.05 mm NMR tubeStopped-flowContinuous-flow5.2 5.35.1 5.3 229 Further it should be noted that the T1 of a nucleus is a physical constant for a particular resonance at a particular external field strength, temperature, and concentration. Therefore, depending on residence time of analyte under continuous-flow conditions and the T1 for a resonance, spins may not become fully polarized prior to NMR measurement. This is referred to as in-flow effects. Furthermore, a T1 value estimated under continuous-flow conditions does not represent the true T1 of the resonance, rather a complex relationship to reach maximum polarization considering non-polarized spins entering, polarized spins pulsed and observed, and spins leaving the reading frame. This is referred to as out-flow effects. While these phenomena have been known for decades, work by Hall et al. has nicely described these effects with modern high-field NMR instrumentation and highlighted a simple correction factor to compensate for in-flow effects.180 Additionally, Bara-Estaún et al. recently highlighted the use of paramagnetic relaxation agents in flow NMR reaction monitoring analyses, allowing for faster polarization of spins.182 For each component of this imination reaction system, the true T1 values of each of the aryl fluoride resonances were estimated using the inversion recovery experiment under static conditions (Section 5.4.3.1). The T1 values for all 19F resonances were estimated to be ~ 4 s or less (Figure 5.3a). While sufficient time for polarization buildup was confidently supplied in our stopped-flow and 5 mm NMR tube experiments, the nature of reaction profiles for the continuous-flow analysis suggest that a polarization steady-state was additionally achieved prior to 19F{1H} NMR measurements. While these imination reaction data highlight the consistent reaction profiles that may be achieved with either stopped-flow or continuous-flow monitoring techniques for when all monitored resonances possess reasonable T1 values, differences arise in the SNR for a given resonance, acquired with the same number of scans with each technique (Figure 5.4). This 230 highlights a consideration that may alone lead one to choose one monitoring technique over another with a benchtop NMR system. Figure 5.4. Superimposed NMR spectra (19F{1H}, 58 MHz, normalized to noise) for an imine product resonance (δF -118.9 ppm) from the same timepoint of the reaction. Spectra showcase the relative SNR differences for data acquired with the same acquisition parameters between 5 mm NMR tube analysis (orange), stopped-flow (green), and continuous-flow (purple) analyses. In the case of stopped-flow, the reaction mixture was halted in the active volume of the instrument for well over 5 × T1 prior to pulse excitation. This means over 99 % polarization was achieved, lending to maximum amount of signal to be acquired considering the analyte within the active volume in the flow cell. Under continuous-flow conditions, however, the same amount of analyte is present within the active volume, but the previously described in-flow effects overall decrease the amount of polarized spins, and therefore signal. As an example, for the imine product resonance at 𝛿F -118.9 ppm, the continuous-flow 0.4 h timepoint showcased 72 % of the SNR relative to the stopped-flow analysis at the same timepoint. -119.5-119.0-118.5f1 (19F / ppm)5 mm NMR tube (SNR: 39.5) Stopped-flow (SNR: 25.2) Continuous-flow (SNR: 18.2) 231 Therefore, it should be highlighted that while more data points per unit time could be acquired with continuous-flow analyses, these results suggest that the data density comes at an intrinsic SNR cost when considering data acquired with the same acquisition. In contrast, the relative increase in sensitivity for stopped-flow analyses, comes at a cost of time as the NMR flow cell must be replenished, the flow must be halted, and time must be supplied for polarization of spins prior to measurement of an NMR spectrum. Additionally, it is important to note that for a fixed period of time more scans per data point could be acquired with continuous-flow analyses, therefore increasing sensitivity of measurements. While possible, it would become imperative to consider the repetition time and the out-flow effects on the apparent T1 values with signal averaged data - where the need for further correction factors may result.256 Therefore, this inherent sensitivity trade-off and/or complexity of data analysis represents important considerations when selecting an appropriate sampling method for a reaction system with resonances with reasonable T1 values. When comparing the data from stopped-flow and 5 mm NMR tube analyses, in either case sufficient time for polarization of spins was supplied (>5 × T1). Therefore, the difference in observed SNR can be rationalized purely from the difference in the amount of analyte present in the active volume of the NMR instrument between the 5 mm NMR tube and the glass flow cell. The larger internal volume of the 5 mm NMR tube suggests more spins in the active volume that can in turn be excited, resulting in more signal and higher SNR. For one of the imine products resonances (𝛿F -118.9 ppm), the stopped-flow 0.4 h timepoint showcased 64 % of the SNR relative to the 5 mm NMR tube analysis at the same timepoint. Overall, this homogeneous reaction example highlights that, while consistent reaction trends may be able to be acquired with either stopped- or continuous-flow analyses, there will be 232 an intrinsic SNR benefit considering data measured with the same number of scans. For the case of reaction monitoring, where observation of low-level species (intermediates, side-products, etc.) is often desired, stopped-flow can provide the maximum SNR for a particular flow cell and set of data acquisition parameters, and without the introduction of correction factors for either in-flow or out-flow effects. Most importantly, this relative SNR maximum is of interest with the decrease in sensitivity inherent to benchtop NMR systems. 5.2.2 Heterogeneous (biphasic) carboxylic activation PBSF (5.6) has long been reported as a reagent used in the deoxyfluorination of alcohols.257 The Hein lab has been involved in work exploring a similar organic transformation,238 including some included in Chapter 3 of this thesis, monitoring the activation of a carboxylic acid to the corresponding acyl fluoride with SO2F2, a toxic gaseous reagent. We therefore sought to perform a similar transformation with a commercially available liquid substitute. The goal was to monitor the activation of 4-fluorobenzoic acid (5.4) with PBSF (5.6) to prepare the corresponding acyl fluoride (5.10). The reaction was again studied via 19F{1H} NMR. While monitoring this reaction with the various techniques (stopped-flow, continuous-flow, 5 mm NMR tube), aryl fluoride resonances consistent with the carboxylic acid starting material, an intermediate (later identified as symmetrical intermediate 5.9, see Scheme 5.1 and Section 5.4.6.1.2), and acyl fluoride product were readily observed. 233 Scheme 5.1. Plausible reaction pathways for the activation of 4-fluorobenzoic acid (5.4) with PBSF (5.6) in the presence of diisopropylethylamine (DIPEA) to access the associated acyl fluoride 5.10. The aryl fluoride resonances consistent with species 5.4, 5.9, and 5.10 were observed with chemical shifts of 𝛿F -112.5, -103.0, and -101.3 ppm, respectively. Representative data for this transformation for the stopped-flow monitoring trial can be found in Figure 5.5. Similar to the analysis conducted with the previous homogeneous imination reaction, reactions sampled under continuous-flow conditions resulted in the lowest SNR, stopped-flow with a relatively higher SNR, and the reaction performed in an NMR tube resulted in the highest SNR for a given mole fraction conversion timepoint and data collected with the same acquisition. The reasons for these observed SNR differences are consistent with those as previously described for the imination reaction. FMeCNFOHOF SO OFFFFFFFFFFODIPEAFOO OFFOOFOOSO OFF FF FF FF FFO SO OFFFFFFFFFF+5.4 5.5 5.7 5.105.85.95.55.5 5.85.6 234 Figure 5.5. a) Reaction scheme for the activation of 5.4 (0.30 M, 1.0 eq., δF -112.5 ppm) with 5.6 (1.1 eq.) to form the corresponding acyl fluoride 5.10 (δF -101.3 ppm) in MeCN with DIPEA (1.2 eq.). b) Representative zoomed decimated stacked array of 19F{1H} NMR spectra (58 MHz) of the transformation when monitored via stopped-flow NMR. c) Reaction profile resulting from tracking each resonance with time. Further, reaction profiles and apparent rate constants for this reaction system, with each analysis method, were directly compared (Figure 5.6). Considering carboxylic acid starting material 5.4 of this heterogenous, biphasic reaction system, reaction trends and apparent rate constants acquired under stopped-flow and continuous-flow conditions showcased great agreement. Additionally, consistent with literature,143 monitoring this resonance and reaction with flow resulted in a significantly faster reaction compared to if the reaction is performed in a 5 mm NMR tube. This can be observed qualitatively with the reaction trends or quantitatively with the apparent rate constants when fit to first-order exponential. This expected behaviour is consistent with more efficient mass transfer as a result of stirring in the reaction vial when performed in batch. FMeCNFOHO+ F SO OFFFFFFFFFFO+ O SO OFFFFFFFFFDIPEAFOO OF5.4 5.6 5.9 5.10 5.8-130-125-120-115-110-105-100f1 (19F / ppm)a)t=0.1 ht=19.8 hIncreasing Timeb) c)00.10.20.30 5 10 15 20Concentration (M)Time (h)5.45.105.9 235 Figure 5.6. a) Reaction scheme for the activation of 5.4 (0.30 M, 1.0 eq., δF -112.5 ppm) to form the corresponding acyl fluoride 5.10 (δF -101.3 ppm) using PBSF (5.6, 1.1 eq.), along with estimated T1 values for the two aryl fluoride resonances. Observed reaction trends from 19F{1H} NMR spectra (58 MHz) are compared for each component monitored via stopped-flow (purple circle), continuous-flow (pink diamonds), and reaction performed in 5 mm NMR tube (grey cross): b) carboxylic acid starting material 5.4 and c) aryl fluoride of acyl fluoride product 5.10. d) Apparent rate constants for each component/resonance when fitted to first-order exponential. Interestingly, when comparing reaction trends for the aryl fluoride resonance of acyl fluoride product 5.10, the reaction profiles and apparent rate constants acquired with stopped-flow and continuous-flow analyses were not in agreement. Instead, the stopped-flow analysis suggested faster product formation, unexpected as the reactions were performed under the same conditions (scale, temperature, etc.). Furthermore, the reaction performed in a 5 mm NMR tube resulted in a slower reaction trend than that monitored via stopped-flow as expected, but unexpectedly matched that from the continuous-flow trial. FMeCNFOHO+ F SO OFFFFFFFFFFO+ O SO OFFFFFFFFFDIPEA5.4 5.10a)00.10.20.30 5 10 15 20Time (h)00.10.20.30 5 10 15 20Apparent Concentration (M)Time (h)T1 = 3.5 sT1 = 14.7 sb) c)5 mm NMR tube Continuous-flowStopped-flowcarboxylic acid starting material (5.4) acyl fluoride product (5.10)d)Component / ResonanceApparent Rate Constant (h-1 ) 0.200.400.605 mm NMR TubeStopped-flowContinuous-flow5.4 5.10 236 Upon consideration of the resulting reaction trends and estimation of aryl fluoride T1 values, it was hypothesized that the previously described in-flow effects of flow on resonance polarization was an influencing factor in the discrepancy. The estimated T1 of the aryl fluoride of product 5.10 (14.7 s) was significantly longer than that of the carboxylic acid starting material 5.4 (3.5 s). Therefore, we posit the very long T1 of the product’s aryl fluoride resonance results in inadequate buildup of polarization prior to 19F{1H} spectral acquisition during the continuous-flow analysis. While the use of correction factors has been reported to compensate for such deviations due to in-flow effects,180 this may have been applied for a more accurate representation of the apparent concentration over time for 5.10 under continuous-flow conditions. However, even without correction, the apparent rate constant would be expected to be in agreement with the stopped-flow trial, so long that the apparent T1 and all other physical factors (such as pump flow rate) remain unchanged throughout the reaction. Therefore, the disagreement between stopped-flow and continuous-flow rate constants for 5.10, therefore, suggests some inconsistencies through the course of the reaction. For instance, T1 values are known to be dependent on many physical properties, such as viscosity of solvent, concentration, and temperature.200,201 As the species is being formed through the reaction, the concentration inherently changed (from 0 M to ~ 0.2 M). Additionally, as the reaction went from a heterogeneous, biphasic solution, to a homogeneous solution, a change in viscosity of the reaction solvent is evident. This change could impact the flow rate, intrinsically changing the extent of in-flow and out-flow effects. Therefore, with the many factors that would need be accounted for to accurately monitor this dynamic system over the entire reaction course, we 237 avoided the application of a correction factor in effort to simplify data analysis, with the ultimate goal of highlighting a method for robust walk-up analyses for our synthetic chemist colleagues. Additionally, analysis of the apparent mass balance with acquired 19F{1H} NMR data (Figure 5.7) from the continuous-flow trial are further consistent with our previous hypothesis of inadequate polarization of the resonance consistent with the aryl fluoride of 5.10. While the apparent mass balance is expected to be constant throughout the reaction course if any and all flow effects are accounted for, the sum of aryl fluoride concentrations for continuous-flow monitoring showcased a decrease over the first 5 hours, followed by a slow increase over the remainder of time. This is in contrast to the mass balance trends of that from the 5 mm NMR tube and stopped-flow trials that showcased a mass balance closer to what would be expected. Therefore, the un-corrected continuous-flow data are consistent with the underestimation of a reaction component over the time course as the product is being formed. 238 Figure 5.7. a) Summation of reaction component concentrations used for uncorrected mass balance analysis. b) Results of uncorrected mass balance with line equation for linear line of best fit displayed (line not shown) for: b) 5 mm NMR tube, c) stopped-flow, and d) continuous-flow. While all previous data were acquired on a benchtop NMR instrument, we were curious if the inadequate polarization of acyl fluoride 5.10 would be observed to the same extent with the utilization of a high-field NMR instrument. The magnitude of the impacts of flow on NMR data have been documented to be dependent on magnet design.180 Additionally this was particularly of interest with the difference in stray field available to polarize nuclei with flow analyses for high-field systems with superconducting magnets and benchtop NMR systems with permanent magnets.183 Therefore, activation of the same carboxylic acid 5.4 with PBSF (5.6) was performed under the same flow conditions (concentration, flow rate, etc.) but monitored via 19F NMR at 471 MHz (Figure 5.8, see Section 5.4.2.2 for system setup). In effort to probe the question, the reaction initially was monitored under continuous-flow conditions but part way through the reaction course the pump was turned off and the monitoring continued under static conditions for the remainder of the time course. FOHOFFO++FOO OF5.4 5.9 5.10y = -0.0004x + 0.212100.20.40.60 5 10 15 20Time (h)y = -0.0018x + 0.268100.20.40.60 5 10 15 20Time (h)y = -2E-05x + 0.303100.20.40.60 5 10 15 20Apparent Concentration (M)Time (h)a)b)5 mm NMR tube Stopped-flowd)c)Continuous-flow 239 The same polarization phenomenon was observed under the same conditions but monitoring via high-field NMR. This was particularly evident by comparing the apparent concentrations of the last data point with the pump “on” and the first data point with the pump “off” for starting material 5.4, intermediate 5.9, and product 5.10 (Figure 5.8). With all the final data points with the pump “on” normalized, the integrations for resonance of both starting material 5.4 and intermediate 5.9 increased by 16 % when flow was halted. While it is expected that integrations would increase with the flow halted (for reasons highlighted in previous discussion regarding T1 and polarization), the integral values for all species were expected to increase by the same relative amount if the same relative polarization was achieved prior to spectral measurement. Instead, we observed a much larger (47 %) increase in resonance integration for product 5.10. 