Science, Faculty of
Chemistry, Department of
DSpace
UBCV
Sato, Yusuke
Doctor of Philosophy - PhD
University of British Columbia
Real-time sample analysis, including in situ analysis and automated sampling/injection, provides timely measurements of analytes and facilitates efficient reaction elucidations. In contrast to manual sampling, real-time sample analysis eliminates laborious sample preparations and increases efficiency and robustness in obtaining data-rich information. Unfortunately, many instrumental analytical tools used for real-time reaction monitoring are only applicable to homogeneous conditions, leaving heterogeneous conditions a major challenge. This thesis explores developments and applications of new heterogenous sampling platforms to investigate reaction details. Combing commercially available laboratory equipment with an in-line dynamic mixer, an online HPLC reaction monitoring system has been developed to investigate solid/liquid heterogeneous reactions. Using this platform, a slurry tetrabenazine (TBZ) synthesis has been investigated. The isolation and characterization of unseen enone and iminium intermediates proved that the reaction underwent the aza-Michael-Mannich annulation pathway. Our increased mechanistic understanding has allowed for the reaction rate to be boosted five-fold. For liquid/liquid heterogeneous reaction monitoring, a phase-selective sampling system was developed. This was achieved by developing a novel hydrophilic/oleophobic stainless steel filter. Partition coefficients of boronic acids with varying functional groups have been tested using this platform. Biphasic Suzuki-Miyaura coupling reaction was also explored. In addition to the heterogeneous conditions, nanocluster synthesis was also known to create challenging conditions to be monitored due to its complicated polydisperse cluster formations. This thesis lastly demonstrated that real-time LCMS monitoring revealed size growth of gold nanoclusters synthesis and potential intermediates.
DEVELOPMENT OF PROCESS ANALYTICAL TECHNOLOGIES AND APPLICATION FOR COMPLICATED REACTION CONDITIONS by Yusuke Sato B.Sc., The University of Shizuoka, 2017 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) January 2023 © Yusuke Sato, 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: Development of Process Analytical Technologies and Application for Complicated Reaction Conditions submitted by Yusuke Sato in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Chemistry Examining Committee: Jason E. Hein, Professor, Chemistry, UBC Supervisor Glenn Sammis, Professor, Chemistry, UBC Supervisory Committee Member Marco A. Ciufolini, Professor, Chemistry, UBC University Examiner Russ Algar, Professor, Chemistry, UBC University Examiner Additional Supervisory Committee Members: David Perrin, Professor, Chemistry, UBC Supervisory Committee Member Zachary M. Hudson, Professor, Chemistry, UBC Supervisory Committee Member iii Abstract Real-time sample analysis, including in situ analysis and automated sampling/injection, provides timely measurements of analytes and facilitates efficient reaction elucidations. In contrast to manual sampling, real-time sample analysis eliminates laborious sample preparations and increases efficiency and robustness in obtaining data-rich information. Unfortunately, many instrumental analytical tools used for real-time reaction monitoring are only applicable to homogeneous conditions, leaving heterogeneous conditions a major challenge. This thesis explores developments and applications of new heterogenous sampling platforms to investigate reaction details. Combing commercially available laboratory equipment with an in-line dynamic mixer, an online HPLC reaction monitoring system has been developed to investigate solid/liquid heterogeneous reactions. Using this platform, a slurry tetrabenazine (TBZ) synthesis has been investigated. The isolation and characterization of unseen enone and iminium intermediates proved that the reaction underwent the aza-Michael-Mannich annulation pathway. Our increased mechanistic understanding has allowed for the reaction rate to be boosted five-fold. For liquid/liquid heterogeneous reaction monitoring, a phase-selective sampling system was developed. This was achieved by developing a novel hydrophilic/oleophobic stainless steel filter. Partition coefficients of boronic acids with varying functional groups have been tested using this platform. Biphasic Suzuki-Miyaura coupling reaction was also explored. In addition to the heterogeneous conditions, nanocluster synthesis was also known to create challenging conditions to be monitored due to its complicated polydisperse cluster formations. This thesis lastly demonstrated that real-time LCMS monitoring revealed size growth of gold nanoclusters synthesis and potential intermediates. iv Lay Summary Modern monitoring technologies enabled an efficient, timely analysis to obtain kinetic profiles of chemical components in reactions. While most of the applications were demonstrated in ideal homogeneous conditions, more complicated conditions frequently seen in industrial reactions were insufficiently monitored. Therefore, I have developed solid/liquid and liquid/liquid heterogeneous sampling platforms and a new analytical methodology for nanocluster syntheses. These methodologies have enabled reaction monitoring of a variety of previously challenging conditions ranging from a slurry active pharmaceutical ingredient synthesis to state-of-the-art gold nanocluster preparation. Obtaining information is important to reveal reaction mechanisms, side reactions, and optimized reaction conditions. v Preface Chapter 1 serves as an introduction to the topics covered throughout this thesis. I wrote this chapter with feedback from my supervisor, Prof. Jason E. Hein. Chapter 2 is a published article titled “Real-Time Monitoring of Solid−Liquid Slurries: Optimized Synthesis of Tetrabenazine” (Sato, Y.; Liu, J.; Kukor, A. J.; Culhane, J. C.; Tucker, J. L.; Kucera, D. J.; Cochran, B. M.; Hein, J. E. J. Org. Chem. 2021, 86 (20), 14069–14078.). Collaborators at Neurocrine Biosciences provided us with the synthesis conditions and reaction compounds. Through biweekly meetings, they also provided meaningful feedback. Dr. Lars Yunker played an integral role in the development of the automated reaction monitoring platform, specifically in writing the Python script to sequence the sampling events. Prof. Jason E. Hein and I designed the experiments described herein. Based on the experimental plans, I conducted all experiments and isolated all compounds. I analyzed the data and wrote the manuscript with help from Mr. Junliang Liu and Mr. Andrew Kukor. Chapter 3 is unpublished. Collaborators at Amgen provided us with an opportunity to visit Amgen at Thousand Oaks, US, and allowed me to conduct experiments with cryogen-free 400 MHz NMR. Dr. Ikenna Ndukwe played an important role in setting up NMR parameters, and Dr. James Murray and I designed the flow NMR monitoring platform and experiments described herein. Prof. Jason. E. Hein and I designed the online HPLC monitoring platform and experiments described herein. Based on the experimental plans, I conducted all experiments and isolated all compounds. I analyzed the data and wrote the manuscript with help from Mr. Junliang Liu and Mr. Andrew Kukor. Chapter 4 is unpublished. Collaborators, Prof. Cathleen M. Crudden, Ms. Viveka K. Kulkarni, and Mr. Angus Sullivan, in the Crudden group at Queen’s University, provided us with vi the synthesis conditions and reaction compounds. Through biweekly meetings, they also provided meaningful feedback. Prof. Jason. E. Hein and I designed the experiments described herein. Based on the experimental plans, I conducted all experiments and isolated all compounds. I analyzed the data and wrote the manuscript with help from Mr. Junliang Liu, Mr. Andrew Kukor, Ms. Viveka K. Kulkarni, and Mr. Angus Sullivan. vii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ............................................................................................................................... iv Preface .............................................................................................................................................v Table of Contents ........................................................................................................................ vii List of Tables ................................................................................................................................xv List of Figures ............................................................................................................................. xvi List of Schemes ......................................................................................................................... xxiv List of Abbreviations .................................................................................................................xxv Acknowledgements .................................................................................................................. xxxi Dedication ............................................................................................................................... xxxiii Chapter 1: Introduction ................................................................................................................1 1.1 Importance of Analytical Chemistry ............................................................................... 1 1.1.1 History of Analytical Chemistry ............................................................................. 1 1.1.2 Qualitative Analysis ................................................................................................ 2 1.1.2.1 Optical Spectroscopies ........................................................................................ 3 1.1.2.1.1 Nuclear Magnetic Resonance (NMR) ........................................................... 4 1.1.2.1.2 Infrared (IR) Spectroscopy ........................................................................... 6 1.1.2.1.3 Ultraviolet-visible (UV-Vis) spectroscopy ................................................... 7 1.1.2.1.4 Mass Spectrometry........................................................................................ 8 1.1.2.2 Separation Methodologies ................................................................................ 10 1.1.2.2.1 High Performance Liquid Chromatography (HPLC) ................................. 10 1.1.3 Quantitative Analysis ............................................................................................ 11 viii 1.1.3.1 Calibration Curve .............................................................................................. 12 1.1.3.1.1 Conventional Preparation of Calibration Curve ......................................... 12 1.1.3.1.2 Standard Addition ....................................................................................... 13 1.1.3.2 Limitations and Considerations of Quantitative Analysis by Analytical Instrumentations ................................................................................................................ 14 1.1.3.2.1 Beer-Lambert Law Limitations in Spectroscopy ........................................ 14 1.1.3.2.2 Ion Suppression Effect in Mass Spectrometry ............................................ 14 1.1.3.2.3 Considerations for Quantitative NMR ........................................................ 15 1.1.4 Reaction Monitoring ............................................................................................. 16 1.1.4.1 Importance of Reaction Monitoring.................................................................. 16 1.1.4.2 Methods to Collect Reaction Monitoring Data: Manually, Automatically, and Instrumental Considerations ............................................................................................. 17 1.1.4.2.1 Manual Sampling vs. Automatic Sampling ................................................ 17 1.1.4.2.2 In Situ vs. Ex Situ Reaction Monitoring Techniques .................................. 19 1.1.4.3 Analytical Instruments for Reaction Monitoring .............................................. 20 1.1.4.3.1 In Situ IR and Raman .................................................................................. 20 1.1.4.3.2 Flow NMR .................................................................................................. 22 1.1.4.3.3 Online HPLC .............................................................................................. 23 1.1.4.3.4 In Situ Particle Analysis .............................................................................. 24 1.1.4.4 Limitations of Reaction Monitoring ................................................................. 25 1.1.4.4.1 Liquid/Liquid Heterogeneous Reaction Conditions ................................... 25 1.1.4.4.2 Solid/Liquid Heterogeneous Reaction Conditions...................................... 27 1.1.4.4.3 Resolution Limit for Complicated Reaction Monitoring ............................ 28 ix 1.2 Overview of Chapters ................................................................................................... 29 Chapter 2: Solid/Liquid Heterogeneous Reaction: In-Depth Reaction Profile of The Synthesis of Tetrabenazine..........................................................................................................31 2.1 Introduction ................................................................................................................... 31 2.2 Research Target ............................................................................................................ 33 2.3 Results and Discussion ................................................................................................. 37 2.3.1 Development of Online HPLC for Slurries .......................................................... 37 2.3.2 Standard Addition ................................................................................................. 40 2.3.3 Reaction Monitoring ............................................................................................. 41 2.3.4 Effect of pH on the Michael Addition .................................................................. 48 2.3.5 Secondary vs. Tertiary Amine .............................................................................. 52 2.3.6 Role of Sodium Iodide .......................................................................................... 57 2.4 Conclusion .................................................................................................................... 58 2.5 Experimental Section .................................................................................................... 60 2.6 General procedure for reaction monitoring................................................................... 61 2.7 Synthetic Procedures ..................................................................................................... 61 2.7.1.1 Tetrabenazine (TBZ) ((rac)-2.1). ...................................................................... 61 2.7.1.2 3-[(dimethylamino)methyl]-5-methylhexan-2-one (2.12). ............................... 62 2.7.1.3 trimethyl-[2-(2-methylpropyl)-3-oxobutyl]-azanium iodide. ........................... 63 2.7.2 5-methyl-3-methylidenehexan-2-one (2.14). ........................................................ 63 2.7.3 TBZ diastereomers (2.22). .................................................................................... 64 2.7.4 6,7-dimethoxy-2-[2-(2-methylpropyl)-3-oxobutyl]-3,4-dihydroisoquinolin-2-ium (2.23). .................................................................................................................... 65 x 2.8 Online HPLC Monitoring Equipment ........................................................................... 66 2.8.1 Dynamic Mixer (Akta M-925 mixing cartridge, 0.6 mL) ..................................... 66 2.8.2 Mettler-Toledo EasySampler Probe Function and Geometry (sampling device) . 67 2.8.3 EasyViewer ........................................................................................................... 67 2.8.4 pH Probe ............................................................................................................... 68 2.9 HPLC Methods ............................................................................................................. 69 2.10 The Role of Mixer Volume ........................................................................................... 71 2.11 TBZ Calibration Curve ................................................................................................. 72 2.12 Standard Addition as Internal Calibration Curve.......................................................... 73 Chapter 3: Liquid/Liquid Heterogeneous Reaction: Biphasic Suzuki Miyaura Cross Coupling ........................................................................................................................................75 3.1 Introduction ................................................................................................................... 75 3.2 Development of a Hydrophilic/Lipophobic SS Filter ................................................... 80 3.3 System Description ....................................................................................................... 82 3.4 Application to Partition Coefficient of Boronic Acids ................................................. 84 3.5 Reaction Monitoring of Liquid/Liquid Biphasic Suzuki Miyaura Cross Coupling ...... 94 3.6 Conclusion .................................................................................................................... 98 3.7 Experimental Section .................................................................................................... 99 3.7.1 NMR ..................................................................................................................... 99 3.7.2 HPLC .................................................................................................................. 100 3.7.3 Other Hardware ................................................................................................... 101 3.7.4 Surface Modification of Stainless Steel Filter .................................................... 102 3.7.5 Calibration Curve for NMR Reaction Monitoring.............................................. 102 xi 3.7.6 Volume Change Caused an Increase of BA Peak Area in Organic Layer .......... 102 3.8 General Reaction Monitoring Procedure .................................................................... 104 3.8.1 Flow NMR (Organic Layer Monitoring) ............................................................ 105 3.8.2 Flow NMR (Aqueous Layer Monitoring) ........................................................... 105 3.8.3 Online HPLC (Organic and Aqueous Layer Monitoring) .................................. 105 3.9 Detail of Online HPLC Platform ................................................................................ 106 3.9.1 HPLC Sample Valve ........................................................................................... 106 3.9.2 Organic and Aqueous Selective Sampling Mode of Online HPLC .................... 107 3.9.3 Detailed Steps of Online HPLC Sampling.......................................................... 107 3.10 Experimental Procedure .............................................................................................. 108 3.10.1 Partition Coefficient Test .................................................................................... 108 3.10.1.1 Online HPLC .................................................................................................. 108 3.10.1.2 Flow NMR ...................................................................................................... 109 3.10.2 Suzuki Miyaura Coupling Reaction .................................................................... 109 3.10.2.1 Online HPLC .................................................................................................. 109 3.10.2.2 Flow NMR ...................................................................................................... 109 3.11 Zaiput Membrane Separator ....................................................................................... 110 3.12 Identification of KBr formation in the Aqueous Layer .............................................. 112 Chapter 4: Gold Nanoclusters (AuNCs): HPLC Analysis for Complex Reaction Mixtures......................................................................................................................................................115 4.1 Introduction ................................................................................................................. 115 4.2 HPLC Method Development ...................................................................................... 117 4.3 Analytical Method Development ................................................................................ 119 xii 4.4 Reaction Monitoring of [Au13(NHC)9Cl3]Cl2 (4.1) Synthesis .................................... 121 4.5 Optimization of the [Au13(NHC)9Cl3]Cl2 (4.1) Synthesis .......................................... 126 4.6 Reaction Monitoring of [Au24(NHC)14Cl2H3] [BF4]3 (4.2) Synthesis ........................ 128 4.7 Conclusion .................................................................................................................. 131 4.8 General Information .................................................................................................... 132 4.9 HPLC Methods ........................................................................................................... 132 4.10 Synthetic Procedures ................................................................................................... 135 4.10.1 1,3-dibenzyl-1H-benzo[d]imidazolium chloride ................................................ 135 4.10.2 (1,3-Dibenzyl-1H-benzo[d]imidazol-2-ylidene)gold(I) chloride (4.3) ............... 135 4.11 General Reaction Monitoring Procedure .................................................................... 136 4.11.1 [Au13(NHC)9Cl3]Cl2 (4.1) Synthesis (Section 4.4) Monitoring Procedure ......... 136 4.11.2 [Au13(NHC)9Cl3]Cl2 (4.3) Synthesis by Sequential Dose (Section 4.5) Monitoring Procedure ............................................................................................................ 136 4.11.3 [Au24(NHC)14Cl2H3] [BF4]3 (4.2) Synthesis (Section 4.6) Monitoring Procedure ... ............................................................................................................................. 137 4.12 MS Signal Found in Regional Analysis for Au13 Synthesis ....................................... 137 4.12.1 Small Region ....................................................................................................... 137 4.12.2 Medium Region .................................................................................................. 142 4.13 By-/Side Product Formations in Sequential Dose Experiment ................................... 146 4.14 MS Signal Found in Regional Analysis for Au24 Synthesis ....................................... 147 4.14.1 Small Region ....................................................................................................... 147 4.14.2 Medium Region .................................................................................................. 153 4.15 High Resolution Mass Spectrometry (HRMS) Data of 4.1 ........................................ 158 xiii 4.16 HPLC Spectra Comparison between Synthesis of 4.1 and 4.2 ................................... 159 Chapter 5: Conclusions and Outlook .......................................................................................160 References ...................................................................................................................................164 Appendix A: NMR Spectra for Chapter 2 .............................................................................. 191 A.1 Tetrabenazine (TBZ) ((rac)-2.1) ......................................................................... 191 1H NMR (400 MHz, CDCl3) ............................................................................................... 191 A.2 3-[(dimethylamino)methyl]-5-methylhexan-2-one (2.12) .................................. 192 1H NMR (400 MHz, CDCl3) ............................................................................................... 192 A.3 5-methyl-3-methylidenehexan-2-one (2.14) ....................................................... 193 1H NMR (400 MHz, CDCl3) ............................................................................................... 193 A.4 trimethyl-[2-(2-methylpropyl)-3-oxobutyl]-azanium iodide .............................. 194 1H NMR (400 MHz, CDCl3) ............................................................................................... 194 A.5 TBZ diastereomers ((rac)-2.22) .......................................................................... 195 1H NMR (400 MHz, CDCl3) ............................................................................................... 195 A.6 6,7-dimethoxy-2-[2-(2-methylpropyl)-3-oxobutyl]-3,4-dihydroisoquinolin-2-ium (2.23) ................................................................................................................... 196 1H NMR (400 MHz, CDCl3) ............................................................................................... 196 Appendix B: NMR Spectra for Chapter 3 .............................................................................. 200 B.1 2-Fluoro-5-pyridyl-boronic acid (Partition Test Section 3.4, Figure 3.5 B) (3.1) .... ............................................................................................................................. 200 B.2 2-Fluoro-5-pyridyl-boronate (Partition Test Section 3.4, Figure 3.5 F) (3.1) .... 202 B.3 3-Fluoro-5-hydroxyphenyl-boronic acid (Partition Test Section 3.4, Figure 3.6 B) (3.2) ..................................................................................................................... 204 xiv B.4 4-(trifluoromethyl)phenyl-boronic acid (Partition Test Section 3.4, Figure 3.7 B) (3.3) ..................................................................................................................... 206 B.5 4-(trifluoromethyl)phenyl-boronate (Partition Test Section 3.4, Figure 3.7 F) (3.3) ............................................................................................................................ 207 B.6 NMR spectra of reaction monitoring with 2-fluoro-5-pyridyl-boronic acid (organic) .............................................................................................................. 210 Starting materials: 1H NMR (400 MHz, 2-MeTHF) ........................................................... 210 Starting materials: 19F NMR (377 MHz, 2-MeTHF) .......................................................... 211 Starting materials: 11B NMR (128 MHz, 2-MeTHF).......................................................... 