240 Figure 5.8. a) Reaction scheme for the activation of 5.4 (0.30 M, δF -112.5 ppm) with 5.6 (1.1 eq.) to form the corresponding acyl fluoride 5.10 (δF -101.3 ppm) in MeCN with DIPEA (1.2 eq.). b) Observed reaction trends resulting from tracking each 19F resonance (471 MHz) of interest, with the pump turned “off” part way through the reaction course. c) Relative normalized comparisons of last point with pump “on” and first point with pump “off”. d) Uncorrected mass balance analysis as result of tracking the sum of aryl fluoride components over time. The observed difference in relative concentrations for the last data point with the pump “on” and the first point with the pump “off” can be rationalized based on the estimated T1 values. The significantly large relative difference for the aryl fluoride resonance of product 5.10 suggested that an unequal proportion of spins remained unpolarized in continuous-flow conditions, compared to starting material 5.4 and intermediate 5.9 prior to acquiring the fluorine spectra. This result is consistent with the in-flow effects of flow NMR, where the long estimated T1 (14.7 s) for 5.10 suggests that a smaller proportion of spins may be polarized for a given flow rate relative to starting material 5.4 (estimated T1 of 4.7 s). Then upon halting the reaction mixture in the instrument, all the spins existed in the external magnetic field such that over 99 % polarization was achieved prior to spectral measurement, regardless of the specific resonance. 00.20.40.60 5 10 15Apparent Concentration (M)Time (h)FMeCNFOHO+ F SO OFFFFFFFFFFO+ O SO OFFFFFFFFFDIPEAFOO OF5.4 5.6 5.9 5.10 5.8++[a)00.10.20.30 5 10 15Apparent Concentration (M)Time (h)b) d)c)Pump “OFF”Pump “ON”Chemical speciesLast data point withpump “ON”First data point withpump “OFF”1 1.161 1.161 1.47Pump “OFF”Pump “ON”Relative concentrations with/without flowAryl Fluoride Mass Balance]5.45.105.95.105.95.4 5.105.95.4 241 Additionally, through monitoring the aryl fluoride apparent mass balance for carboxylic acid starting material 5.4, symmetric anhydride intermediate 5.9, and acyl fluoride 5.10 for the same trial, interesting behaviour is observed (Figure 5.8d). During the first part of the reaction, when the system was monitored via continuous-flow, one can observe similar downward trend to that observed in the continuous-flow trial utilizing the benchtop NMR. Then once the pump is turned off the mass balance becomes, as expected, linear with a slope of zero. These data are therefore consistent with previous observations and further are consistent with inadequate polarization for the continuous-flow conditions used, even when acquired with a different magnet geometry and high-field NMR spectrometer. 5.3 Conclusion With the increase in commercially available benchtop NMR instruments and associated on-line flow systems, the potential for NMR to serve as a convenient process analytical technology is ever increasing. With such a system, a reaction can be easily monitored stopped-flow (flowing reaction solution to the NMR, stopping the solution, acquiring a spectrum, repeat) or continuous-flow (acquire NMR spectrum as solution is flowing through NMR). As in the literature a substantial difference one may observe in reactions performed in a 5 mm NMR tube and those monitored by continuous-flow has been reported,143 we sought to directly compare stopped-flow and continuous-flow sampling methods for NMR reaction monitoring. Our work suggests that even in instances where the resulting reaction trends may agree between sampling techniques there will always be an inherent SNR benefit to stopped-flow analyses as maximum polarization of NMR active spins for a particular volume may be achieved, considering the data measured with the same acquisition parameters. This difference in SNR may be particularly of interest to benchtop NMR users with the sensitivity limitation inherent to 242 benchtop instruments. The work presented on the homogeneous imination reaction particularly showcases the SNR differences as described. It should be noted that under continuous-flow conditions, however, either a higher degree of data density could be collected, or data can be collected with more scans to improve SNR. Furthermore, the work presented on the heterogeneous activation of a 4-fluorobenzoic acid (5.4) to the corresponding acyl fluoride (5.10) using PBSF (5.6) highlights where one can observe differences in reaction profiles between stopped-flow and continuous-flow trials - when the T1 of a resonance of interest is long. In this case, continuous-flow conditions may not allow for ap-propriate polarization to accurately characterize a given profile. It is important to note that correction factors may be applied to compensate for in-flow effects. However, under dynamic reaction conditions, where a change in T1 (due to change in concentration or solvent viscosity) or change in flow rate (due to change in reaction mixture viscosity) may make for challenging corrections. Additionally, our work highlights this may not solely be a limitation of benchtop NMR systems, as the same observations resulted with the same reaction system monitored with a high-field NMR system. In the interest of furthering benchtop NMR as an accessible reaction monitoring tool for non-NMR specialists, stopped-flow analyses allow under quantitative data acquisition without correction factors for in-flow effects and with the convenience of using a flow system. While reaction monitoring under continuous-flow conditions may be the method of choice for a faster reaction due to higher data density, stopped-flow analyses can enhance the ease of ensuring the quantitative nature of the benchtop NMR reaction data. 243 5.4 Experimental and further data 5.4.1 General 5.4.1.1 Chemicals All materials were obtained from commercial sources and used as received. 4-fluorobenzaldehyde (5.1), 4-fluoroaniline (5.2), 4-fluorobenzoic acid (5.4), perfluorobutanesulfonyl fluoride (PBSF, 5.6), diisopropylethylamine (DIPEA) were obtained from Sigma-Aldrich and used as received. Additionally, acetonitrile (MeCN) and methanol (MeOH) were obtained from Fisher Scientific. 5.4.1.2 NMR data collection, processing, and analysis NMR measurements for reaction monitoring were conducted on a 1.46 T Magritek Spinsolve 60 benchtop NMR system (1H: 62 MHz, 19F: 58 MHz) and a 11.74 T Bruker AVANCE III HD system (1H: 500 MHz, 19F: 471 MHz) equipped with a nitrogen-cooled Prodigy broadband probe. Chemical shifts (δ) are reported in parts-per-million (ppm) and coupling constants (J) are provided in hertz (Hz). All NMR data were processed and analyzed with Mestrelab’s Mnova software. The following abbreviations were used to describe multiplicities of resonances in the characterization data: s = singlet, d = doublet, dd = doublet of doublets, m = multiplet. All benchtop19F{1H} NMR reaction monitoring data were processed with baseline correction (3rd order polynomial fit) and auto phase correction (manual phase correction applied if additional correction necessary). Additionally, data were processed with applied exponential apodization of 2.0 Hz. 244 Offline high-field NMR data for structure elucidation were collected with a 7.0 T Avance spectrometer (resonance frequencies of 300 and 282 MHz for 1H and 19F, respectively), 9.4 T Bruker Avance spectrometer (resonance frequencies of 400, 377, and 101 MHz, for 1H, 19F, and 13C, respectively), and 14.1 T Bruker Avance (resonance frequencies of 600 and 151 MHz for 1H and 13C, respectively). 5.4.1.3 Hazards and experimental precautions Reactions included in this work include hazardous material that must be taken under special consideration. Reactions using perfluorobutanesulfuryl fluoride (PBSF, 5.6) may result in the formation of hydrofluoric acid, highly corrosive and dangerous. 5.4.2 Details on NMR flow systems 5.4.2.1 Benchtop NMR flow system 5.4.2.1.1 General information The on-line benchtop NMR stopped-flow system (Figure 5.1) consisted of three hardware components: a benchtop NMR spectrometer, a peristaltic pump (Vapourtec SF-10 reagent pump), and a six-port valve (Vici C2, two-ports plugged). These components were connected by either ethylene tetra-fluoroethylene (ETFE, 1/16′′ outer diameter (O.D.), 0.02′′ inner diameter (I.D.)) or polyether ether ketone (PEEK, 1/16′′ O.D., 0.01′′ I.D.) tubing. No thermal regulation of these lines was implemented, as a lack of thermal regulation is a known and well-established limitation of many benchtop NMR instruments. With this temperature consideration in mind, all reaction solutions in the primary reaction solution (either NMR tube or scintillation vial) were maintained at 26 °C (internal temperature of magnet) to ensure the integrity of direct comparisons between analysis techniques. 245 In addition to the hardware components listed above, an NMR glass flow cell from the instrument manufacturer was used where the analyte solution entered from the bottom of the instrument and exited the top. The entire volume of this system, with all tubing to/from the reaction vial and the glass flow cell, was determined to be 1.76 mL (Section 5.4.2.1.3). For stopped-flow analyses (Figure 5.1a), an internally developed Python script was used. This script allowed central control of pump flow rate, valve position, and benchtop NMR data acquisition (experiment, acquisition parameters, number of spectra, and overall time between spectra). Reaction solution initially was pumped from the vial through the valve and NMR flow cell, returning to the vial (valve position “A”). At a pre-determined timepoint, the valve position switched (valve position “B”), resulting in the reaction solution being pumped from the reaction vial to the valve and returning to the vial, without entering the NMR loop. After a lock and calibrate protocol, and pre-magnetization time in this static condition, data were acquired. Once acquisition completed, the valve position switched (position “A”) to allow for reaction solution to be replenished and the procedure repeats. For continuous-flow analyses (Figure 5.1b), the same hardware system and Python script was used but the valve position was not toggled through the reaction course (i.e., valve remained in position “A”). This allowed for reaction mixture to continuously flow through the system, with data acquisition occurring as the sample flowed through the spectrometer. In all flow analyses, a flow rate of 2.7 mL/min was used. This flow rate resulted in a 38 s residence time for analyte within the entire benchtop NMR flow system (valve position “A”) and allowed for timely transfer of reaction solution from the reaction vial to the benchtop NMR for analysis. It is acknowledged that a slower flow rate may be leveraged and may be beneficial in enhancing polarization in continuous-flow analyses. However, this comes at the expense of 246 lengthening the time to which reaction solution is exposed to conditions not representative of the reaction vial (e.g., if reaction vial is heated/cooled or mechanically stirred). 5.4.2.1.2 Calibration of system’s peristaltic pump The used Vapourtec SF-10 reagent pump was calibrated with THF and four flow rates. These flow rates were later determined to be 1.8, 2.4, 3.0 and 3.7 mL/min. Scintillation vials were pre-weighed using an analytical balance and THF was pumped through the flow system and collected into the pre-weighed scintillation vial. This was completed for each flow rate, where THF was collected for two minutes at each rate. The mass of THF pumped in this time interval was converted to a volume using the density of THF. Within the flow rate range analyzed, these data suggested a conversion factor of 0.6202 to determine the actual flow rate (Figure 5.9). Figure 5.9. Calibration of Vapourtec SF-10 reagent pump (with THF) for stopped-flow NMR system. 5.4.2.1.3 Determination of benchtop NMR flow system volume To measure the volume of this system (as shown in Figure 5.1), a stock solution of 0.36 M benzotrifluoride was prepared in acetonitrile (MeCN). Using a volumetric pipet, 3.00 mL of y = 0.6202x - 0.0667R² = 1012340 2 4 6 8Real Flow Rate (mL/min)Set Flow Rate (mL/min) 247 this solution was transferred to a scintillation vial, equipped with a magnetic stir bar, fitted with a septum filled cap, and set aside. The stock solution was flowed through the flow system (valve position: “A”) at 3.0 mL/min and collected into a waste container, ensuring this solution was purely within the reading frame of the instrument. The pump was stopped and three 19F NMR spectra (“pre” spectra) were measured on the solution, each with the same acquisition parameters: 90º pulse, 1 scan, no dummy scans, 3.28 s AQ, 20,000 Hz (343.5 ppm) SW, -40.0 ppm spectral offset, and 17.3 s 𝜏*. Post data acquisition, the solution in the flow system was evacuated and fresh MeCN was flowed into the system (again, collecting into waste at 3.0 mL/min with valve in position “A”). With the system primed with fresh MeCN, the inlet and outlet lines of the system were transferred to the scintillation vial with the 3.00 mL of the 0.36 M benzotrifluoride standard solution. On a magnetic stir plate, the solution in the vial was stirred (300 rpm) and the inlet line was placed well below the liquid level. The pump was then turned on (3.00 mL/min) and the solution was able to circulate and reach an equilibrium concentration over 20 minutes. After this time, the pump was turned off and three 19F NMR spectra (“post” spectra) were acquired on the solution with the same acquisition parameters previously described for the “pre” spectra, but spectral offset set to -55.0 ppm. Once spectra were imported and processed in Mnova, the absolute integration of the trifluoromethyl resonance (𝛿F -63.3 ppm) of benzotrifluoride was determined. The average “pre” integration (17.27, 1.33 % RSD) and average “post” integration (10.89, 0.65 % RSD) were used to determine the volume of the system based on a 3.00 mL “pre” volume. Therefore, the system’s volume (calculated 1.76 mL) was equal to the “post” volume minus the “pre” volume. The “post” volume was calculated using Equation 3.1 in Chapter 3. 248 5.4.2.2 High-field NMR flow system 5.4.2.2.1 General information The use of the six-port valve in the NMR flow system enables for great hardware flexibility when with the flow system itself. To further probe whether the differing geometries of high-field and benchtop systems lend to differing effects of continuous-flow on reaction profiles for reaction monitoring, we incorporated a Bruker Avance III 500 MHz system (1H: 500 MHz, 19F: 471 MHz) into the flow system. This was easily completed with the use of a Bruker InsightMR system and varying the flow path to the benchtop NMR flow system by changing the valve connection ports as shown in the schematic in Figure 5.10. This allowed for benchtop and high-field spectrometers to be connected in series. Further, a picture of the lab space with the flow system (with both high-field and benchtop spectrometer) is shown in Figure 5.11. 249 Figure 5.10. Schematic highlighting the flow NMR system with both benchtop and high-field NMR spectrometers connected in series. For the majority of this work, the high-field NMR system was taken out of the loop and not used. 500 MHz60 MHzReaction Vial in EasyMaxPumpBenchtop NMR High-field NMR FLOWINGFLOWINGFLOWINGValve 250 Figure 5.11. Picture highlighting the lab space with the complete high-field and benchtop flow NMR system. For the majority of this work, the high-field NMR system was taken out of the loop and not used. 5.4.2.2.2 Determination of the volume of the benchtop NMR system with integration of a high-field NMR To measure the volume of this system (as shown in Figure 5.10 and Figure 5.11 above), the same stock solution of 0.36 M of benzotrifluoride in MeCN was used as in the determination of the benchtop NMR flow system (Section 5.4.2.1.3). Using a volumetric pipet, 3.00 mL of this solution was transferred to a scintillation vial, equipped with a magnetic stir bar, fitted with a septum filled cap, and set aside. 251 The 19F NMR spectra of the 0.36 M stock solution (“pre”) used previously to determine the volume of the flow system only with the benchtop NMR (Section 5.4.2.1.3) was also used for this trial as this was completed consecutively. Therefore, fresh MeCN was flowed into the system (collecting into waste at 3.0 mL/min) and once the system was primed with fresh MeCN, the inlet and outlet lines of the system were transferred to the scintillation vial with the 3.00 mL of the 0.36 M benzotrifluoride standard solution. On a magnetic stir plate, the solution in the vial was stirred (300 rpm) and the inlet line was placed well below the liquid level. The pump was then turned on (3.00 mL/min) and the solution was able to circulate and reach an equilibrium concentration over 20 minutes. After this time, the pump was turned off and three benchtop 19F NMR spectra (“post” spectra) were measured on the solution, each with the same acquisition parameters: 90º pulse, 1 scan, no dummy scans, 3.28 s AQ, 20,000 Hz (343.5 ppm) SW, -40.0 ppm spectral offset, and 17.3 s 𝜏*. Once spectra were imported and processed in Mnova, the absolute integration of the trifluoromethyl resonance (𝛿F -63.3 ppm) of benzotrifluoride was determined. The average “pre” integration (17.27, 1.33 % RSD) and average “post” integration (6.92, 2.66 % RSD) were used to determine the volume of the system based on a 3.00 mL “pre” volume. Therefore, the system’s volume (calculated 4.48 mL) was equal to the “post” volume minus the “pre” volume, with the “post” volume calculated using Equation 3.1 in Chapter 3. 