212 B.7 NMR spectra of reaction monitoring with 2-fluoro-5-pyridyl-boronic acid (aqueous) ............................................................................................................. 213 Starting materials: 11B NMR (128 MHz, water) ................................................................. 215 xv List of Tables Table 2.1. Online HPLC Column and Separation Method Detail. ................................................69 Table 3.1. HPLC Column and Separation Method Detail. ..........................................................100 Table 3.2. Other hardware used in this study...............................................................................101 Table 3.3. The evaluation of mass balance of Pyr-BA 3.4. .........................................................103 Table 4.1. HPLC method for separation development using acetonitrile and formic acid as modifier ........................................................................................................................................132 Table 4.2. HPLC method for separation development using methanol and formic acid as modifier......................................................................................................................................................133 Table 4.3. HPLC method for separation development using methanol and TFA as modifier ....133 Table 4.4. HPLC method for reaction monitoring .......................................................................134 Table 4.5. HPLC method for separation development using methanol and TFA as modifier ....134 xvi List of Figures Figure 1.1. Summary of wavelengths, corresponding excitation modes of chemical property, and analytical instruments for various electromagnetic waves ..............................................................2 Figure 1.2. The splitting magnetic moment of a nucleus by exposure to an external magnetic field. .................................................................................................................................................5 Figure 1.3. Illustration of total reflection -Fourier transform infrared ..........................................21 Figure 1.4. Illustration of the flow NMR system used by Maschmeyer et al. for quantitative real-time reaction monitoring ................................................................................................................23 Figure 1.5. Illustration of the EasyViewer and captured images of a) oil droplet, b) primary nucleation of crystals, and c) grown crystals. ................................................................................25 Figure 2.1. Structures of (±)-Tetrabenazine and Valbenazine. ......................................................33 Figure 2.2. Schematic diagram of automated sampling platform used for reaction monitoring. ..38 Figure 2.3. Calibration curves of TBZ generated using sampling platforms with (a) or without (b) a dynamic mixer. TBZ precipitates at concentrations above 0.13 M in a solution of 30% water in isopropyl alcohol at 45 ºC. .............................................................................................................38 Figure 2.6. Relationship of volume changes against solid dose of TBZ, isoquinoline 2.9 and NaI in a solution of 30% water in isopropyl alcohol at room temperature. ..........................................41 Figure 2.7. Reaction profile under initial conditions. Reaction conditions: [2.9•HCl] = 0.64 M, [2.12] = 0.8 M, [NaI] = 0.25 M in a solution of 30% water in isopropyl alcohol at 45 ºC. ..........42 Figure 2.8. Reaction profile substituting β-amino ketone 2.12 with enone 2.14 and DMA 2.15. Reaction conditions: [2.9•HCl] = 0.64 M, [2.14] = 0.8 M, [2.15] = 0.8 M, [NaI] = 0.25 M in a solution of 30% water in isopropyl alcohol at 45 ºC. ....................................................................43 xvii Figure 2.9. TBZ formation trends using different initial concentrations of enone 2.14 and DMA 2.15. Reaction conditions: [2.9•HCl] = 0.64 M, [2.14] = 0.8 or 0.4 M, [2.15] =0.8 or 0.4 M, [NaI] 0.25 M in a solution of 30% water in isopropyl alcohol at 45 ºC. .................................................45 Figure 2.10. TBZ formation trends from iminium intermediate 2.23 under three different conditions. Reaction conditions: [2.23] = 0.12 M, [Amine] = 0.072 M or 0 M in a solution of 30% water in isopropyl alcohol at 45 ºC........................................................................................47 Figure 2.11. The proposed trimolecular transition structure and modelled pH profile: Initial rate, free isoquinoline ratio and free HA ratio were plotted. The initial rate was calculated by rate = k’*(Ka1/(Ka1+[H]+))*([H+]/(Ka2+[H]+)). When I applied pKa1 = 5.8 for the conjugate acid of isoquinoline and pKa2 = 8.5 for HA, the modelled pH profile fit the experimental data well. ......49 Figure 2.12. (a) TBZ formation and (b) pH trends using different initial amine concentrations with DMA 2.15 and DIPEA. Reaction conditions: [2.9•HCl] = 0.64 M, [2.14] = 0.8 or 0.4 M, [Amine] =0.8 or 0.4 M, [NaI] 0.25 M in a solution of 30% water in isopropyl alcohol at 45 ºC..53 Figure 2.14. TBZ formation trends with or without NaI under reaction 1 or reaction 2. ..............58 Figure 2.15. The dynamic mixer as shown from (a) the front and (b) the side. ............................66 Figure 2.16. Mettler-Toledo EasySampler (a) closed position. (b) extended position77 ...............67 Figure 2.17. online HPLC spectra (240 nm and 280 nm) at 5 hours under reaction 1 conditions.........................................................................................................................................................70 Figure 2.18. Delivery kinetics of heterogeneous TBZ and homogeneous isoquinoline when using (a) the no mixer volume (b) 0.05 mL mixer volume and wait 30 seconds. (c) 0.2 mL mixer volume and wait 30 seconds. (d) 0.3 mL mixer volume and wait 30 seconds. (e) 0.4 mL mixer volume and wait 30 seconds. .........................................................................................................71 xviii Figure 2.19. Calibration curve of TBZ using 0.4 mL mixer volume and wait 30 seconds method.........................................................................................................................................................73 Figure 2.20. Reaction monitoring profile of isoquinoline with initial points standard addition. ..74 Figure 2.21. Reaction monitoring profile of TBZ with ending points standard addition. .............74 Figure 3.1 (a) Illustration of aqueous and organic droplets on the surface of hydrophobic, hydrophilic, oleophobic and oleophilic materials. Static contact angle θ changes depending on the surface material. (b) Illustration of aqueous and organic droplets on PTFE material (top); illustration of desired material for selective aqueous layer sampling (bottom). ............................78 Figure 3.2 (a) 10 mL of collected sample from MeTHF/water mixture, before any modification of the alloy filter, flow rate = 3.0 mL/min. (b) 10 mL of collected sample from MeTHF/water mixture, After 5 M K2CO3 modification of the alloy filter, flow rate = 3.0 mL/min. (c) 10 mL of collected sample from MeTHF/water mixture, After 5 M K2CO3 modification of the alloy filter, flow rate = 1.0 mL/min. (d) The sampling system used for the test of alloy filter efficiency, an aqueous layer has been colored by the addition of green food dye (3 drops in total). ..................81 Figure 3.3 Biphasic sampling system used in this research, alloy filter used for aqueous layer selection is represented in blue; PTFE filter used for organic layer sampling is presented in red.........................................................................................................................................................83 Figure 3.4 Sampling system used in this research on Amgen site (left figure), a PTFE filter used when organic sampling was required (top right of the figure); an alloy filter was used when aqueous layer sampling was required (bottom right of the figure) ................................................84 Figure 3.5 Concentration of HPLC (shown in orange) and NMR (shown in blue) data for the partition test of boronic acid 3.4, both organic (shown in the solid squares) and aqueous layers (shown in the void squares) are plotted. Mixture compositions: A. 250 mM 3.4 (15 mmol) in 60 xix mL MeTHF; B: 3.4 (15 mmol) in 60 mL MeTHF and 60 mL water; C: 3.4 (15 mmol) in 60 mL MeTHF and 60 mL water + 0.25 eq. K2CO3 (0.75 mL); D: 3.4 (15 mmol) in 60 mL MeTHF and 60 mL water + 0.50 eq. K2CO3 (1.5 mL); E: 3.4 (15 mmol) in 60 mL MeTHF and 60 mL water + 1.0 eq. K2CO3 (3.0 mL); F: 3.4 (15 mmol) in 60 mL MeTHF and 60 mL water + 2.0 eq. K2CO3 (6.0 mL). HPLC experiment was conducted 6.25 mmol scale. .....................................................87 Figure 3.6 Concentration of HPLC (shown in orange) and NMR (shown in blue) data for the partition test of boronic acid 3.5, both organic (shown in the solid squares) and aqueous layers (shown in the void squares) are plotted. Mixture compositions in NMR experiment: A. 250 mM 3.5 (15 mmol) in 60 mL MeTHF; B: 3.5 (15 mmol) in 60 mL MeTHF and 60 mL water; C: 3.5 (15 mmol) in 60 mL MeTHF and 60 mL water + 0.25 eq. K2CO3 (0.75 mL); D: 3.5 (15 mmol) in 60 mL MeTHF and 60 mL water + 0.50 eq. K2CO3 (1.5 mL); E: 3.5 (15 mmol) in 60 mL MeTHF and 60 mL water + 1.0 eq. K2CO3 (3.0 mL); F: 3.5 (15 mmol) in 60 mL MeTHF and 60 mL water + 2.0 eq. K2CO3 (6.0 mL). HPLC experiment was conducted 6.25 mmol scale...........88 The generation of unknown peaks in the organic layer was only observed in the partition test with CF3-phenyl boronic acid 3.6 (Figure 3.10). This further supports the unidentical trends between HPLC and NMR occurred only with 3.6. ........................................................................92 Figure 3.15 Volume test by mixing 25 mL of MeTHF and 25 mL of water. Left: before the addition of 25 mL of pure water; right: after the addition of 25 mL of pure water. ....................104 Figure 3.16 Illustration of the 4-port Cheminert Nanovolume™ UHPLC internal sample injector (VICI). A. Load position; B. Inject Position ................................................................................106 Figure 3.17. Online HPLC platform diagram at organic sampling state .....................................107 Figure 3.18. Online HPLC platform diagram at aqueous sampling state ....................................107 xx Figure 3.19. Diagram of the sampling platform is shown in figure SX. After the liquid/liquid biphasic mixture was separated, an x-type selector chose which layer to deliver to the HPLC analysis. ........................................................................................................................................110 Figure 3.20. Diagram of phase selective sampling platform using s Zaiput membrane separator.......................................................................................................................................................111 Figure 3.21. Liquid/liquid separation of MeTHF and water with a red food dye by a Zaiput membrane separator (left). Fouling of palladium black on the membrane (right).......................112 Figure 4.1. X ray structures of [Au13(NHC)9Cl3]Cl2 (4.1) (left) and [Au24(NHC)14Cl2H3][BF4]3 (4.2) (right). ..................................................................................................................................117 Figure 4.2 Methods development for RP-HPLC-MS. Top, green: A water/acetonitrile gradient with 0.1 % formic acid. Middle, blue: a water/methanol gradient with 0.1 % formic acid. Bottom, red: a water/methanol gradient with 0.1 % TFA..........................................................................118 Figure 4.3. Chromatogram of the synthesis of 4.1 taken at four critical points in the reaction. A. Sample taken before the addition of NaBH4. B. Sample taken immediately following the addition of NaBH4 C. Sample taken after the 3 hour reaction. D. Sample taken after HCl etching..........120 Figure 4.4. Analysis of the Au13 reaction over time. The total peak area of each region was analyzed and monitored over the course of the reaction. Reaction conditions: 4 mM of 4.3 in 1 mL of DCM, cooled in an ice-bath for 10 mins, then the addition of 40 μL NaBH4 (100 mM, 1 eq) EtOH solution. The reaction was monitored for 1 hour at 0 °C and for 2 hours at room temperature. After 3 hours concentrated HCl solution (12 M, 0.33 μL, 1 eq.) was added to the reaction. ........................................................................................................................................122 Figure 4.5 Reaction spectra from both HPLC and mass spectrometry extracted of reaction time at 0 hour (top), 30 minutes (middle), and 1 hour (bottom). 4.1 (shaded in red), 4.2 (shaded in xxi yellow) and a newly identified AuNC [Au14(NHC)9Cl3]2+ (shaded in blue) were shown in the figure. ...........................................................................................................................................125 Figure 4.6 Au13 NC synthesis by sequential doses method. Reaction condition: 4 mM of 4.3 in 3 mL of DCM under r.t. 24 μL NaBH4 (100 mM, 0.2 eq) EtOH solution was dosed into the reaction successfully. ...................................................................................................................127 Figure 4.7 Analysis of the Au24 synthesis reaction over time. The total peak area of each region was analysed and monitored over the course of the reaction. Reaction conditions: 1.5 mM of 4.6 in 1 mL of toluene, cooled in ice bath for 10 mins, then the addition of 100 μL NaBH4 (15 mM, 1 eq) in EtOH dropwise and DCM (50 μL). The reaction was allowed to warm to r.t. and monitored for 2 hours...................................................................................................................130 Figure 4.8. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 0 min .............138 Figure 4.9. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 1 min .............139 Figure 4.10. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 15 min ...........139 Figure 4.11. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 30 min ...........140 Figure 4.12. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 45 min ...........140 Figure 4.13. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 60 min ...........141 xxii Figure 4.14. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 75 min ...........141 Figure 4.15. Medium region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 0 min ..142 Figure 4.16. Medium region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 1 min ..143 Figure 4.23. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 0 min .............148 Figure 4.24. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 1 min .............148 Figure 4.25. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 15 min ...........149 Figure 4.26. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 30 min ...........149 Figure 4.27. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 45 min ...........150 Figure 4.28. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 60 min ...........150 Figure 4.29. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 75 min ...........151 Figure 4.30. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 90 min ...........151 xxiii Figure 4.33. Medium region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 0 min ..153 Figure 4.34. Medium region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 1 min ..153 Figure 4.43. HPLC spectrum of isolated [Au13(NHC)9Cl3]Cl2 at 290 nm wavelength ...............158 Figure 4.44. HRMS data and a predicted mass pattern of isolated [Au13(NHC)9Cl3]2+ ..............158 Figure 4.45. HPLC spectra comparison between synthesis of 4.1 and 4.2. Reaction samples at 1 minute point from each reaction (Figure 4.4 and 4.7) were compared using 290 nm wavelength.......................................................................................................................................................159 The HPLC spectrum of the synthesis of 4.2 showed two peaks with m/z 793, which is the same as the mass of bis-NHC complex byproduct 4.4. Since [NHC-Au-Py]BF4 4.6 was used as starting material, the two peaks indicated [NHC-Au-NHC]+ coordinated with two different counter ions (BF4- and Cl-). ..............................................................................................................................159 xxiv List of Schemes Scheme 2.1. Reported synthesis methodologies for the core structure of TBZ. ............................35 Scheme 2.2. (a) Original synthetic procedure for (±)-TBZ (b) potential mechanistic pathways to access (±)-TBZ...............................................................................................................................36 Scheme 2.3. Formation of iminium intermediate 2.23. .................................................................46 Scheme 2.4. Proposed reaction acceleration mechanism under different amine concentrations with DMA 2.15 and DIPEA...........................................................................................................54 Scheme 2.5. Proposed kinetic controlled Mannich cyclization step via chair like transition state and thermodynamic epimerization mechanisms. ...........................................................................56 Scheme 2.6. Proposed mechanism of acid catalyzed TBZ synthesis. ...........................................59 Scheme 3.1 Two pathways of boronic acids exhibit acidity, as Brønsted (1); and electrophile (2).........................................................................................................................................................85 Scheme 3.2 Boronic acid used in this research: 3.4: (6-fluoropyridin-3-yl)boronic acid; 3.5: (3-fluoro-5-hydroxyphenyl)boronic acid; 3.6: (4-(trifluoromethyl)phenyl)boronic acid ...................85 xxv List of Abbreviations A absorbance API active pharmaceutical ingredient appox approximate Aq. aqueous or aqueous layer Ar aryl ATR attenuated total reflection AU absorbance units AuNC gold nanocluster AuNP gold nanoparticle BA boronic acid Bn benzyl Bu butyl C concentration CA California cat catalyst COSY ¹H-¹H Correlation Spectroscopy d doublet D deuterium DAD diode array detector DCM dichloromethane DIPA diisopropylamine DIPEA N,N-diisopropylethylamine xxvi DMA dimethylamine EDG electron donating group EI electron impact ELSD evaporative light scattering detector Eq. equation equiv. equivalent(s) ESI-MS electrospray ionization-mass spectrometry Et ethyl EtOAc ethyl acetate Et2O diethyl ether EtOH ethanol Expt experiment ε molar absorption coefficient FBRM focused beam reflectance measurement FDA U.S. Food and Drug Administration FLIPS Faster Longitudinal relaxation Investigated by Progression Saturation FTIR Fourier transform infrared GC gas chromatography G2 generation 2 HA general acid HMBC ¹H-¹³C Heteronuclear Multiple Bond Correlation Spectroscopy HOMO highest occupied molecular orbital HPLC high-performance liquid chromatography xxvii HPH high pH HRMS high resolution mass spectrometry HSQC ¹H-¹³C Heteronuclear Single Quantum Coherence Spectroscopy HTBZ dihydrotetrabenazine HTS high-temperature superconducting iPr isopropyl iBu isobutyl IPA isopropyl alcohol IR infrared J coupling constant (NMR spectroscopy) k rate constant K equilibrium constant KIE kinetic isotope effect l optical path length LC liquid chromatography LUMO lower unoccupied molecular orbital λ wavelength m multiplet Me methyl MeCN acetonitrile MeOH methanol MeTHF 2-methyl tetrahydrofuran MHz megahertz xxviii MS mass spectrometry MSD mass spectrometry detector MW molecular weight m/z mass-to-charge ratio NC nanocluster NHC N-heterocyclic carbene NMR nuclear magnetic resonance Nu nucleophile -o ortho substituted Org organic or organic layer -p para substituted PAT process analytical technology PEEK polyether ether ketone pH potential of hydrogen Ph phenyl pKa acid strength ppm parts per million PTFE Polytetrafluoroethylene q NMR quantum NMR rac racemic R organic substituent RP reverse phase RPKA reaction progress kinetic analysis xxix r.t. room temperature or retention time rxn reaction s second or singlet SMC Suzuki Miyaura cross coupling T temperature T1 spin-lattice relaxation time tBu tert-butyl TBZ tetrabenazine TFA trifluoroacetic acid THF tetrahydrofuran TLC thin-layer chromatography TOF time-of-flight θ static contact angle UHPLC ultra-high-performance liquid chromatography UV ultraviolet V volt VBZ valbenazine Vis visible vs versus W wave number XAS X-ray absorption spectroscopy XRD X-ray diffraction 2D 2 dimensional xxx 3D 3 dimensional xxxi Acknowledgements Foremost, I would like to express my deep and sincere appreciation to the support of family, friends, and Hein Lab members. Without their presence, none of this would have been possible. The following words are an attempt to acknowledge those who kept me motivated to complete this thesis. I need to thank my supervisor, Professor Jason E. Hein, for his guidance which I am most grateful for. You are a passionate person and always pay attention to innovative technologies. Your dynamism and vision motivated and inspired me to learn broad knowledge, not only chemistry but also engineering and computer science. Your kind personality also enabled me to relocate to Vancouver from Japan without fear. I strongly remember the very kind words from you right after I joined the Hein Lab, “Yusuke, you are our family member.” After these words, this place, UBC, has become my second home. Next, I would like to thank my wife, Midori. I am extremely grateful for your love and dedication in supporting my research life. I found that enjoying things together refreshed my focus on taking the next steps in my research. You taught me how to improve my work-life balance, and I learned how to be a good adult as well as being a good scientist. I would like to thank my supervisory committee: Prof. Glenn Sammis, Prof. David Perrin, and Prof. Zachary M. Hudson for your comments and guidance during my graduate career. A fond appreciation and thanks are owed to the researchers at Neurocrine Biosciences, Amgen, and Crudden group in Queen’s University throughout the collaborations discussed in Chapter 2, 3 and 4 respectively. I appreciated all insightful feedback comments through the biweekly meetings. xxxii I would like to acknowledge the funding agencies. The graduate scholarships and research funding made this project possible and allowed me to experience invaluable research. I truly appreciate the unconditional support from my parents and sister. Your support has been essential in guiding me to focus on my research and complete this thesis. Last but not least, I would like to thank all my fellow Hein Lab group members both past and present. Each of us has a dramatically different background from chemistry to computer science. The diversity is our strength, creating synergy that allows us to achieve innovative findings, as we are all able to learn from one another and apply this shared knowledge in for our own research topics. Specifically, I would like to thank Junliang Liu for being a best co-worker/friend. You are always my first choice to discuss research and enjoy things together at any time from early morning to late at night. This long journey would never have happened without you. xxxiii Dedication This work is dedicated to my wife and parents. Your love and guidance have encouraged me to pursue my curiosity over the years. You are my light with endless brightness, pointing me in the right direction. “科学の歴史は裏から見れば失敗と停滞の歴史でもある。しかし早い段階での失敗がなかったら、成功も飛躍もなかったであろう。” ― 湯川秀樹 Translation “The history of science is, from the back perspective, a history of failure and stagnation. However, without the early failures, there would have been no successes or breakthroughs.” ― Hideki Yukawa 1 Chapter 1: Introduction 1.1 Importance of Analytical Chemistry 1.1.1 History of Analytical Chemistry Analytical chemistry has been recognized as a systematic subject for studying chemical composition since the mid-18th century.1–4 The history of analytical chemistry is even longer than that. Friedrich Hoffmann (1660-1742) had already precipitated MgSO4 and CaSO4 before this time using sulfuric acid from different ores of the earth, magnesia and calcareous, respectively.3 Hoffman used his sense of taste, rather than modern analytical instruments, to determine the difference between bitter MgSO4 and tasteless CaSO4. The classical analysis only requires simple equipment, including a balance and glassware, to determine the sample properties.1,5 Gravimetric analysis is a standard classical method to determine the weight of a purely isolated target substance, for instance by means of precipitation as salt. Another classical methodology is titrimetric analysis, which quantitatively determines the amount of analyte based on the volume of a standard solution required to react with the analyte stoichiometrically. These methodologies are now called “classical” analysis to differentiate from modern analytical tools, but the classical approach is still widely used in daily chemistry.6–11 This is because classic analysis requires inexpensive apparatus and their detection can be completed by human senses, such as color change and weight of materials. This also makes them popular analysis techniques in teaching environments where students are learning to understand the scientific method based on their observations of the world around them. In the 20th century, the development of instrumental analysis progressed dramatically along with the development of the industry.1,12,13 Unlike classical analysis, instrumental analysis measures chemical properties via optical or electrical signals. These signals are significantly more 2 challenging for humans to detect than the detection methods used in classical analysis. Therefore, these methods of chemical interrogation require specialized, often expensive equipment, typically directing electromagnetic waves toward the analyte to analyze the response obtained by a detector. A variety of electromagnetic waves can be used to excite different chemical properties (Figure 1.1). The development of analytical instruments has been revolutionary for mankind, and these achievements have been awarded numerous Nobel prizes in the last century.14–19 Figure 1.1. Summary of wavelengths, corresponding excitation modes of chemical property, and analytical instruments for various electromagnetic waves 1.1.2 Qualitative Analysis The purpose of qualitative analysis is to answer the fundamental question, “what component is in this sample?” For unknown substances, qualitative analysis is generally performed first to determine the elements, molecules, ions, functional groups, and isotopes before any quantification. A flame test is a conventional qualitative analysis, in which the presence of a specific metal ion is detected by the produced color in flame.20,21 The flame test rapidly detects the type of ion by color changes, which is often used for educational purposes in high schools and Wavelength (m)Excitation ModeAnalysis Method1 10310-310-610-910-12Electron Bond vibrationRotation Nuclear spinNMRmicrowaveIRRamanUV-VisXRDXAS etc.Outer ShellInner Shell3 undergraduate laboratories due to the simplicity and excitement of the experiments.22,23 However, the increasing demands to characterize more complex organic, biological, and material compounds require scientists to continuously develop qualitative analytical methods to detect additional chemical or physical properties.24,25 Since the 1900s, scientists have explored chemical or physical properties other than the ones detected by classical methods such as color, boiling points, solubility, odor, weight, and volume.1 Along with the development of the electronics and computer industries, the qualitative measurement of a variety of physical properties such as conductivity, electrode potential, light absorption or emission, mass-to-charge ratio, and fluorescence have become accessible by various instrumental analyses. Furthermore, highly efficient chromatographic and electrophoretic techniques have been accessible since the 1970s for the separation of components of complex mixtures prior to their analysis.26–30 These new methods for separating and characterizing chemical species are known as instrumental analytical methods. The major categories of instrumental methods are optical spectroscopies, electrochemical sensors, and separatory techniques. Many of these instrumental analysis methods can be used for both qualitative and quantitative analysis, but in this section, the discussion will be directed toward typical instrumental methods for conducting qualitative analysis. 1.1.2.1 Optical Spectroscopies Optical spectral analytical methods use electromagnetic radiation which is emitted, absorbed or scattered by the analytes exposed to the light of different wavelengths.31–33 The different structural motifs in a molecule absorb the light that matches their excitation energy. For instance, while the energy of infrared (IR) wavelength is close to that of molecule bond vibration, the energetically much higher energy ultraviolet (UV) light can excite electrons between electronic 4 orbitals and cause electronic transitions between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO). Its broad application scope makes optical spectroscopy one of the largest categories of instrumental analytical methods and results in spectroscopy often being used as a detection technique to measure any one of a number of chemical or physical properties. 1.1.2.1.1 Nuclear Magnetic Resonance (NMR) Nuclear magnetic resonance (NMR) spectroscopy is based on the absorption of electromagnetic radiation by the nuclei of atoms rather than the valence electrons that are used in ultraviolet-visible (UV-Vis) spectroscopy or molecular vibrations in IR spectroscopy.34,35 In the field of qualitative analysis, NMR spectroscopy is one of the most powerful instrumental methods for the elucidation of the structure of chemicals due to its ability to distinguish between different chemical environments.36–40 In 1924, W. Pauli suggested that certain atomic nuclei have spins and magnetic moments that could be split under an external magnetic field (Figure 1.2).41,42 A few decades after the proposal of the NMR theory, chemists became aware that the chemical environment can influence the energy gap of the nucleus and this effect can be correlated with the molecular structure. 5 Figure 1.2. The splitting magnetic moment of a nucleus by exposure to an external magnetic field. The first high-resolution NMR instrument built for chemical structural elucidation was constructed in 1953. Since then, the development of NMR spectroscopy has been extremely prolific. Nowadays, NMR spectroscopy has found wide applications not only in chemistry, but also in pharmaceutical, medical, petrochemical, material science and many other disciplines. The wide utility and importance of NMR for qualitative analysis is due to the amount of structural information it can provide. The energy gap difference between the applied external magnetic field and the existing magnetic field on each nucleus can be measured as a chemical shift, while this chemical shift information can provide general chemical environmental information for each nucleus. Spin-spin coupling caused by adjacent nuclei provides more detailed structural understandings. Furthermore, multi-pulse NMR and multidimensional NMR (2D and 3D NMR) have enabled completely new experiments to identify resonances coupled through space, allowing complex structures to be elucidated via through-bond and/or through-space interactions.43,44 6 1.1.2.1.2 Infrared (IR) Spectroscopy Infrared spectroscopy encompasses radiation between the visible and microwave regions of the electromagnetic spectrum, which corresponds to roughly from 750 nm to 100 µm. Traditionally, wave number is utilized in the field of IR spectroscopy, and the wave number (W, cm-1) is the reciprocal form of its wavelength (λ, cm) (Eq. 1.1). Therefore, the IR wavelength range (750 nm – 50 µm) can be alternatively represented in wavenumbers as 13333 to 100 cm-1. 𝑊 = 1 𝜆⁄ (Eq. 1.1) Conventionally the IR region is subdivided into three regions: near-IR (13000-4000 cm-1), mid-IR (4000-400 cm-1) and far-IR (< 400 cm-1).45–48 While near- and far-IR provide important information for many materials, the mid-IR range in particular interacts with common organic molecule bond vibrations, such as X-H (4000-2500 cm-1), triple bond (2500-2000 cm-1), double bond (2000-1500 cm-1) and the fingerprint region (1500-400 cm-1).49–52 IR signals consist of the absorption, emission, and/or reflection of the molecular species. These signals arise from changes in energy levels corresponding to vibrational or rotational energy states. Regarding qualitative analysis, IR spectroscopy is a rapid, non-destructive spectroscopic technique widely used in labs. The useful aspect of IR spectroscopy comes from its capability to identify different functional groups in chemical compounds. The example can be seen between ketone (ca.1720 cm-1) vs. amide (ca.1670 cm-1), where the resonance effect by the lone pair of the nitrogen decreases the C=O bond strength. In addition, the same functional group in different molecules can have different chemical environments, which varies the wave number of the absorption of the functional group and can allow for the identification and quantification of similar species. This difference is useful for detecting the difference between secondary structures (e.g. α-helix vs. β-sheet in polyamide).53 7 1.1.2.1.3 Ultraviolet-visible (UV-Vis) spectroscopy Chemical species absorb energy from electromagnetic radiation in the ultraviolet or visible range, with the specific regions of such compounds responsible for this absorption being referred to as “chromophores”.54 This type of energy absorption accounts for valence electrons being excited to a higher energy molecular orbital.55 In contrast to previously discussed NMR spectroscopy and IR spectroscopy, UV-Vis spectroscopy cannot provide as detailed structural information for the interrogated molecules due to the broadness of the peaks appearing in the UV-Vis spectrum. This is because electronic excitations that are usually accompanied by vibrational transitions are usually not resolved in UV-Vis spectroscopy.56 As a result, UV-Vis spectroscopy is more widely used for quantitative determination of the concentration of the analyte under interest rather than compound identification and structural elucidation. However, in some fields UV-Vis spectroscopy is still a helpful technique for qualitative analysis as it can assist in identification of key spectroscopic features associated with specific species or reactions57–59 For example, many transition metal ions have a distinct UV-Vis spectrum where d to d transitions correspond to energy in the ultraviolet or visible portion of the spectrum. These UV-Vis peaks can be changed dramatically by the coordinated ligands, as the ligands affect the energies of the d orbitals and therefore the possible transitions between them.60–62 As a result, UV-Vis spectroscopy is often used in metal complexes studies to confirm the presence of certain metals and/or to observe ligand transitions due to characteristic transitions associate with particular ligand environments. In particular, UV-Vis spectroscopy is a common method for the identification of newly synthesized metal nanoclusters (NCs) since slight differences in metal NC composition can lead to changes in UV-vis peak shape and absorbance.63–65 This makes UV-Vis spectroscopy 8 extremely useful for interrogating such complex systems where many possible clusters can be formed. 1.1.2.1.4 Mass Spectrometry Mass spectrometry (MS) is one of the most widely used analytical techniques for qualitative analysis among all the analytical tools because it can not only provide information about the structure of molecules, but also determine their exact elemental composition, isotopic ratios of atoms, and more. The general concept of mass spectrometry is the separation of ions by their mass-to-charge ratio (m/z). The generation of these ions requires the analyte to be in the gaseous state from where it is subjected to either a hard or a soft ionization source. The most prominent ionization methods to achieve this initial vaporization and ionization, include electron impact (EI) for hard- and chemical ionization or electrospray ionization (ESI) for soft ionization. Of particular interest to organic chemists is EI as it gives structural information on the desired molecules due to fragmentation.66 This is achieved by bombarding the gas-phase analyte with high-energy electrons, resulting in collisions between the electrons and analytes. These collisions give the analyte enough energy for its electrons to jump to an excited state, followed by a relaxation process with the fragmentation of the analyte to produce molecular ions with lower masses. As a result, the injected sample now becomes charged fragments that can then be analyzed to determine the structure of the original molecule. ESI-MS enables a broad detection of various compounds, including organometal catalysts and bio-molecules.67,68 The ESI-MS has been an increasingly important technique due to its high sensitivity, speed and dynamic range with little fragmentations.68,69 This also makes ESI especially 9 useful in combination with HPLC as the solvent eluting from the column can be nebulized and evaporated to form small charged droplets, facilitating easy compound ionization and identification directly after analysis by another detector such as UV-Vis. In addition to simple compound identification and fragmentation by low-resolution MS, high-resolution MS can provide an accurate molecular mass of up to four digital figures. This accuracy provides a way to confirm the exact chemical formula of the analyte under interest and therefore unambiguously confirm the exact number and type of atoms present, allowing for exact structural confirmation once another structural elucidation technique has been employed (such as NMR spectroscopy or EI-MS).70 Confirmation of composition by high-resolution MS is usually required by academic journals to provide concrete evidence that the proposed compounds were synthesized, especially if they have not previously been reported in the literature. Lastly, MS is often applied in isotopic analysis, where one or multiple elements in a reagent are changed to their other stable mass isotopes. Such isotopic labelling can allow for precise mechanistic information to be determined, as only bond-making and breaking events should incorporate these heavier isotopes. Their inclusion can thus point to key sites of reactivity on a molecule and highlight changing bonds.71,72 Additionally, competition studies of multiple substrates with the possibility for new isotope incorporation (kinetic isotope effect, KIE) can give insight into reactivity and further support mechanistic elucidation.73–76 A combination of other spectroscopies and MS can therefore be critical to determine the exact mechanism of a particular reaction, making this technique imperative for reaction understanding in many scenarios. 10 1.1.2.2 Separation Methodologies 1.1.2.2.1 High Performance Liquid Chromatography (HPLC) In chemistry research, and especially in the field of organic synthesis, very few samples will contain only a single chemical species. Instead, almost all samples of interest will be mixtures of multiple components. As a result, any analysis of the mixture will return signals representing the bulk property of the analyte, with each analyte potentially contributing to the response generated from an instrument. Many detection techniques such as NMR and IR spectroscopy can detect variations in signal caused by different moieties or functional groups, allowing peaks from different chemical species to be distinguished. However, this becomes ambiguous and harder to confirm as the mixture contains a higher number of more and more similar structure species which can result in overlapping peaks and difficulty in both identifying and quantitating these components. As a result, the separation of the analyte from potential interferences is quite often a vital step in analytical procedures, including the identification of key features to distinguish similar molecules or the separation of similar species to facilitate simpler analysis. Classical separation methods such as precipitation, distillation and extraction were the only choices for chemists who needed to do separation for their analytes until the mid-twentieth century. However, nowadays chromatography has become a much more efficient method and is often carried out for analytical separations. In particular, high performance liquid chromatography (HPLC) is the most versatile and widely used chromatographic method. HPLC separates chemical mixtures via differences between each component interacting with the stationary phase, causing different elution rates of each component, which leads to separation of these components as they exit the chromatographic environment at different times. 11 In terms of qualitative analysis, general information of the analyte’s size and/or polarity can be elucidated by comparing the properties of the stationary phase and mobile phase with analyte retention time. Most importantly, HPLC instruments can be coupled with a number of unique detectors including UV-Vis detectors,77 fluorescent detectors, evaporative light scattering detector (ELSD),78 or even NMR79 as an online detector. These powerful detectors facilitate characterization of analytes during the separation of a wide variety of substrates in HPLC. 1.1.3 Quantitative Analysis Of the above-mentioned techniques, all of them can be used to determine the chemical composition of samples, i.e., for qualitative analysis. However, many of them can be also used for quantitative or semi-quantitative analysis, which provides absolute or relative numerical information of the amount of analyte (e.g., concentration). Weight and volume are both measurable amounts and can be easily accessed by a balance and a volumetric flask, respectively. They have classically been determined in this manner to quantify the amount of analyte present in a sample. Concentration is also a quantifiable value but requires both the amount (e.g., weight or mass) and volume (Eq. 1.2) in conventional approach. 𝐶𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑖𝑜𝑛 = 𝐴𝑚𝑜𝑢𝑛𝑡 𝑜𝑓 𝑠𝑜𝑙𝑢𝑡𝑒𝑇𝑜𝑡𝑎𝑙 𝑣𝑜𝑙𝑢𝑚𝑒 (Eq. 1.2) However, modern optical spectroscopies such as UV-Vis and IR allow for direct access to concentration information without needing to already know the amount of solute and total volume. In such spectroscopies, the absorbance of a substance (A) is proportional to the length of its optical path (l) and its concentration (C) (Eq. 1.3). This relationship is known as the Beer-Lambert law: 𝐴 = 𝜀𝑙𝐶 (Eq. 1.3) 12 In the Beer-Lambert law, (ε) is known as the molar absorption coefficient and is a sample dependent property, which describes how strongly the substance absorbs a given wavelength of light. Experimentally, the coefficient can be determined from the slope in a calibration curve which plots concentration (C) as the x-axis and the absorbance of a substance (A) as the y-axis. 1.1.3.1 Calibration Curve 1.1.3.1.1 Conventional Preparation of Calibration Curve A calibration curve is a linear regression between the quantity or concentration of an analyte and the instrument response. To make a calibration curve, standard solutions that contain known concentrations of analytes need to be prepared. In addition, to measure the background responses that may interfere with the analysis of the analyte, a blank solution that only contains the solvent and/or the sample matrix is also typically prepared. Through the calibration curve, several pieces of information can be extracted. First, the linear portion of a calibration curve is directly proportional to the quantity of analyte, and thus the slope of this linear part can be used to determine the concentration as per Eq 1.3. Second, the dynamic range, in which a calibration curve has a linear relationship between analyte quantity and instrument response, can be extracted and interpreted as the instrumental ability for quantitative analysis. Lastly, the nonlinear part at high concentrations usually indicates that detector saturation is not used for analyte quantitation.80 While multi-point calibration, which uses more than two different concentration samples, has less uncertainty, analytical chemists prefer using single-point calibration requiring less effort.81,82 Since the single-point calibration is generated by combining the single experimental point with a linear function with zero intercepts, it is important that the blank sample has almost zero signal intensity for the single-point calibration. 13 1.1.3.1.2 Standard Addition Instead of making individual known concentrations of standard solutions of the analytes in new vessels, the standard addition method involves the addition of a known quantity of analyte directly to an unknown sample to calibrate the instrument in a single experiment. The relationship between the signal (A) and the amount of analyte in solution (n) is expressed in Eq. 1.4 using the absorption coefficient (K) and the volume (V). 𝐴 = 𝐾𝑛𝑉 (Eq. 1.4) By transforming the Eq. 1.4 to Eq. 1.5, the absorption coefficient can be calculated using the known and obtained parameters. 𝐾 =𝛥𝐴𝑉𝛥𝑛=(𝐴𝑎𝑓𝑡𝑒𝑟 ×∙𝑉𝑎𝑓𝑡𝑒𝑟)−(𝐴𝑏𝑒𝑓𝑜𝑟𝑒 ×∙𝑉𝑏𝑒𝑓𝑜𝑟𝑒)𝑇ℎ𝑒 𝑘𝑛𝑜𝑤𝑛 𝑎𝑑𝑑𝑒𝑑 𝑎𝑚𝑜𝑢𝑛𝑡 (Eq. 1.5) Standard addition is especially important to consider when the sample composition is complex and has the potential to affect the analytical signal.83 In such cases, preparing individual samples using a combination of solvent and supplementary components can be extremely challenging to reproduce the same composition of the original sample. As a result, if the standard solution used for the calibration curve does not match the composition of the unknown sample, the calibration curve generated is not reliable.84 The standard addition method is especially useful for in situ reaction monitoring techniques or online time course analysis.85,86 The calibration curve of each component can be prepared by the addition of a known amount of the reaction starting materials, product, intermediate(s) potential side product(s) and/or by-product(s) in the same environment as the reaction. This would not require reaction sampling or offline analysis, as the in-situ reaction monitoring techniques and/or 14 online reaction sample system would immediately respond to a net increase reflecting the standard addition action. 1.1.3.2 Limitations and Considerations of Quantitative Analysis by Analytical Instrumentations 1.1.3.2.1 Beer-Lambert Law Limitations in Spectroscopy The Beer-Lambert Law describes the ideal absorption behavior of media containing relatively low analyte concentrations. However, at high concentrations the extent of solute-solvent interactions, solute-solute interactions, or hydrogen bonding can affect the analyte environment and its absorptivity.87 In other words, in concentrated solutions, the average distance between solute molecules can decrease to a level that they begin to influence each other in terms of their charge distributions and thus their ability to absorb a given wavelength of radiation. When this happens, deviations from the linear relationship between absorbance and concentration occur. This effect can be lessened by simple dilution of the sample. In off-line sampling (where a sample is taken and measured external to the reaction environment at a later time), dilution can be done manually, but this can be tedious and/or laborious work. However, recently developed automated sampling systems88 can perform the sampling and dilution/quenching in an automated fashion, greatly improving this approach (vide infra). Among the various instrumental analytical techniques, some techniques are accepted as quantitative tools which accurately calibrate the amount of analyte based on the obtained signal. In this section, the limitations to using mass spectrometry and NMR for quantitation are discussed. 1.1.3.2.2 Ion Suppression Effect in Mass Spectrometry 15 Mass spectrometry has been proven a powerful qualitative instrumental analytical technique due to its sensitivity to the analyte's molecular weight (MW). Therefore, mass spectrometry is often coupled with HPLC and GC spectroscopy. However, the use of mass spectrometry for quantitative purposes would require the consideration of various factors to achieve the quantification capability. The most important factor that affects this quantitative analytic capability is the ion suppression effect, which unpredictably changes the intensity of certain analytes under co-eluting compounds.89 Ion suppression is thought to result from the presence of less volatile compounds that can change the efficiency of droplet formation or sample evaporation, which in turn affects the amount of charged ions in the gas phase that ultimately reaches the detector.90 Furthermore, it has been shown that higher mass ions often suppress the signal of smaller molecules,91 and that more polar analytes are more easily suppressed than non-polar ones.92 1.1.3.2.3 Considerations for Quantitative NMR To use NMR spectroscopy as a quantitative methodology (qNMR), a series of parameters must be optimized before the data acquisition.93 For instance, data has to be acquired such that all resonances of interest are equally excited. While equal excitation is generally achieved with nuclei of a smaller chemical shift range (such as 1H), this must particularly be a consideration when measuring spectra of nuclei with a larger chemical shift range (such as 19F). Additionally, if signal-averaged data are acquired, sufficient time for relaxation is supplied between subsequent pulses. Typically, a minimum of five times the spin-lattice relaxation time (T1) of the resonance is required for this relaxation, where the T1 can be estimated using techniques such as the inversion-recovery method or Faster Longitudinal relaxation Investigated by Progression Saturation 16 (FLIPS).94 Lastly, the signal(s) used for quantification should be carefully chosen, ensuring no overlap with neighbouring resonances and that the resonance is not in exchange with any other species in the solution. 1.1.4 Reaction Monitoring 1.1.4.1 Importance of Reaction Monitoring When starting to study or develop a novel chemical transformation, analytics are needed to have an initial understanding of the reaction. These analytics are needed to determine which reaction parameters are suspected to be critical for the reaction outcomes. This understanding of the relationships between reaction variables (parameters) and the reaction outcomes can lead to the elucidation of reaction mechanism understanding, which in turn helps the development of new conditions, catalysts, and/or reagents for other desired transformations.95 As a result, the collection of analytical data for the reaction under study is crucial for chemistry research. Not only does this data have to be accurate and reproducible, but it also needs to provide as much information about the reaction as possible to facilitate mechanistic elucidation. This ensures that research can proceed as efficiently and accurately as possible. In traditional reaction analysis, a researcher usually begins by deciding on a reaction time, often based on a similar reaction scheme published by others or their own chemical intuition or past experiences. After a reaction has been allowed to occur under certain reaction conditions for this predefined period, a single end-point sample is then manipulated (workups, quench or dilution) and analyzed by an off-line instrumental method. This type of single-point approach does give some insight into the result of the reaction in terms of desired reaction product yield, by-products formed and/or side-products formation and reaction selectivity. At the same time, only conducting 17 a single-point analysis for a reaction can miss valuable information. This could include the kinetics of the reaction, which can then be further interpreted to gather reaction mechanistic understanding. Additionally, the observation of unstable and/or transient reaction components could be missed, which often involves reaction intermediate(s) that are essential for understanding the reaction mechanisms. Sampling the reaction repeatedly at a timed interval can provide a time-course reaction profile, indicating the behaviour of multiple species over the course of the reaction. This profile can shed light on what is occurring in the reaction flask in terms of the changes in starting material, intermediate, product and by-product/side-product concentrations as the reaction proceeds. While the classical single-point analysis can be described as providing merely a snapshot of the reaction, time-course reaction monitoring can be compared more closely to the full story of the reaction.96 After having time-course reaction monitoring trends in hand, reaction progress kinetic analysis (RPKA) can be applied to extract maximum kinetic information from a minimal number of reaction monitoring experiments.97 By comparing two reaction profiles with different concentrations of a single reagent, these “different excess” experiments enable the determination of the reaction order of each component, therefore providing insight into the reaction mechanism. RPKA is also known to be an invaluable diagnostic tool for the recognition of off-cycle equilibrium and catalyst inhibition/competitive reactions.98–101 1.1.4.2 Methods to Collect Reaction Monitoring Data: Manually, Automatically, and Instrumental Considerations 1.1.4.2.1 Manual Sampling vs. Automatic Sampling Typically, time-course data collection involves manual reaction sampling by withdrawing timed aliquots from the reaction mixture. These reaction aliquots are treated with a specified 18 method (e.g., quench, dilution, and derivatization) before they are transferred to a dedicated analytical instrument for offline analysis. Although this method can achieve many analyses, there are still several inherent disadvantages to this manual approach. First, random differences can occur when sampling a reaction, such as in the volume of aliquot withdrawn (and thus the amount of analyte analyzed). Additionally, reaction environments are not always homogeneous, and the presence (or lack) of bubbles, solids, or concentration gradients at different sampling times can affect sampling. This can even occur when sampling from different locations within a single flask, if for example solids are denser at the bottom or there are more bubbles closer to a stir bar at the center. All of these variations can lead to inconsistent concentration information for reaction components, which then leads to misunderstanding results and hypotheses. Secondly, one of the most challenging aspects of understanding chemical processes is the ability to measure a process without significant perturbation. A manual sampling of a reaction can risk exposure of the reaction environment to uncontrolled conditions such as moisture or oxygen, resulting in a higher and higher risk of affecting a reaction the more manual samples are desired to be obtained. Finally, manually taking timed aliquots for a single reaction requires a human operator to be physically beside the reaction and repeatedly take samples. For longer reactions or cases where rapid sampling is desired this can be extremely laborious and time-consuming. To fix the above-mentioned problems, the use of in situ measurements or ex situ reaction monitoring techniques with automated online reaction monitoring can be applied, taking samples and analyzing them at a defined time interval, specified by a user. Most importantly, these instruments take and analyze their samples in the exact same manner every time, which eliminates the potential for random sampling errors to occur. Furthermore, with the assistance of well-engineered hardware and devices, the act of sampling using these techniques can occur with little 19 to no perturbation to the reaction environment, affecting a reaction significantly less than with manual sampling methods. This is especially true for the in situ reaction monitoring technique, where a measurement is made in the reaction environment itself and no sample dilution, quenching, or derivatization needs to be performed as there is virtually no perturbation to the reaction environment. In this section, the different types of reaction monitoring techniques are discussed and classified as either in situ or ex situ analysis. A series of methods available on the market are then introduced. This list is by no means comprehensive as many other process analytical technologies (PATs) can also be applied for the purpose of reaction monitoring, but they serve as a general overview of the techniques commonly employed by chemists to monitor reactions. 