5.4.3 Spin-lattice relaxation time (T1) estimations In effort to allow for sufficient polarization and relaxation to ensure quantitative NMR conditions, T1 values for each of the major chemical species were estimated in effort to determine the necessary time required for adequate polarization to be accumulated. To do so, the inversion recovery experiment73,74 was applied with the used benchtop NMR spectrometer (19F: 58 MHz). 252 5.4.3.1 Species relevant to imination reaction To determine the T1 of 4-fluorobenzaldehyde (5.1), an NMR tube of the starting material was prepared in the reaction solvent mixture (1:1 MeCN:MeOH) at the relevant reaction concentration (0.22 M). Then, using the inversion recovery experiment, the time between the 180° and 90° pulses (𝜏) was varied in 64 linearly spaced increments between 𝜏start (0.001 s) and 𝜏stop (30.0 s). 19F NMR data were measured with 2 scans, no dummy scans, 1.64 s AQ, 5,000 Hz (85.9 ppm) SW, -110.0 ppm spectral offset, and 198.6 s 𝜏*. Once processed in Mnova, these data were analyzed by integrating the signal corresponding to the aryl fluoride resonance (𝛿F -105.0 ppm) and plotting this integration against 𝜏. These data were fitted to a line of best fit in Mnova and the T1 was calculated (3.6 s). For results for this resonance, see Figure 5.12. Figure 5.12. Results from application of the inversion recovery experiment for T1 estimation of the aryl fluoride resonance of 5.1 (δF -105.0 ppm, 58 MHz, 26 °C). These results are shown a) qualitatively with the resonance of interest (decimated spectra, normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values. -115-110-105-100-95f1 (19F / ppm)0 4 8 12 16 20 24 28Tau (s)-10-5051015IntegrationY' = B+F*exp(-Tau *G)B=16.26; F=-28.34; G=0.2749;Error: 2.532T1 = 3.6 sIncreasing !a) b)FHO5.1 253 Similar to 5.1 above, an NMR tube of 4-fluoroaniline (5.2) was prepared in the reaction solvent mixture (1:1 MeCN:MeOH) at the relevant reaction concentration (0.22 M). Then, using the inversion recovery experiment, the time between the 180° and 90° pulses (𝜏) was varied in 27 linearly spaced increments between 𝜏start (0.001 s) and 𝜏stop (20.0 s). 19F NMR data were measured with 2 scans, no dummy scans, 1.64 s AQ, 5,000 Hz (85.9 ppm) SW, -125.0 ppm spectral offset, and 198.6 s 𝜏*. Once processed in Mnova, these data were analyzed by integrating the signal corresponding to the aryl fluoride resonance (δF -129.6 ppm) and plotting this integration against 𝜏. These data were fitted to a line of best fit in Mnova and the T1 was calculated (3.8 s). For results for this resonance, see Figure 5.13. 254 Figure 5.13. Results from application of the inversion recovery experiment for T1 estimation of the aryl fluoride resonance of 5.2 (δF -129.6 ppm, 58 MHz, 26 °C). These results are shown a) qualitatively with the resonance of interest (decimated spectra, normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values. Lastly, a completed reaction solution was used to determine the T1 values of the two aryl fluorides consistent with imine product 5.3 (in 1:1 MeCN:MeOH, 0.22 M). Using the inversion recovery experiment, the time between the 180° and 90° pulses (𝜏) was varied in 6 linearly spaced increments between 𝜏start (0.001 s) and 𝜏stop (12.5 s). 19F NMR data were measured with 2 scans, no dummy scans, 1.64 s AQ, 5,000 Hz (85.9 ppm) SW, -115.0 ppm spectral offset, and 198.6 s 𝜏*. Once processed in Mnova, these data were analyzed by integrating the signals corresponding to the two aryl fluoride resonances (δF -110.0 and -118.9 ppm) and plotting this integration against 𝜏. These data were fitted to a line of best fit in Mnova and the T1 was calculated (3.4 and 4.1 s for resonances with chemical shifts of 𝛿F -110.0 and -118.9 ppm, respectively). For results for these resonances, see Figure 5.14. -140-135-130-125-120f1 (19F / ppm)Increasing ! Y' = B+F*exp(-Tau *G)B=20.85; F=-36.07; G=0.2630;Error: 2.016T1 = 3.8 s0 2 4 6 8 10 12 14 16 18 20Tau (s)-1001020Integrationa) b)H2NF5.2 255 Figure 5.14. Results from application of the inversion recovery experiment for T1 estimation of the two aryl fluoride resonances of 5.3 (δF -110.0 and -118.9 ppm, 58 MHz, 26 °C). These results are shown a) qualitatively with the resonance of interest (decimated spectra, normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values. 5.4.3.2 Species relevant to carboxylic acid activation with PBSF To determine the T1 of the aryl fluoride of 4-fluorocarboxylic acid (5.4), an NMR tube of the starting material (along with 1.2 eq. DIPEA, for solubility) was prepared in the reaction solvent (MeCN) at the relevant reaction concentration (0.30 M). Then, using the inversion recovery experiment, the time between the 180° and 90° pulses (𝜏) was varied in 27 linearly spaced increments between 𝜏start (0.001 s) and 𝜏stop (20.0 s). 19F NMR data were measured with 2 scans, no dummy scans, 1.64 s AQ, 5,000 Hz (85.9 ppm) SW, -110.0 ppm spectral offset, and 198.6 s 𝜏*. Once processed in Mnova, these data were analyzed by integrating the signal corresponding to the aryl fluoride resonance (δF -112.5 ppm) and plotting this integration against 𝜏. These data were fitted to a line of best fit in Mnova and the T1 was calculated (3.5 s). For results for this resonance, see Figure 5.15. -130-120-110-100f1 (19F / ppm)0 1 2 3 4 5 6 7 8 9 10 11 12 13Tau (s)-505IntegrationY' = B+F*exp(-Tau *G)B=8.064; F=-13.79; G=0.2910;Error: 0.3122T1 = 3.4 s Y1' = B+F*exp(-Tau *G)B=8.685; F=-14.52; G=0.2412;Error: 0.4291T1 = 4.1 sIncreasing !a) b)FNF5.3 256 Figure 5.15. Results from application of the inversion recovery experiment for T1 estimation of the aryl fluoride resonance of 5.4 (δF -112.5 ppm, 58 MHz, 26 °C). These results are shown a) qualitatively with the resonance of interest (decimated spectra, normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values. To determine the T1 of the aryl fluoride of the acyl fluoride product (5.10), a completed reaction solution was used (in MeCN). Using the inversion recovery experiment, the time between the 180° and 90° pulses (𝜏) was varied in 64 linearly spaced increments between 𝜏start (0.001 s) and 𝜏stop (30.0 s). 19F NMR data were measured with 4 scans, no dummy scans, 1.64 s AQ, 5,000 Hz (85.9 ppm) SW, -100.0 ppm spectral offset, and 198.6 s 𝜏*. Once processed in Mnova, these data were analyzed by integrating the signal corresponding to the aryl fluoride resonance (δF -101.3. ppm) and plotting this integration against 𝜏. These data were fitted to a line of best fit in Mnova and the T1 was calculated (14.7 s). For results for this resonance, see Figure 5.16. -120-115-110-105f1 (19F / ppm)0 2 4 6 8 10 12 14 16 18 20Tau (s)-10-5051015IntegrationY' = B+F*exp(-Tau *G)B=18.40; F=-31.79; G=0.2862;Error: 2.174T1 = 3.5 sIncreasing !a) b)FOHO5.4 257 Figure 5.16. Results from application of the inversion recovery experiment for T1 estimation of the aryl fluoride resonance of 5.10 (δF -101.3 ppm, 58 MHz, 26 °C). These results are shown a) qualitatively with the resonance of interest (decimated spectra, normalized to noise) and b) graphically with peak integration of the resonance graphed with application of various 𝜏 values. 5.4.4 Reaction monitoring procedures 5.4.4.1 Imination Reaction For both stopped- and continuous-flow trials, 1:1 MeCN:MeOH (7.20 mL) was added to septum capped vial equipped with a magnetic stir bar. This solution was then circulated through the flow system at a flow rate of 2.7 mL/min. To this vial 4-fluorobenzaldehyde (5.1, 0.18 mL, 1.7 mmol, 1.0 eq.) was added, followed by 4-fluoroaniline (5.2, 0.18 mL, 1.9 mmol, 1.1 eq.). After mixing, the Python script controlling data acquisition was started. For the reaction completed in a 5 mm NMR tube, 1:1 MeCN:MeOH (1.00 mL) was added to an NMR tube, followed by 4-fluorobenzaldehyde (5.1, 0.025 mL, 0.23 mmol, 1.0 eq.) and 4-fluoroaniline (5.2, 0.025 mL, 0.26 mmol, 1.1 eq.). The tube was inverted multiple times to achieve good mixing and was entered into the NMR spectrometer. The Python script was then started (pump and valve not used, lines commented out in code) controlling data collection. -105-100-95f1 (19F / ppm)0 4 8 12 16 20 24 28Tau (s)-10-50510IntegrationY' = B+F*exp(-Time*G)B=15.32; F=-26.04; G=0.06792;Error: 4.787T1 = 14.7 sIncreasing !a) b)FFO5.10 258 Spectra were collected every 250 s, and a lock and calibration protocol (~ 55 s), followed by 20 s pause time, was completed just before each 19F{1H} NMR experiment was initiated. For the stopped-flow trial, 25 spectra were acquired, where for continuous-flow and 5 mm NMR tube reaction, 36 spectra were collected in total. Additionally, due to the lock and calibration protocol and designated pause time, ~ 75 s was supplied for the reaction solution to stabilize in the NMR prior to spectral measurement in the case of stopped-flow analysis. In all cases 19F{1H} NMR data were measured with a 90° pulse, 1 scan, no dummy scans, 1.64 s AQ, 5,000 Hz (85.9 ppm) SW, -115.0 ppm spectral offset, and a 4.0 s 𝜏*. 5.4.4.2 Activation of carboxylic acid with PBSF For both stopped- and continuous-flow trials, 4-fluorobenzoic acid (5.4, stopped-flow: 349.95 mg, 2.4 mmol, 1 eq.; continuous-flow: 349.93, 2.4 mmol, 1.0 eq.) was weighed into a septum capped vial. To this vial, MeCN (7.20 mL) was added and was equipped with a magnetic stir bar. DIPEA (0.54 mL, 3.0 mmol, 1.2 eq.) was next added. This solution was then circulated through the flow system, with flow rate of 2.7 mL/min. Finally, PBSF (5.6, 0.54 mL, 2.7 mmol, 1.1 eq.) was added. After mixing, data acquisition was started and only the MeCN layer was sampled. This was achieved as the PBSF layer was both small (~ 6 % of the total initial volume) and more dense than the MeCN layer. Therefore, by placing the intake line near the surface of the liquid level, we were able to ensure only the MeCN layer was pumped through the system and sampled with the NMR. For the reaction completed in a 5 mm NMR tube, 4-fluorobenzoic acid (5.4, 39.43 mg, 0.28 mmol, 1.0 eq.) was weighed into a vial. To this vial, MeCN (0.80 mL), DIPEA (0.060 mL, 0.34 mmol, 1.2 eq.), and PBSF (5.6, 0.055 mL, 0.31 mmol, 1.1 eq.) were added. Upon quickly mixing the contents of the vial, the entire solution was transferred to a 5 mm NMR tube and entered into 259 the NMR spectrometer such that only the MeCN soluble layer was within the reading frame of the instrument. The Python script was then started for data collection where the pump and valve were not active. Spectra were collected every 540 s for the stopped-flow and continuous-flow analyses and every 600 s for the reaction performed in a 5 mm NMR tube. A lock and calibration protocol (~ 55 s), followed by 40 s pause time, was completed just before each 19F{1H} NMR experiment was initiated. For stopped-flow, continuous-flow, and 5 mm NMR tube reactions, 132, 129, and 394 spectra were collected in total, respectively. Additionally, due to the lock and calibration protocol and designated pause time, ~ 95 s was supplied for the reaction solution to stabilize in the NMR prior to spectral measurement in the case of stopped-flow analysis. Additionally, as the reaction progressed, all reaction solutions became homogeneous. In all cases (stopped- or continuous-flow, 5 mm NMR tube), 19F{1H} NMR data were measured with a 90° pulse, 1 scan, no dummy scans, 1.64 s AQ, 5,000 Hz (85.9 ppm) SW, -100.0 ppm spectral offset, and a 10.0 s 𝜏*. For the high-field continuous-flow/no flow trial, 4-fluorobenzoic acid (5.4, 459.50 mg, 3.2 mmol, 1 eq) was weighed into a septum capped vial. To this vial, MeCN (9.48 mL) was added and was equipped with a magnetic stir bar. To this solution, DIPEA (5.6, 0.70 mL, 3.9 mmol, 1.2 eq.) was added. This solution was then circulated through the flow system, with flow rate of 2.7 mL/min. Finally, PBSF (0.70 mL, 3.6 mmol, 1.1 eq.) was added. Only the MeCN layer was sampled. After manual acquisition of the first 19F NMR spectrum, additional datasets were acquired utilizing the Bruker “multi_zgvd” command where the 90 spectra were collected with a 613 s fixed delay. For the first 90 minutes, data were acquired under continuous-flow conditions. For the 260 remainder of the trial, data were acquired on the static solution as the pump was turned off for the remainder of the time. The 19F NMR data were measured with a 90° pulse, 1 scan, no dummy scans, 1.50 s AQ, 208,333 Hz (442.7 ppm) SW, -100.0 ppm spectral offset, and a 6.5 s 𝜏*. 5.4.5 Further data relevant to imination reaction 5.4.5.1.1 Additional reaction profiles Reaction profiles resultant from tracking the fluorine resonance of the aniline starting material (5.2) and the aryl fluoride of the imine product (5.3) not shown in Figure 5.3 are displayed in Figure 5.17 below. Figure 5.17. a) Reaction scheme for coupling 5.1 (0.22 M, δF -105.0 ppm) and 5.2 (1.1 eq., δF -129.6 ppm) to form corresponding imine 5.3 (δF -110.0 and -118.9 ppm), along with estimated T1 values of each fluorine resonance using the inversion recovery experiment. Observed reaction trends from benchtop 19F{1H} NMR spectra (58 MHz) monitored via stopped-flow (purple circle) and continuous-flow (pink diamonds) and with the reaction performed in 5 mm NMR tube (grey cross): b) aniline starting material (5.2) and imine product (5.3). FN1:1 MeCN:MeOHFHO FH2O+ +H2NF5.1 5.2 5.3a)b)00.10.20.0 0.5 1.0 1.5 2.0Apparent Concentration (M)Time (h)c)5 mm NMR tube Continuous-flowStopped-flowaniline starting material (5.2) imine product (5.3)T1 = 3.6 sT1 = 3.8 sT1 = 4.1 sT1 = 3.4 s00.10.20.0 0.5 1.0 1.5 2.0Time (h) 261 5.4.5.1.2 Apparent rate constant determination For the imination reaction and each reaction monitoring method, a concentration versus time profile (including all the relevant reaction components) was prepared in Mnova. Then using a “Three Parameter Exponential Fit”, the data were fit where the resulting equation was used to determine the apparent rate constant to first-order approximation. The apparent rate constants for each species and each sampling method (5 mm NMR tube, stopped-flow, continuous-flow) is summarized in Table 5.1. Additionally, the profiles and equations for each method can be found in Figure 5.18, Figure 5.19, Figure 5.20 for 5 mm NMR tube, stopped-flow, and continuous-flow analyses, respectively. Table 5.1. Summary of apparent rate constants for each component/resonance for imination reaction monitored via benchtop 19F{1H} NMR and fitted to first-order exponential. ComponentNMR tube apparent rate constant (h-1)Stopped-flow apparent rate constant (h-1)Continuous-flow apparent rate constant (h-1) Standard Dev. Average (h-1) % RSD4-fluorobenzaldehyde (5.1) 4.025 4.260 4.107 0.12 4.13 2.894-fluoroaniline (5.2) 5.591 3.162 3.903 1.24 4.22 29.51imine product (5.3) 3.778 3.925 3.054 0.47 3.59 13.00imine product (5.3) 3.948 4.374 3.699 0.34 4.01 8.52 262 Figure 5.18. Reaction profile for imination reaction performed in 5 mm NMR tube. 4-fluoroaldehyde (5.1, δF -105.0 ppm) is displayed in red, 4-fluoroaniline (5.2, δF -129.6 ppm) in blue, and imine product (5.3) is displayed in orange and green (for resonances δF -110.0 and -118.9 ppm, respectively). Figure 5.19. Reaction profile for imination reaction monitored via stopped-flow. 4-fluoroaldehyde (5.1, δF -105.0 ppm) is displayed in red, 4-fluoroaniline (5.2, δF -129.6 ppm) in blue, and imine product (5.3) is displayed in orange and green (for resonances δF -110.0 and -118.9 ppm, respectively). 263 Figure 5.20. Observed reaction profile for imination reaction monitored via continuous-flow. 4-fluoroaldehyde (5.1, δF -105.0 ppm) is displayed in red, 4-fluoroaniline (5.2, δF -129.6 ppm) in blue, and imine product (5.3) is displayed in orange and green (for resonances δF -110.0 and -118.9 ppm, respectively). 5.4.5.1.3 Signal-to-noise ratio (SNR) determination Spectra from the same relative reaction timepoint (0.4 h) from reactions performed in a 5 mm NMR tube and monitored via stopped-flow and continuous-flow were all processed in Mnova with the same parameters (application of 2.0 Hz exponential apodization, 3rd order polynomial fit baseline correction, and auto phase correction). After strict alignment of peaks, the “SNR Calculation Non-Interactive…” tool in Mnova was used. For this tool, a noise region of δF -135 to -145 ppm was designated along with a signal region of δF -118.3 to -119.3 ppm. The results, both qualitatively and quantitatively, are displayed in Figure 5.4 in the chapter above. 