1.1.4.2.2 In Situ vs. Ex Situ Reaction Monitoring Techniques For a real-time sensor that is applied to a reaction system, there are generally two options on how this sensor can be used: first, ex situ, where the sensor is located not in the reaction itself, but outside the reaction. In other words, ex situ methods require the sample to be physically transported to the sensor to be analyzed. This is often achieved using a flow-through external loop system. The flow-through system is commonly used in flow NMR applications.102–104 While capable of obtaining real-time measurements, the use of ex situ systems is generally considered at risk of introducing artifacts into the measurement due to the physical transportation of the sample altering mixing behaviour and reaction times.105 However, this artifact can be reduced if the loop-reaction volume difference is sufficiently large, which can be achieved by minimizing the volume of a sample contained inside the loop and maximizing the reactor volume. 20 In contrast, in situ techniques are those where the sensor is located physically inside the reactor. The clear advantage of using in situ techniques is keeping the reaction constant while sampling is still happening. To achieve in situ reaction monitoring, physically robust fiber optic-based sensors are usually deployed to allow a measurement to be made in a probe within the reaction environment and then detected by an instrument located outside the vessel. A typical example of an in situ technique is in situ IR spectroscopy. 1.1.4.3 Analytical Instruments for Reaction Monitoring 1.1.4.3.1 In Situ IR and Raman The improvement in computer technology associated with spectroscopy has led to the expansion of quantitative IR spectroscopy.106 To enable the IR technique to be used as an in situ reaction monitoring sensor, the light signal needs to be transferred from the reactor to the IR detector with no loss of light intensity and quality. To achieve this, an attenuated total reflection -Fourier transform infrared (ATR-FTIR) probe connected via an optical conduit or fiber-optic cable is usually employed. In the next step, a beam of infrared radiation passes through a crystal located at the tip of the probe and reflects off the internal surface of the crystal, which is in contact with the reaction solution.107 This reflected light carries the reaction solution information and goes back to the detector. 21 Figure 1.3. Illustration of total reflection -Fourier transform infrared ATR-FTIR is a powerful technique to collect time-course data because it is a type of non-destructive and easy-to-use method to implement, simply by inserting the probe into the reaction. The in situ IR is also capable of producing very dense data as it can collect IR spectrum data at very short time intervals: take the Mettler Toledo ReactIR as an example, which is intensely used in the Hein Lab, the sampling interval can be about 10 seconds. Furthermore, the use of different types of probe crystals (either silicon-based or diamond-based) makes the in situ IR applicable to a wide range of reaction matrixes. In situ IR has been applied to monitor a variety of reaction progress.108–112 This technique is particularly useful when the chemical species of interest have strong characteristic absorption in the IR frequency range, especially when functional group conversion is happening throughout the reaction’s progress. Likewise, an in situ Raman spectroscopy probe and instrument functions using similar principles as in situ IR. Raman is especially useful to track species which are IR inactive (usually contains polarizable bonds).113–115 22 1.1.4.3.2 Flow NMR Solution state NMR spectroscopy is one of the non-destructive, quantitative, and potentially most powerful structure elucidation tools for chemists. The simplest way to leverage NMR as a reaction monitoring technique is by taking multiple timed static NMR tube experiments. This is a method that can be categorized as a type of manual reaction monitoring experiment. Alternatively, time-course NMR experiments can also be performed in an automatic way, by installing a flow-through external loop system. However, quantitative analysis using flow NMR requires extra attention to be successful. Notably, elements such as flow cell geometry, the residence time of the analyte in the flow cell, and analyte pre-magnetization can all affect the quality of the result.102,116–118 Maschmeyer et al. reported that these issues could be circumvented by applying a stopped-flow fashion of the system.102 Besides the recent advantage of quantitative flow NMR technology, flow NMR systems are not widely used for reaction monitoring purposes. This may be because of the complexity of the system which requires special hardware to be installed, and the lack of available NMR instrumentation in each research facility. To this end, commercially available benchtop NMR systems are physically smaller spectrometers that are much more convenient to have in research laboratories. In addition, the purchase price and the maintenance cost are also significantly less for the benchtop NMR compared to the traditional high field NMR. 23 Figure 1.4. Illustration of the flow NMR system used by Maschmeyer et al. for quantitative real-time reaction monitoring 1.1.4.3.3 Online HPLC The previously discussed tools including in situ IR and flow NMR are powerful technologies in the field of reaction progress monitoring. However, they all potentially suffer from one fundamental limitation: the resolution of the spectrum can become challenging to elucidate when the reaction sample is highly complicated with many species. To circumvent this, it is better to couple a separation technique together with analytical sensors to get better quality data. This is essentially true for HPLC coupled with a variety of detectors. However, HPLC is usually made for offline sampling purposes, where samples are prepared by the analyst in a defined small vial by diluting a small quantity (usually less than 10 μL) of the original reaction solution with some solvent (MeOH or acetone is often used). After placing the prepared sample into the HPLC sample tray, an internally equipped sampling needle would withdraw several microliters of the diluted sample and deliver the sample to the column and then to the detector for analysis. In recent years, the classical offline method of sampling reactions has moved towards its online counterpart, in which sampling, delivery, and/or quenching are performed automatically 24 and are coupled with subsequent HPLC analysis.86,88 The efficiency on the sampling and the concomitant reproducibility makes HPLC become an even more powerful reaction monitoring technique.119 The Hein Lab is one of the leading research groups in the design of online sampling systems. The computer-controllable samplers, liquid handlers, multiport valves and high-pressure compatible pumps are used to build platforms,120–122 which can investigate many complicated catalytic organic transformations.123–125 1.1.4.3.4 In Situ Particle Analysis The EasyViewer (Mettler Toledo) is an in situ, probe-based imaging and particle size analysis tool.126 For the last few decades, industry-standard particle analysis has used focused beam reflectance measurement (FBRM). While FBRM uses a laser to directly measure particle size, the EasyViewer captures real-time high-resolution images of crystals and droplets as they exist in a process. iC Vision, EasyViewer corresponding software package, contains algorithms that analyze the acquired microscopic images. Through this analysis, the software can detect the phase boundary between particles and solvent, and therefore quantify solution turbidity, particle size, and particle shape. However, optimizing the brightness of the EasyViewer’s lasers and the image focus depth is critical to obtain sufficient contrast to successfully determine the particle boundary edges. A major benefit of this technique over FBRM is the acquisition of particle images. Not only are particle statistics reported by the software, but images can be analyzed by chemists (or additional advanced image analysis programs) to identify the presence of oils, the shapes/habits of crystals, and particle behaviour over time (such as aggregation or new phase development) that may not be easily understood from a purely statistics-based analysis. From this detailed image data, 25 important insights from the reaction including dissolution, nucleation, crystal growth and more can be understood to give a full picture of a reaction process. Figure 1.5. Illustration of the EasyViewer and captured images of a) oil droplet, b) primary nucleation of crystals, and c) grown crystals. 1.1.4.4 Limitations of Reaction Monitoring 1.1.4.4.1 Liquid/Liquid Heterogeneous Reaction Conditions Despite the importance of chemical analysis and monitoring, the application of this field is typically limited to ideal homogeneous conditions. However, many reactions performed in both academic research laboratories and industrial manufacturing are not simple homogeneous reactions. Instead, a variety of heterogeneous reactions are conducted in many fields.127–129 Roughly, heterogeneous reactions can be categorized into three types if the gaseous phase reactions are not included. The first category is liquid/liquid biphasic systems, which usually involve one organic phase and one aqueous phase; three phasic liquid state reactions exist but are rare. One of these types of reaction is the biphasic Suzuki-Miyaura cross coupling reaction where the inorganic base needs to be dissolved in an aqueous solution.130–132 For liquid/liquid biphasic reactions, reaction (a) (b) (c) 26 monitoring techniques such as in situ IR and flow NMR would experience issues. For in situ IR, which uses the ATR-FTIR technique for probing the reaction kinetics, there could be quantification considerations when probing liquid/liquid biphasic reactions. This is because the ATR-FTIR’s quantitative capability relies on the uniformity of the evanescent wave depth, which occurs at the contact surface of the sensor crystal and the reaction solution. If the reaction solution is homogeneous, the depth of the evanescent wave would be unchanged for every scan. Since the depth of the evanescent wave is essentially the length path term in Beer’s law, the signal intensity would only change if the concentration of the reaction component changes along with the reaction progresses in the homogeneous case. In contrast, in a heterogeneous case, the depth of the evanescent wave would vary as the IR radiation could reflect on either the organic or aqueous phases. This leads to uncertainty of the IR spectrum quantification for the reaction, making it challenging to represent reaction kinetic trends accurately. On the other hand, flow NMR also suffers when handling liquid/liquid heterogeneous reactions. This is because the NMR cannot lock/shim well when there are multiple phases present in the NMR flow cell. Besides the incapability of in situ IR and flow NMR when it comes to liquid/liquid heterogeneous solutions, online HPLC can also be problematic in dealing with this situation. Even though HPLC can inject both layers and then separate them with no problem, the consistency in terms of how much each layer gets injected into the instrument is questionable. In the online HPLC system setups, a needle or a probe with a sampling pocket is usually used to withdraw reaction samples; they work perfectly with homogeneous reactions. However, due to the difference in surface tension and compressibility between the aqueous layer and the organic layer, it is almost impossible to take a reproducible amount of both layers every single time. Besides the instrumental issues, the distribution of reaction components in each layer may also contain enormous amounts 27 of invaluable information about a biphasic reaction. This could include the distinct behavior of one species in different layers, such as more polar species favoring an aqueous layer; acid-base equilibria between phases governing reactivity; the importance of mass transfer between phases towards the overall reaction kinetics; and/or the concentration effect by solvent miscibility.124 To this end, a system that can analyze each layer separately and individually can solve the instrumental issues arising from in situ IR, flow NMR and online HPLC, by effectively monitoring each layer separately. Additionally, such a system can extract the invaluable phasic reaction information mentioned above. 1.1.4.4.2 Solid/Liquid Heterogeneous Reaction Conditions Other than the liquid/liquid heterogeneous case, the solid/liquid heterogeneous reaction is another major type of heterogeneous reaction frequently applied in both academic research and manufacturing. The solid part in a solid/liquid heterogeneous reaction is usually inorganic salts that cannot dissolve in the organic solvent.133 In industry, many reactions are conducted in a solid/liquid manner to keep starting materials at their highest concentration, thus pushing the reaction to finish.134 Some coupling reactions also produce large size conjugated molecules or polymers as products that can be precipitated out from the solvent as they form due to their low solubility. In such cases, in situ IR could be a good choice to monitor only the solution phase selectively, because it is largely insensitive toward solid components in a heterogeneous system. However, a solid presence in the reaction is by no means a good sign for either flow NMR or online HPLC. For flow NMR, the solid parts in the sample tube would again interfere with the data acquisition and produce low-quality data during magnetization and analysis. For both flow NMR and online HPLC, the solid presented in the reaction could potentially be an enormous issue 28 for tube clogging. Since both of these systems use thin tubing for samples to be delivered to the analytical device, either an external flow-through system or liquid handling valves with sample loops. This could happen quite frequently if the reaction system is heated, because once the reaction solution leaves the original vessel, its temperature drops, and thus the solubility of all the reaction components decreases, where they would have the potential to crystallize out from the solution in the sampling tubes and clog the sampling device. In the solid/liquid heterogeneous situation, applying a filter on the tip of the sampling tube could be a solution to the aforementioned clogging issue. However, filter tips which usually use porous material would be a great base for crystals to grow and accumulate, which can also cause clogging. Besides, the quantitative information of the solid part is also useful information for understanding the reaction. For example, if the reaction components are the solid parts in a heterogeneous reaction system, blocking the solid part for the ease of sampling to be successful would result in an unchanged trend for each reaction component in the solution phase, because their concentration would always be the saturation concentration in this solvent. This could cease further analysis on reaction kinetics. A better solution would be to take both liquid and solid portions of the reaction simultaneously. Instead of directly delivering the heterogeneous sample into the analytical instrument, another device could be added in the middle of the sampling loop, in order to have an “external dissolving center”, where it brings in another type or portion of solvent with a stirring function to dissolve the undissolved parts presented in the original reaction. 1.1.4.4.3 Resolution Limit for Complicated Reaction Monitoring Owing to the nature of most complex chemical reactions, many reaction components can be presented at the same time of a reaction mixture. Furthermore, many of the reaction components 29 may share similar chemical structures since they could be the product or substrate of each other through some chemical transformations. This means they would display closely resembled signals in the analytical instrument. In this case, the multi-overlapping peaks can be extremely difficult to analyze. For traditional organic reactions or catalytic cycles, reaction components including the starting materials, products, by-products and/or side-products are relatively easily predicted with an analyst's chemical intuition. After creating a hypothesis for the chemical structure of each individual species giving a signal shown on the spectrum, it is possible to confirm their identity by using orthogonal analytical devices. However, for novel reactions with little to no pre-established data, assigning each peak from the spectrum to chemical species can be challenging. This can be very true for nanocluster synthesis reactions. These types of unique materials are still prepared using a black box approach, where in situ reduction gives high energy metal sites that rapidly aggregate to higher order aggregates and eventually nanoclusters. The problem is that the number of different aggregates formed in a nanocluster synthesis reaction can be enormous. Monitoring nanocluster formation, which contains all these unknown structures of the nanoclusters using NMR or IR can therefore be very challenging. To this end, when studying complicated systems with a lack of fundamental understanding, first separating the mixture before analysis can dramatically decrease the difficulty. HPLC as a combined technique with both separation and analysis capability is ideal for such a situation. An example of using HPLC as a powerful tool to monitor the complex gold nanocluster synthesis reaction is presented in the later chapter. 1.2 Overview of Chapters Despite the importance of chemical analysis and reaction monitoring, the application is typically limited to ideal homogeneous conditions. Therefore, the first objective of this thesis is to 30 develop new analytical methodologies to monitor challenging conditions by existing PATs. In chapters 2 and 3, I developed new automated sampling platforms for solid/liquid and liquid/liquid heterogeneous mixtures. Nanocluster synthesis is also out of the ideal homogeneous conditions due to its complicated mixture, and the monitoring by existing PATs remains challenging. In chapter 4, I demonstrated a new methodology to use LCMS for nanocluster synthesis. The second objective of this thesis is the application of the newly developed analytical methodologies. To demonstrate the abilities, I investigated three different reactions. Chapter 2 presents tetrabenazine (TBZ) synthesis involving a slurry formation which contains both solid and liquid. Chapter 3 first presents partition coefficient changes of various boronic acids by base addition. Liquid/liquid biphasic Suzuki Miyaura Coupling (SMC) reaction was also monitored using a new sampling technique. Chapter 4 presents NHC-protected Au13 and Au24 nanoclusters (NCs) synthesis. The newly proposed analytical methodologies using LCMS exploited the meaningful information from complicated polydisperse AuNC mixtures. 31 Chapter 2: Solid/Liquid Heterogeneous Reaction: In-Depth Reaction Profile of The Synthesis of Tetrabenazine 2.1 Introduction Solid-liquid heterogeneous conditions are extensively used in the chemical and pharmaceutical industries,135 particularly in process chemical scale up. These conditions can offer higher reaction rates, afford significant solvent reductions, and in turn deliver improvements to process mass intensity. Slurry batches are also readily telescoped into isolation and purification processes by leveraging crystallization.136 Lastly, additional benefits may be realized when the targeted product has incompatible solubility with the reaction mixture. In this case, crystallization enables the product to be protected through phase segregation. For these reasons, slurry process batch reactions are among the fastest growing segments of chemical manufacturing and represent a correspondingly significant set of challenges facing industrial discovery and process chemistry. As new clinical candidates move forward, refining and optimizing a fit-to-purpose synthetic scheme requires data-intensive reaction information. Optimization relies on a detailed understanding of how reaction outcomes (e.g., yield, selectivity, time) are impacted by operational parameters (e.g., reagent concentration, temperature, pH).135,137 Since the FDA published its process analytical technology (PAT) guidelines in 2004, real-time reaction monitoring has been highlighted as a means of providing data-rich reaction information for efficient experimental design.138 There is also further guidance that in order to adopt Quality by Design manufacturing practices, data-rich experimentation should be every institution's goal. 32 Moreover, proving that an optimized synthetic process is robust and reproducible is paramount for filing and regulatory approval. However, most conventional real-time reaction analytical tools, such as NMR,139 IR,111,140,141 Raman,142,143 and mass spectrometry144 face two major obstacles to implementation with solid-liquid reaction slurries. First, these techniques cannot easily separate mixtures of reaction components such as starting materials, intermediates, products and byproducts. Second, conventional tools are designed to study well-behaved systems that tend to be homogenous, operate at relatively low temperatures and concentrations, and involve stable species. Therefore, very limited spectroscopic techniques are capable of understanding component compositions of solid-liquid heterogeneous reactions.145 HPLC analysis is an appealing technique due to its excellent separation capabilities, data richness, and abundance of detection methods (e.g. UV, MSD, and ELSD).146 Adapting this gold-standard analytical method to monitor solid-liquid reaction slurries therefore presents a significant opportunity. To access this potential, the Hein Lab has previously reported the use of HPLC platforms to monitor heterogeneous reactions.127 In our first iteration, the use of a Mettler-Toledo EasySampler and a liquid handling robot enabled automated sampling, but HPLC analysis was decoupled from the reaction and performed offline to allow for slurry dissolution. While this approach avoided the manual labor endemic to off-line analysis, the intrinsic time delay between sampling and analysis remained at play. This time delay provides an opportunity for post-sampling reactions and/or the decay of short-lived intermediates, which can compromise data integrity.147,148 More recently, the Hein Lab developed an online HPLC platform to delineate the reaction profiles of the dissolved components in a heterogeneous Suzuki reaction containing poorly 33 dissolved CsCO3 salt.77 Monitoring both the solid and liquid components in this system, however, was hindered by two major issues: compounds with low solubility risked line clogging, and the homogeneous and heterogeneous components were found to have different delivery kinetics during sampling. I therefore identified the need for a sampling method to efficiently dissolve heterogeneous components prior to analysis. In this chapter, I am reporting a new robust online HPLC platform equipped with a dynamic mixer for heterogeneous reaction monitoring. 2.2 Research Target To test our platform, I chose to monitor the synthesis of tetrabenazine (TBZ, (rac)-2.1, Figure 2.1). TBZ is an active pharmaceutical ingredient (API) prescribed for the management of neuromuscular symptoms arising from Huntington’s disease.149 The TBZ derivative, Valbenazine (VBZ, 2, Figure 1), received FDA approval in 2017 and is marketed as Ingrezza by the collaborator, Neurocrine Biosciences Inc., San Diego, CA, to treat tardive dyskinesia, a similar neuromuscular disorder.150,151 VBZ is a particularly potent compound because it is metabolized in vivo to a single, highly bio-active stereoisomer (+)-α-dihydrotetrabenazine ((2R,3R,11bR)-HTBZ), while the metabolic pathway of TBZ is not stereoselective.152,153 These factors have incited interest in optimizing the synthesis of TBZ as a route to VBZ. Figure 2.1. Structures of (±)-Tetrabenazine and Valbenazine. NMeOMeOOHNMeOMeOOHOH2N(±)-Tetrabenazine (TBZ) Valbenazine (VBZ)(rac)-2.1 2.2NMeOMeOOHH(+)-α-dihydrotetrabenazine((2R,3R,11bR)-HTBZ)34 There are two major synthetic routes to rac TBZ (Scheme 2.1). TBZ was firstly synthesized by Hoffmann-La-Roche in the 1950s via the cyclization of tetrahydro-isoquinoline derivatives (Figure 2.1.A).154 The three step synthesis started from the Mannich condensation, in which the iminium formation between formaldehyde 2.4 and tetrahydro-isoquinoline derivatives 2.3 was followed by the addition of nucleophilic diester 2.5 to form 2.6. Intra molecular Dieckmann condensation cyclized the ring to form diester intermediate 2.7. Lastly, the decarboxylation step eliminated the ester group to afford the core structure of TBZ 2.8. In 1963, Openshaw et al. reported another concise synthesis method via the annulation reaction between 3,4-dihydro-isoquinoline derivatives and β-trimethyl amino ketone (Figure 2.1.B).155 Under these conditions, the intramolecular bond formation and cyclization all occurred in a one-pot multistep manner. Therefore, isolation and purification of intermediates were eliminated. Due to its simplicity, the latter method has been developed and employed by Neurocrine to access the important synthetic intermediate for VBZ. 35 Scheme 2.1. Reported synthesis methodologies for the core structure of TBZ. Through modification of Openshaw’s synthesis method, Neurocrine synthesized TBZ by formal annulation between 3,4-dihydro-isoquinoline 2.9 HCl salt and β-amino ketone 2.12 (Scheme 2.2).155 The optimized reaction conditions include substituting the original ethanol solvent for 30% water in isopropyl alcohol (IPA; v/v), allowing favorable reaction kinetics and high diastereoselective to be achieved while reducing the reaction temperature from reflux to 45 ºC. While this modification furnished enhanced yield, reduced byproducts and overall advantageous process conditions, TBZ exhibits remarkably low solubility (<0.13 M) yielding a heterogeneous reaction mixture incompatible with conventional reaction monitoring techniques. Several mechanisms have been proposed for this formal 2+4 annulation reaction (Scheme 2.2.a), including a Mannich-aza-Michael pathway and an aza-Michael-Mannich pathway as shown in Scheme 2.2.b (highlighted in blue/red and green respectively). Elimination from the β-amino ketone to generate enone 2.14 and dimethylamine 2.15 may precede a concerted 4+2 NHCOOR2R1OR1OH HOCOOMeCOOMeR2+ +NR2OOCR1OR1OCOOMeR3COOMeMannichcondensationDieckmanncondensationNR1OR1OOR1OOCCOOMeR3DecarboxylationNR1OR1OOR3(A) Hoffmann-La-Roche method(B) Openshaw methodOR5Me2NNMeOMeO Alcohol, refluxNMeOMeOOR4R4+H2.3 2.4 2.5 2.62.7 2.82.9 2.10 (rac)-2.1136 cycloaddition (black pathway, Scheme 2.2.b) However, despite the industrial-scale production of TBZ and the benefits of understanding its reaction mechanism to optimize synthetic procedures, a comprehensive mechanistic study has not been reported to date. Scheme 2.2. (a) Original synthetic procedure for (±)-TBZ (b) potential mechanistic pathways to access (±)-TBZ. Herein, I present mechanistic insights into the synthesis of TBZ under solid-liquid slurry conditions. These insights were gained by combining online HPLC reaction monitoring with an automated sampling platform. Though online HPLC provides access to reaction composition data in heterogeneous mixtures, it provides no data on two other aspects of the slurry reaction. Firstly, since Michael additions are typically catalyzed by acids or bases, pH could play an 37 important role in this reaction. Additionally, online HPLC involves heterogeneous component dissolution by diluent solvent, so real-time crystal information during the reaction is not obtained (e.g., crystal shape, size, nucleation). Therefore, I applied Mettler-Toledo’s pH probe and EasyViewer to complement our compositional data obtained via HPLC to obtain a comprehensive understanding of the TBZ synthesis mechanism. 2.3 Results and Discussion 2.3.1 Development of Online HPLC for Slurries Our initial sampling platform (Figure 2.2) was based on modified hardware adapted from a system previously reported for monitoring a heterogeneous Suzuki reaction.77 Using this device, a slurry aliquot is obtained from the reaction vessel and delivered to an HPLC injection loop. Critically, the new system incorporates an inline-dynamic mixer (Akta M-925 mixing cartridge, 0.6 mL) between the reaction sampler and injection valve, which acts to both quench and dilute the sample in preparation for HPLC analysis. Further, the dynamic mixer serves to homogenize the heterogeneous slurry, preventing line clogging while ensuring accurate analysis of all reaction components. A comparison of the capability of the two setups with or without dynamic mixer was visualized by generating TBZ mixture calibration curves (Figure 2.3). The dynamic mixer installation allowed for generation of a linear calibration curve of the slurry TBZ mixture without the clog. 38 Figure 2.2. Schematic diagram of automated sampling platform used for reaction monitoring. Figure 2.3. Calibration curves of TBZ generated using sampling platforms with (a) or without (b) a dynamic mixer. TBZ precipitates at concentrations above 0.13 M in a solution of 30% water in isopropyl alcohol at 45 ºC. y = 4565.1x + 51.832R² = 0.99970200040006000020004000600080001000012000140000 0.2 0.4 0.6 0.8Peak area (with using dynamic mixer)Peak area (without using dynamic mixer)[TBZ] (M)Solubility(b) Without dynamic mixer (not linear)(a) With dynamic mixerHeterogeneous39 However, when I tested this system to sample a slurry mixture consisting of isoquinoline 2.9 as a homogeneous component and TBZ as a heterogeneous component, I observed different delivery kinetics (Figure 2.4). This indicated that the solid component passed through the dynamic mixer before the dissolution to homogenize the sample. Figure 2.4. Delivery kinetics of heterogeneous TBZ and homogeneous isoquinoline using the new sampling platform coupled with a dynamic mixer. Therefore, a wait time is required to achieve a complete dissolution after pushing a certain volume (mixer volume) to deliver the heterogeneous sample aliquot into the dynamic mixer. To this end, I increased the amount of mixer volume followed by a 30 second wait time. Since the measured volume between the EasySampler pocket to dynamic mixer is 0.225 mL, I observed that less than 0.2 mL mixer volume was not enough to obtain the same delivery kinetic both of homogeneous and heterogeneous components. In contrast, using 0.4 mL as the mixer volume fixed this inconsistency and the two phases followed the same delivery kinetics after 0.6 mL dilution volume (Figure 2.5, the delivery kinetics with different mixer volume was summarized in section 2.11). 40 Figure 2.5. Delivery kinetics of heterogeneous TBZ and homogeneous isoquinoline using 0.4 mL mixer volume in the new sampling platform coupled with a dynamic mixer. 2.3.2 Standard Addition After establishing the general procedure for the collection and injection of samples for a heterogeneous reaction into the HPLC, the only thing missing is the conversion of peak area into concentration via Beer’s law. In most cases, pre-calibration of all the reaction components were needed to make quantitative measurements (offline calibration curve). This requires multiple data points of concentration vs. signal to acquire the slope. Instead, I took advantage of our in-situ reaction monitoring technique and used standard addition85 as an internal calibration method to transform the signal (peak area) into concentrations (section 2.13). However, the standard addition method requires accurate reaction volume measurements. Specifically, the volume changes due to the addition of solids were ambiguous. To this end, I conducted experiments to test the volume changes of the solid reagents (2.9 and NaI) of this reaction and TBZ (Figure 2.6). The slopes of these trends represent the reciprocal of the density of each chemical. As expected, NaI has the lowest slope as its mass density was the highest, while TBZ and 2.9 have higher slopes as organic compounds. The trends of these chemicals are linear before and after 41 their solubility limits, allowing for the calibrating of reaction volume using these slopes. Notably, the solid dose can significantly change the total volume of the reaction. Under the condition of this reaction, the total volume increases by 12.7% due to the solid dose of isoquinoline and NaI. Taking these considerations into account and using the measured volume calibrations (Figure 2.6), the standard addition method enabled accurate calibration curve preparation. These curves converted our raw signal vs time data to concentration vs time trends for later described reaction monitoring. Figure 2.6. Relationship of volume changes against solid dose of TBZ, isoquinoline 2.9 and NaI in a solution of 30% water in isopropyl alcohol at room temperature. 2.3.3 Reaction Monitoring First, I monitored the reaction under previously identified conditions, which involved reacting isoquinoline salt 2.9 with β-amino ketone 2.14 using NaI in iPrOH/H2O (Figure 2.7). Reaction monitoring by online HPLC revealed three new components; the major product TBZ, (rac)-2.1, the minor product diastereomers 2.22, and intermediate enone 2.14. The presence of 42 enone 2.14 as a steady-state intermediate conclusively demonstrates that the reaction is initiated via elimination of dimethyl amine (DMA, 2.15), as opposed to direct C-C bond formation via the Mannich-like coupling involving a substrate enolate (blue pathway, Scheme 2.2). Moreover, the relatively high concentration of enone 2.14 (~0.2 M) suggests that the elimination is rapid and not the rate-determining step. Figure 2.7. Reaction profile under initial conditions. Reaction conditions: [2.9•HCl] = 0.64 M, [2.12] = 0.8 M, [NaI] = 0.25 M in a solution of 30% water in isopropyl alcohol at 45 ºC. The productive intermediacy of enone 2.14 was confirmed by repeating synthesis of TBZ, but replacing β-amino ketone 2.12 with enone 2.14 and DMA 2.15 (Figure 2.8). Interestingly, the reaction profile and rate of TBZ formation closely parallels the optimized 5.06.07.08.09.010.000.20.40.60.80 10 20 30 40pHComponent (M)Reaction TIme (hr)IsoquinolineEnoneTBZTBZ diastereomersOEnone, 2.14pH43 conditions initiated with β-amino ketone 2.12 conditions. This equivalence in reaction rates implies that enone 2.14 exerts no kinetic driving force on the overall reaction cascade and could be classified as possessing a zeroth order in the overall reaction. This conclusion is borne out due to identical rates of TBZ generation over the first 10 hrs, despite the two reactions having dramatically different concentrations of the enone 2.14 within this time regime. Figure 2.8. Reaction profile substituting β-amino ketone 2.12 with enone 2.14 and DMA 2.15. Reaction conditions: [2.9•HCl] = 0.64 M, [2.14] = 0.8 M, [2.15] = 0.8 M, [NaI] = 0.25 M in a solution of 30% water in isopropyl alcohol at 45 ºC. To unambiguously confirm the reaction order for enone 2.14, its initial concentration was varied. Reducing [2.14]0 to 0.4 M from 0.8 M resulted in a concomitant reduction in the rate of 5.06.07.08.09.010.000.20.40.60.80 5 10 15 20pHComponent (M)Reaction Time (hr)IsoquinolineEnoneTBZTBZ diastereomerspH44 product formation (Figure 2.9). This suggests that enone 2.14 has a positive order in this reaction, but there are notable deviations from ideal first-order behavior. In particular, the initial rate of reaction is identical from T = 0 - 1.5 hrs, then deviates sharply after this time point, indicating the initial concentration of enone does exert a significant role in the observed rate of reaction and is thus coupled to the rate-limiting step, but that other factors are still at play. The observation of this complex behavior spurred me to re-examine our initial reaction profiles from Figure 2.7 and 2.8. While the rates of product formation were nearly identical, I noted that the pH vs. time trends between reaction 1, (Figure 2.7, with β-amino ketone 2.12) and reaction 2 (Figure 2.8, with enone 2.14 and DMA 2.15) showed significant differences. While the pH increased from 7 to 8 when the β-amino ketone 2.12 was utilized, a decreasing pH trend, from 9 to 8, was observed when the reaction was performed with enone 2.14 and DMA 2.15. This latter pH trend, dropping from 9 to ~8, was also observed when the initial concentration of enone 2.14 was decreased to 0.4 M. Taken together these observations suggest that the reaction displayed a positive kinetic order with respect to enone 2.14, but that the rate or reaction is suppressed at high pH. This antagonistic behavior between enone 2.14 and pH is responsible for the fortuitous similarity in reaction profile for the two experiments (Figure 2.8). This hypothesis spurred me to modify reaction pH by reducing the initial concentration of DMA 2.15 to 0.4 M, while setting [2.14]0 at 0.8 M. In line with our expectations, the initial pH of the reaction dropped to ~7 and displayed a similar decrease in pH over the course of the reaction, resulting in a solution with pH at ~5.5 at the reaction’s end. More importantly, this modification also led to a five-fold increase in the reaction rate over the initial test conditions (Figure 2.9). Further investigation revealed that an initial pH of ~7 was ideal. Removing DMA 45 2.15 entirely, which gave a solution at an initial pH of ~3.3, nearly arrested the formation of TBZ entirely (Figure 2.9). Figure 2.9. TBZ formation trends using different initial concentrations of enone 2.14 and DMA 2.15. Reaction conditions: [2.9•HCl] = 0.64 M, [2.14] = 0.8 or 0.4 M, [2.15] =0.8 or 0.4 M, [NaI] 0.25 M in a solution of 30% water in isopropyl alcohol at 45 ºC. While executing the reaction without added DMA 2.15 did not produce an appreciable quantity of TBZ, a new intermediate was observed. After isolation and characterization, this species was confirmed to be iminium 2.23 (Scheme 2.3), which is likely formed via acid-catalyzed aza-Michael addition between isoquinoline 2.9 and enone 2.14. 00.20.40.60 5 10 15 20[TBZ] (M)Reacition Time (hr)[2.14]0 = 0.8M [2.15]0 = 0.4M pHintial = 7[2.14]0 = 0.8M [2.15]0 = 0.8M pHintial = 9[2.14]0 = 0.4 M [2.15]0 = 0.8 M pHintial = 9[2.14]0 = 0.8 M [2.15]0 = 0 M pHintial = 3.346 Scheme 2.3. Formation of iminium intermediate 2.23. After acquiring an authentic sample of this intermediate, I was able to confirm that iminium 2.23 is detectable at low concentrations in all reactions. Iminium 2.23 is the keto tautomer of enol 2.16 and 2.19. Therefore, this data confirms that the synthesis of TBZ likely proceeds via sequential aza-Michael addition, followed by annulation involving the corresponding enol or enolate (green pathway, Scheme 2.2). To investigate the final cyclization step of iminium 2.23 to TBZ, the isolated iminium 2.23 was subjected to three different conditions (Figure 2.10): (i) no addition of amine; (ii) addition of 0.6 equivalents of DMA; and (iii) addition of 0.6 equivalent of N,N-diisopropylethylamine (DIPEA). In the absence of amine, the rate of TBZ formation was significantly slow. In contrast, the addition of either dimethyl amine or DIPEA resulted in a rapid formation of TBZ, approximately 80% conversion by 0.6 equivalent of amine. Although DMA and DIPEA exhibit similar basicity, the different rates of TBZ formation suggest that the reaction can proceed either through a slow base-catalyzed route (with DIPEA) or a fast enamine intermediate route (with DMA). While the base-catalyzed route is compatible with either a secondary or tertiary amine, the enamine intermediate can only be formed in the presence of a secondary amine. Since the isolated conditions for iminium intermediate 2.23 was very acidic conditions (pH = 3.3), it is concluded that the final cyclization step is only accelerated by basic conditions. 47 Figure 2.10. TBZ formation trends from iminium intermediate 2.23 under three different conditions. Reaction conditions: [2.23] = 0.12 M, [Amine] = 0.072 M or 0 M in a solution of 30% water in isopropyl alcohol at 45 ºC. According to the fact that TBZ formation was accelerated with decreasing initial amine concentration from 0.8 M to 0.4 M (Figure 2.9), this result suggests that the final cyclization step is not the rate determining step as decreasing the initial amine concentration would slow down product formation if this were the case. Therefore, I propose that the rate determining step of the TBZ 2+4 annulation is instead the aza-Michael addition. NMeOMeOOi-Bu2.23IPA / water45 °CAmine+(rac)-2.1NMeOMeOOi-BuH0.12 M48 2.3.4 Effect of pH on the Michael Addition The optimal pH for this reaction was found to be around 7, as the reaction rate declined when shifting the pH In either direction. The concept of an optimal pH range is frequently seen in enzymatic chemistry, in which multiple amino acid residue with different pKa value played an important role for the catalytic system.156–158 This suggests that the rate determining step (the aza-Michael addition) requires both the deprotonation of a nucleophile (i.e. the isoquinoline HCl salt, pKa 5.8) as well as the protonation of an electrophile (i.e. the enone 2.14) or of a general acid. Since the conjugated acid form of the enone 2.14 is known to have a very low pKa (around -2), it is unlikely that it will be protonated at the optimal pH of 7. These data seem to suggest that the aza-Michael addition step is catalyzed by some general acid (HA) with a pKa higher than 7 (Figure 2.11). Balancing the protonation of the general acid with the deprotonation of the nucleophile (isoquinoline) therefore leads to the observed optimal pH of 7 (modeled in Figure 2.11, with pKa of HA being 8.5). This modeled behavior closely fits the observed rates for various pH’s tested. 49 Figure 2.11. The proposed trimolecular transition structure and modelled pH profile: Initial rate, free isoquinoline ratio and free HA ratio were plotted. The initial rate was calculated by rate = k’*(Ka1/(Ka1+[H]+))*([H+]/(Ka2+[H]+)). When I applied pKa1 = 5.8 for the conjugate acid of isoquinoline and pKa2 = 8.5 for HA, the modelled pH profile fit the experimental data well. The rate equation for the aza-Michael addition can therefore be expressed as: Rate=k1[enone 2.14][isoquinoline 2.9][HA] (Eq 2.1) However, this equation shows no immediate relation to the reaction pH nor the pKa of any species. To support our proposed mechanism, a derived rate law including information in terms of pH, pKa of isoquinoline and pKa of HA is therefore necessary. This can be achieved by NMeOMeOi-BuOHANMeOMeOOHi-Bumodeled pKa1 = 5.8modeledpKa2 = 8.50.01.02.00.00.20.40.60.81.02.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0Isoquinolineor HARatio Initial Rate (mM/s)pHexperimental value50 assuming the two major acid-base processes involving the conjugate acid of isoquinoline 2.9 (2.9•H+) and HA are in quasi-equilibrium with one another, and thus I can use their Ka’s: 𝐾𝑎1 =[𝟐.𝟗][𝐻+][𝟐.𝟗 •𝐻+] (Eq 2.2) 𝐾𝑎2 =[𝐴−][𝐻+][𝐻𝐴] (Eq 2.3) The conservation of mass for both isoquinoline and general acid provide their mass balance equations: [𝟐. 𝟗]𝑡𝑜𝑡𝑎𝑙 = [𝟐. 𝟗] + [𝟐. 𝟗 • 𝐻+] (Eq 2.4) [𝐴]𝑡𝑜𝑡𝑎𝑙 = [𝐻𝐴] + [𝐴−] (Eq 2.5) Combining the definitions for the Ka’s with the conservation law results in the following expressions: [𝟐. 𝟗] = [𝟐.𝟗]𝑡𝑜𝑡𝑎𝑙 𝐾𝑎1 𝐾𝑎1+ [𝐻+] (Eq 2.6) [𝐻𝐴] = [𝐴]𝑡𝑜𝑡𝑎𝑙 [𝐻+]𝐾𝑎2+ [𝐻+] (Eq 2.7) Finally, combining these equations (Eq 2.6, 2.7) with the reaction rate law (Eq 2.1) allows for the rate to be expressed strictly in terms of the pH and pKa of species present: 51 𝑟𝑎𝑡𝑒 = 𝑘1 [𝟐. 𝟏𝟒] [𝟐.𝟗]𝑡𝑜𝑡𝑎𝑙 𝐾𝑎1 𝐾𝑎1+ [𝐻+] ∙ [𝐴]𝑡𝑜𝑡𝑎𝑙 [𝐻+]𝐾𝑎2+ [𝐻+] (Eq 2.8) 𝑟𝑎𝑡𝑒 = 𝑘1 [𝟐. 𝟏𝟒][𝟐. 𝟗]𝑡𝑜𝑡𝑎𝑙 [𝐴]𝑡𝑜𝑡𝑎𝑙 𝐾𝑎1 𝐾𝑎1 + [𝐻+] ∙ [𝐻+]𝐾𝑎2 + [𝐻+] = 𝑘′ 𝐾𝑎1 𝐾𝑎1+ [𝐻+] ∙ [𝐻+]𝐾𝑎2+ [𝐻+] (Eq 2.9) This allowed for modeling the reaction rate based on the solution pH and pKa of the nucleophile and general acid. This model (Figure 2.11) showed excellent agreement with our observed reaction rates at various pH’s, strongly supporting our proposed mechanism. Furthermore, if the reaction occurs at a very low pH, [H+] >> Ka1 and Ka2 so equation 2.9 simplifies into a more succinct rate law: 𝑟𝑎𝑡𝑒 = 𝑘′ 𝐾𝑎1 [𝐻+] (Eq 2.10) log 𝑟𝑎𝑡𝑒𝑙𝑜𝑤 𝑝𝐻 = log 𝑘′ − 𝑝𝐾𝑎1 + 𝑝𝐻 (Eq 2.11) Similarly, if the reaction occurs at a very high pH, [H+] << Ka1 and Ka2 and thus an alternate simplified equation is obtained: 𝑟𝑎𝑡𝑒 = 𝑘′ [𝐻+] 𝐾𝑎2 (Eq 2.12) log 𝑟𝑎𝑡𝑒ℎ𝑖𝑔ℎ 𝑝𝐻 = log 𝑘′ + 𝑝𝐾𝑎2 − 𝑝𝐻 (Eq 2.13) This hypothesis can explain the reaction profiles. When pH is high (around 9), most of the general acid HA are deprotonated. It would slow down the aza-Michael addition. On the 52 other hand, when pH is low (approx. 3.3), the isoquinoline 2.9 is fully protonated. It would impede the ability of the isoquinoline 2.9 to nucleophilic attack the enone 2.14. 2.3.5 Secondary vs. Tertiary Amine Secondary amines, such as dimethylamine 2.15, can catalyze the reaction as either a simple base catalyst or an organocatalyst through enamine or iminium chemistry. To investigate the catalytic manner, I also tried N,N-diisopropylethylamine (DIPEA) as a tertiary amine both in 0.8 M and 0.4 M conditions (Figure 2.12). 53 Figure 2.12. (a) TBZ formation and (b) pH trends using different initial amine concentrations with DMA 2.15 and DIPEA. Reaction conditions: [2.9•HCl] = 0.64 M, [2.14] = 0.8 or 0.4 M, [Amine] =0.8 or 0.4 M, [NaI] 0.25 M in a solution of 30% water in isopropyl alcohol at 45 ºC. (a) (b) 54 Interestingly, the observed TBZ formation rate was significantly lower with the 0.8 M tertiary amine, suggesting that a secondary amine accelerates the reaction through iminium chemistry (Scheme 2.4). On the contrary, with 0.4 M amine, the TBZ formation trend and pH profile with DIPEA were identical to the ones with dimethyl amine. This implied that the Michael addition is simply catalyzed by protonation rather than iminium formation in lower pH. Scheme 2.4. Proposed reaction acceleration mechanism under different amine concentrations with DMA 2.15 and DIPEA. Crystallization While online HPLC demonstrated the capability of both heterogeneous and homogeneous component profiles, EasyViewer,126 an in-situ, probe-based imaging microscope, provided a method to measure the physical properties of reaction mixtures, such as dissolution, primary crystallization, and crystal growth. I found in the EasyViewer images that the primary crystallization occurred when the TBZ concentration reached approximately 0.25 M. Moreover, I found that there was a relationship between the crystallization and TBZ ratio over the diastereomers 2.22 (Figure 2.13). This ratio could be affected by kinetic control of the Mannich i-BuOMe2HNi-BuO2.14NHMe2Fast0.4 M DMA0.4 M DIPEA0.8 M DIPEAProtonationi-BuOHAza-Michael additionNMeOMeO2.9 NMeOMeOOHi-Bu0.8M DMAIminium formationi-BuNMe2Aza-Michael additionNMeOMeONMe2i-BuNMeOMeO2.9PdtRate-Determining-Step+2.1555 cyclization step, epimerization between TBZ and TBZ diastereomers 2.22, and crystallization of TBZ (Scheme 2.5). Figure 2.13. Trends of TBZ ratio over TBZ and TBZ diastereomers under different amine concentrations with DMA or DIPEA same as conditions in Figure 7. 56 Scheme 2.5. Proposed kinetic controlled Mannich cyclization step via chair like transition state and thermodynamic epimerization mechanisms. The initial ratio indicated that the kinetic control of the Mannich reaction generated TBZ preferably. This was likely due to the 1,3-diaxial interaction of the isobutyl group presented in the assumed transition state to form the diastereomers 2.22. The data showed that all reactions had a 96% initial ratio with the exception of 91% observed under 0.4 M DMA conditions. This suggested that the final cyclization proceeded through different mechanisms in 0.4 M DMA conditions (enamine assisted). On the other hand, TBZ and its diastereomers 2.22 can interchange to each other through the epimerization process. The epimerization equilibrium was a result of thermodynamic control. It was reasonable to assume the epimerization equilibrium would stop at a different TBZ/diastereomers ratio from the kinetic controlled result of the Mannich reaction. Theoretically, the TBZ/diastereomers ratio would be driven to the equilibrium point by the difference in concentrations. Under 0.8 M DIPEA conditions, epimerization from TBZ to diastereomers 2.22 resulted in the decreasing TBZ ratio over the reaction. This result implied that the epimerization was a slow process, requiring over 20 hours. On the contrary, reactions with 0.8 M DMA and 0.4 M DIPEA followed the same decreasing trends until the NMeOMeOOHi-BuNMeOMeOOi-BuHNMeOMeOOi-BuH(rac)-2.1(rac)-2.22EpimerizationKinetic Control Thermodynamic ControlCrystallizationMeOMeONH OHi-BuHMeOMeONH OHHi-Bu57 crystallization of TBZ. The crystallization significantly suppressed the epimerization or inverted the epimerization direction. This was because the crystallization process dropped the TBZ concentration from supersaturation state to saturation state. Moreover, while the produced TBZ immediately precipitated out, diastereomers 2.22 concentration kept increasing. The flat trend seen in 0.4 M DMA conditions illustrated that either there was no epimerization, or it already reached the equilibrium. Overall, I found that the epimerization process decreased kinetically obtained TBZ/diastereomers ratio. This process required time to reach the equilibrium and was significantly suppressed by crystallization events. Therefore, crystallization at an early reaction time can increase the ratio. 2.3.6 Role of Sodium Iodide Ions in aqueous solutions have an important role for solubility of organic compounds. Typically, this phenomenon is known as salting-out (decreasing the solubility of solute in water) and salting-in (increasing the solubility of solute in water), and is utilized for purification and extraction.159 While chloride ion is used as a salting-out reagent due to its hardness, iodide is known to increase the solubility of organic compounds in water due to its high polarizability. I predicted that the addition of NaI into TBZ synthesis reaction would change the counter anion for the isoquinoline from Cl- to I-, which increases the isoquinoline’s solubility. To test this, I conducted both reactions 1 and 2 in the absence of NaI. TBZ formation on each condition showed an almost identical trend (Figure 2.14). However, EasyViewer showed that the isoquinoline was not fully dissolved under reaction 2 without NaI conditions. This observation can explain that reaction 2 without NaI conditions had a slightly slower TBZ formation than 58 reaction 2 with NaI conditions shown in Figure 2.14, which also implies that isoquinoline has positive order in this reaction. Figure 2.14. TBZ formation trends with or without NaI under reaction 1 or reaction 2. 