5.4.6 Further data relevant to PBSF activation reaction 5.4.6.1.1 Apparent reaction constant determination For the carboxylic acid activation reaction with PBSF and each reaction monitoring method, a concentration versus time profile (including the relevant reaction components) was prepared in Mnova. Then using a “Three Parameter Exponential Fit”, the data were fit where the 264 resulting equation was used to determine the apparent rate constant to first-order approximation. The apparent rate constants for each species and each sampling method (5 mm NMR tube, stopped-flow, continuous-flow) is summarized in Table 5.2. Additionally, the profiles and equations for each method can be found below in Figure 5.21, Figure 5.22, and Figure 5.23 for 5 mm NMR tube, stopped-flow, and continuous-flow analyses, respectively. Table 5.2. Summary of apparent rate constants for each component for carboxylic acid 5.4 activation with PBSF (5.6) monitored via benchtop 19F{1H} NMR and fitted to first-order exponential. Figure 5.21. Reaction profile for the carboxylic acid activation with PBSF performed in 5 mm NMR tube. 4-fluorobenzoic acid (5.4, δF -112.5 ppm) is displayed in red and acyl fluoride product (5.10, δF -101.3 ppm) is displayed in blue. ComponentNMR tube apparent rate constant (h-1)Stopped-flow apparent rate constant (h-1)Continuous-flow apparent rate constant (h-1) Standard Dev. Average (h-1) % RSD4-fluorobenzoic acid (5.4) 0.1002 0.5209 0.5665 0.26 0.40 64.94acyl fluoride product (5.10) 0.09328 0.5598 0.1308 0.26 0.26 99.20 265 Figure 5.22. Reaction profile for the carboxylic acid activation with PBSF monitored via stopped-flow. 4-fluorobenzoic acid (5.4, δF -112.5 ppm) is displayed in red and acyl fluoride product (5.10, δF -101.3 ppm) is displayed in blue. Figure 5.23. Observed reaction profile for the carboxylic acid activation with PBSF monitored via continuous-flow. 4-fluorobenzoic acid (5.4, δF -112.5 ppm) is displayed in red and acyl fluoride product (5.10, δF -101.3 ppm) is displayed in blue. 266 5.4.6.1.2 Mechanistic investigation Before gaining some mechanistic insight from these data, we had to consider two plausible reaction pathways to successfully access the desired acyl fluoride product (Scheme 5.1). Upon deprotonation of 4-fluorocarboxylic acid (5.4) with DIPEA, the corresponding carboxylate (5.5) reacts with PBSF (5.6) resulting in a mixed anhydride intermediate 5.7 with a perfluorinated tail and expulsion of fluoride. Then there are two reaction paths the reaction could proceed though: i. fluoride could react directly with 5.7 to provide the desired acyl fluoride product 5.10 and sulfonate 5.8 or ii. carboxylate 5.5 could react with 5.7, releasing sulfonate 5.8 and providing access to symmetrical anhydride 5.9. Fluoride could then react with 5.9 to provide the desired acyl fluoride product 5.10. With observation of an intermediate with our acquired 19F{1H} NMR data, it was sought to infer the chemical identity of the observed intermediate. In effort to gain some reaction mechanism information on the system and further probe sampling method differences, a mass balance analysis was conducted considering the aryl fluoride resonances of each observed reaction components (Figure 5.24). This was performed by plotting the sum of each component’s concentration with time. It is important to note two mass balance schemes were possible, depending on the identity of the intermediate: i. if intermediate had one aryl fluoride, consistent with observation of mixed anhydride intermediate 5.7 or ii. the intermediate had two symmetrical aryl fluorides, consistent with symmetric anhydride intermediate 5.9 (Figure 5.24a). 267 Figure 5.24. a) For mass balance confirmation and to aid in intermediate identification, two summations of concentrations existed depending on if the intermediate possessed one aryl fluoride (blue) or two symmetrical aryl fluorides (red). Uncorrected mass balance for these two schemes, along with line equation for line of best fit (actual line not shown for visual clarity) for: b) 5 mm NMR tube, c) stopped-flow, and d) continuous-flow. If all components are accurately accounted for, one would expect a line with slope of zero for the mass balance sum of all species with time. The mass balance for our reaction system for 5 mm NMR tube, stopped-flow, and continuous-flow sampling methods are displayed in Figure 5.24b-d, respectively. Additionally, the line equation for the line of best fit is displayed considering either observed intermediate scheme (actual line of best fit not shown for enhanced visual clarity). For data acquired with all sampling methods, the slope for the line of best fit is closer to zero when considering the intermediate possessing two symmetric aryl fluorides - consistent with the symmetric anhydride 5.9 as the observed intermediate. Also, it is worth noting that our previous work (Chapter 3), which involved activating the same carboxylic acid substrate 5.4 to acyl fluoride 5.10 but with SO2F2 as the activating reagent, resulted in observation of the FOHOFOOSO OFF FF FF FF FFFO++5.4 5.7 5.10FOHOFFO++FOO OF5.4 5.9 5.10y = -0.0004x + 0.2121y = -0.0014x + 0.232700.20.40.60 5 10 15 20Time (h)y = -0.0018x + 0.2681y = -0.0027x + 0.28700.20.40.60 5 10 15 20Time (h)y = -2E-05x + 0.3031y = -0.0002x + 0.322200.20.40.60 5 10 15 20Apparent Concentration (M)Time (h)a)b)5 mm NMR tube Stopped-flowd)c)Continuous-flowORIntermediate with one aryl fluoride Intermediate with two (symmetrical) aryl fluorides 268 same symmetric anhydride intermediate. Further, the chemical shift is consistent with the intermediate observed in this work. 5.4.7 Product characterization 5.4.7.1 N,1-bis(4-fluorophenyl)methanimine (5.3) 5.3 was synthesized from 5.1 and 5.2 in 1:1 MeCN:MeOH, per procedures highlighted above in Section 5.4.4.1. Upon completion of the reaction, the mixture was dried down to successfully isolate the desired imine product as a yellow powder. 1H NMR (400.2 MHz, CD2Cl2) δH 8.43 (s, 1H), 7.92 (m, 2H), 7.26 - 7.14 (m, 4H), 7.10 (m, 2H); 13C{1H} NMR (100.6 MHz, CD2Cl2) δC 165.13 (d, J = 251.6 Hz), 161.66 (d, J = 244.4 Hz), 158.94, 148.36 (d, J = 3.0 Hz), 133.09 (d, J = 3.1 Hz), 131.15 (d, J = 8.8 Hz), 122.73 (d, J = 8.4 Hz), 116.35 (d, J = 5.6 Hz), 116.13 (d, J = 6.1 Hz); 19F NMR (282.4 MHz, CD2Cl2) δF -108.90 (m), -118.00 (m); MS-EI (m/z) 216.1 [M-H]+ (Calculated for C13H9F2NO, 216.1). 5.4.7.2 4-fluorobenzoyl fluoride (5.10) 5.10 was synthesized from 5.4 and 5.6 in MeCN with DIPEA, per Section 5.4.4.2. Isolation of this product was attempted via silica gel column chromatography but was unsuccessful (compound has been reported to be slightly unstable to silica gel.245 Nonetheless, characterization was successful with analysis of the neat reaction mixture - resulting in data consistent with previously reported data.245,246 FNF5.3 269 1H NMR (600.4 MHz, MeCN) δH 8.07 (m, 2H), 7.28 (m, 2H); 13C{1H} NMR (151.0 MHz, MeCN) δC 167.70 (d, J = 256.6 Hz), 157.11 (d, J = 342.2 Hz), 135.01 (dd, J = 10.2 Hz, J = 4.0 Hz), 121.80 (dd, J = 62.7 Hz, J = 2.8 Hz), 117.18 (d, J = 22.8 Hz); 19F NMR (376.6 MHz, MeCN) δF 16.96 (s), -102.48 (m); MS-EI (m/z) 142.1 [M]+ (Calculated for C7H4F2O, 142.02). FFO5.10 270 Chapter 6: Conclusion and future work 6.1 Conclusion Nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical technique that is uniquely capable of discerning both structurally rich qualitative and quantitative information on individual chemical components in a sample. The increasing commercial availability of smaller and cheaper benchtop NMR instruments is furthering the accessibility and practicality of leveraging NMR spectroscopy as a reaction monitoring tool. However, these benefits arise from the permanent magnet used by such instruments and the lower external magnetic fields also result in a discernable decrease in both the sensitivity and signal dispersion relative to the larger magnetic fields with high-field NMR spectrometers. As the compact size of benchtop NMR spectrometers allows for NMR analyses to be conducted in non-traditional settings (e.g., in/near a fumehood or glovebox), these systems are uniquely suited to be applied for reaction monitoring analyses as the spectrometer can be physically placed near the active synthetic chemistry, allowing for the process to be performed under “normal” conditions. This is in contrast to the use of high-field NMR instrumentation where the chemistry is likely to be moved, and reaction conditions may need be adjusted to allow for the process to be performed near an NMR spectrometer. However, many systems (e.g., in-situ stopped-flow, rapid injection, on-line continuous-flow, etc.) have been leveraged to allow for successful monitoring analyses with these high-field NMR spectrometers. This thesis aims to focus and expand the effort to increase the practical application of benchtop NMR spectrometers for convenient, real-time reaction and process monitoring analyses, particularly of interest in pharmaceutical settings. 271 Chapter 2 of this thesis explores the use of an on-line continuous-flow benchtop NMR system, where the analyte (i.e., reaction solution) is moving through the spectrometer during data measurement. This was particularly of interest as some of the observed impacts of flow (such as in-flow effects) have been attributed to the magnet configuration of the instrument and the associated stray magnetic field. Therefore, the relevance of this chapter is highlighted by the use of a modern, commercially available spectrometer (Nanalysis Scientific Corp.) and accompanying glass flow cell made by the instrument manufacturer. The results of the exploration of an on-line continuous-flow benchtop NMR suggests a great deal of nuance in selection of conditions for analysis. For example, it may seem ideal to increase the flow rate of the reaction solution to some high rate, resulting in the transfer time of reaction solution to the NMR spectrometer to be minimized for spectral measurement. However, our visual analyses (possible in thanks to a Python script developed by Veronica Lai) showcased the eddying behaviour that may be caused with higher flow rates, resulting in increased inhomogeneity across the flow cell, counter-productive filling/emptying efficiency, and a non-linearity in analytical response. While applying low flow rates can avoid the unpredictable mixing behaviours resultant from higher flow rates, the significantly slower transfer of reaction solution from the reaction vessel to the NMR for analysis prompts the consideration of how representative the NMR data would be on to the bulk reaction solution. Additionally, large concentration gradients in the flow cell may result with slower analyte flow. Application of a medium flow rate, however, resulted in the most ideal plug flow like behaviour. While, in-flow effects may reduce recovered signal due to insufficient polarization of spins due to the spin-lattice relaxation time of the resonance, the out-flow effects may allow for a smaller repetition time for signal averaged data. All-in-all, these 272 results suggest the complex impacts on measuring NMR data on a moving sample with a modern, commercially available benchtop NMR spectrometer. In effort to allow for more robust reaction monitoring analyses, an on-line stopped-flow benchtop NMR system was devised with the same benchtop spectrometer used in the exploration of on-line continuous-flow conditions. The system was applied in Chapter 3 to monitor two model reaction systems that may be difficult to observe with other methods via NMR spectroscopy. Importantly, this system was designed such that the convenience of an on-line flow system could be leveraged, but data acquisition would occur under no flow static conditions. This importantly circumvented complexities observed with continuous-flow analyses in the preceding chapter. Additionally, the presented on-line stopped-flow system was highly practical as the system’s hardware (i.e., peristaltic pump, valve, benchtop NMR spectrometer) was all controlled with a single Python script (developed by Dr. Lars P. E. Yunker). Upon configuration of the on-line stopped-flow system, a “go-to” set of NMR data acquisition parameters was determined for 1D 19F NMR spectra to be measured for the reaction monitoring trials. Special consideration to data measurement ensured quantitative conditions. Observation of 19F NMR was selected as the large chemical shift increases signal dispersion in spectra relative to 1H NMR, important as an overall decrease in signal dispersion is a limitation of benchtop NMR spectrometers compared to high-field NMR spectrometers. Additionally, the practicality of monitoring 19F NMR in pharmaceutical settings is underscored with an increase of fluorine nuclei present in active pharmaceutical ingredients. The utility of the on-line stopped-flow system was demonstrated as the formation and dissolution of SO2F2 into a reaction solvent in a fumehood was successfully monitored. Additionally, the system was successfully leveraged to monitor the hydrolysis of this reagent upon 273 addition of water and base. This is particularly of interest as this highlights the benefit of such system as real-time quantitative information could be acquired on the destruction of this toxic and gaseous reagent. This reagent was then successfully used to activate a carboxylic acid to the corresponding acyl fluoride, particularly of interest as the acyl fluoride could be used for subsequent amide formation. Nonetheless, the acyl fluoride forming process was successfully monitored and insightful species were analytically observed, including the symmetric anhydride intermediate and fluoride anion. The on-line stopped-flow system was further applied to monitor carbamate formation as a result of an isocyanate (formed from modified Curtius rearrangement of an acyl azide formed using a carboxylic acid and DPPA) captured with an alcohol. This system represents another challenging reaction to monitor as hazardous azide handling and gas evolution was involved. The process was successfully monitored where the impact of the order of addition of reagents and conditions was elucidated. This study allowed for interesting insight into the relative rates of each transformation and allowed for suppression of a side product species by fully converting acyl azide to isocyanate with exposure of the reaction vial to heat prior to alcohol addition. Additionally, simultaneously monitoring via benchtop NMR and ReactIR highlighted the representative nature across orthogonal analytical techniques, even despite a heated reaction solution and the use of the non-thermally insulated on-line stopped-flow system. Nonetheless, the model systems successfully monitored in this chapter highlights the utility of the on-line stopped-flow system and showcases how processes underway in a fumehood could conveniently and quantitatively be monitored via benchtop NMR. The work highlighted in Chapter 4 showcases an external referencing qNMR method that allows for convenient quantitative analyses both without the need for a reference material to be 274 added to the sample and without specific hardware requirements with the spectrometer. The robust method relies on determining and applying a CCF with linear regression models. For our benchtop NMR system, we determined a CCF using this method and a single analyte when observing either 1H or 19F nuclei. For demonstration purposes, the robustness of the determined CCF method was displayed with a multi-analyte test. The same benchtop NMR system, analyte conditions (static in flow cell), and data treatment (both data measurement and processing) was used. Importantly, the same CCF for 1H NMR was determined despite a different analyst (Dr. José G. Napolitano), a larger concentration range, analytes in different solvent from initial CCF determination, and the analysis was performed nearly a year later. The utility of the external calibration qNMR method was highlighted with application to a highly relevant synthetic transformation in the pharmaceutical industry: CDI promoted acid activation and subsequent amide coupling. An on-line stopped-flow benchtop NMR system (with Magritek spectrometer) was used and the qNMR method allowed for accurate and easily obtained information regarding the potency of the activating reagent, information highly relevant yet sometimes elusive to a process chemist. Upon adding a carboxylic acid, the activation process was successfully monitored quantitatively via 19F