2.4 Conclusion In summary, I have developed a robust sampling platform, enabling solid/liquid heterogeneous monitoring in a slurry reaction. The installation of a dynamic mixer prepared the 59 well-mixed homogeneous sample prior to sample loading and prevented the clogging of lines by the undissolved solid. I applied this platform with orthogonal monitoring techniques to reveal comprehensive information on slurry TBZ synthesis reactions from 3,4-dihydro-isoquinoline 2.9 and β-amino ketone 2.12. Identification of two important intermediates, the enone 2.14 and the iminium 2.23, supports the notion that this reaction proceeds via an aza-Michael-Mannich pathway (Scheme 2.6). The reaction begins through the rapid formation of the enone 2.14 intermediate and dimethyl amine 2.15. The following aza-Michael addition forms iminium intermediate 2.23. Scheme 2.6. Proposed mechanism of acid-catalyzed TBZ synthesis. The existence of an optimal pH supports that this step is the rate determining step. The subsequent cyclization step from iminium intermediate 2.23 to TBZ is facilitated by base, in which a secondary amine had faster cyclization than the tertiary one. By tuning the reaction with OOMe2NHNNMeOMeOOHi-BuNMeOMeOONMeOMeOOHi-Bu2.92.12 2.14NMeOMeOAza-Michael additionMannichcyclizationNMeOMeOO2.23NMeOMeOi-BuOHOH2.15HH2.19 2.16(rac)-2.160 different concentrations of amines, an optimal amine concentration of 0.4 M demonstrated a five-fold increase in the reaction rate over previously optimized TBZ synthesis. Furthermore, assuming that the aza-Michael addition is the rate determining step in this reaction, I explained the bell-shaped pH profile with a model. Based on the model, the aza-Michael addition has optimal pH 7 derived from pKa of isoquinoline (5.8) and HA (8.5) In addition to online HPLC analysis, with the assistance of Mettler-Toledo EasyViewer, I found that NaI helped the isoquinoline dissolution in aqueous solvent, and the crystallization process significantly changed TBZ ratio over its diastereomers 2.22. 2.5 Experimental Section 6,7-Dimethoxy-1,2,3,4-tetrahydro-quinoline hydrochloride salt 2.9 and 3-[(dimethylamino)methyl]-5-methylhexan-2-one oxalate 2.12 were supplied by Neurocrine Biosciences. Optima-grade UHPLC solvents and sodium iodide were purchased from Fisher. Iodomethane was purchased from Alfa Aesar. Potassium hydroxide, dimethylamine solution, and N,N-diisopropylethylamine were purchased from Sigma. All other reagents and solvents were purchased from conventional suppliers. All reagents and solvents were used as received. NMR spectra were recorded on a Bruker Avance III 300 (300 MHz and 75 MHz for 1H and 13C, respectively), or a Bruker AV III HD 400 (400 MHz and 100 MHz for 1H and 13C, respectively) and were calibrated with the solvent (CDCl3: 7.26 ppm for 1H NMR and 77.16 ppm for 13C NMR). NMR spectra were analyzed by using the software MNova. High-resolution mass spectrometry data were acquired by the UBC Department of Chemistry Mass Spectrometry Center. 61 2.6 General procedure for reaction monitoring Monitored experiments were performed in Mettler-Toledo EasyMax 102 Advanced Thermostat System to enable online control of temperature and stir rate via iControl software. A Mettler-Toledo 50 mL one-piece glass reactor was used, allowing the attachment of multiple monitoring equipment with five openings. To a 50 mL EasyMax flask equipped with a stir bar were added isopropyl alcohol (IPA), water and NaI. Isoquinoline 2.9 was added in two portions as standard additions followed by β-amino ketone 2.12 (or enone 2.14/amine) as a single portion. The mixture was stirred vigorously at 45 °C under monitoring with online HPLC, EasyViewer and pH probe. After the reaction was judged to be completed, (rac)-2.1 and enone 2.14 were added in two portions as standard additions. Online HPLC sample was obtained using a modified reaction monitoring platform similar to which has been reported in our group previously.77 2.7 Synthetic Procedures 2.7.1.1 Tetrabenazine (TBZ) ((rac)-2.1).160 To a 25 mL three-necked, pear shaped flask equipped with a stir bar were added IPA (5.1 mL), water (2.1 mL), 3-[(dimethylamino)methyl]-5-methylhexan-2-one 2.12 (1.37 g, 8.00 mmol), 6,7-dimethoxy-1,2,3,4-tetrahydro-quinoline hydrochloride salt 2.9 (1.46 g, 6.40 mmol), and NaI (384 mg, 2.56 mmol). The mixture was stirred vigorously for 24 hours at 45 °C. After 24 hours, IPA was added to the mixture until completely dissolving a yellow precipitate at 70 °C NMeOMeOOH(rac)-2.162 and was then cooled down to r.t. to afford tetrabenazine (1.20 g, 59.0%) as white crystals. 1H NMR (400 MHz, CDCl3) δ 6.60 (s, 1H), 6.54 (s, 1H), 3.84 (s, 3H), 3.81 (s, 3H), 3.49 (d, J = 11.5 Hz, 1H), 3.27 (dd, J = 11.5 Hz, 6.3 Hz, 1H), 3.15 – 3.03 (m, 2H), 2.88 (dd, J = 13.5, 3.0 Hz, 1H), 2.79 – 2.67 (m, 2H), 2.63 – 2.47 (m, 2H), 2.34 (t, J = 11.6 Hz, 1H), 1.84 – 1.73 (m, 1H), 1.70 – 1.59 (m, 1H), 1.07 – 0.96 (m, 1H), 0.89 (dd, J = 5.4, 4.6 Hz, 6H); 13C NMR (101 MHz, CDCl3) δ 210.1, 147.9, 147.6, 128.5, 126.1, 111.5, 107.9, 62.5, 61.5, 56.1, 56.0, 50.7, 47.6, 47.6, 35.1, 29.4, 25.5, 23.3, 22.2; MS ESI+ (calc. for C19H27NO3, 317.20): m/z = 318.2 [M+H]+. 2.7.1.2 3-[(dimethylamino)methyl]-5-methylhexan-2-one (2.12).160 3-[(Dimethylamino)methyl]-5-methylhexan-2-one oxalate (41.9 g, 160 mmol) was suspended in Et2O (80 mL) and water (200 mL). 2 M KOH solution (200 mL, 400 mmol) was charged, generating a white precipitate. The mixture was stirred vigorously for 1 hour at r.t., and was then transferred to a separatory funnel with Et2O (200 mL). The mixture was washed with water (2×200 mL). The organic layer was dried over Na2SO4 and concentrated in vacuo to afford 3-[(dimethylamino)methyl]-5-methylhexan-2-one (25.8 g, 93.9% yield) as colorless oil. 1H NMR (400 MHz, CDCl3) δ 2.82 – 2.70 (m, 1H), 2.57 (t, J = 11.6 Hz, 1H), 2.13 (s, 3H), 2.17 – 2.10 (m, 1H), 2.12 (s, 6H), 1.56 – 1.40 (m, 2H), 1.25 – 1.14 (m, 1H), 0.88 (t, J = 7.0 Hz, 6H); 13C NMR (101 MHz, CDCl3) δ 212.3, 62.4, 49.7, 45.8, 39.5, 28.4, 26.2, 23.1, 22.3; MS ESI+ (calc. for C10H21NO, 171.16): m/z = 172.2 [M+H]+. OMe2N2.1263 2.7.1.3 trimethyl-[2-(2-methylpropyl)-3-oxobutyl]-azanium iodide.160 3-[(dimethylamino)methyl]-5-methylhexan-2-one 2.12 (25.7 g, 150 mmol) was charged in methanol (150 mL). To the stirred solution was added iodomethane (25.56 g, 180 mmol) dropwise. The mixture was stirred vigorously for 5 hours at r.t., and the solvent was removed under reduced pressure. The remaining solid was washed with Et2O to afford trimethyl-[2-(2-methylpropyl)-3-oxobutyl]-azanium iodide (43.5 g, 92.6 % yield) as a white crystal. 1H NMR (400 MHz, Acetone-d6) δ 4.22 – 4.06 (m, 1H), 3.71 – 3.60 (m, 2H), 3.38 (s, 9H), 2.41 (s, 3H), 1.92 – 1.75 (m, 1H), 1.66 – 1.47 (m, 1H), 1.42 – 1.25 (m, 1H), 1.05 (d, J = 6.5 Hz, 3H), 0.96 (d, J = 6.6 Hz, 3H); MS ESI+ (calc. for C11H24NO+, 186.19): m/z = 186.2 [M]+. 2.7.2 5-methyl-3-methylidenehexan-2-one (2.14).161 Trimethyl[2-(2-methylpropyl)-3-oxobutyl]-azanium iodide (43.5 g, 233 mmol) was charged in water (350 mL) and Et2O (466 mL). To the stirred solution was added 10 M KOH (140 mL, 1.40 mol). The mixture was stirred vigorously for 18 hours at r.t., and was then transferred to a separatory funnel. The mixture was washed with water (3×300 mL). The organic layer was dried over Na2SO4 and concentrated in vacuo to afford 5-methyl-3-methylidenehexan-2-one (18.3 g, 62.1% yield) as colorless oil. 1H NMR (400 MHz, CDCl3) δ 5.98 (s, 1H), 5.71 – OMe3NIO2.1464 5.65 (m, 1H), 2.28 (s, 3H), 2.09 (dd, J = 7.2, 1.1 Hz, 2H), 1.74 – 1.61 (m, 1H), 0.81 (d, J = 6.7 Hz, 6H); 13C NMR (101 MHz, CDCl3) δ 200.0, 148.3, 125.9, 40.1, 27.2, 26.0, 22.4. 2.7.3 TBZ diastereomers (2.22). To a 100 mL EasyMax flask equipped with a stir bar was added crude, unfiltered reaction mixture from a TBZ synthesis reaction. The mixture was stirred vigorously at 60 °C for 4 days to produce the diastereomers, then cooled to 5 °C at 0.1 K/min and filtered to separate out the solid TBZ. The filtrate containing TBZ and the TBZ diastereomers had solvent removed in vacuo and was dissolved in 30 mL DCM. Silica gel (5 g) was added, and the solvent was again removed in vacuo. The dry-loaded solids were purified via flash column chromatography (0-70% EtOAc in hexanes) using a RediSepRf gold column (24 g) to afford 30 mg of TBZ diastereomers (30 mg, 0.4%) as an off-white solid. 1H NMR (400 MHz, CDCl3) δ 6.62 (s, 1H), 6.56 (s, 1H), 3.86 (s, 3H), 3.83 (s, 3H), 3.44 (br d, J = 11.5 Hz, 1H), 3.19 – 3.08 (m, 1H), 3.07 – 2.93 (m, 2H), 2.82 (ddd, J = 14.2, 3.3, 1.5 Hz, 1H), 2.72 (dd, J = 11.6, 4.0 Hz, 1H), 2.68 – 2.59 (m, 2H), 2.58 – 2.49 (m, 2H), 1.85 – 1.73 (m, 1H), 1.60 – 1.46 (m, 2 H), 0.93 (d, J = 6.2 Hz, 3H), 0.88 (d, J = 6.3 Hz, 3H); 13C NMR (100 MHz, CDCl3) δ 212.6, 147.7, 147.7, 128.9, 126.6, 111.4, 107.8, 62.2, 59.8, 56.1, 56.0, 51.8, 49.2, 45.4, 40.7, 29.4, 25.9, 22.8, 22.4; MS ESI+ (calc. for C19H27NO3, 317.20): m/z = 318.2 [M+H]+. NMeOMeOOi-BuH(rac)-2.2265 2.7.4 6,7-dimethoxy-2-[2-(2-methylpropyl)-3-oxobutyl]-3,4-dihydroisoquinolin-2-ium (2.23). To a 25 mL three-necked, pear-shaped flask equipped with a stir bar were added IPA (5.1 mL), water (2.1 mL), 5-methyl-3-methylidenehexan-2-one 2.14 (1.01 g, 8.00 mmol), 6,7-dimethoxy-1,2,3,4-tetrahydro-quinoline hydrochloride salt 2.9 (1.46 g, 6.40 mmol), and NaI (384 mg, 2.56 mmol). The mixture was stirred vigorously for 24 hours at 45 °C, and then transferred to a separatory funnel. The mixture was extracted with DCM (100 mL) and washed with water (3×100 mL), leaving most of the isoquinoline salt 2.9 in the water layer. The organic layer was concentrated in vacuo to remove the remaining enone 2.14. Recrystallization with AcOEt gave 6,7-dimethoxy-2-[2-(2-methylpropyl)-3-oxobutyl]-3,4-dihydroisoquinolin-2-ium salt 2.23 (54 mg, 2.7% yield) as a yellow crystal. 1H NMR (400 MHz, CDCl3) δ 9.67 (s, 1H), 7.60 (s, 1H), 6.85 (s, 1H), 4.22 (d, J = 8.9 Hz, 2H), 4.05 (t, J = 7.8 Hz, 2H), 3.98 (s, 3H), 3.89 (s, 3H), 3.61 – 3.50 (m, 1H), 3.23 (t, J = 8.1 Hz, 2H), 2.32 (s, 3H), 1.74 – 1.60 (m, 2H), 1.41 – 1.33 (m, 1H), 1.00 (d, J = 6.2 Hz, 3H), 0.95 (d, J = 6.3 Hz, 3H); 13C NMR (101 MHz, CDCl3) δ 210.0, 165.5, 158.0, 149.1, 132.5, 117.3, 116.1, 110.8, 59.9, 57.0, 56.9, 50.0, 49.8, 39.0, 29.7, 26.2, 26.0, 23.0, 23.0; MS HRMS (calc. for C19H28NO3+, 318.2069): m/z = 318.2059 [M]+. NMeOMeOOi-Bu2.2366 2.8 Online HPLC Monitoring Equipment 2.8.1 Dynamic Mixer (Akta M-925 mixing cartridge, 0.6 mL) Figure 2.15. The dynamic mixer as shown from (a) the front and (b) the side. Inline dynamic mixers are frequently used to facilitate the mixing of two homogeneous solution phases and/or solvents. The AKTA M-925 mixer has inlets for two separate solutions to enter, and a mixing chamber with magnetic stir bar that, with the assistance of an external rotating magnetic field, stirs and facilitates optimal mixing of the two solutions. I have adapted this for assisting in the dissolution of minute solids in the sample aliquot before delivery to the HPLC for analysis. Heterogeneous samples (containing solids suspended in reaction solution) are pushed via a diluent solvent (chosen to be able to dissolve all components, which in this case was acetonitrile). However, dissolution takes time and is assisted by mechanical stirring to break up solids. Delivering the heterogeneous sample aliquot from the EasySampler to the inline dynamic mixer ensures total solids dissolution before sample is passed to the sample loop and introduced onto the HPLC, ensuring accurate and reproducible quantitation, and avoiding clogging. This sample enters a 600 μL mixer chamber through one of the two available inlet ports (with the other port blocked, as no second solution is being used and only the diluent already present is BlockedOutletInlet(a) (b) 67 assisting in dilution). After entering the mixer and undergoing mechanical agitation, the sample is pushed into the sample loop and injected onto the HPLC. 2.8.2 Mettler-Toledo EasySampler Probe Function and Geometry (sampling device) The EasySampler is a commercially available probe-based device. The sampling head consists of a 20 μL pocket to capture both solid and liquid phases from the reactor. At each sampling event, the probe head and pocket are first filled with inert gas to prevent dilution by releasing the solution (Figure 2.16 a). Then, extending the head pocket into the reactor fills the pocket with a slurry sample (Figure 2.16 b). While in the extended position, the internal fluidic pathway of EasySampler is primed with quenching solvent (yellow line in Figure 2.16 b). Next, the head pocket is retracted, and a captured aliquot is delivered onto the sample loop with diluent solvent. This process can be visualized in an animation published on YouTube. https://www.youtube.com/watch?v=IMVZw3wMhU0 Figure 2.16. Mettler-Toledo EasySampler (a) closed position. (b) extended position77 2.8.3 EasyViewer Mettler-Toledo EasyViewer 100 was used as an in-situ, probe-based imaging and video microscope that captures high-resolution images of crystals, particles, and droplets as they exist in a process. With Mettler-Toledo’s iC Vision software, EasyViewer provided real-time images 68 of the physical properties of reaction mixtures such as dissolution, primary nucleation, and crystal growth. 2.8.4 pH Probe The pH values were Mettler-Toledo InLab® Semi-Micro-L pH electrode. The pH probe was calibrated with pH 7 and pH 4 buffer solutions prior to each reaction monitoring session. Mettler Toledo iControl was used in conjunction with the pH probe for the acquisition and recording of real time pH trends. 69 2.9 HPLC Methods The online Liquid Chromatography (LC) samples were analyzed by HPLC conducted on an Agilent 1260 HPLC equipped with DAD detector using the following configuration: Table 2.1. Online HPLC Column and Separation Method Detail. Column: Agilent HPH C18 2.7 µm, 3.0 x 50 mm Column Temperature: 40 °C Flow Rate: 0.45 mL/min Acquisition Time: 7.0 min run time 2.0 min post run time Mobile Phase: Solvent A = Water Solvent B = Methanol with 0.1% DIPA (DIPA prevented partial protonation of nitrogen containing compounds including TBZ) Mobile Phase Program: Time 0.00 min 6.0 min B% 10 100 DAD: 190 – 480 nm was collected. The following wave lengths were used for reaction component peaks; TBZ 1 (280 nm), isoquinoline 3 (264 nm), TBZ diastereomers 7 (280 nm), enone 5 (240 nm) ESI-MSD: positive mode scan for m/z 110 – 1500 running at 0.8 sec/cycle. drying gas = 7.0 l/min, nebulizer pressure = 20 psi, gas temperature = 300 °C, capillary voltage = 4000 V 70 HPLC Spectra Neurocrine’s optimized conditions (Reaction 1 conditions) Figure 2.17. online HPLC spectra (240 nm and 280 nm) at 5 hours under reaction 1 conditions. No. Rt (min) 1 3.23 isoquinoline 2.9 2 4.59 enone 2.14 3 5.53 TBZ (rac)-2.1 4 5.69 TBZ diastereomers (rac)2.22 Reaction time = 5 hours (240nm) 1 2 3 4 Reaction time = 5 hours (280nm) 71 2.10 The Role of Mixer Volume Using heterogeneous solution (including unknown conc. of TBZ and Isoquinoline: TBZ is heterogeneous and Isoquinoline is homogeneous component), I increased the amount of mixer volume (no dynamic mixer volume, 0.05 mL, 0.2 mL, 0.3 mL and 0.4 mL) followed by 30 seconds wait time. Figure 2.18. Delivery kinetics of heterogeneous TBZ and homogeneous isoquinoline when using (a) the no mixer volume (b) 0.05 mL mixer volume and wait 30 seconds. (c) 0.2 mL mixer volume (a) No mixier volume (b) 0.05 mL (c) 0.2 mL (d) 0.3 mL (e) 0.4 mL 72 and wait 30 seconds. (d) 0.3 mL mixer volume and wait 30 seconds. (e) 0.4 mL mixer volume and wait 30 seconds. With no mixer volume, I observed different delivery kinetics of heterogeneous and homogeneous components. This indicated that the dynamic mixer could not dissolve the heterogeneous component immediately. Since the minimum volume required to deliver the sample aliquot to the dynamic mixer is 0.225 mL, I observed that less than 0.2 mL mixer volume caused different delivery profiles for both homogeneous and heterogeneous components (Figure 2.18). In contrast, 0.3 mL and 0.4 mL dynamic volumes had sufficient volume to deliver the slurry sample to the chamber, and the identical delivery kinetic was observed for both homogeneous and heterogeneous components. 2.11 TBZ Calibration Curve The calibration curves of TBZ were generated using a Mettler-Toledo 50 mL one-piece glass reactor at 45 ºC controlled in EasyMax 102 Advanced Thermostat System. TBZ precipitates at concentrations above 0.13 M in a solution of 30% water in isopropyl alcohol at 45 ºC. To get accurate total volume, the volume of solid was also considered using relationship of volume changes against solid dose of TBZ (Figure 2.6). 73 Figure 2.19. Calibration curve of TBZ using 0.4 mL mixer volume and wait 30 seconds method. Our online HPLC platform generated a linear calibration curve of the slurry TBZ solution with low relative standard deviations (<3%). 2.12 Standard Addition as Internal Calibration Curve We used the standard addition method, which is reported by Burés et.al.,85 to generate “an internal calibration curve” along with the setup of the reaction. Methods to make an in-situ calibration curve (standard addition method) for all reaction components without interfering with the reaction monitoring process are below: Standard addition at the initial points of reactions (isoquinoline 2.9): Standard addition of starting material could be conducted by sequential addition of a known amount of starting material before adding other components. Several samples were taken after each addition. By knowing the total volume and starting material amounts before and after each addition, I can derive the equation from calculating the slope between concentration and signal for the starting material. This is similar to making a 2-point calibration curve. [TBZ](M) TBZ Peak AreaRSD (%)0.8 3695.5 2.170.4 1877.0 2.070.2 995.6 0.700.1 532.9 1.470.05 266.9 2.870.025 133.3 2.5974 Figure 2.20. Reaction monitoring profile of isoquinoline with initial points standard addition. Standard addition at the ending points of reactions (TBZ (rac)-2.1 and enone 2.14): After the reaction is finished or slowed down enough, the concentration of the product of this reaction is not going to change anymore. A known amount of compounds is added for ending points' standard addition, and taking samples. Notice that, unlike the initial points’ standard addition, the concentration of components is not known. To calculate the slope of a calibration curve, the added amount and the volume before and after the standard addition must be known. As a result, K for product is calculated by using the addition amount and volume. Figure 2.21. Reaction monitoring profile of TBZ with ending points standard addition. 𝑲𝑹 =[𝑹𝒆𝒂𝒄𝒕𝒂𝒏𝒕]𝒂𝒇𝒕𝒆𝒓 𝑺𝑨 − [𝑹𝒆𝒂𝒄𝒕𝒂𝒏𝒕]𝒃𝒆𝒇𝒐𝒓𝒆 𝑺𝑨𝑺𝒊𝒈𝒏𝒂𝒍𝒂𝒇𝒕𝒆𝒓 𝑺𝑨 − 𝑺𝒊𝒈𝒏𝒂𝒍𝒃𝒆𝒇𝒐𝒓𝒆 𝑺𝑨 [𝑹𝒆𝒂𝒄𝒕𝒂𝒏𝒕]𝒕 = 𝑲𝑹 ∙ 𝒔𝒊𝒈𝒏𝒂𝒍𝒕 [𝑹𝒆𝒂𝒄𝒕𝒂𝒏𝒕]𝒕 = 𝒏𝑺𝑨𝑽𝒕 𝒏𝒕𝑽𝒕= 𝑲𝒑 ∙ 𝒔𝒊𝒈𝒏𝒂𝒍𝒕 𝒏𝒕 = 𝑲𝒑 ∙ 𝒔𝒊𝒈𝒏𝒂𝒍𝒕 ∙ 𝑽𝒕 ∆𝒏 = 𝑲𝒑 ∙ (𝒔𝒊𝒈𝒏𝒂𝒍𝑺𝑨 ∙ 𝑽𝑺𝑨 − 𝒔𝒊𝒈𝒏𝒂𝒍𝒃𝒆𝒇𝒐𝒓𝒆 𝑺𝑨 ∙ 𝑽𝒃𝒆𝒇𝒐𝒓𝒆 𝑺𝑨) 𝑲𝒑 =∆𝒏(𝒔𝒊𝒈𝒏𝒂𝒍𝑺𝑨 ∙ 𝑽𝑺𝑨 − 𝒔𝒊𝒈𝒏𝒂𝒍𝒃𝒆𝒇𝒐𝒓𝒆 𝑺𝑨 ∙ 𝑽𝒃𝒆𝒇𝒐𝒓𝒆 𝑺𝑨) Isoquinoline standard addition TBZ standard addition 75 Chapter 3: Liquid/Liquid Heterogeneous Reaction: Biphasic Suzuki Miyaura Cross Coupling 3.1 Introduction Homogeneous reaction conditions consisting of all components dissolved in a reaction solution are often desired for reaction monitoring due to the compatibility with conventional instruments. However, liquid-liquid biphasic reaction conditions have gained increasing attention recently in the chemical and pharmaceutical industries instead of these homogeneous reactions conducted in only organic solvents.162,163 Such biphasic conditions usually consist of all components being fully dissolved in two distinct immiscible liquid phases, one more polar such as water and another less polar organic solvent. The addition of this immiscible polar (aqueous) phase allows much more polar reagents to be implemented than what would otherwise be soluble in less polar organic solvents. Not only are inorganic bases usually less expensive than other organic-soluble bases, but the use of mildly basic aqueous biphasic conditions may increase functional group tolerance. This provides a clear benefit to biphasic liquid-liquid conditions over reactions carried out purely in an organic solvent. Classic examples of these biphasic liquid-liquid conditions include C-N couplings such as the Buchwald-Hartwig amination,164 C-C couplings such as the Suzuki Miyaura cross coupling,165 and phase transfer catalysis reactions with a catalyst serving to ferry reagents that are very different in polarity back and forth between polar and nonpolar phases.166 As the importance of these reactions has increased over time, the desire to obtain detailed information regarding their mechanisms and kinetics has also increased, including the ability to observe and prevent side reactions or undesired product formation. To obtain such detailed reaction information, real-time reaction monitoring tools called process analytical technology (PAT) are often used to obtain in-76 depth data for ongoing processes. While these technologies have been implemented more and more frequently in recent years, many conventional analytical tools such as flow NMR and in situ IR spectroscopy require the interrogated solutions to have all components fully dissolved in a single homogeneous solution. Varying the solution composition can change the background signal and complicate the measurement during liquid-liquid biphasic reactions, or completely impede the ability of these spectroscopic techniques to acquire data if a background lock must be maintained (as in NMR). This severely limits their potential applications to biphasic systems and doesn’t account for the added complication of the differing densities usually exhibited by the two phases. These different densities can make sampling even more challenging with a single instrument, as a solution flowing vertically through an instrument (such as the flow cell of a benchtop NMR) could have the layers begin to separate in the lines or flow cell and therefore only be constantly removing one of the two layers. Such geometrical constraints can further limit the ability of these biphasic systems to be accurately monitored by conventional in situ or online analytical techniques. One solution to this sampling issue is to stop a biphasic liquid-liquid reaction from stirring and allow the layers to settle before sampling only one layer with PAT. This overcomes the issue of sampling multiple layers at once, as well as having to deal with difficulties arising from the physical properties of having two phases (such as differing densities). This approach provides higher quality data and allows for phase-specific sampling based on probe placement, such as sampling a less dense organic phase by placing a probe at the top of a reactor and stirring at a sufficient speed that the layers partially separate. However, this approach is also time-consuming and not compatible with faster reactions. If a reaction occurs on a very short timescale, waiting for stirring to stop and start again between sampling events will not be feasible for accurately monitoring its progress. Additionally, since stir speed can affect mixing of immiscible layers, 77 stopping stirring can further slowdown a reaction. This could impact the ability to monitor a reaction under “untouched” conditions where this stir rate change is not occurring, and therefore nullify the usefulness of any data collected by this method. Unlike these in situ or flow-based sampling techniques, ex situ sampling techniques can allow sample aliquots to be taken and analyzed external to the reaction solution without the sampled solution needing to be completely homogeneous. This allows for a biphasic solution to be sampled, then fully dissolved with a solvent miscible with both liquid-liquid layers before being analyzed externally. An example of this could include sampling a biphasic water-tetrahydrofuran (THF) solution and diluting it with methanol, which is miscible with both of these solvents and capable of making a single homogeneous solution for sample analysis. However, this approach wouldn’t provide phase-specific data, which may be of interest if a reaction is known to be occurring only in one phase or if partition coefficients change as a reaction progresses (therefore requiring knowledge of the concentrations in each individual phase). Another option is to employ a phase-selective sampling technique such as porous polymeric filters, which have been reported to selectively sample the organic phase of such liquid-liquid biphasic reactions.124 The Hein Lab has previously reported the use of online HPLC to perform real-time ex situ analysis of biphasic phase transfer catalysis reactions using a porous polymeric filter for selective organic phase sampling. This allowed for the collection of real-time kinetic data leading to catalyst decomposition pathways and rate laws for the reaction to be determined. Despite the success of this organic-selective sampling method, no known method has previously been reported for selectively sampling the aqueous phase of a biphasic reaction. Based on the successful organic selective sampling, the PTFE filter is considered as oleophilic/hydrophobic material. In the last decades, research activities on surface science have 78 attracted a tremendous amount of attention due to the famous self-cleaning surface on the lotus leaf.167,168 Among the surface science community, the broadly accepted definitions of hydro/oleo-philic vs. hydro/oleo-phobic vs. super-hydro/oleo-phobic are determined by static contact angle θ (Figure 3.1 (a)).169–171 Material surface is called hydro/oleo-philic when its static contact angle θ is < 90°, and hydro/oleo-phobic when θ is > 90°. When the static contact angle θ becomes > 150°, the material surface is extremely repellent to the liquid and called super-hydro/oleo-phobic. By accepting this definition, the PTFE filter surface could be described in Figure 3.1 (b) top. Despite the success of this organic-selective sampling method, no known method has previously been reported for selectively sampling the aqueous phase of a biphasic reaction. Therefore, the first objective of this chapter is to seek a new hydrophilic/oleophobic for the selective aqueous layer sampling (Figure 3.1 (b) bottom). Figure 3.1 (a) Illustration of aqueous and organic droplets on the surface of hydrophobic, hydrophilic, oleophobic and oleophilic materials. Static contact angle θ changes depending on the surface material. (b) Illustration of aqueous and organic droplets on PTFE material (top); illustration of desired material for selective aqueous layer sampling (bottom). 79 Known methods of selectively separating an aqueous phase from an organic phase include the use of polymeric or ceramic membranes to preferentially allow only one phase through for selective sampling. However, these membranes have a variety of issues associated with them such as requiring a low flow rate (based on their capacity to allow solvent through), having a high susceptibility to fouling (thanks to small pore sizes) and rapidly declining in efficiency during operation as fouling occurs.172 I initially investigated a commercially available membrane separator manufactured by Zaiput Flow Technologies that is marketed for separating biphasic organic-aqueous mixtures. (Section 3.11) While this membrane separator worked well for separating simple mixtures of 2-methyl tetrahydrofuran (MeTHF) and water, it rapidly clogged when I attempted to monitor a biphasic Suzuki Miyaura coupling reaction due to the buildup of solid palladium particles on the membrane surface (Section 3.11). I therefore looked for other options that would be more suitable for reaction monitoring when many reagents are present instead of being suitable only for simple solvent mixture separations. Surface-coated stainless steel mesh has shown promising potential in the fields of biomimetic and environmental chemistry due to its extremely hydrophilic surface.173 While currently being applied for the purification of oil-contaminated water, I investigated if a similar surface-coated stainless steel filter could be used as an aqueous-selective filter by modifying a commercially available stainless steel filter with aqueous potassium carbonate solution. This allowed me to sample both the organic phase (via porous polymeric filter) and the aqueous phase of a biphasic reaction and allowed me to acquire real-time data with the use of our lab’s online HPLC monitoring system combined with flow NMR. To demonstrate my system’s capabilities, I conducted simple partition coefficient tests for various boronic acids with differing amounts of the base in a biphasic solvent mixture using flow NMR and online HPLC. After confirming that the 80 system had high reproducibility both within and between these techniques, I then applied my system to monitor a liquid-liquid biphasic Suzuki Miyaura coupling reaction. 