benchtop NMR, despite the chemistry taking place six carbons away from the 19F nuclei observed in the NMR experiments. The work further shows how the NMR data can be used to inform decisions in real-time (i.e., add more activating reagent). Once full activation to the acyl imidazole was achieved a fluorinated aniline species was dosed into the reaction to form the desired amide product. Not only could the apparent rate constant of amide formation be determined based on the quantitative data, but resonances consistent with both the cis- and trans-amide conformers could be observed at 57 MHz. The work included in this chapter, therefore, highlights both the advantage of this qNMR technique and also the usefulness 275 of benchtop NMR for quantitatively monitoring highly relevant chemical transformations for the pharmaceutical industry. The work included in Chapter 5 of this thesis compares the use of monitoring chemical reactions via benchtop NMR with both on-line stopped- and continuous-flow systems, with a commercially available benchtop NMR instrument and hardware for the flow system. The ultimate goal of this work was to increase both the accessibility and practicality of using benchtop NMR as a reaction monitoring tool, even for non-NMR experts. All reactions were additionally monitored by performing the reaction in a 5 mm NMR tube and all reactions were monitored via 19F{1H} benchtop NMR using a Magritek spectrometer. The first reaction monitored and compared between the analysis techniques involved the homogeneous imination reaction between fluorinated aldehyde and aniline species. While stopped-flow and continuous-flow analyses resulted in agreement in trends (likely due to reasonable T1 values for tracked resonances), the sensitivity was less for data measured under continuous-flow conditions, compared to stopped-flow conditions with the same data acquisition, due to in-flow effects of an actively moving NMR sample during analysis. With the sensitivity decrease inherent to benchtop NMR systems, this may of consideration for an analyst when determining which technique may be more beneficial. The second reaction monitored in this chapter was the activation of a carboxylic acid with PBSF to form the corresponding acyl fluoride. This biphasic heterogeneous reaction highlighted a system where differences in reaction trends may be observable between stopped-flow and continuous-flow techniques: when a resonance has a long T1 value. While the use of correction factors have been previously leveraged to compensate for in-flow effects, in this instance this would not have been appropriate as the reaction system was dynamic. This may be as the T1 may 276 have changed over the reaction course and/or the physical conditions likely evolved, such as a change in solvent viscosity changing the actual flow rate of solution. Therefore, this study further supports that the use of an on-line stopped-flow system may allow for more robust and easily accessible reaction monitoring analyses with a benchtop NMR. 6.2 Future work With the increased attention paid to benchtop NMR spectrometers for a variety of applications, and especially reaction monitoring, it will be very exciting to see the future work that applies these benchtop systems and inadvertently builds on the work reported in this thesis. Considering the work highlighted in Chapter 2, where the use of an on-line continuous-flow benchtop NMR flow system was explored, it would be interesting to further explore differing flow cell geometries compatible with the applied spectrometer to reduce the vortices and eddying behaviour observed in flow rates that may be more attractive for reaction monitoring. Additionally, it would be interesting to prepare a device that is compatible with a commercially available benchtop NMR spectrometer that allows for pre-magnetization of spins prior to entering the NMR spectrometer, in effort to reduce the observed in-flow effects of flow. In terms of the work presented with an on-line stopped-flow benchtop NMR system (Chapter 3, Chapter 4, and Chapter 5), it would be insightful to monitor a wide range of chemical transformations with larger chemical structures to better understand the limitations associated with detection of chemical species with the inherent signal dispersion limitation of benchtop NMR. For 19F NMR, for instance, it would seem valuable to empirically understand how close the observed NMR active nucleus must be to the chemistry occurring to be able to unambiguously observe the change in measured signal over time. As the chemistry reported in this dissertation all involved small molecules as reactants and products, this understanding would allow for a deeper level of 277 understanding of what the practical limitations are, considering chemical structures that might be even more relevant and representative in pharmaceutical applications. For instances where the signal dispersion is not significant enough to allow for complete spectral resolution of resonances in the frequency domain, it would be of high interest to apply CRAFT (Complete Reduction to Amplitude Frequency Table).63,64 CRAFT analyzes NMR data in the time domain, rather than the conventional frequency domain, and leverages the concept that frequency domain attributes (chemical shift, integration, line width, and phase) can be orthogonally determined in the time domain (frequency, amplitude, decay rate, and phase). This is highly beneficial to qNMR applications as resonances that are spectrally overlapped in the frequency domain are generally fully resolved and accessible for quantitation in the time domain. Therefore, this may be a data processing and analysis tool that can increase the utility of benchtop NMR and to increase the robustness of acquired quantitative data. Furthermore, subjective processing parameters (such as phase or baseline corrections), which arguably introduce the most common sources of qNMR error, become irrelevant. In the case of leveraging either an on-line continuous- or stopped-flow benchtop NMR system, one of the largest limitations of benchtop NMR is the incapability of variable temperature control of the sample within the magnet. While this is a high priority of vendors to address, some progress has been made, such as a benchtop NMR system developed by Oxford Instruments that allows temperature control from 0 °C to 65 °C.258 As systems more readily become capable of temperature control outside of temperature of the internal magnet, it will be interesting to devise a flow system that allows for thermal control and allows for acquired data to be that much more representative of the native reaction flask. 278 Additionally, the work reported in this thesis does not involve reaction solutions involving solids. It would be interesting and valuable to conceive a reaction monitoring platform that is capable of reliable sampling the solution phase of a solid-liquid heterogenous mixture and allow for analysis via benchtop NMR. This would increase the scope of reactions to which a benchtop NMR flow system could be applicable to. Lastly, while not specifically “benchtop” NMR as described here, the further development and application of NMR spectrometers that use high temperature superconducting magnets will be interesting for reaction monitoring analyses.259–261 6.3 Concluding remarks All chapters of this thesis considered, this body of work serves to promote the usage of benchtop NMR spectrometers for reaction monitoring analyses. It is desired that the work reported herein allows for insight into how a system may be devised with a benchtop NMR promote analysis of a desired process in the most robust and representative manner. Additionally, it is my hope that the work included in this thesis highlights the insightful information that can be achieved with the application of a benchtop NMR spectrometer, especially with the observation of 19F nuclei. A great deal of chemical information can be obtained with the systems currently available and it will be exciting to observe the continued development with such systems over the next decade. 279 References 1. N. C. Thomas. The Early History of Spectroscopy. J. Chem. Educ. 1991, 68, 631–364. 2. P. Crews, J. Rodríguez, M. Jaspars. Organic Structure Analysis (2nd ed.), Oxford University Press 2010. 3. L. D. Field, H. L. Li, A. M Magill. Organic Structures from Spectra (6th ed.), Wiley & Sons 2020. 4. J. Keeler, Understanding NMR Spectroscopy (2nd ed.), Wiley & Sons 2010. 5. R. Bowling Barnes, R. C. Gore, R. W. Stafford, V. Z. Williams. Qualitative Organic Analysis and Infrared Spectrometry. Anal. Chem. 1948, 20, 402–410. 6. J. A. Anderson, Jr, W. D. Seyfried. Determination of Oxygenated and Olefin Compound Types by Infrared Spectroscopy. Anal. Chem. 1948, 20, 998–1006. 7. S. H. Hastings, A. T. Watson, R. B. Williams, J. A. Anderson, Jr. Determination of Hydrocarbon Functional Groups by Infrared Spectroscopy. Anal. Chem. 1952, 24, 612–618. 8. W. Jiang, A. Saxena, B. Song, B. B. Ward, T. J. Beveridge, S. C. B. Myneni. Elucidation of Functional Groups on Gram-Positive and Gram-Negative Bacterial Surfaces Using Infrared Spectroscopy. Langmuir 2004, 20, 11433–11442. 9. R. Norman Jones. The Ultraviolet Absorption Spectra of Anthracene Derivatives. Chem Rev. 1947, 41, 353-371. 10. L. N. Ferguson. Relationship between Absorption Spectra and Spectra and Chemical Constitution of Organic Molecules. Chem. Rev. 1948, 43, 385–446. 11. J. R. Platt. Isoconjugate Spectra and Variconjugate Sequences. J. Chem. Phys. 1951, 19, 101–118. 12. B. Tan, D. N. Soderstrom. Qualitative Aspects of UV-Vis Spectrophotometry of 𝛽-Carotene and Lycopene. J. Chem. Educ. 1989, 66, 258–260. 13. R. M. Silverstein, F. Webster, D. J. Kiemle, D. L. Bryce. Spectroscopic Identification of Organic Compounds (8th Ed.), Wiley & Sons 2014. 14. W. F. Reynolds, R. G. Enríquez, L. I. Escobar, X. Lozoya. Total assignment of 1H and 13C spectra of kauradien-9(11),16-oic acid with the aid of heteronuclear correlated 2D spectra optimized for geminal and vicinal 13C–1H coupling constants: or what to do when "INADEQUATE" is impossible. Can. J. Chem. 1984, 62, 2421–2425. 15. E. E. Kwan, S. G. Huang. Structure Elucidation with NMR Spectroscopy: Practical Strategies for Organic Chemists. Eur. J. Org. Chem. 2008, 2671–2688. 16. R. C. Breton, W. F. Reynolds. Using NMR to identify and characterize natural products. Nat. Prod. Rep. 2013, 30, 501–524. 17. M. Elyashberg. Identification and structure elucidation by NMR spectroscopy. TrAC - Trends Anal. Chem. 2015, 69, 88–97. 280 18. G. C. Bassler, R. M. Silverstein. Spectrometry in Organic Analysis. Application to Small Samples. J. Food Sci. 1963, 50, 446–452. 19. C. W. Jefford, R. McCreadie, P. Muller, J. Pfyffer. Spectroscopy and structure elucidation. Coordinated experimental exercises in advanced organic chemistry. J. Chem. Educ. 1973, 50, 181–185. 20. G. Topcu, A. Ulubelen. Structure elucidation of organic compounds from natural sources using 1D and 2D NMR techniques. J. Mol. Struct. 2007, 834–836, 57–73. 21. I. I. Rabi, J. R. Zacharias, S. Millman, P. Kusch. A New Method of Measuring Nuclear Magnetic Moment. Phys. Rev. 1938, 53, 318. 22. E. M. Purcell, H. C. Torrey, R. V. Pound. Resonance Absorption by Nuclear Magnetic Moments in a Solid. Phys. Rev. 1946, 69, 37–38. 23. F. Bloch, W. W. Hansen, M. Packard. Nuclear Induction. Phys. Rev. 1946, 69, 127. 24. G. A. Morris. Varian Associates and the birth of commercial NMR spectroscopy. J. Magn. Reson. 2019, 306, 12–16. 25. D. L. Rabenstein. NMR Spectroscopy: Past and Present. Anal. Chem. 2001, 73, 214 A–223 A. 26. C. Boesch. Nobel Prizes for Nuclear Magnetic Resonance: 2003 and Historical Perspectives. J. Magn. Reson. Imaging 2003, 20, 177–179. 27. M. Zloh. NMR spectroscopy in drug discovery and development: Evaluation of physico-chemical properties. ADMET and DMPK 2019, 7, 242–251. 28. A. M. Gronenborn. Small, but powerful and attractive: 19F in biomolecular NMR. Structure 2022, 30, 6–14. 29. I. P. Gerothanassis, C. G. Tsanaktsidis. Nuclear Electric Quadrupole Relaxation. Concepts Magn. Reson. 1996, 8, 63–74. 30. L. Ronconi, P. J. Sadler. Applications of heteronuclear NMR spectroscopy in biological and medicinal inorganic chemistry. Coord. Chem. Rev. 2008, 252, 2239–2277. 31. H.-L. Deng, X.-S. Luo, Z. Lin, J. Niu, M.-H. Huang. 14N NMR as a General Tool to Characterize the Nitrogen-Containing Species and Monitor the Nitration Process. J. Org. Chem. 2021, 86, 16699–16706. 32. J. S. Wood, G. Dal Poggetto, X. Wang, M. Reibarkh, R. T. Williamson, R. D. Cohen. Quantitative nuclear magnetic resonance of chloride by ana ccurate internal standard approach. Magn. Reson. Chem. 2023, 61, 22–31. 33. S. J. Chan, A. G. Howe, J. M. Hook, J. B. Harper. 79Br NMR spectroscopy as a practical tool for kinetic analysis. Magn. Reson. Chem. 2009, 47, 342–347. 34. T. D. W. Claridge. High-Resolution NMR Techniques in Organic Chemistry (3rd ed.), Elsevier 2016. 35. J. A. Koutcher, C. T. Burnt. Principles of Nuclear Magnetic Resonance J. Nucl. Med. 1984, 25, 101–111. 281 36. R. R. Ernst, G. Bodenhausen, A. Wokaun. Principles of Nuclear Magnetic Resonance in One and Two Dimensions (2nd ed.), Oxford 1987. 37. W. G. Proctor, F. C. Yu. The Dependence of a Nuclear Magnetic Resonance Frequency upon Chemical Compound. Phys. Rev. 1950, 77, 717. 38. W. C. Dickinson. Dependence of the F19 Nuclear Resonance Position on Chemical Compound. Phys. Rev. 1950, 77, 736–737. 39. J. T. Arnold, S. S. Dharmatti, M. E. Packard. Chemical Effects on Nuclear Induction Signals from Organic Compounds. J. Chem. Phys. 1951, 19, 507. 40. R. R. Ernst, W. A. Anderson. Application of Fourier Transform Spectroscopy to Magnetic Resonance. Rev. Sci. Instrum. 1966, 37, 93–102. 41. I. P. Gerothanassis, A. Troganis, V. Exarchou, K. Barbarossou. Nuclear Magnetic Resonance (NMR) Spectroscopy: Basic Principles and Phenomena, and their Applications to Chemistry, Biology and Medicine. Chem. Educ. Res. Pract. 2002, 3, 229–252. 42. A. G. Redfield. Nuclear Magnetic Resonance Saturation and Rotatory Saturation in Solids. Phys. Rev. 1955, 98, 1787–1809. 43. A. E. Derome. Modern NMR Techniques for Chemistry Research, Pergamon Press 1987. 44. S. Braun, H.-O. Kalinowski, S. Berger. 150 and More Basic NMR Experiments: A Practical Course, Wiley 1998. 45. S. Berger, S. Braun. 200 and More Basic NMR Experiments: A Practical Course, Wiley 2004. 46. M. Findeisen, S. Berger. 50 and More Essential NMR Experiments: A Detailed Guide, Wiley 2013. 47. A. Ariza-Castolo. Beyond Excitation NMR Relaxation. Concepts Magn. Reson. Part A. 2008, 32A, 168–182. 48. R. M. Gregory, A. D. Bain. The Effects of Finite Rectangular Pulses in NMR: Phase and Intensity Distortions for a Spin-1/2. Concepts Magn. Reson. Part A. 2009, 34A, 305–364. 49. J. C. Cobas, M. A. Bernstein, M. Martín-Pastor, P. G. Tahoces. A new general-purpose fully automatic baseline-correction procedure for 1D and 2D NMR data. J. Magn. Reson. 2006, 183, 145–151. 50. D. D. Traficante, M. Rajabzadeh. Optimum Window Function for Sensitivity Enhancement of NMR Signals. Concepts Magn. Reson. Part A. 2000, 12, 83–101. 51. P. A. Keifer. 90° Pulse Width Calibrations. Concepts Magn. Reson. Part A. 1999, 11, 165–180. 52. P. Fellgett. Les principes généraux des méthodes nouvelles en spectroscopie interférentielle - A propos de la théorie du spectromètre interférentiel multiplex. J. Phys. Radium 1958, 19, 187–191. 53. M. L. Gyngell. The Steady-State Signals in Short-Repetition-Time Sequences. J. Magn. Reson. 1989, 81, 474–483. 282 54. D. E. Jones, H. Sternlicht. Fourier Transform Nuclear Magnetic Resonance I. Repetitive Pulses. J. Magn. Reson. 1972, 6, 167–182. 55. I. J. Lowe, R. E. Norberg. Free-Induction Decays in Solids. Phys. Rev. 1957, 107, 46–61. 56. J. W. Cooley, J. W. Tukey. An Algorithm for the Machine Calculation of Complex Fourier Series. Math. Comp. 1965, 332, 297–301. 57. R. K. Harris, E. D. Becker, S. M. Cabral de Menezes, R. Goodfellow, P. Granger. NMR NOMENCLATURE. NUCLEAR SPIN PROPERTIES AND CONVENTIONS FOR CHEMICAL SHIFTS (IUPAC Recommendations 2001). Pure Appl. Chem. 2001, 73, 1795–1818. 58. G. V. D. Tiers. Reliable Proton Nuclear Resonance Shielding Values by “Internal Referencing” with Tetramethyl-silane. J. Phys. Chem. 1958, 62, 1151–1152. 59. D. S. Wishart, C. G. Bigam, J. Yao, F. Abildgaarg, H. J. Dyson, E. Oldfield, J. L. Markley, B. D. Sykes. 1H, 13C and 15N chemical shift referencing in biomolecular NMR. J. Biomol. NMR 1995, 6, 135–140. 60. S. L. Carr, C. Long, W. G. Moulton. Nuclear Magnetic Resonance of 31P in the Antiferromagnetic State of Metallic Uranium Monophosphide. Phys. Rev. Lett. 1969, 23, 786–788. 61. B. N. Figgis. N.m.r. chemical shifts in solutions containing Tl205. Part 1. Trans. Faraday Soc. 1959, 55, 1075–1085. 