3.2 Development of a Hydrophilic/Lipophobic SS Filter The Hein Lab has built a variety of custom-built, robotic systems that allow for reaction progress monitoring for different reaction conditions, including in situ mode, off-line mode or online mode. These systems are made up of modern programmable valves and pumps, some of which use commercially available liquid handling systems such as the Gilson and EasySampler. As a brief list, a stop-flow 19F NMR system102; an organic-layer-selective off-line HPLC system174 and the mile-stone online HPLC system.77 The operation of these systems relies on custom-built computer software. On top of the foundation that was built by Hein Lab alumni, I chose a simple external flow-through system which is similar to the flow NMR as the base for our phase-selective online HPLC/NMR reaction monitoring system. The flow-through function is achieved by using the SF-10, a high-pressure solvent tolerant robust peristaltic pump produced by Vapourtec. This pump allows for digital control of the flow rate, pump stop/continue and pump direction by using RS-232 communication by the computer, allowing for control of the flowing parameters according to the sampling situations in terms of the solution phase, injection mode and phase-selection situations. After the assembling of the system (Figure 3.2 (d)) by connecting the reaction flask with PTFE tubing with a brand-new A392 alloy HPLC filter on the tip with the pump, a solution containing 25 mL to 25 mL MeTHF and water was first tested. At this point, the alloy filter was not modified with any solution. 10 mL of the mixture solution was collected using the system. The 81 result showed no selectivity between the organic and the aqueous layers by using a 3 mL/min flow rate (Figure 3.2 (a)). This indicates the alloy filter does not have any selection of one layer over the other one at this point. Figure 3.2 (a) 10 mL of collected sample from MeTHF/water mixture, before any modification of the alloy filter, flow rate = 3.0 mL/min. (b) 10 mL of collected sample from MeTHF/water mixture, After 5 M K2CO3 modification of the alloy filter, flow rate = 3.0 mL/min. (c) 10 mL of collected sample from MeTHF/water mixture, After 5 M K2CO3 modification of the alloy filter, flow rate = 1.0 mL/min. (d) The sampling system used for the test of alloy filter efficiency, an aqueous layer has been colored by the addition of green food dye (3 drops in total). The modification of the alloy filter was then conducted with 5 M K2CO3 solution for 5 minutes with sonication. With the base-modified filter, the collected 10 mL solution showed a dramatic ratio change. By reading the volume from the marked scale from the graduate cylinder, 95% to 5% of the aqueous layer and organic layer were collected (Figure 3.2 (b)), showing the significant change the modification has had on the alloy filter. To further improve the separation performance, it was thought that the flow rate is important as a fast flow rate would decrease the contacting time of the filter to the solvents, which 82 in turn decreases the selection of the aqueous phase over the organic phase. As such, a lower flow rate was tested by using 1.0 mL/min instead of 3.0 mL/min. As a result, a much better selectivity was achieved with over 99 % of the aqueous layer collected (Figure 3.2 (c)). 3.3 System Description With the modified alloy filter tip with outstanding selectivity in hand, I started to develop a system that is capable of sampling both phases in turns (Figure 3.3). On the top of the flow-through system described above, another line with a PTFE filter was used to take the organic layer. To selectively sample either layer in turn, a solenoid 2-path selection valve with a relay board was used. The combination of pumping, valve selection and flow path are coordinated using a custom Python script. In terms of the sampling interval, a dense data experiment is preferred as more detailed information can be recorded. To this end, the sampling interval should be kept at a minimum while ensuring each sampling event can be completed without interferences by the previous or next sampling. The maximum sampling rate is achieved when the sampling interval is equal to the sample acquisition time (collection of phase-specific aliquot) plus the HPLC run time. Specifically, for this phase selective reaction monitoring system, organic phase sampling and aqueous phase sampling must be completed sequentially to make the same density of data for each layer. For our system, 11 mins of overall sampling interval were selected, thus 22 mins sampling interval for each layer. 83 Figure 3.3 Biphasic sampling system used in this research, alloy filter used for aqueous layer selection is represented in blue; PTFE filter used for organic layer sampling is presented in red. To couple the newly developed liquid/liquid sampling system with a flow NMR system, I collaborated with Amgen Inc. who possesses a cryogen free 400 MHz NMR.175–177 The magnet is a high-temperature superconducting (HTS) magnet (MR 9T4-54, iron-yoke NMR magnet) supplied by HTS-110 (Lower Hutt, New Zealand) and operating at 9.40 T (400.32 MHz for 1H, 376.82 for 19F, and 128.46 MHz for 11B observation). The magnet always operates in the driven mode with a current regulated by a high-stability power supply (Danfysik System 8500 model 854, Taastrup, Denmark). The cooling of the magnet is achieved by a Cryomech PT807 (Syracuse, NY) pulse tube cooler with a Cryomech CP2800 helium compressor. An air-cooled chiller (Huber Unichiller 040T, Offenburg, Ger- many) provides water cooling to the power supply. The NMR console is an AVANCE III HD NMR (Bruker BioSpin, Billerica, MA). The flow NMR configuration for the biphasic sampling made use of an existing flow NMR apparatus in place in the process chemistry group at Amgen and adapted technology previously developed by other Hein Lab members.178 While our original intention was to sequentially alternate the selective phase extraction flow (following an alternative flow strategy such as selective organic – selective aqueous – selective organic – etc.), the geometry of the flow cell prevented efficient clearance and exchange 84 of the immiscible phases, precluding a segmented sampling strategy. Instead, I set up two independent single-phase sampling systems for monitoring, the first using only the PTFE filter for selective organic phase measurements, and the second configured to use the modified stainless steel sintered filter selective for the aqueous phase (Figure 3.4). Figure 3.4 Sampling system used in this research on Amgen site (left figure), a PTFE filter used when organic sampling was required (top right of the figure); an alloy filter was used when aqueous layer sampling was required (bottom right of the figure) 3.4 Application to Partition Coefficient of Boronic Acids Before running the reaction, the phase distribution of various boronic acids in MeTHF/water with K2CO3 was conducted to test the sampling robustness and capability of the system. These experiments not only provided initial hardware validation on the system but also provided some of the first recorded analytical data on the changes in relative solubility and partitioning for different boronic acids as a function of aqueous phase pH. A neutral organic molecule may be selectively driven from the organic phase to the aqueous phase through ionization resulting from proton exchange, solvolysis or some combination of these processes. Boronic acids may be considered as weak Brønsted acids, leading to ionization via deprotonation at a pendant hydroxyl group with some Brønsted base (Scheme 3.1 (1)). The 85 vacant p orbital on boron provides an alternative mode of ionization by participating as a Lewis acid, where the capture of a nucleophilic solvent (water) forms a tetrahedral boronate species (Scheme 3.1 (2)). Scheme 3.1 Two pathways of boronic acids exhibit acidity, as Brønsted (1); and electrophile (2). Some boronic acids have been shown to ionize exclusively via the above Brønsted acid pathway (Scheme 3.1 (1)) due to steric restrictions.179 However, for this study I chose representative arylboronic acids (seen in Scheme 3.2) that are reported to primarily act as Lewis acids, leading to ionization via boronate complex.179–181 Scheme 3.2 Boronic acid used in this research: 3.4: (6-fluoropyridin-3-yl)boronic acid; 3.5: (3-fluoro-5-hydroxyphenyl)boronic acid; 3.6: (4-(trifluoromethyl)phenyl)boronic acid The three boronic acids chosen for this study (3.4,3.5,3.6) are expected to have a significant distinct behaviour in the biphasic system due to their different structural motifs: 3.4 features a basic pyridyl ring; 3.5 features an acidic hydroxy group; 3.6 as a neutral comparison. Furthermore, 86 all three candidates contain fluorine, allowing the use of 19F NMR analysis, which has a wider range of chemical shifts than proton NMR. The HPLC and NMR results for 3.4 are shown in Figure 3.5. After the addition of pure water (25 mL) to the boronic acid solution in MeTHF, the concentration of the corresponding boronic acid increased in both layers. This observation is unexpected as the concentration increase in both layers may seem to be inconsistent with the mass balance rule. (i.e., the boronic acid is transferred from the organic layer to the aqueous layer, so a decreased concentration should be observed in the organic layer.) However, this obfuscating behaviour can be explained by a volume change of each layer, as the organic layer (MeTHF) was partially miscible with water (14g/100g),182 the MeTHF layer's total volume would shrink after the addition of water. This reduction in the volume of the organic phase with little to no loss of dissolved components would equate to an increase in the relative concentration of the organic layer (See section 3.7.6). After the addition of pure water, portions of 5 M K2CO3 were added (0.25 eq., 0.25 eq., 0.5 eq., 1.0 eq. compared to the boronic acid) to the mixture as a solution. Both NMR and HPLC signals changed immediately after each addition of the base. The signal intensities of 3.4 dropped correspondingly in the organic layer, indicating the formation of the boronate species and transferring from the organic layer to the aqueous layer. After 2.0 eq. of K2CO3 was added to the mixture, 90% of 3.4 was transferred to the aqueous layer. 87 Figure 3.5 Concentration of HPLC (shown in orange) and NMR (shown in blue) data for the partition test of boronic acid 3.4, both organic (shown in the solid squares) and aqueous layers (shown in the void squares) are plotted. Mixture compositions: A. 250 mM 3.4 (15 mmol) in 60 mL MeTHF; B: 3.4 (15 mmol) in 60 mL MeTHF and 60 mL water; C: 3.4 (15 mmol) in 60 mL MeTHF and 60 mL water + 0.25 eq. K2CO3 (0.75 mL); D: 3.4 (15 mmol) in 60 mL MeTHF and 60 mL water + 0.50 eq. K2CO3 (1.5 mL); E: 3.4 (15 mmol) in 60 mL MeTHF and 60 mL water + 1.0 eq. K2CO3 (3.0 mL); F: 3.4 (15 mmol) in 60 mL MeTHF and 60 mL water + 2.0 eq. K2CO3 (6.0 mL). HPLC experiment was conducted 6.25 mmol scale. Similarly, 3.5 was tested using the same experimental conditions (Figure 3.6). The general phase transfer trend was similar to 3.4 where the BA transferred as more K2CO3 was dosed into the mixture. While 3.4 transferred about 90% after 2.0 eq of K2CO3 was added, only 55% of 3.5 050100150200250300[BA or Boronate] (mM)Org NM R Aq NM R Org HPLC Aq HPLCA B C D E FNB(OH)2F3.4250 mMin 2-Me-THF (60 mL)K2CO3 (portional dose, in total 2.0 eq., 6 mL)H2O (60 mL)NB(OH)2F3.4+NB(OH)3F3.7organic layer aqueous layer88 was transferred instead. The difference in concentration decrease of the organic layer indicates the water affinity difference between these two boronic acids. Figure 3.6 Concentration of HPLC (shown in orange) and NMR (shown in blue) data for the partition test of boronic acid 3.5, both organic (shown in the solid squares) and aqueous layers (shown in the void squares) are plotted. Mixture compositions in NMR experiment: A. 250 mM 3.5 (15 mmol) in 60 mL MeTHF; B: 3.5 (15 mmol) in 60 mL MeTHF and 60 mL water; C: 3.5 (15 mmol) in 60 mL MeTHF and 60 mL water + 0.25 eq. K2CO3 (0.75 mL); D: 3.5 (15 mmol) in 60 mL MeTHF and 60 mL water + 0.50 eq. K2CO3 (1.5 mL); E: 3.5 (15 mmol) in 60 mL MeTHF and 60 mL water + 1.0 eq. K2CO3 (3.0 mL); F: 3.5 (15 mmol) in 60 mL MeTHF and 60 mL water + 2.0 eq. K2CO3 (6.0 mL). HPLC experiment was conducted 6.25 mmol scale. 050100150200250300350[BA or Boronate] (mM)Org NM R Org HPLC Aq HPLCA B C D E F250 mMin 2-Me-THF (60 mL)K2CO3 (stepwise dose, in total 2.0 eq., 6 mL)H2O (60 mL)organic layer aqueous layerB(OH)2OHF3.5B(OH)2OHF3.5B(OH)3OHF3.889 While HPLC and NMR data were consistent between those two boronic acids, NMR and HPLC had significantly different trends with 3.6 (Figure 3.7). While the concentration of 3.6 in the organic layer was not decreased dramatically in HPLC data, a significant drop was observed by the flow NMR. This could involve speciation of the boronic acid 3.6. In addition, it is noteworthy that HPLC showed only one single peak of 3.6. This phenomenon resulted from the inherent interaction of the HPLC eluting solvent with the analytes. Since acidified solvent (1.0 % acetonitrile) was used, other species derived from speciation such as oligomers may be hydrolyzed and transformed into the boronic acid counterpart in HPLC. Only integrating the major signal in NMR would cause disagreement with the HPLC signal in quantification. Figure 3.7 Concentration of HPLC (shown in orange) and NMR (shown in blue) data for the partition test of boronic acid 3.6, both organic (shown in the solid square) and aqueous layers (shown in the void square) are plotted. Mixture compositions in NMR experiment: A. 250 mM 3.6 (15 mmol) in 60 mL MeTHF; B: 3.6 (15 mmol) in 60 mL MeTHF and 60 mL water; C: 3.6 (15 050100150200250300350[BA or Boronate] (mM)Org NM R Aq NM R Org HPLC Aq HPLCA B C D E F250 mMin 2-Me-THF (60 mL)K2CO3 (stepwise dose, in total 2.0 eq., 6 mL)H2O (60 mL)organic layer aqueous layerB(OH)2F3C3.6B(OH)2F3C3.6B(OH)3F3C3.990 mmol) in 60 mL MeTHF and 60 mL water + 0.25 eq. K2CO3 (0.75 mL); D: 3.6 (15 mmol) in 60 mL MeTHF and 60 mL water + 0.50 eq. K2CO3 (1.5 mL); E: 3.6 (15 mmol) in 60 mL MeTHF and 60 mL water + 1.0 eq. K2CO3 (3.0 mL); F: 3.6 (15 mmol) in 60 mL MeTHF and 60 mL water + 2.0 eq. K2CO3 (6.0 mL). HPLC experiment was conducted 6.25 mmol scale. One of the typically known speciations of boronic acid is oligomerization such as dimer and trimer. Chaudhari reported that 3.6 had a complex mixture of monomer 3.6, dimer 3.10, and trimer 3.11 in CDCl3 solution.183 In my flow NMR, 1H NMR spectrum of 250 mM of 3.6 in MeTHF (Figure 3.8) also showed multiple peaks. The singlet proton at 7.48 ppm indicated the pendant hydroxyl protons. Since 3.6, 3.10, and 3.11 have a different ratio between the aromatic protons and the hydroxyl protons, 2:2:2, 4:4:2, and 6:6:0 respectively, it is reasonable to consider that the hydroxyl protons belong to 3.6 with two aromatic protons at 8.05 ppm and the other two protons at 7.67 ppm. The biggest peaks at 8.33 and 7.79 ppm which seem to have no corresponding hydroxyl protons belong to the trimer 3.11, and the dimer 3.10 could hide behind as minor peaks. To obtain a reliable conclusion, additional NMR experiments such as 1H 2D-EXSY (exchange spectroscopy) are essential. 91 Figure 3.8 The structures of monomer, dimer, and trimer (top). 1H NMR spectrum of 250 mM of 3.6 in MeTHF (bottom). However, comparing the time course data of 1H NMR with one of 19F NMR (Figure 3.9), speciation happened after the base addition generated multiple minor peaks in 19F NMR (Figure 3.9, B-F) which were not observed in the mixture of monomer 3.6, dimer 3.10, and trimer 3.11 (Figure 3.9, A). The newly observed unknown peaks are too numerous and too small to determine the exact structures given the currently available data. However, the singlet peak could be key information, suggesting the boronic acid hydroxyl protons, at 8.2 ppm in 1H NMR (Figure 3.9, B) disappeared after the addition of K2CO3. This indicates that the hydrogen transfer on the hydroxyl group is accelerated by either the high pH or the presence of K2CO3. Using this information, the proposed structures of the unknown peaks are still vague, but boronate species such as 3.9 could be possible candidates. 92 Figure 3.9 Time course spectra of 1H (left) and 19F (right) NMR. Mixture compositions: A. 250 mM 3.6 (15 mmol) in 60 mL MeTHF; B: 3.6 (15 mmol) in 60 mL MeTHF and 60 mL water; C: 3.6 (15 mmol) in 60 mL MeTHF and 60 mL water + 0.25 eq. K2CO3 (0.75 mL); D: 3.6 (15 mmol) in 60 mL MeTHF and 60 mL water + 0.50 eq. K2CO3 (1.5 mL); E: 3.6 (15 mmol) in 60 mL MeTHF and 60 mL water + 1.0 eq. K2CO3 (3.0 mL); F: 3.6 (15 mmol) in 60 mL MeTHF and 60 mL water + 2.0 eq. K2CO3 (6.0 mL). The generation of unknown peaks in the organic layer was observed only in the partition test with CF3-phenyl boronic acid 3.6 (Figure 3.10). This further supports the unidentical trends between HPLC and NMR occurred only with 3.6. 93 Figure 3.10. Single 19F signals were detected for 3.4 and 3.5; while multiple 19F NMR signals were detected for 3.6 in the organic layer (right) 94 3.5 Reaction Monitoring of Liquid/Liquid Biphasic Suzuki Miyaura Cross Coupling Next, a liquid/liquid biphasic Suzuki Miyaura cross coupling reaction was investigated. Typically proposed catalytic cycles are drawn in Figure 3.11.184–186 Before the catalytic cycle, the pre-catalyst generates active Pd (0) species with the assistance of the base. The first step of the catalytic cycle is oxidative addition, where the Pd(0) forms two new bonds with aryl carbon and bromide to form the Pd(II) complex 3.15. Two pathways are typically proposed. One involves the substitution of hydroxide with bromide to form Pd(II)-hydroxyl complex 3.16, followed by the addition of boronic acid to form Pd(II)-boronate complex 3.17. The other pathway proceeds via direct attack of boronate to form 3.17 with the release of bromide ion. The complex 3.17 then proceeds to the transmetalation step to form 3.18. This step releases boric acid by-product 3.13. The final reductive elimination step regenerates the active Pd(0) species with the formation of a biaryl product. Based on the proposed mechanism, in addition to the major components such as starting materials and product, boric acid 3.13 and KBr 3.14 can be key components to elucidate the reaction. 95 Figure 3.11. Reaction conditions of planed Suzuki Miyaura cross coupling reaction and proposed mechanism. B(OH)3 3.13 lacks a suitable chromophore moiety for UV-Vis detection, and therefore HPLC analysis. In addition, 1H NMR is not expected to detect the hydroxyl protons due to the rapid hydrogen exchange. Therefore, 11B NMR was chosen to detect 3.13. In an initial investigation, it was found that the detection of the bromide ion can be achieved by HPLC (Section 3.12). By injection of KBr solution into HPLC, a peak with a significant UV absorbance at 210 nm was eluted at the injection head. With appropriate analytical tools in hand, Suzuki Miyaura coupling reaction with the pyridyl boronic acid 3.4 was monitored. Figure 3.12 shows reaction component trends located in LnPd(II) prectalystPd(0)LnAr1-Pd(II)Ln-BrAr1-Pd(II)Ln-OHAr1 Pd(II)LnAr1-Pd(II)Ln-Ar2Ar2B(OH)3BrBrOHAr2B(OH)2HOB(OH)2Ar2B(OH)3Ar1-Ar2 Ar1-Br3.153.183.133.163.17Pd precat.BaseB(OH)3 KBr3.13 3.14Ar1-Ar2Ar1-Br Ar2B(OH)296 the organic layer. Similar to the partition test, 3.4 was kept in low concentration in the organic layer over the course of the Suzuki Miyaura cross coupling reaction. On the other hand, the aryl halide coupling partner 3.19 was mostly located in the organic layer. In both NMR and HPLC, the signal representing the coupling product 3.20 showed a gradual increase in the organic layer. Figure 3.12. Reaction component trends in the organic layer by flow NMR and online HPLC. Reaction conditions in flow NMR: 15 mmol of 3.4, 15 mmol of 3.10, 0.75 mmol of Xphos Pd G2, and 30 mmol of K2CO3 in 66 mL of MeTHF and 66 mL of water. Reaction conditions in flow NMR: 6.25 mmol of 3.4, 6.25 mmol of 3.10, 0.31 mmol of Xphos Pd G2, and 12.5 mmol of K2CO3 in 27.5 mL of MeTHF and 27.5 mL of water. NBFOHOHBrXphos Pd G2 (5 mol%)K2CO3 (2eq.) NF250 mM 250 mMFFB(OH)3 KBr3.4 3.19 3.20 3.13 3.14MeTHF/H2O00.20.40.60.811.21.41.61.820501001502002503000 2 4 6 8 10 12Normalized Peak Area of PdtComponent Conc. (mM)Time (h)3.19 (HPLC)3.19 (NMR) 3.20 (HPLC)3.20 (NMR)3.4 (HPLC)3.4 (NMR)97 In contrast, reaction trends in the aqueous layer include the three components, boronic acid 3.4, B(OH)3 3.13, and KBr 3.14 (Figure 3.13). As expected, B(OH)3 3.13 was only observed in flow NMR and gradually increased over the course of the reaction as a by-product. HPLC monitoring revealed the KBr formation that NMR cannot detect. Figure 3.13. Reaction component trends in the aqueous layer by flow NMR and online HPLC. Reaction conditions in flow NMR: 15 mmol of 3.4, 15 mmol of 3.10, 0.75 mmol of Xphos Pd G2, and 30 mmol of K2CO3 in 66 mL of MeTHF and 66 mL of water. Reaction conditions in flow NMR: 6.25 mmol of 3.4, 6.25 mmol of 3.10, 0.31 mmol of Xphos Pd G2, and 12.5 mmol of K2CO3 in 27.5 mL of MeTHF and 27.5 mL of water. To elucidate the reaction mechanism, the shape of the product formation trend was overlaid with those of the key by-product formation trends (Figure 3.14). The shape of the time-course trends between the boric acid 3.13 and the product 3.20 overlapped. However, the formation of KBr 3.14 was more rapid at the beginning and did not superimpose on the trace for product 3.20. Considering the formation of KBr came from the dissociation of Br anion from the Pd core, this 00.20.40.60.811.21.41.61.820501001502002503000 2 4 6 8 10 12Normalized Peak Area for KBrand Boric AcidComponent Conc. (mM)Time (h)NB(OH)3FB(OH)33.13 (NMR)KBr3.14 (HPLC)3.7 (HPLC)3.7 (NMR)98 kinetics disagreement can indicate the oxidative addition and the following ligand exchange (Figure 3.11) are not the rate-determining-step. Instead, the trans-metalation where the release of the boric acid is likely the rate-determining-step. Figure 3.14. The overlaid trends with product 3.20 and B(OH)3 3.13 (left), and KBr 3.14 (right). From this experiment, the data from each PAT showed agreed trends of all starting material and product concentrations, which strongly evidenced the reliability of each instrument for reaction monitoring purposes. In addition, the example of the detection of unique by-product formation by orthogonal reaction monitoring techniques proves the benefits gained by using multiple PAT instead of only one, which could cause the missing of kinetically important data. 3.6 Conclusion In conclusion, I have developed a biphasic reaction monitoring platform capable of accurately monitoring reaction progress in both the aqueous phase and organic phase using online HPLC and multinuclear flow NMR. Commercial PTFE filters allowed selective extraction of the 99 organic phase and simple base-modified stainless steel filters facilitated analysis of the aqueous phase. This technology was deployed to study the partition coefficients of several boronic acids under basic conditions and revealed significant differences in speciation and phase distribution depending upon boronic acid structure. The utility of this technique was demonstrated through the application of phase-selective reaction monitoring of biphasic Suzuki-Miyaura reactions. Reaction profiles of starting materials, products, and by-products were obtained for both the aqueous and organic layers. The unique detection of boric acid and KBr are obtained by NMR and HPLC, respectively, proving the importance of orthogonal reaction monitoring methodology. This technology will afford researchers the long sought-after ability to conduct in situ phase selective reaction monitoring of complex biphasic systems and facilitate mechanistic studies into these widely utilized reaction conditions. 3.7 Experimental Section The boronic acids were purchased from Combi Blocks (3.6) and AmBeed (3.4 and 3.5). Pd XPhos G2 was purchased from AK Scientific. Potassium carbonate and 1-bromo-4-fluorobenzene were purchased from Sigma. Optima-grade UHPLC solvents were purchased from Fisher. All other reagents and solvents were purchased from conventional suppliers. All reagents and solvents were used as received. 3.7.1 NMR The HTS NMR instrument has several components. The magnet is a high-temperature superconducting (HTS) magnet (MR 9T4-54, iron-yoke NMR magnet) supplied by HTS-110 (Lower Hutt, New Zealand) and operating at 9.40 T (400.32 MHz for 1H, 376.82 for 19F, and 100 128.46 MHz for 11B observation). The magnet always operates in the driven mode with a current regulated by a high-stability power supply (Danfysik System 8500 model 854, Taastrup, Denmark). The cooling of the magnet is achieved by a Cryomech PT807 (Syracuse, NY) pulse tube cooler with a Cryomech CP2800 helium compressor. An air-cooled chiller (Huber Unichiller 040T, Offenburg, Germany) provides water cooling to the power supply. The NMR console is an AVANCE III HD NMR (Bruker BioSpin, Billerica, MA). Additional information on this NMR system can be found in reported articles by Amgen. NMR spectra were analyzed by using the software MNova. The abbreviations s, d, t, m signify singlet, doublet, triplet, multiplet respectively. 3.7.2 HPLC High pressure liquid chromatography (HPLC) samples were analyzed with an Agilent 1200 HPLC equipped with a DAD detector. HPLC data was acquired and formatted with OpenLAB ChemStation LC software. The injected samples were separated with InfinityLab Poroshell 120 Phenyl-Hexyl, 3×50 mm, 2.7 μm column. The detailed separation gradient is listed in Table 3.1. Table 3.1. HPLC Column and Separation Method Detail. Column: Phenyl-Hexyl 2.7 µm, 3.0 x 50 mm Column Temperature: r.t. Flow Rate: 0.65 mL/min Acquisition Time: 6.0 min run time 2.0 min post run time Mobile Phase: Solvent A = Water Solvent B = Acetonitrile with 0.1% formic acid 101 Mobile Phase Program: Time 0.00 min 0.10 min 1.50 min 4.00 min B% 0 40 40 100 Injection Volume: 50 nL 3.7.3 Other Hardware Table 3.2. Other hardware used in this study Item Vendor Product Name/Number : description Peristaltic pump Vapourtec SF10 reagent pump/50-1345 Solenoid valve Bürkert Type 6724/299250 : 3/2-way Whisper Valve with media separation 8-channel USB Relay Module Sainsmart USB Eight Channel Relay Board for Automation - 12 V 15,000 psi Internal Sample Injectors - 1/16" fittings VICI C84X-6574-.05D : Cheminert Nanovolume™ UHPLC Internal Sample Injector (50 nL) HPLC trigger cable (DB9 male- soldering pin 1 and 3) Yusuke Handmade Trigger HPLC analysis controlled by the relay module 102 3.7.4 Surface Modification of Stainless Steel Filter A stainless steel (SS) sintered metal filter (Scipro: A-302A, Solvent Filter inlet 1/4-28) was immersed in 5 M K2CO3 solution for 5 min under sonication. The SS filter was washed with DI water and air-dried 3 times before reaction monitoring. 