62. T. H. Baum, C. E. Larson, G. May. Ligand-stabilized copper(I) hexafluoroacetylacetonate complexes: NMR spectroscopy and the nature of the copper-alkene bond. J. Organomet. Chem. 1992, 425, 189–200. 63. K. Krishnamurthy. Complete Reduction to Amplitude Frequency Table (CRAFT)–A perspective. Magn. Reson. Chem. 2021, 59, 757–791. 64. K. Krishnamurthy. CRAFT (complete reduction to amplitude frequency table)–robust and time-efficient Bayesian approach for quantitative mixture analysis by NMR. Magn. Reson. Chem. 2013, 51, 821–829. 65. L. Helm. Relaxivity in paramagnetic systems: Theory and mechanisms. Prog. Nucl. Magn. Reson. Spectrsoc. 2006, 49, 45–64. 66. O. A. Gansow, A. R. Burke. A Shiftless Relaxation Reagent for Carbon-13 Magnetic Resonance of Organometallic Carbonyl Compounds. J. Chem. Soc., Chem. Commun. 1972, 456–457. 67. G. C. Levy, U. Edlund, J. G. Hexem. A Comparison between Two “Intert” Paramagnetic Relaxation Agents. J. Magn. Reson. 1975, 19, 259–262. 68. D. D. Dischino, E. J. Delaney, J. E. Emswiler, G. T. Gaughan, J. S. Prasad, S. K. Srivastava, M. F. Tweedle. Synthesis of nonionic gadolinium chelates useful as contrast agents for magnetic resonance imaging: 1,4,7-tris(carboxymethyl)-10-substituted-1,4,7,10-tetraazacyclododecanes and their corresponding gadolinium chelates. Inorg. Chem. 1991, 30, 1265–1269. 283 69. U. Holzgrabe. Quantitative NMR spectroscopy in pharmaceutical applications. Prog. Nucl. Magn. Reson. Spectrsoc. 2010, 57, 229–240. 70. S. K. Bharti, R. Roy. Quantitative 1H NMR spectroscopy. TrAC - Trends Anal. Chem. 2012, 35, 5–26. 71. P. B. Kingsley. Methods of Measuring Spin-Lattice (T1) Relaxation Times: An Annotated Bibliography. Concepts Magn. Reson. Part A. 1999, 11, 243–276. 72. R. Wei, C. L. Dickson, D. Uhrín, G. C. Lloyd-Jones. Rapid Estimation of T1 for Quantitative NMR. J. Org. Chem. 2021, 86, 9023–9029. 73. R. L. Vold, J. S. Waugh, M. P. Klein, D. E. Phelps. Measurement of Spin Relaxation in Complex Systems. J. Chem. Phys. 1968, 48, 3831–3832. 74. R. Freeman, H. D. W. Hill, High-Resolution Studies of Nuclear Spin-Lattice Relaxation J. Chem. Phys. 1969, 51, 3140–3141. 75. A. Gupta, T. Stait-Gardner, W. S. Price. Is it Time to Forgo the Use of the Terms “Spin-Lattice” and “Spin-Spin” Relaxation in NMR and MRI. J. Phys. Chem. Lett. 2021, 12, 6305–6312. 76. H. Y. Carr, E. M. Purcell. Effects of Diffusion on Free Precession in Nuclear Magnetic Resonance Experiments. Phys. Rev. 1954, 94, 630–638. 77. S. Meiboom, D. Gill. Modified Spin Echo Method for Measuring Nuclear Relaxation Times. Rev. Sci. Instrum. 1958, 29, 688–691. 78. J. A. Aguilar, M. Nilsson, G. Bodenhausen, G. A. Morris. Spin echo NMR spectra without J modulation. Chem. Commun. 2012, 48, 811–813. 79. J. L. Jungnickel, J. W. Forbes. Quantitative Measurement of Hydrogen Types by Integrated Nuclear Magnetic Resonance Intensities. Anal. Chem. 1963, 35, 938–942. 80. D. P. Hollis. Quantitative Analysis of Aspirin, Phenacetin, and Caffeine Mixtures by Nuclear Magnetic Resonance Spectrometry. Anal. Chem. 1963, 35, 1682–1684. 81. G. Khirich. A Monte Carlo Method for Analyzing Systematic and Random Uncertainty in Quantitative Nuclear Magnetic Resonance Measurements. Anal. Chem. 2021, 93, 10039–10048. 82. R. K. Harris. N.m.r. and the periodic table. Chem. Soc. Rev. 1976, 5, 1–22. 83. G. F. Pauli, S.-N. Chen, C. Simmler, D. C. Lankin, T. Gödecke, B. U. Jaki, J. B. Friesen, J. B. McAlpine, J. G. Napolitano. Importance of Purity Evaluation and the Potential of Quantitative1H NMR as a Purity Assay. J. Med. Chem. 2014, 57, 9220–9231. 84. Almanac 2011: Analytical Tables and Product Overview, Bruker 2011. 85. N. F. Ramsey. Chemical Effects in Nuclear Magnetic Resonance and in Diamagnetic Susceptibility. Phys. Rev. 1952, 86, 243–246. 284 86. S. Mohanty. Paramagnetic contribution of magnetic shielding constant in some tetrahedral and octahedral molecules. J. Chem. Phys. 1973, 59, 4415–4417. 87. P. Meakin, J. P. Jesson. Computer Simulation of Multipulse and Fourier Transform NMR Experiments. I. Simulations Using the Bloch Equations. J. Magn. Reson. 1973, 10, 290–315. 88. D. D. Traficante, M. M. McGregor. Simple Laboratory Experiments to Observe the Manifestations of the Sinc Function. Concepts Magn. Reson. Part A. 2002, 14, 308–325. 89. W. G. Proctor, F. C. Yu. On the Nuclear Magnetic Moments of Several Stable Isotopes. Phys. Rev. 1951, 81, 20–30. 90. H. S. Gutowsky, D. W. McCall. Nuclear Magnetic Resonance Fine Structure in Liquids. Phys. Rev. 1951, 82, 748–749. 91. E. L. Hahn, D. E. Maxwell. Chemical Shift and Field Independent Frequency Modulation of the Spin Echo Envelope. Phys. Rev. 1951, 84, 1246–1247. 92. M. Karplus. Contact Electron-Spin Coupling of Nuclear Magnetic Moments. J. Chem. Phys. 1959, 30, 11–15. 93. M. Karplus. Vicinal Proton Coupling in Nuclear Magnetic Resonance. J. Am. Chem. Soc. 1963, 85, 2870–2871. 94. V. F. Bystrov. Spin-spin coupling and the conformational states of peptide systems. Prog. Nucl. Magn. Reson. Spectrosc. 1976, 10, 41–82. 95. H. S. Gutowsky, M. Karplus, D. M. Grant. Angular Dependence of Electron‐Coupled Proton Interactions in CH2 Groups. J. Chem. Phys. 1959, 31, 1278–1289. 96. C. A. G. Haasnoot, F. A. A. M. de Leeuw, C. Altona. The Relationship Between Proton-Proton NMR Coupling Constant and Substituent Electronegativities-I. An Empirical Generalization of the Karplus Equation. Tetrahedron, 1980, 36, 2783–2792. 97. M. Barfield, D. M. Grant. The Effect of Hyperconjugation on the Geminal Spin-Spin Coupling Constant. J. Am. Chem. Soc. 1963, 85, 1899–1904. 98. P. Crews, R. R. Kintner, H. C. Padgett. Localization or Delocalization of Nonbonded Electrons in Unsaturated Heterocycles. J. Org. Chem. 1973, 38, 4391–4395. 99. T. R. Hoye, P. R. Hanson, J. R. Vyvyan. A Practical Guide to First-Order Multiplet Analysis in NMR Spectroscopy. J. Org. Chem. 1994, 59, 4096–4103. 100. J. Homer, M. Sultan-Mohammadi. A simple, general method for predicting the relative intensities of first order, NMR spin-spin coupled multiplets. J. Chem. Educ. 1983, 60, 932. 101. R. J. Abraham, H. J. Bernstein. The Analysis of Nuclear Magnetic Resonance Spectra V. The Analysis of Deceptively Simple Spectra. Can. J. Chem. 1961, 39, 216–230. 285 102. T. Schafer. The Proton Resonance Spectrum of 2-Furanacrolein. Can. J. Chem. 1962, 40, 1678–1683. 103. G. Bodenhausen, D. J. Ruben. Natural abundance nitrogen-15 NMR by enhanced heteronuclear spectroscopy. Chem. Phys. Lett. 1980, 69, 185–189. 104. A. Bax, R. Freeman. Investigation of complex networks of spin-spin coupling by two-dimensional NMR. J. Magn. Reson. 1981, 44, 542–561. 105. A. Bax, M. F. Summers. 1H and 13C from Assignments Sensitivity-Enhanced Detection of Heteronuclear Multiple-Bond Connectivity by 2D Multiple Quantum NMR. J. Am. Chem. Soc. 1986, 108, 2094–2096. 106. K. Johnson, L. G. Barrientos, L. Le, P. P. N. Murthy. Application of Two-Dimensional Total Correlation Spectroscopy for Structure Determination of Individual Inositol Phosphates in a Mixture. Anal. Biochem. 1995, 231, 421–431. 107. E. G. Paul, D. M. Grant. Carbon-13 Magnetic Resonance. I. Improved Carbon-13 Magnetic Resonance Spectra Obtained by Proton Decoupling and Rapid Sample Spinning. J. Am. Chem. Soc. 1964, 86, 2977–2983. 108. D. M. Grant, E. G. Paul. Carbon-13 Magnetic Resonance. II. Chemical Shift Data for the Alkanes. J. Am. Chem. Soc. 1964, 86, 2984–2990. 109. K. F. Kuhlmann, D. M. Grant. The Nuclear Overhauser Enhancement of the Carbon-13 Magnetic Resonance Spectrum of Formic Acid. J. Am. Chem. Soc. 1968, 90, 7355–7357. 110. K. F. Kuhlmann, D. M. Grant, R. K. Harris. Nuclear Overhauser Effects and 13C Relaxation Times in 13C-{H} Double Resonance Spectra. J. Chem. Phys. 1970, 52, 3439–3448. 111. D. Doddrell, V. Glushko, A. Allerhand. Theory of Nuclear Overhauser Enhancement and 13C-1H Dipolar Relaxation in Proton‐Decoupled Carbon‐13 NMR Spectra of Macromolecules. J. Chem. Phys. 1972, 56, 3683–3689. 112. P. Wikus, W. Frantz, R. Kümmerle, P. Vonlanthen. Commercial gigahertz-class NMR magnets. Supercond. Sci. Technol. 2022, 35, 033001. 113. J. W. Emsley, J. Feeney. Forty years of Progress in Nuclear Magnetic Resonance Spectroscopy. Prog. Nucl. Magn. Reson. Spectrosc. 2007, 50, 179–198. 114. H. Schwalbe. New 1.2 GHz NMR Spectrometers-New Horizons? Angew. Chem. Int. Ed. 2017, 56, 10252–10253. 115. A. Krunić, J. Orjala. Application of high-field NMR spectroscopy for characterization and quantification of submilligram quantities of isolated natural products. Magn. Reson. Chem. 2015, 53, 1043–1050. 116. E. Luchinat, L. Barbieri, M. Cremonini, L. Banci. Protein in-cell NMR spectroscopy at 1.2 GHz. J. Biomol. NMR 2021, 75, 97–107. 117. V. Martins, J. Xu, I. Hung, Z. Gan, C. Gervais, C. Bonhomme, Y. Huang. 17O solid-state NMR at ultrahigh magnetic field 35.2 T: Resolution of inequivalent oxygen sites in different phases of MOF MIL-53(A1). Magn. Reson. Chem. 2021, 59, 940–950. 286 118. J. C. Edwards. The emergence of benchtop NMR systems and the exciting future of the technology. Magn. Reson. Chem. 2016, 54, 492–493. 119. T. A. van Beek. Low-field benchtop NMR spectroscopy: status and prospects in natural product analysis. Phytochem. Anal. 2021, 32, 24–37. 120. J. F. Araneda, T. M. Barbosa, P. Hui, M. C. Leclerc, J. Ma, A. F. G. Maier, S. D. Riegel. Incorporating Benchtop NMR Spectrometers in the Undergraduate Lab: Understanding Resolution and Circumventing Second-Order Effects. J. Chem. Educ. 2021, 98, 1227–1232. 121. R. W. Morrison, M. Zhang. Applications of benchtop NMR in the organic chemistry instructional laboratory. Magn. Reson. Chem. 2020, 58, 1187–1192. 122. I. J. Lawson, C. Ewart, A. Kraft, D. Ellis. Demystifying NMR spectroscopy: Applications of benchtop spectrometers in the undergraduate teaching laboratory. Magn. Reson. Chem. 2020, 58, 1256–1260. 123. J. Duffy, A. Urbas, M. Niemitz, K. Lippa, I. Marginean. Differentiation of fentanyl analogous by low-field NMR spectroscopy. Anal. Chim. Acta 2019, 1049, 161–169. 124. P. H. J. Keizers, F. Bakker, J. Ferreira, P. F. K. Wackers, D. van Kollenburg, E. van der Aa, A. van Beers. Benchtop NMR spectroscopy in the analysis of substandard and falsified medicines as well as illegal drugs. J. Phar. Biomed. Anal. 2020, 178, 112939. 125. W. G. Lee, M. T. Zell, T. Ouchi, M. J. Milton. NMR spectroscopy goes mobile: Using NMR as process analytical technology at the fume hood. Magn. Reson. Chem. 2020, 58, 1193–1202. 126. N. Nestle, Z. J. Lim, T. Böhringer, S. Abtmeyer, S. Arenz, F. C. Leinweber, T. Weiß, E. von Harbou. Taking compact NMR monitoring real reactions in large-scale chemical industries-General considerations and learings from a lab-scale test case. Magn. Reson. Chem. 2020, 58, 1213–1221. 127. J. G. Napolitano, C. Yang, B. Conklin, Y. He, J. L. Ochoa. Toward the Development of Rapid, Automated Identification Tests for Neat Organic Liquids Using Benchtop NMR Instrumentation. Anal. Chem. 2022, 94, 16095–16102. 128. J. Wiss, C. Fleury, U. Onken. Safety Improvement of Chemical Processes Involving Azides by Online Monitoring of the Hydrazoic Acid Concentration. Org. Process Res. Dev. 2006, 10, 349–353. 129. K. Holger, G. Hessel, W. Schmitt. Improvement of Process Safety and Efficiency of Grignard Reactions by Real-Time Monitoring. Org. Process Res. Dev. 2007, 11, 1135–1140. 130. Z. Li, C. Cheng, X. Ming, Y. Cong, Q. Li, Z. Wei, X. Ma. A Study on the Reaction Mechanisms and Process Safety of Pyrisoxazole Synthesis. Org. Process Res. Dev. 2021, 25, 2482–2489. 131. A. Jordan, R. M. Denton, H. F. Sneddon. Development of a More Sustainable Appel Reaction. ACS Sustainable Chem. Eng.2020, 8, 2300–2309. 132. D. Hebrault, A. J. Rein, B. Wittkamp. Chemical Knowledge via In Situ Analytics: Advancing Quality and Sustainability. ACS Sustainable Chem. Eng. 2022, 10, 5072–5077. 287 133. H.-R. Bjørsvik. Online Spectroscopy and Multivariate Data Analysis as a Combined Tool for Process Monitoring and Reaction Optimization. Org. Proc. Res. Dev. 2004, 8, 495–503. 134. S. A. Eisenbeis, R. Chen, M. Kang, M. Barrila, R. Buzon. Utilization of ReactIR in Fit for Purpose Process Enhancement. Org. Proc. Res. Dev. 2015, 19, 244–248. 135. E. Frauendorfer, W.-D. Hergeth. Industrial application of Raman spectroscopy for control and optimization of vinyl acetate resin polymerization. Anal. Bioanal. Chem. 2017, 409, 631–636. 136. J. Liu, Y. Sato, F. Yang, A. J. Kukor, J. E. Hein. An adaptive auto-synthesizer using online PAT feedback to flexibility perform a multistep reaction. Chem. Methods 2022, 2, e202200009. 137. M. C. Deem, J. S. Derasp, T. C. Malig, K. Legard, C. P. Berlinguette, J. E. Hein. Ring walking as a regioselectivity control element in Pd-catalyzed C-N cross-coupling. Nat. Commun. 2022, 13, 2869. 138. R. Chung, J. E. Hein. The More, The Better: Simultaneous In Situ Reaction Monitoring Provides Rapid Mechanistic and Kinetic Insight. Top. Catal. 2017, 60, 594–608. 139. K. Zhang, K. L. Kurita, C. Venkatramani, D. Russell. Seeking universal detectors for analytical characterizations. J. Pharm. Biomed. Anal. 2019, 162, 192–204. 140. Y. Ben-Tal, P. J. Boaler, H. J. A. Dale, R. E. Dooley, N. A. Fohn, Y. Gao, A. García-Domínguez, K. M. Grant, A. M. R. Hall, H. L. D. Hayes, M. M. Kucharski, R. Wei, G. C. Lloyd-Jones. Mechanistic analysis by NMR spectroscopy: A users guide. Prog. Nucl. Magn. Reson. Spectrosc. 2022, 129, 28–106. 141. K. Parker, D. K. Das Gupta. Application of nuclear-magnetic resonance to semicontinuous reaction monitoring. Proc. Inst. Electr. Eng. 1969, 116, 1060–1064. 142. M. A. Bernstein, M. Štefinović, C. J. Sleigh. Optimizing reaction performance in the pharmaceutical industry by monitoring with NMR. Magn. Reson. Chem. 2007, 45, 564–571. 143. D. A. Foley, A. L. Dunn, M. T. Zell. Reaction monitoring using online vs tube NMR spectroscopy: seriously different results. Magn. Reson. Chem. 2016, 54, 451–456. 144. Y. Yokoyama, M. Nakakoshi, H. Okuno, Y. Sakamoto, S. Sakuri. Mechanism for the direct synthesis of tryptophan from indole and serine: a useful NMR technique for the detection of a reactive intermediate in the reaction mixture. Magn. Reson. Chem. 2010, 48, 811–817. 145. F. Susanne, D. S. Smith, A. Codina. Kinetic Understanding Using NMR Reaction Profiling. Org. Process Res. Dev. 2012, 16, 61–64. 146. X. Wang, J. Vu, C. Luk, E. Njoo. Benchtop 19F nuclear magnetic resonance spectroscopy enabled kinetic studies and optimization of the synthesis of carmofur. Can. J. Chem. 2023, 101, 518–524. 147. T. Bartik, B. Bartik, B. E. Hanson, T. Glass, W. Bebout. Comments on the synthesis of trisulfonated triphenylphosphine: reaction monitoring by NMR spectroscopy. Inorg. Chem. 1992, 31, 2667–2670. 148. J. L. Sudmeier, J. J. Pesek. Fast Kinetics by Stopped-Flow Chlorine-35 Nuclear Magnetic Resonance. Reactions of Mercury(II)-Bovine Serum Albumin with Various Ligands. Inorganic Chemistry 1971, 10, 860–863. 288 149. J. Grimaldi, J. Baldo, C. McMurray, B. D. Sykes. Stopped-Flow Nuclear Magnetic Resonance Spectroscopy. J. Am. Chem. Soc. 1972, 94, 7641–7645. 150. A. L. Dunn, C. R. Landis. Progress toward reaction monitoring at variable temperatures: a new stopped-flow NMR probe design. Magn. Reson. Chem. 2017, 55, 329–336. 151. S. Funahashi, K. Ishihara, S. I. Aizawa, T. Sugata, M. Ishii, Y. Inada, M. Tanaka. High-pressure stopped-flow nuclear magnetic resonance apparatus for the study of fast reactions in solution. Rev. Sci. Instrum. 1993, 64, 130–134. 152. R. Wei, A. M. R. Hall, R. Behrens, M. S. Pritchard, E. J. King, G. C. Llyod-Jones. Stopped-Flow 19F NMR Spectroscopic Analysis of a Protodeboronation Proceeding at the Sub-Second Time-Scale. Eur. J. Org. Chem. 2021, 2331–2342. 153. A. García-Domínguez, T. H. West, J. J. Primozic, K. M. Grant, C. P. Johnston, G. C. Cumming, A. G. Leach, G. C. Lloyd-Jones. Difluorocarbene Generation from TMSCF3: Kinetics and Mechanism of NaI-Mediated and Si-Induced Anionic Chain Reactions. J. Am. Chem. Soc. 2020, 142, 14649–14663. 154. C. L. Perrin, I. A. Rivero. Apparatus for direct addition of reagents into a nuclear magnetic resonance (NMR) sample in the NMR probe. Rev. Sci. Instrum. 1999, 70, 2173–2174. 155. A. C. Jones, A. W. Sanders, M. J. Bevan, H. J. Reich. Reactivity of Individual Organolithium Aggregates: A RINMR Study of n-Butyllithium and 2-Methoxy-6(methoxymethyl)phenyllithium. J. Am. Chem. Soc. 2007, 129, 3492–3493. 156. G. Suryan. Nuclear resonance in flowing liquids. Proc. Indian Acad. Sci. (Math. Sci.) 1951, 33, 107–111. 157. C. A. Fyfe, M. Cocivera, S. W. H. Damji. High Resolution Nuclear Magnetic Resonance Study of Chemical Reactions Using Flowing Liquids: Kinetic and Thermodynamic Intermediates Formed by the Attack of Methoxide Ion on 3,5-Dinitrocyanobenzene. J. Chem. Soc.,Chem. Comm. 1973, 19, 743–744. 158. C. A. Fyfe, M. Cocivera, S. W. H. Danji, T. A. Hostetter, D. Sproat, J. O’Brien. Apparatus for the Measurement of Transient Species and Effects in Flowing Systems by High-Resolution Nuclear Magnetic Resonance Spectroscopy. J. Magn. Reson. 1976, 23, 377–384. 159. M. Cocivera, C. A. Fyfe, A. Effio, S. P. Vaish, H. E. Chen. Flow Nuclear Magnetic Resonance Study of the Dehydration of the Tetrahedral Intermediate Resulting from the Addition of Hydroxylamine to Acetaldehyde. J. Am. Chem. Soc. 1976, 98, 1573–1578. 160. C. A. Fyfe, L. Van Veen, Jr. Flow nuclear magnetic resonance investigation of the intermediates formed during the bromination of phenols in acetic acid. J. Am. Chem. Soc. 1977, 99, 3366–3371. 161. C. A. Fyfe, M. Cocivera, S. W. H. Damji. Flow and stopped-flow nuclear magnetic resonance investigations in chemical reactions. Acc. Chem. Res. 1978, 11, 277–282. 162. E. Bayer, K. Albert, M. Nieder, E. Grom, T. Keller. On-line coupling of high-performance liquid chromatography and nuclear magnetic resonance. J. Chromatogr. A 1979, 186, 497–507. 163. K. Albert. Liquid chromatography-nuclear magnetic resonance spectroscopy. J. Chromatogr. A 1999, 856, 199–211. 289 164. P. A. Keifer. Flow techniques in NMR spectroscopy. Annu. Rep. NMR Spectrosc. 2007, 62, 1–47. 165. M. Khajeh, M. A. Bernstein, G. A. Morris. A simple flowcell for reaction monitoring by NMR. Magn. Reson. Chem. 2010, 48, 516–522. 166. D. A. Foley, E. Bez, A. Codina, K. L. Colson, M. Fey, R. Krull, D. Piroli, M. T. Zell, B. L. Marquez. NMR Flow Tube for Online NMR Reaction Monitoring. Anal. Chem. 2014, 86, 12008–12013. 167. Bruker InsightMR, https://www.bruker.com/fr/products-and-solutions/mr/nmr-pharma-solutions/InsightMR.html (date accessed: December 13, 2023). 168. Magritek Reaction Monitoring, https://magritek.com/products/benchtop-nmr-spectrometer-spinsolve/addons/reaction-monitoring/ (date accessed: December 13, 2023). 169. Nanalysis Sci. Corp. NMReady-flow, https://www.nanalysis.com/nmready-flow (date accessed: December 13, 2023). 170. A. Saib, A. Bara-Estaún, O. J. Harper, D. B. G. Berry, I. A. Thomlinson, R. Broomfield-Tagg, J. P. Lowe, C. L. Lyall, U. Hintermair. Engineering aspects of FlowNMR spectroscopy setups for online analysis of solution-phase processes. React. Chem. Eng. 2021, 6, 1548–1573. 171. D. A. Foley, C. W. Doecke, J. Y. Buser, J. M. Merritt, L. Murphy, M. Kissane, S. G. Collins, A. R. Maguire, A. Kaerner. ReactNMR and ReactIR as Reaction Monitoring and Mechanistic Elucidation Tools: The NCS Mediated Cascade Reaction of 𝛼-Thioamides to 𝛼-Thio-𝛽-chloroacrylamides. J. Org. Chem. 2011, 76, 9630–9640. 172. A. L. Dunn, A. Codina, D. A. Foley, B. L. Marquez, M. T. Zell. A detailed mechanistic investigation into the reaction of 3-methylpentanoic acid with Meldrum’s acid utilizing online NMR spectroscopy. Magn. Reson. Chem. 2016, 54, 477–484. 173. J. Y. Buser, A. D. McFarland. Reaction characterization by flow NMR: quantitation and monitoring of dissolved H2 via flow NRM at high pressure. Chem. Commun. 2014, 50, 4234–4237. 174. A. Nordon, A. Diez-Lazaro, C. W. L. Wong, C. A. McGill, C. A. McGill, D. Littlejohn, M. Weerasinge, D. A. Mamman, M. L. Hitchman, J. Wilkie. Consideration of some sampling problems in the on-line analysis of batch processes by low-field NMR spectrometry. Analyst 2008, 133, 339–347. 175. A. Nordon, C. A. McGill, D. Littlejohn. Process NMR spectrometry. Analyst 2001, 126, 260–272. 176. M. Maiwald, H. H. Fischer, Y.-K. Kim, H. Hasse. Quantitative on-line high-resolution NMR spectroscopy in process engineering applications. Anal. Bioanal. Chem. 2003, 375, 1111–1115. 177. M. Maiwald, H. H. Fischer, Y.-K. Kim, H. Hasse. Quantitative high-resolution on-line NMR spectroscopy in reaction and process monitoring. J. Magn. Reson. 2004, 166, 135–146. 178. F. Dalitz, M. Cudaj, M. Maiwald, G. Guthausen. Process and reaction monitoring by low-field NMR spectroscopy. Prog. Nucl. Magn. Reson. Spectrosc. 2012, 60, 52–70. 290 179. F. Dalitz, M. Maiwald, G. Guthausen. Considerations on the design of flow cells in by-pass systems for process analytical applications and its influence on the flow profile using NMR and CFD. Chem. Eng. Sci. 2012, 75, 318–326. 180. A. M. R. Hall, J. C. Chouler, A. Codina, P. T. Gierth, J. P. Lowe, U. Hintermair. Practical aspects of real-time reaction monitoring using multi-nuclear high resolution FlowNMR spectroscopy. Catal. Sci. Technol. 2016, 6, 8406–8417. 181. K. Meyer, S. Kern, N. Zientek, G. Guthausen, M. Maiwald. Process control with compact NMR. TrAC - Trends Anal. Chem. 2016, 83, 39–52. 182. A. Bara-Estaún, M. C. Harder, C. L. Lyall, J. P. Lowe, E. Suturina, U. Hintermair. Paramagnetic Relaxation Agents for Enhancing Temporal Resolution and Sensitivity in Multinuclear FlowNMR Spectroscopy. Chem. Eur. J. 2023, 29, e202300215. 183. N. Zientek, C. Laurain, K. Meyer, M. Kraume, G. Guthausen, M. Maiwald. Simultaneous 19F-1H medium resolution NMR spectroscopy for online reaction monitoring. J. Magn. Reson. 2014, 249, 53–62. 184. D. A. Laude, Jr, R. W.-K. Lee, C. L. Wilkins. Analytical Applications of a Recycled Flow Nuclear Magnetic Resonance System: Signal Enhancement of Slowly Relaxing Nuclei. Anal. Chem. 1985, 57, 1281–1286. 185. D. A. Laude, Jr, C. L. Wilkins. Applications of a Recycled-Flow Fourier Transform Nuclear Magnetic Resonance System: Molecular Weight Determination of Siloxane Polymers by 29Si NMR. Macromolecules 1986, 19, 2295–2300. 186. J. F. Haw, T. E. Glass, H. C. Dorn. Conditions for Quantitative Flow FT-1H NMR Measurements under Repetitive Pulse Conditions. J. Magn. Reson. 1982, 49, 22–31. 187. R. Neudert, E. Ströfer, W. Bremser. On-line NMR in Process Engineering. Magn. Reson. Chem. 1986, 24, 1089–1092. 188. T. F. Molinski. NMR of natural products at the ‘nanomole-scale’. Nat. Prod. Rep. 2010, 27, 321–329. 189. R. C. Breton, W. F. Reynolds. Using NMR to identify and characterize natural products. Nat. Prod. Rep. 2013, 30, 501–524. 190. T. R. Hoye, B. M. Eklov, T. D. Ryba, M. Voloshin, L. J. Yao. No-D NMR (No-Deuterium Proton NMR) Spectroscopy: A Simple Yet Powerful Method for Analyzing Reaction and Reagent Solutions. Org. Lett. 2004, 6, 953–956. 191. Installation Planning Guide (Pub. No. 01-999262-00, Rev. A0305), Varian, Inc. NMR Systems. 192. M. T. Drexler, D. A. Foley, H. W. Ward, II, H. J. Clarke. IR and NMR Reaction Monitoring Techniques for Nucleophilic Addition Reactions: In Situ Monitoring of the Addition of Benzimidazole to a Pyridinium Salt. Org. Process Res. Dev. 2015, 19, 1119–1127. 193. M. Goldbach, E. Danieli, J. Perlo, B. Kaptein, V. M. Litvinov, B. Blümich, F. Casanova, A. L. L. Duchateau. Preparation of Grignard reagents from magnesium metal under continuous flow conditions and on-line monitoring by NMR spectroscopy. Tetrahedron Lett. 2016, 57, 122–125. 291 194. A. M. Torres, W. S. Price. Common problems and artifacts encountered in solution-state NMR experiments. Concepts Magn. Reson. Part A 2017, 45A, e21387. 195. E. Danieli, J. Perlo, A. L. L. Duchateau, G. K. M. Verzijl, V. M. Litvinov, B. Blümich, F. Casanova. On-Line Monitoring of Chemical Reactions by using Bench-Top Nuclear Magnetic Resonance Spectroscopy. ChemPhysChem 2014, 15, 3060–3066. 196. V. Sans, L. Porwol, V. Dragone, L. Cronin. A self optimizing synthetic organic reactor system using real-time in-line NMR spectroscopy. Chem. Sci. 2015, 6, 1258–1264. 197. C. M. Archambault, N. E. Leadbeater. A Benchtop NMR Spectrometer as a Tool for Monitoring Mesoscale Continuous-Flow Organic Synthesis: Equipment Interface and Assessment in Four Organic Transformations. RSC Adv. 2016, 6, 101171–101177. 198. M. V. Silva Elipe, R. R. Milburn. Monitoring chemical reactions by low-field benchtop NMR at 45 MHz: pros and cons. Magn. Reson. Chem. 2016, 54, 437–443. 199. B. Gouilleux, B. Charrier, S. Akoka, P. Giraudeau. Gradient-based solvent suppression methods on a benchtop spectrometer. Magn. Reson. Chem. 2017, 55, 91–98. 200. R. W. Mitchell, M. Eisner. Concentration Dependence of NMR Spin-Lattice Relaxation Times in Solutions. J. Chem. Phys. 1961, 34, 651–654. 201. K. Hatada, T. Kitayama, Y. Terawaki, Y. Tanaka, H. Sata. Structural Dependence of Carbon-13 NMR Spin-Lattice Relaxation Times of 1,4-Polyisoprenes. Polym. Bull. 1980, 2, 791–797. 202. F. Malz, H. Jancke. Validation of quantitative NMR. J. Pharm. Biomed. Anal. 2005, 38, 813–823. 203. C. Sterling, R. Crouch, D. J. Russell, A. I. Calderón. 1H-NMR Quantification of Major Saccharides in Açaí Raw Materials: a Comparison of the Internal Standard Methodology with the Absolute Intensity qNMR Method. Phytochem. Anal. 2013, 24, 631–637. 204. A. O. Mattes, D. Russell, E. Tishchenko, Y. Liu, R. H. Cichewicz, S. J. Robinson. Application of 19F NMR to pharmaceutical analysis. Concepts Magn. Reson. Part A 2016, 45A, e21422. 205. M. Bornemann-Pfeiffer, K. Meyer, J. Lademann, M. Kraume, M. Maiwald. Contributions towards variable temperature shielding for compact NMR instruments. Magn. Reson. Chem. 2023, in-press. 206. M. Edgar, B. C. Percival, M. Gibson, J. Masania, K. Beresford, P. B. Wilson, M. Grootveld. Benchtop NMR Spectroscopy and Spectral Analysis of the cis- and trans-Stilbene Products of the Witting Reaction. J. Chem. Educ. 2019, 96, 1938–1947. 207. N. Gilbert, R. E. Mewis, O. B. Sutcliffe. Fast & fluorinated – Development and validation of a rapid benchtop NMR approach and other routine screening methods for the detection and quantification of synthesized fluorofentanyl derivatives. Forensic Chem. 2021, 23, 100321. 208. D. Fallaise, H. Balkwill Tweedie, J. Konzuk, C. Cheyne, E. E. Mack, J. G. Longstaffe. Practical application of 1H benchtop NMR spectroscopy for the characterization of a nonaqueous phase liquid from a contaminated environment Magn. Reson. Chem. 2019, 57, 93–100. 292 209. K. Heerah, S. Waclawek, J. Konzuk, J. G. Longstaffe. Benchtop 19F NMR spectroscopy as a practical tool for testing of remedial technologies for the degradation of perfluorooctanoic acid, a persistent organic pollutant. Magn. Reson. Chem. 2020, 58, 1160–1167. 210. T. H. Rehm, C. Hofmann, D. Reinhard, H.-J. Kost, P. Löb, M. Besold, K. Welzel, J. Barten, A. Didenko, D. V. Sevenard, B. Lix, A. R. Hilson, S. D. Riegel. Continuous-flow synthesis of fluorine-containing fine chemicals with integrated benchtop NMR analysis. React. Chem. Eng. 2017, 2, 315–323. 211. P. M. Richardson, A. J. Parrott, O. Semenova, A. Nordon, S. B. Duckett, M. E. Halse. SABRE hyperpolarization enables high-sensitivity 1H and 13C benchtop NMR spectroscopy. Analyst 2018, 143, 3442–3450. 212. H. Chae, S. Min, H. J. Jeong, S. K. Namgoong, S. Oh, K. Kim, K. Jeong. Organic Reaction Monitoring of a Glycine Derivative Using Signal Amplification by Reversible Exchange-Hyperpolarized Benchtop Nuclear Magnetic Resonance Spectroscopy, Anal. Chem. 2020, 92, 10902–10907. 213. Nanalysis Scientific Corp. Products Overview, https://www.nanalysis.com/products-overview (date accessed: December 13, 2023). 214. Magritek Spinsolve Multi X, https://magritek.com/products/benchtop-nmr-spectrometer-spinsolve/addons/multinuclear-options/ (date accessed: December 13, 2023). 215. Oxford Instruments X-Pulse, https://nmr.oxinst.com/x-pulse (date accessed: December 13, 2023). 216. P. Giraudeau. Challenges and perspectives in quantitative NMR. Magn. Reson. Chem. 2017, 55, 61–69. 217. L. Griffiths, A. M. Irving. Assay by nuclear magnetic resonance spectroscopy: quantification limits. Analyst 1998, 123, 1061–1068. 218. S. Akoka, L. Barantin, M. Trierweiler. Concentration Measurement by Proton NMR Using the ERETIC Methods. Anal. Chem. 1999, 71, 2554–2557. 219. K. Mehr, B. John, D. Russell, D. Avizonis. Electronic Referencing Techniques for Quantitative NMR: Pitfalls and How To Avoid Them Using Amplitude-Corrected Referencing through Signal Injection. Anal. Chem. 2008, 80, 8320–8323. 220. R. D. Farrant, J. C. Hollerton, S. M. Lynn, S. Provera, P. J. Sidebottom, R. J. Upton. NMR quantification using an artificial signal. Magn. Reson. Chem. 2010, 48, 753–562. 221. C. H. Cullen, G. J. Ray, C. M. Szabo. A comparison of quantitative nuclear magnetic resonance methods: internal, external, and electronic referencing. Magn. Reson. Chem. 2013, 51, 705–713. 222. Y. Zhou, J. Wang, Z. Gu, S. Wang, W. Zhu, J. Luis Aceña, V. A. Soloshonok, K. Izawa, H. Liu. Next Generation of Fluorine-Containing Pharmaceuticals, Compounds Currently in Phase II–III Clinical Trials of Major Pharmaceutical Companies: New Structural Trends and Therapeutic Areas. Chem. Rev. 2016, 116, 422–518. 223. H. Mo, J. S. Harwood, D. Raftery. Receiver gain function: the actual NMR receiver gain. Magn. Reson.Chem. 2010, 48, 235–238. 224. M. A. Bernstein, S. Sýkora, C. Peng, A. Barba, C. Cobas. Optimization and Automation of Quantitative NMR Data Extraction. Anal. Chem. 2013, 85, 5778–5786. 293 225. Y. Lee, Y. Matviychuk, D. J. Holland. Quantitative analysis using external standards with a benchtop NMR spectrometer. J. Magn. Reson. 2020, 320, 106826. 226. M. R. Derrick, H. D. Burgess, M. T. Baker, N. E. Binnie. Sulfuryl Fluoride (Vikane): A Review of its Use as a Fumigant. J. Am. Inst. Conserv. 1990, 29, 77–90. 227. R. Lekkala, R. Lekkala, B. Moku, K. P. Rakesh, H.-L. Qin. Applications of sulfuryl fluoride (SO2F2) in chemical transformations. Org. Chem. Front. 2019, 6, 3490–3516. 228. M. Epifanov, J. Y. Mo, R. Dubois, H. Yu, G. M. Sammis. One-Pot Deoxygenation and Substitution of Alcohols Mediated by Sulfuryl Fluoride. J. Org. Chem. 2021, 86, 3768–3777. 229. C. Lee, J. Lai, M. Epifanov, C. X. Wang, G. M. Sammis. Efficient protocol for the SO2F2-mediated deoxyfluorination of aliphatic alcohols. J. Fluorine Chem. 2021, 251, 109888. 230. S.-M. Wang, C. Zhao, X. Zhang, H.-L. Qin. Clickable coupling of carboxylic acids and amines at room temperature mediated by SO2F2: a significant breakthrough for the construction of amides and peptide linkages. Org. Biomol. Chem. 2019, 17, 4087–4101. 231. S.-M. Wang, N. S. Alharbi, H.-L. Qin. Construction of Esters through Sulfuryl Fluoride (SO2F2) Mediated Dehydrative Coupling of Carboxylic Acids with Alcohols at Room Temperature. Synthesis 2019, 51, 3901–3907. 232. J. Dong, K. B. Sharpless, L. Kwisnek, J. S. Oakdale, V. V. Fokin. SuFEx-Based Synthesis of Polysulfates. Angew. Chem. Int. Ed. 2014, 53, 9466–9470. 233. B. Gao, L. Zhang, Q. Zheng, F. Zhou, L. M. Klivansky, J. Lu, Y. Liu, J. Dong, P. Wu, K. B. Sharpless. Bifluoride-catalysed sulfur(VI) fluoride exchange reaction for the synthesis of polysulfates and polysulfonates. Nat. Chem. 2017, 9, 1083–1088. 234. E. R. Falardeau, D. D. DesMarteau. Synthesis of Pentafluorophenoxy Derivatives of Sulfur(IV) and -(VI) Fluorides. J. Chem. Eng. Data 1976, 21, 386–387. 235. C. Veryser, J. Demaerel, V. Bieliu̅nas, P. Gilles, W. M. De Borggraeve. Ex Situ Generation of Sulfuryl Fluoride for the Synthesis of Aryl Fluorosulfates. Org. Lett. 2017, 19, 5244–5247. 236. G. H. Cady, S. Misra. Hydrolysis of Sulfuryl Fluoride. Inorg. Chem. 1974, 13, 837–841. 237. A. Dhillon, M. Nair, D. Kumar. Analytical methods for determination and sensing of fluoride in biotic and abiotic sources: a review. Anal. Methods 2016, 8, 5338–5352. 238. P. J. Foth, T. C. Malig, H. Yu, T. G. Bolduc, J. E. Hein, G. M. Sammis. Halide-Accelerated Acyl Fluoride Formation Using Sulfuryl Fluoride. Org. Lett. 2020, 22, 6682–6686. 239. T. Shioiri, K. Ninomiya, S. Yamada. Diphenylphosphoryl azide. New convenient reagent for a modified Curtius reaction and for peptide synthesis. J. Am. Chem. Soc. 1972, 94, 6203–6205. 240. K. Ninomiya, T. Shioiri, S. Yamada. Phosphorus in organic synthesis-VII: Diphenyl phosphorazidate (DPPA). A new convenient reagent for a modified curtius reaction. Tetrahedron 1974, 30, 2151–5157. 294 241. Y. Hirooka, K. Ikeuchi, Y. Kawamoto, Y. Akao, T. Furuta, T. Asakawa, M. Inai, T. Wakimoto, T. Fukuyama, T. Kan. Enantioselective Synthesis of SB-203207. Org. Lett. 2014, 16, 1646–1649. 242. Y. E. Türkmen, M. Gravel, V. H. Rawal. Studies Directed toward the Synthesis of Aspidophytine: Construction of its Perhydroquinoline Core. J. Org. Chem. 2016, 81, 10454–10462. 243. S. A. Nuñez, K. Yeung, N. S. Fox, S. T. Phillips. A Structurally Simple Self-Immolative Reagent That Provides Three Distinct, Simultaneous Responses per Detection Event. J. Org. Chem. 2011, 76, 10099–10113. 244. B. Lal, B. N. Pramanik, M. S. Manhas, A. K. Bose. Diphenylphosphoryl azide a novel reagent for the stereospecific synthesis of azides from alcohols. Tetrahedron Lett. 1977, 18, 1977–1980. 245. J. A. Birrell, J.-N. Desrosiers, E. N. Jacobsen. Enantioselective Acylation of Silyl Ketene Acetals through Fluoride Anion-Binding Catalysis. J. Am. Chem. Soc. 2011, 133, 13872–13875. 246. Y. Liang, Z. Zhao, N. Shibata. Pd-catalyzed fluoro-carbonylation of aryl, vinyl, and heteroaryl iodides using 2-(difluoromethoxy)-5-nitropyridine. Commun. Chem. 2020, 3, 59. 247. P. Giraudeau, F.-X. Felpin. Flow reactors integrated with in-line monitoring using benchtop NMR spectroscopy. React. Chem. Eng. 2018, 3, 399–413. 248. M. T. Sabatini, L. T. Boulton, H. F. Sneddon, T. D. Sheppard. A green chemistry perspective on catalytic amide bond formation. Nat. Catal. 2019, 2, 10–17. 249. R. Paul, G. W. Anderson. N,N’-Carbonyldiimizole, a New Peptide Forming Reagent. J. Am. Chem. Soc. 1960, 82, 4596–4600. 250. C. A. G. N. Montalbetti, V. Falque. Amide bond formation and peptide coupling. Tetrahedron 2005, 61, 10827–10852. 251. O. K. Baryshnikova, T. C. Williams, B. D. Sykes. Internal pH indicators for biomolecular NMR. J. Biomol. NMR 2008, 41, 5–7. 252. P. Panini, R. G. Gonnade, D. Chopra. Experimental and computational analysis of supramolecular motifs involving Csp2(aromatic)–F and CF3 groups in organic solids. New J. Chem. 2016, 40, 4981–5001. 253. S. D. Riegel, G. M. Leskowitz. Benchtop NMR spectrometers in academic teaching. TrAC - Trends Anal. Chem. 2016, 83, 27–38. 254. L. Tadiello, H.-J. Drexler, T. Beweries. Low-Field Flow 31P NMR Spectroscopy for Organometallic Chemistry: On-Line Analysis of Highly Air-Sensitive Rhodium Diphosphine Complexes. Organometallics 2022, 20, 2833–2843. 255. F. Dalitz, L. Kreckel, M. Maiwald, G. Guthausen. Quantitative Medium-Resolution NMR Spectroscopy Under Non-Equilibrium Conditions, Studied on the Example of an Esterification Reaction. Appl. Magn. Reson. 2014, 45, 411–425. 256. S. K. Bharti, N. Sinha, B. S. Joshi, S. K. Mandal, R. Roy, C. L. Khetrapal. Improved quantification from 1H-NMR spectra using reduced repetition times. Metabolomics 2008, 4, 367–376. 295 257. B. Bennua-Skalmowski, H. Vorbrüggen. A facile conversion of primary or secondary alcohols with n-perfluorobutane-sulfonyl fluoride/1,8-diazabicyclo[5.4.0]undec-7-ene into their corresponding fluorides. Tetrahedron Lett. 1995, 36, 2611–2614. 258. Oxford Instruments X-Pulse, https://nmr.oxinst.com/x-pulse-variable-temperature (date accessed: December 13, 2023). 259. M. V. Silva Elipe, N. Donovan, R. Krull, D. Pooke, K. L. Colson. Performance of new 400-MHz HTS power-driven magnet NMR technology on typical pharmaceutical API, cinacalcet HCl. Magn. Reson. Chem. 2018, 56, 817–825. 260. M. V. Silva Elipe, A. Cherney, R. Krull, N. Donovan, J. Tedrow, D. Pooke, K. L. Colson. Application of the New 400 MHz High-Temperature Superconducting (HTS) Power-Driven Magnet NMR Technology for Online Reaction Monitoring: Proof of Concept with a Ring-Closing Metathesis (RCM) Reaction. Org. Process Res. Dev. 2020, 24, 1428–1434. 261. Y. Sato, J. Liu, I. D. Ndukwe, M. V. S. Elipe, D. J. Griffin, J. I. Murray, J. E. Hein. Liquid/liquid heterogeneous reaction monitoring: Insights into biphasic Suzuki-Miyaura cross-coupling. Chem Catal. 2023, 3, 100687. 296 Appendices Appendix A High-field NMR data for Chapter 3 A.1 4-fluorobenzoyl fluoride (3.11) Figure A.1. 1D 1H NMR spectrum (300 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). 3.7OHOFSO2F2DIPEAMeCN3.11FOF3.1internal standard:CF3012345678910f1 (1H / ppm)2.032.008.058.157.357.50≈ 297 Figure A.2. 1D 13C{1H} NMR spectrum (75 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). 3.7OHOFSO2F2DIPEAMeCN3.11FOF3.1internal standard:CF3050100150200f1 (13C / ppm)110130150170 298 Figure A.3. 1D 19F NMR spectrum (282 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). -200-1000100f1 (19F / ppm)0.731.00-103.1-102.63.7OHOFSO2F2DIPEAMeCN3.11FOF3.1internal standard:CF3 299 Figure A.4. 2D 1H-1H COSY NMR spectrum (300 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). 12345678f2 (1H / ppm)12345678f1 (1H / ppm)3.7OHOFSO2F2DIPEAMeCN3.11FOF3.1internal standard:CF3 300 Figure A.5. 2D 1H-13C HSQC NMR spectrum (300/75 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). 12345678f2 (1H / ppm)0102030405060708090100110120130140150f1 (13 C / ppm)3.7OHOFSO2F2DIPEAMeCN3.11FOF3.1internal standard:CF3 301 Figure A.6. Expansion of the 2D 1H-13C HSQC NMR spectrum (300/75 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). 7.47.67.88.08.28.48.6f2 (1H / ppm)100105110115120125130135140145f1 (13 C / ppm)3.7OHOFSO2F2DIPEAMeCN3.11FOF3.1internal standard:CF3 302 Figure A.7. 2D 1H-13C HMBC NMR spectrum (300/75 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). 12345678f2 (1H / ppm)050100150200f1 (13 C / ppm)3.7OHOFSO2F2DIPEAMeCN3.11FOF3.1internal standard:CF3 303 Figure A.8. Expansion of 2D 1H-13C HMBC NMR spectrum (300/75 MHz, DMSO-d6) of DMSO soluble reaction components, including 4-fluorobenzoyl fluoride (3.11). 7.47.67.88.08.28.48.6f2 (1H / ppm)105110115120125130135140145150155160165170175f1 (13 C / ppm)3.7OHOFSO2F2DIPEAMeCN3.11FOF3.1internal standard:CF3 304 A.2 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17) Figure A.9. 1D 1H NMR spectrum (400 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). 012345678910f1 (1H / ppm)1.002.310.812.017.07.17.27.37.45.85.93.17HNFOOCF3CF3 305 Figure A.10. 1D 13C{1H} NMR spectrum (101 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). 3.17HNFOOCF3CF3050100150200f1 (13C / ppm)67.3367.6768.0268.3668.71116.25116.48119.71121.60121.68122.51125.31132.78150.29159.02161.44 306 Figure A.11. Expansion of 1D 13C{1H} NMR spectrum (101 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). 110120130140150160f1 (13C / ppm)116.25116.48119.71121.60121.68122.51125.31132.78150.29159.02161.443.17HNFOOCF3CF3≈ 307 Figure A.12. 1D 19F NMR spectrum (282 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). -250-200-150-100-50050100f1 (19F / ppm)0.746.00-74.0-73.7-118.4-118.03.17HNFOOCF3CF3 308 Figure A.13. 2D 1H-1H COSY NMR spectrum (400 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). 0123456789f2 (1H / ppm)0123456789f1 (1H / ppm)3.17HNFOOCF3CF3 309 Figure A.14. 2D 1H-13C HSQC NMR spectrum (400/101 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). -10123456789f2 (1H / ppm)020406080100120140160f1 (13 C / ppm)3.17HNFOOCF3CF3 310 Figure A.15. Expansion of 2D 1H-13C HSQC NMR spectrum (400/101 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). 6789f2 (1H / ppm)405060708090100110120130f1 (13 C / ppm)3.17HNFOOCF3CF3 311 Figure A.16. 2D 1H-13C HMBC NMR spectrum (400/101 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). 012345678f2 (1H / ppm)-101030507090110130150170190f1 (13 C / ppm)3.17HNFOOCF3CF3 312 Figure A.17. Expansion of 2D 1H-13C HMBC NMR spectrum (400/101 MHz, CD2Cl2) of 1,1,1,3,3,3-hexafluoropropan-2-yl (4-fluorophenyl) carbamate (3.17). 5.56.06.57.07.58.0f2 (1H / ppm)60708090100110120130140150160170180f1 (13 C / ppm)3.17HNFOOCF3CF3 313 A.3 Reaction end point: all reagents for modified Curtius rearrangement added directly after one another to heated solution Figure A.18. 1D 1H NMR spectrum (300 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. 024681012f1 (1H / ppm)6.57.07.58.08.5TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 314 Figure A.19. 1D 13C{1H} NMR spectrum (101 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. 050100150200f1 (13C / ppm)TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 315 Figure A.20. 1D 19F NMR spectrum (282 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. -250-200-150-100-50050f1 (19F / ppm)-76.0-75.0-74.0-73.0-120-115-110-105TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 316 Figure A.21. 1D 19F{1H} NMR spectrum (282 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. -250-200-150-100-50050f1 (19F / ppm)-75.0-74.5-74.0-73.5-119.45-119.30-102.00TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 317 Figure A.22. 1D 31P{1H} NMR spectrum (162 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. -200-150-100-50050100f1 (31P / ppm)-12.5-11.5TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 318 Figure A.23. 2D 1H-13C HMBC NMR spectrum (400/101 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. Please excuse excessive t1 noise, necessary to zoom to this level to observe some key correlations (i.e., correlations consistent with ester byproduct). 0246810f2 (1H / ppm)020406080100120140160180f1 (13 C / ppm)TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 319 Figure A.24. Expansion of 2D 1H-13C HMBC NMR spectrum (300/282 MHz, CD2Cl2) of reaction mixture to form 3.17, with all reagents added directly after one another to heated solution. 56789f2 (1H / ppm)-140-130-120-110-100-90-80-70-60f1 (19 F / ppm)TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 320 A.4 Reaction end point: full conversion to isocyanate 3.15 prior to alcohol 3.16 addition Figure A.25. 1D 1H NMR spectrum (300 MHz, CDCl3) of reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. 024681012f1 (1H / ppm)6.57.07.58.08.5TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 321 Figure A.26. 1D 1H NMR spectrum (300 MHz, CDCl3) of dried reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. 024681012f1 (1H / ppm)TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 322 Figure A.27. 1D 13C{1H} NMR spectrum (75 MHz, CDCl3) of dried reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. 050100150200f1 (13C / ppm)TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 323 Figure A.28. 1D 19F NMR spectrum (282 MHz, CDCl3) of reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. -250-200-150-100-50050f1 (19F / ppm)-77-75-73-140-120-100TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 324 Figure A.29. 1D 19F{1H} NMR spectrum (282 MHz, CDCl3) of reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. -250-200-150-100-50050f1 (19F / ppm)-75.5-74.5-73.5-72.5-126-120-114TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 325 Figure A.30. 1D 31P NMR spectrum (121 MHz, CDCl3) of reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. -40-30-20-10010f1 (31P / ppm)TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 326 Figure A.31. 2D 1H-13C HMBC NMR spectrum (300/75 MHz, CDCl3) of dried reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. 0246810f2 (1H / ppm)020406080100120140160180200f1 (13 C / ppm)TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 327 Figure A.32. 2D 1H-19F HMBC NMR spectrum (300/282 MHz, CDCl3) of dried reaction mixture to form carbamate 3.17, with complete isocyanate 3.15 formation prior to addition of alcohol 3.16. 56789f2 (1H / ppm)-140-130-120-110-100-90-80-70-60f1 (19 F / ppm)TEADPPA3.16TolueneΔ3.7OHOF3.17HNFOOCF3CF3 328 Appendix B High-field NMR data for Chapter 4 B.1 N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) Figure B.1. 1D 1H NMR spectrum (500 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole (grey arrows). 024681012f1 (1H / ppm)imidazoleHN N4.11ONHFF3C 329 Figure B.2. Expansion of the 1D 1H NMR spectrum (500 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole (grey arrows). 6.87.07.27.47.67.88.08.2f1 (1H / ppm)2.002.001.982.10imidazoleHN N4.11ONHFF3C 330 Figure B.3. 1D 13C{1H} NMR spectrum (126 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole (grey arrows). 4.11ONHFF3C050100150200f1 (13C / ppm)115.21115.39122.31122.38122.85125.02125.37125.40125.43128.59131.29131.54135.19135.21138.61138.62157.54159.46164.32imidazoleHN N 331 Figure B.4. Expansion of 1D 13C{1H} NMR spectrum (126 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole (grey arrows). 120130140150160f1 (13C / ppm)115.21115.39122.31122.38122.85125.02125.37125.40125.43128.59131.29131.54135.19135.21138.61138.62157.54159.46164.32imidazoleHN N4.11ONHFF3C 332 Figure B.5. 1D 19F NMR spectrum (471 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11). -150-100-500f1 (19F / ppm)0.983.00-61.40-61.30f1 (19F / ppm)-118.50-118.35f1 (19F / ppm)4.11ONHFF3C 333 Figure B.6. 2D 1H-13C HSQC NMR spectrum (500/126 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with some residual imidazole (grey boxes). 024681012f2 (1H / ppm)-100102030405060708090100110120130140f1 (13 C / ppm)imidazoleHN N4.11ONHFF3C 334 Figure B.7. Expansion of 2D 1H-13C HSQC NMR spectrum (500/126 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with some residual imidazole (grey boxes). 7.07.27.47.67.88.08.2f2 (1H / ppm)110112114116118120122124126128130132134136138f1 (13 C / ppm)imidazoleHN N4.11ONHFF3C 335 Figure B.8. 2D 1H-13C HMBC NMR spectrum (500/126 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole (grey boxes). 0246810f2 (1H / ppm)020406080100120140160180200220f1 (13 C / ppm)imidazoleHN N4.11ONHFF3C 336 Figure B.9. Expansion of 2D 1H-13C HMBC NMR spectrum (500/126 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole (grey boxes). 7.07.58.08.59.09.510.010.5f2 (1H / ppm)115120125130135140145150155160165170f1 (13 C / ppm)imidazoleHN N4.11ONHFF3C 337 Figure B.10. 2D 1H-1H COSY NMR spectrum (500 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole. 0246810f2 (1H / ppm)-101234567891011f1 (1H / ppm)4.11ONHFF3C 338 Figure B.11. Expansion of 2D 1H-1H COSY NMR spectrum (500 MHz, DMSO-d6) of N-(4-fluorophenyl)-4-(trifluoromethyl)benzamide (4.11) with residual imidazole. 6.87.07.27.47.67.88.08.28.4f2 (1H / ppm)6.46.66.87.07.27.47.67.88.08.28.4f1 (1H / ppm)4.11ONHFF3C 339 Appendix C High-field NMR data for Chapter 5 C.1 N,1-bis(4-fluorophenyl)methanimine (5.3) Figure C.1. 1D 1H NMR spectrum (400 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). -10123456789101112f1 (1H / ppm)1.002.014.002.00FNF5.3 340 Figure C.2. Expansion of 1D 1H NMR spectrum (400 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). 6.66.87.07.27.47.67.88.08.28.48.68.8f1 (1H / ppm)1.002.014.002.00FNF5.3 341 Figure C.3. 1D 13C{1H} NMR spectrum (101 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). 020406080100120140160180200f1 (13C / ppm)116.10116.16116.32116.37122.69122.77131.11131.20133.08133.11148.34148.37158.95160.45162.88163.88166.38FNF5.3 342 Figure C.4. 1D 19F NMR spectrum (282 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). -200-150-100-500f1 (19F / ppm)1.000.98-109.2-108.61.000.98-118.4-117.81.000.98FNF5.3 343 Figure C.5. 2D 1H-13C HSQC NMR spectrum (400/101 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). 0246810f2 (1H / ppm)020406080100120140160f1 (13 C / ppm)FNF5.3 344 Figure C.6. Expansion of 2D 1H-13C HSQC NMR spectrum (400/101 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). 7.07.58.08.5f2 (1H / ppm)105110115120125130135140145150155160165f1 (13 C / ppm)FNF5.3 345 Figure C.7. 2D 1H-13C HMBC NMR spectrum (400/101 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). 0246810f2 (1H / ppm)020406080100120140160180f1 (13 C / ppm)FNF5.3 346 Figure C.8. Expansion of 2D 1H-13C HMBC NMR spectrum (400/101 MHz, CD2Cl2) of N,1-bis(4-fluorophenyl)methanimine (5.3). 7.07.58.08.59.09.5f2 (1H / ppm)115120125130135140145150155160165170175f1 (13 C / ppm)FNF5.3 347 C.2 4-fluorobenzoyl fluoride (5.10) Figure C.9. 1D 1H NMR spectrum (600 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). -101234567891011121314f1 (1H / ppm)1.00 1.176.87.27.68.01.00 1.17FMeCNFOHOF SO OFFFFFFFFFFODIPEA5.4 5.10 348 Figure C.10. D 13C{1H} NMR spectrum (151 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). 020406080100120140160180200f1 (13C / ppm)117.11117.26121.58121.61122.00122.02134.96134.99135.03135.06155.98158.24166.86168.55FMeCNFOHOF SO OFFFFFFFFFFODIPEA5.4 5.10 349 Figure C.11. Expansion of 1D 13C{1H} NMR spectrum (151 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). 110120130140150160170f1 (13C / ppm)117.11117.26121.58121.61122.00122.02134.96134.99135.03135.06155.98158.24166.86168.55FMeCNFOHOF SO OFFFFFFFFFFODIPEA5.4 5.10 350 Figure C.12. 1D 19F NMR spectrum (377 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). -200-150-100-50050100150f1 (19F / ppm)1.000.8516.817.20.990.85-103.0-102.5-102.01.010.86FMeCNFOHOF SO OFFFFFFFFFFODIPEA5.4 5.10 351 Figure C.13. 2D 1H-1H COSY NMR spectrum (600 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). 012345678910f2 (1H / ppm)012345678910f1 (1H / ppm)FMeCNFOHOF SO OFFFFFFFFFFODIPEA5.4 5.10 352 Figure C.14. Expansion of 2D 1H-1H COSY NMR spectrum (600 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). 7.07.58.08.5f2 (1H / ppm)6.46.66.87.07.27.47.67.88.08.28.4f1 (1H / ppm)FMeCNFOHOF SO OFFFFFFFFFFODIPEA5.4 5.10 353 Figure C.15. 2D 1H-13C HSQC NMR spectrum (600/151 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). -1012345678910f2 (1H / ppm)020406080100120140160f1 (13 C / ppm)FMeCNFOHOF SO OFFFFFFFFFFODIPEA5.4 5.10 354 Figure C.16. Expansion of 2D 1H-13C HSQC NMR spectrum (600/151 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). 7.07.27.47.67.88.08.2f2 (1H / ppm)112114116118120122124126128130132134136138f1 (13 C / ppm)FMeCNFOHOF SO OFFFFFFFFFFODIPEA5.4 5.10 355 Figure C.17. 2D 1H-13C HMBC NMR spectrum (600/151 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). 0246810f2 (1H / ppm)020406080100120140160180f1 (13 C / ppm)FMeCNFOHOF SO OFFFFFFFFFFODIPEA5.4 5.10 356 Figure C.18. Expansion of 2D 1H-13C HMBC NMR spectrum (600/151 MHz, MeCN) of carboxylic acid 5.4 activation to acyl fluoride 5.10 reaction mixture using PBSF (5.6). 7.07.27.47.67.88.08.28.4f2 (1H / ppm)110115120125130135140145150155160165170f1 (13 C / ppm)FMeCNFOHOF SO OFFFFFFFFFFODIPEA5.4 5.10
Thesis/Dissertation
eng
Chemistry
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Hein, Jason
Advancing benchtop nuclear magnetic resonance (NMR) spectroscopy as a tool for pharmaceutical development
Text