3.7.5 Calibration Curve for NMR Reaction Monitoring After having the signal vs. base addition trend in hand, the next task should be quantifying the data, i.e., converting the spectroscopic signal into concentration. This requires the generation of a calibration curve as mentioned in the introduction section. For the BA calibration curve of HPLC data, I used the first 250 mM BA solution in MeTHF as a single-point calibration curve. However, for the NMR calibration curve, using the same method was challenging, as the acquisition changes dramatically after a few samples were taken (shown for 3.4 and 3.6 trends). This sudden change of NMR integral should not correspond to a real concentration change inside the flask, but a sudden change in the reaction matrices which could affect the shimming. As the important information was the concentration after the addition of base, I used the peak intensity after the sudden change as the marking point for single-point calibration in NMR. 3.7.6 Volume Change Caused an Increase of BA Peak Area in Organic Layer After the water addition, even though BA partially transferred from the organic layer into the aqueous layer, the organic layer concentration also increased. E.g., For 3.4, 50 mM of BA was transferred into the aqueous layer, while the organic layer concentration increased from 250 103 mM to 262 mM upon water addition. This indicates the organic layer has been concentrated by solvent decrease, i.e., MeTHF was partially dissolved into the aqueous layer. To take account of the quantity of the concentration change due to this solvent exchange, exact volume information of the miscibility of the MeTHF and water must be obtained. From the reported article, the solubility of MeTHF in water is 16.4 mL MeTHF in 100 mL water. As we know the exact moles of dosed boronic acid, the mass balance can be evaluated using Eq. 3.1. 𝑛𝐵𝐴𝑡𝑜𝑡𝑎𝑙 = 𝐶𝐵𝐴 𝑖𝑛 𝑜𝑟𝑔 ∙ 𝑉𝑜𝑟𝑔 + 𝐶𝐵𝐴 𝑖𝑛 𝑎𝑞 ∙ 𝑉𝑎𝑞 = 𝑐𝑜𝑛𝑠𝑡. (Eq. 3.1) For example, the partition test of Pyr-BA 3.4 (Figure 3.5) was evaluated (Table 3.1). The observation that the concentration of 3.4 increases in both layers is unexpected if the volume changes is not considered (Table 3.1. Region B not considering volume change), where the calculated mole (17.1 mmol) is 14% off from the actual added amount (15.0 mmol). However, when the reported solubility of MeTHF in water (9.84 mL MeTHF in 60 mL water) was taken into account (Table 3.1. Region B considering volume change), the mass balance showed a reasonable value (- 1%). Table 3.3. The evaluation of mass balance of Pyr-BA 3.4. 𝑛𝐵𝐴𝑡𝑜𝑡𝑎𝑙 = 15.0 mmol 𝐶𝐵𝐴 𝑖𝑛 𝑜𝑟𝑔(𝑀) ∙ 𝑉𝑜𝑟𝑔(𝑚𝐿) + 𝐶𝐵𝐴 𝑖𝑛 𝑎𝑞(𝑀) ∙ 𝑉𝑎𝑞(𝑚𝐿) Region A 0.25 ∙ 60 + 0 ∙ 0 = 15.0(𝑚𝑚𝑜𝑙) Region B considering volume change 0.263 ∙ 50.2 + 0.226 ∙ 69.8 = 14.8(𝑚𝑚𝑜𝑙) Region B not considering volume change 0.263 ∙ 60 + 0.226 ∙ 60 = 17.1(𝑚𝑚𝑜𝑙) Actual volume change was also tested using a graduated cylinder. 25 mL of MeTHF (Figure 3.15 left) was poured into 25 mL of pure water in a graduated cylinder (Figure 3.15 right). 104 After the addition of water, the bottom layer (aqueous layer) volume increased from 25.0 mL to 27.2 mL, while the top layer (organic layer) volume decreased from 25.0 mL to 21.3 mL. The actual volume test also proved that the MeTHF dissolved in water. Figure 3.15 Volume test by mixing 25 mL of MeTHF and 25 mL of water. Left: before the addition of 25 mL of pure water; right: after the addition of 25 mL of pure water. 3.8 General Reaction Monitoring Procedure Monitoring experiments were performed in Mettler-Toledo EasyMax 102 Advanced Thermostat System to enable online control of temperature and stir rate via iControl software. A Mettler-Toledo 50 mL one-piece glass reactor was used, with a SF-10 pump in/out, an N2 gas line, and an oil bubbler attached to it. The pump-in tube tip was equipped with either the polyethylene filter (QLA: FIL 010-PT-a, 10 Micron Porous Filters, 1/8” ID UHMW Polyethylene) for organic layer sampling or the base modified SS filter for aqueous layer sampling. 105 3.8.1 Flow NMR (Organic Layer Monitoring) To a glass reactor (Mettler Toledo, EasyMax) equipped with a stir bar was added a boronic acid. The flask was purged with N2 gas for 10 min. MeTHF and mesitylene were added as an internal standard (for partition tests), and the mixture was stirred vigorously at room temperature. The SF-10 pump started sampling the organic layer at 0.5 mL/min and initiated the flow NMR monitoring after an initial shimming. Water and 5 M K2CO3 solution were then sequentially added under N2. Additionally, Pd XPhos G2 was added to initiate the reaction for Suzuki Miyaura cross coupling reactions. The monitoring continued at the same flow rate. 3.8.2 Flow NMR (Aqueous Layer Monitoring) To a glass reactor (Mettler Toledo, EasyMax) equipped with a stir bar was added a boronic acid. The flask was purged with N2 gas for 10 min. MeTHF, water and mesitylene were added as an internal standard (for partition tests), and the mixture was stirred vigorously at room temperature. The SF-10 pump started sampling the aqueous layer at 0.5 mL/min and initiated the flow NMR monitoring after an initial shimming. 5 M K2CO3 solution was then sequentially added under N2. Additionally, Pd XPhos G2 was added to initiate the reaction for Suzuki Miyaura cross coupling reactions. The monitoring continued at the same flow rate. 3.8.3 Online HPLC (Organic and Aqueous Layer Monitoring) To a one-piece glass reactor (Mettler Toledo, EasyMax) equipped with a stir bar were added a boronic acid and trimethoxy benzene as an internal standard (for partition tests). The flask was purged with N2 gas for 10 min. MeTHF was added, and the mixture was stirred vigorously at room temperature. The SF-10 pump started sampling the organic layer at 0.5 mL/min and initiated 106 online HPLC. After water was added, the organic layer and aqueous layer were injected into HPLC in turns (Section 3.9.3). 5 M K2CO3 solution was then sequentially added under N2. Additionally, PdXPhos G2 was added to initiate the reaction for Suzuki Miyaura cross coupling reactions. The more detailed hardware connections and sampling scheme are described in the next section. 3.9 Detail of Online HPLC Platform 3.9.1 HPLC Sample Valve Cheminert Nanovolume™ UHPLC internal sample injector (VICI) was used as an HPLC sampling valve. This valve head has a 50 nL sample slot inside the valve head (Figure 3.16). The valve has two positions, position A (load position) and position B (inject position). The internal sample loop is filled with reaction solution in the position A, and the loaded sample is injected to HPLC when the valve switches to the inject position for the HPLC analysis. Figure 3.16 Illustration of the 4-port Cheminert Nanovolume™ UHPLC internal sample injector (VICI). A. Load position; B. Inject Position 107 3.9.2 Organic and Aqueous Selective Sampling Mode of Online HPLC To enable both organic and aqueous reaction monitoring in one experiment, the solenoid valve (Bürkert) plays an important role in selecting which layer circulates through the entire line, containing the HPLC sample loop. While Figure 3.17 illustrates a sample loading diagram for the organic selective mode, in which the solenoid valve is at an organic selective position, and the Vici valve is at position A (Figure 3.16), Figure 3.18 did aqueous selective mode with the sample loop filled with an aqueous layer. Figure 3.17. Online HPLC platform diagram at organic sampling state Figure 3.18. Online HPLC platform diagram at aqueous sampling state 3.9.3 Detailed Steps of Online HPLC Sampling The following steps describe the detailed actions during the sample injection to HPLC. 108 1. Solenoid valve and Vici valve switch to the initial position, organic selective position and position B (inject position) respectively. 2. The entire line is filled with the organic solution. For the first injection, the entire line is initially filled with N2 gas, requiring 3 min to fill the line. 3. Vici valve switches to position A (load position). The resting state of HPLC is pumping 100 % pure water, so 50 nL pure water filled in the internal sample loop is released to the reactor during this step. 4. Before the sample injection, HPLC is triggered and equilibrates HPLC mobile phase to 60/40 = A/B for 1.5 min. 5. Vici valve switches to position B (inject position) to inject the loaded sample. 6. The solenoid valve switches to the aqueous selective position, filling the entire line with the next solution (organic or aqueous) during the sample analysis by HPLC (sample acquisition time = 8 min) 7. Repeat steps 3-7 for the monitoring. 3.10 Experimental Procedure 3.10.1 Partition Coefficient Test 3.10.1.1 Online HPLC To a 50 mL one-piece glass reactor (Mettler Toledo, EasyMax) equipped with a stir bar were added boronic acid (6.25 mmol), 1,3,5-trimethoxybenzene (12.5 mmol) MeTHF (25 mL) (Figure 3.5,3.6,3.7 A). The mixture was stirred vigorously at room temperature. To the mixture, water (25 mL) was added (Figure 3.5,3.6,3.7 B). To the mixture, 5.0 M K2CO3 solution was 109 sequentially added (0.25 eq. in total: Figure 3.5,3.6,3.7 C, 0.50 eq. in total: Figure 3.5,3.6,3.7 D, 1.0 eq. in total: Figure 3.5,3.6,3.7 E, 2.0 eq. in total: Figure 3.5,3.6,3.7 F.) 3.10.1.2 Flow NMR To a 100 mL glass reactor (Mettler Toledo, EasyMax) equipped with a stir bar were added boronic acid (15.0 mmol), mesitylene (15.0 mmol) MeTHF (60 mL) (Figure 3.5,3.6,3.7 A). The mixture was stirred vigorously at room temperature. To the mixture, water (60 mL) was added (Figure 3.5,3.6,3.7 B). To the mixture, 5.0 M K2CO3 solution was sequentially added (0.25 eq. in total: Figure 3.5,3.6,3.7 C, 0.50 eq. in total: Figure 3.5,3.6,3.7 D, 1.0 eq. in total: Figure 3.5,3.6,3.7 E, 2.0 eq. in total: Figure 3.5,3.6,3.7 F). 3.10.2 Suzuki Miyaura Coupling Reaction 3.10.2.1 Online HPLC A 50 mL one-piece glass reactor (Mettler Toledo, EasyMax) equipped with a stir bar was purged with N2. To the reactor were added 2-fluoro-5-pyridyl-boronic acid (880.7 mg, 6.25 mmol), 1-bromo-4-fluorobenzene (0.69 mL, 6.25 mmol), 2-methyltetrahydrofuran (25 mL), 5.0 M K2CO3 solution (2.5 mL, 12.5 mmol) and water (25 mL). The mixture was stirred vigorously at room temperature. The reaction was initiated by addition of 0.125 M XPhos Pd G2 as slurry mixture (2.5 mL, 0.313 mmol). The reaction was monitored for 14 hours. 3.10.2.2 Flow NMR A 100 mL glass reactor (Mettler Toledo, EasyMax) equipped with a stir bar was purged with N2. To the reactor were added 2-fluoro-5-pyridyl-boronic acid (2.114 g, 15.0 mmol), 1-110 bromo-4-fluorobenzene (1.65 mL, 1.5.0 mmol), 2-methyltetrahydrofuran (60 mL), 5.0 M K2CO3 solution (6.0 mL, 30.0 mmol) and water (60 mL). The mixture was stirred vigorously at room temperature. The reaction was initiated by addition of 0.125 M XPhos Pd G2 as slurry mixture (6.0 mL, 0.750 mmol). The reaction was monitored for 12 hours. 3.11 Zaiput Membrane Separator A membrane-based flow separator (SEP-10 Zaiput Flow Technologies) was also tested in my initial study to achieve phase selective sampling. A hydrophobic membrane (OB-900-S10) was used, thus allowing the organic phase to permeate it, while the aqueous phase passed over (Figure 3.19). Figure 3.19. Diagram of the sampling platform is shown in figure SX. After the liquid/liquid biphasic mixture was separated, an x-type selector chose which layer to deliver to the HPLC analysis. A phase selective sampling platform using the membrane separator was developed (Figure 3.20). The HPLC sample injection line shared a similar system to the two filter system 111 (Figure 3.3). However, the membrane separator required constant pumping of both organic and aqueous layers. Therefore, I installed an x-type selector to select one layer to pump through the HPLC sample loop while the other solvent was bypassed and returned to the reactor. Figure 3.20. Diagram of phase selective sampling platform using s Zaiput membrane separator. This membrane separator worked well for separating simple mixtures of MeTHF and water (Figure 3.21, left). The water was colored using a red food dye. However, when I conducted a biphasic Suzuki Miyaura cross coupling reaction, the membrane resulted in a poor separation due to the buildup of solid palladium particles on the membrane surface (Figure 3.21, right). 112 Figure 3.21. Liquid/liquid separation of MeTHF and water with a red food dye by a Zaiput membrane separator (left). Fouling of palladium black on the membrane (right). 3.12 Identification of KBr formation in the Aqueous Layer In online HPLC monitoring of Suzuki Miyaura cross coupling reaction (Section 3.5), KBr formation was discussed. Since bromide ion is difficult to be monitored by most PATs, the details of HPLC data are discussed in this section. Figure 3.22 compares two HPLC spectra from the conducted reaction in Section 3.5. The top spectrum is from the aqueous sample before the reaction was initiated by the addition of base and palladium, showing only two starting materials. On the other hand, the end reaction sample had a new peak at retention time = 1.74 min. Since the HPLC injection for online HPLC monitoring happened at retention time = 1.5 min (described in Section 3.9.3), the new peak was located right after the sample injection. 113 Figure 3.22. HPLC spectra at 210 nm of two aqueous samples from Suzuki Miyaura cross coupling reaction in Section 3.5. Before the reaction (Top) and End of the reaction (bottom). The early retention time in reverse phase HPLC indicated the new peak was a very polar compound. The first prediction was boric acid due to its observation in flow NMR. However, the boric acid injection into HPLC resulted in no peak due to the low UV absorption of boric acid. On the other hand, KBr in the water sample showed identical retention time and UV spectrum (Figure 3.23). Before rxnAfter rxnF-Pyr-BABrF-Ph-Br114 Figure 3.23. (a) HPLC spectrum at 210 nm of post-reaction sample from Suzuki Miyaura cross coupling reaction in Section 3.5. (b) UV spectrum of the first peak. (c) HPLC spectrum at 210 nm of KBr in water. (d) UV spectrum of the first peak. (a) (b)(c)(d)Sample Injection115 Chapter 4: Gold Nanoclusters (AuNCs): HPLC Analysis for Complex Reaction Mixtures 4.1 Introduction Atomically precise gold nanoclusters (AuNCs) are unique compared with traditional nanoparticles in terms of their smaller size.187,188 Unlike traditional nanoparticles, nanoclusters are isolated as monodisperse species with defined molecular formulae and structures.189,190 AuNCs have molecule-like electronic energy levels and discrete absorption bands.188,191 Their unique properties make AuNCs of interest in many different fields due to their potential luminescence,192 catalytic activity,189,193–196 and semiconductor-like properties.197–199 Recently, the development of diverse synthetic methodologies has enabled selective synthesis and isolation of a wide variety of AuNCs with different gold and ligand compositions.197 Among the reported AuNCs, those protected by N-heterocyclic carbenes (NHCs) have gained increasing attention due to their remarkable quantum yield, stability, and catalytic activity.200,201 Along with the chemical synthesis development, various analytical technologies have been utilized in AuNCs characterization, including EEM, 202 UV-Vis spectroscopy,203 XRD,204,205 and NMR spectroscopy.206 Although these techniques have provided detailed characterization data, they can only be used after full isolation and purification of the compounds. The ability to monitor a process as it occurs is incredibly powerful, yielding far more information about the mechanism and potential optimization.135,207 However, the use of process analytical technology (PAT) to monitor AuNCs reactions in real time has remained stunted. This is mainly because the crude reaction of NCs synthesis contains polydisperse NCs, which has dramatically increased 116 complexity.190,208 Using the above-mentioned analytical techniques to probe such a crude reaction mixture would be challenging. The most frequently used monitoring techniques are UV-Vis209 and mass spectrometry,210 which suffer from limitations of low resolution and quantifiability respectively. This inherently limits our understanding of cluster formation mechanisms and renders comprehensive optimization nearly impossible. As such, the lack of proper techniques for assessing real-time cluster formation and relative purity is a significant omission from the literature. Reverse phase HPLC (RP-HPLC) has shown excellent capabilities to separate AuNCs mixtures with various ligands.211,212 Regarding the assessment of bulk purity, HPLC has demonstrated powerful capabilities to show product and side product compositions with high separation capability.213,214 Despite the importance of HPLC, the applications are still limited to endpoint analysis or preparative purposes in the field of NCs synthesis. I herein report the application of continuous reaction monitoring of the synthesis of NHC-protected AuNCs by LC-MS to examine and understand the details of NC synthesis. I chose the Au13 and Au24 nanoclusters, [Au13(NHC)9Cl3]Cl2 (4.1) and [Au24(NHC)14Cl2H3][BF4]3 (4.2) respectively (Figure 4.1), reported by the collaborator, Crudden et al., as my target in this research.200,215 The effect of temperature, HCl etching, dosing rate and starting materials were explored using LC-MS. Previously unidentified intermediates were unveiled to provide mechanistic insights. 117 Figure 4.1. X ray structures of [Au13(NHC)9Cl3]Cl2 (4.1) (left) and [Au24(NHC)14Cl2H3][BF4]3 (4.2) (right). 4.2 HPLC Method Development Since this study demonstrates the first application of RP-HPLC to separate AuNCs stabilized by NHC ligands, an HPLC method needed to be developed. The method was optimized to minimize elution times while retaining the resolution of each component. A separation method was developed using a reaction mixture containing [Au13(NHC)9Cl3]Cl2 (4.1), NHC-Au(I)-Cl (4.3), and [NHC-Au(I)-NHC]+ (4.4), prepared according to literature procedure.200 Three different HPLC mobile phase combinations were tested to separate these components utilizing a solvent gradient in which the percentage of water was changed from 5 % to 100 % over 2.3 minutes (Figure 4.2). 118 Figure 4.2 Methods development for RP-HPLC-MS. Top, green: A water/acetonitrile gradient with 0.1 % formic acid. Middle, blue: a water/methanol gradient with 0.1 % formic acid. Bottom, red: a water/methanol gradient with 0.1 % TFA. When water/acetonitrile with 0.1 % formic acid (FA) was used as a mobile phase pair, a large peak was observed beside the bis-NHC complex 4.4 peak (Figure 4.2, green). This peak was identified as [NHC-Au(I)-MeCN]+ (4.5) by the observed mass signal (m/z 536.0), suggesting acetonitrile was nucleophilic and exchanged with one ligand. Moreover, Au13 NC 4.1 was not eluted, likely due to its low solubility in acetonitrile. Replacing acetonitrile with methanol resulted in successful elution and resolution of all components (Figure 4.2, blue). Finally, a method with 0.1% trifluoroacetic acid (TFA) in both water and methanol was applied and further improved the resolution (Figure 4.2, red). The increased aqueous phase acidity successfully sharpened the peak for 4.1. This optimized HPLC separation method achieved a good resolution of 4.1, 4.3, and 4.4 with sufficiently 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0HPLC Absorbance at 290 nm (A.U.)Retention Time (min)4.44.14.1 was not elutedWater/MeCN with FAWater/MeOH with FAWater/MeOH with TFA4.14.34.44.3 4.44.1 4.3 4.4NNBnBnAu N MeNNBnBnAuBnBnNN[Au13(NHC)9Cl3]2+4.5119 short elution time, which allowed frequent sampling within the course of the length of NHC-supported AuNC synthesis. However, the reaction mixture was expected to be a more complicated mixture of polydisperse AuNCs than this simple three-component sample. As such, the method was further investigated using samples from the reaction mixture without purification. 4.3 Analytical Method Development Four samples at essential stages within the reaction based on the originally reported procedure (Scheme 4.1) were taken and analysed using the water/MeOH with TFA modifier with a slower gradient. The four samples were taken of 4.3 dissolved in DCM, right after reducing agent (NaBH4) addition, 3 hours after the reaction had been initiated, and after the HCl etching process (Figure 4.3). Scheme 4.1. Published method for the synthesis of [Au13(NHC)9Cl3]Cl2 (4.1). After the addition of NaBH4 (Figure 4.3 B and C), many species other than the known 4.1, 4.3 and 4.4 appeared in the spectrum, indicating polydisperse AuNCs formation triggered by the reducing reagent. The concentrated HCl addition brought down most of the peaks except the stable 4.1 (Figure 4.3 D), proving the effective “size-focusing” process reported by literature.200,216,217 N NBn BnAuClHCl (1.0 eq.)DCM1.5 hr at 0 °C1.5 hr at r.t.Polydisperse gold clusters[Au13(NHC)9Cl3]Cl2NaBH4 in EtOH(100 mM, 1.0 eq.)4.34.0mMEtching4.1120 Figure 4.3. Chromatogram of the synthesis of 4.1 taken at four critical points in the reaction. A. Sample taken before the addition of NaBH4. B. Sample taken immediately following the addition of NaBH4 C. Sample taken after the 3 hour reaction. D. Sample taken after HCl etching. The many overlapping and unidentified peaks in the HPLC chromatogram stemmed from the similarity among the generated polydisperse AuNCs and required a split of the chromatogram into five regions to simplify the analysis (Figure 4.3 B and C). RP-HPLC separates AuNCs by their sizes.211,218 Therefore, species with a lower mass to charge (m/z) 121 ratio have the shortest retention time and species with a larger m/z ratio have longer retention time. The smallest NHC-Au(I)-Cl 4.3 followed by the bis NHC Au complex 4.4 have the shortest retention time. The chromatogram can then be separated into three groups (small, medium, and large regions) according to their retention time. The small region included species which had a retention time of 6.5 to 8.5 minutes and m/z values between 1000 and 2600. The medium region, which contained 4.1 and other by-products, extended from 8.5 to 9 minutes and contained m/z values ranging from 2600 to 3000. Lastly, the large region contained all species with retention times longer than 9 minutes and m/z larger than 3000. No mass signals were observed in the large region due to the m/z limit of the used mass spectrometer (max m/z 3000). 4.4 Reaction Monitoring of [Au13(NHC)9Cl3]Cl2 (4.1) Synthesis With the analytical methods in hand, the synthesis of 4.1 following original procedure was monitored by continuous sampling (Figure 4.4). 122 Figure 4.4. Analysis of the Au13 reaction over time. The total peak area of each region was analyzed and monitored over the course of the reaction. Reaction conditions: 4 mM of 4.3 in 1 mL of DCM, cooled in an ice-bath for 10 mins, then the addition of 40 μL NaBH4 (100 mM, 1 eq) EtOH solution. The reaction was monitored for 1 hour at 0 °C and for 2 hours at room temperature. After 3 hours concentrated HCl solution (12 M, 0.33 μL, 1 eq.) was added to the reaction. After the addition of NaBH4, 4.3 was completely and rapidly consumed (purple trend Figure 4) while [NHC-Au-NHC]+ (4.4) increased dramatically (red trend Figure N NBn BnAuClHCl (1.0 eq.)DCM1.5 hr at 0 °C1.5 hr at r.t.Polydisperse gold clusters[Au13(NHC)9Cl3]Cl2NaBH4 in EtOH(100 mM, 1.0 eq.)4.34.0 mMEtching4.10400080001200016000200000200040006000800010000-0.5 0.5 1.5 2.5 3.5HPLC Peak Area (mAu) of 4.4HPLC Peak Area (mAu)Reaction Time (hour)NaBH4 addition under 0 °CRoom temperatureHCl etchingNHC-Au(I)-Cl (4.3) [NHC-Au(I)-NHC]+ (4.4)Small regionMedium regionLarge region123 4). Such substantial increase in peak area suggests that 4.4 is a by-product during the reaction. This type of bi-ligand complex as a by-product was also previously discovered in thiolate-protected AuNC synthesis, but this evidence supports that it performs a similar role in the formation of NHC-supported AuNCs. No free NHC salt was detected in the LCMS spectra, indicating the ligand transfer to form 4.4 was immediate. In addition to the formation of the byproduct, NHC-AuNC species in the small and medium regions rapidly formed right after the NaBH4 addition. Monitoring the reaction at 0 °C from 0 – 1.5 h, the rate of growth of the medium region slowed down, and the species in the small region gradually diminished. This was coupled with the slow growth of NHC-AuNC species in the large region. These results indicate that the formation of large AuNCs occurred through smaller NHC-AuNC intermediates. After 1.5 hours under 0 °C, the reaction was warmed to room temperature at which point transformations were accelerated. In the first 30 minutes after heating, the small region clusters rapidly vanished with the HPLC peak area dropping to almost zero. During this time, the medium region remained unchanged whereas the large region grew and some amount of 4.3 reformed. This indicates that clusters grow sequentially from the small region to the medium region to the large region. The increase in temperature also caused the decomposition of more thermally unstable intermediates to 4.3. From 2 – 3 hours in the reaction, 4.3, 4.4, and the small region remain unchanged in area. In this time period, clusters in the large region were increasing at a slightly faster rate than before, while the medium region species were consumed. It was noticed that this 124 acceleration happened after no small region NCs remained, indicating that the presence of small region NCs suppressed the transformation from medium to large NCs. After the concentrated HCl was added and the etching process started, I observed that the total peak area of all AuNC regions decreased while the desired product 4.1 peak remained unchanged in the HPLC spectrum (Figure 4.3D). After the HCl etching process, the product was isolated and characterized by both HPLC and high-resolution mass spectrometry (HRMS). The HRMS suggested the peak isolated is Au13 (Section 4.15), and the retention time was the same as during the reaction. The transformations between different regions of NCs provide a general picture of this AuNCs synthesis process. In addition to the cluster transformations between small, medium, and large regions, the combination of HPLC and mass spectrometry can also provide insights into interchanges of AuNCs species within the medium region. Cluster species identified in the medium region were [Au13(NHC)9Cl3]Cl2 4.1 and [Au24(NHC)14Cl2H3][BF4]3 4.2, and a newly detected species with m/z = 2774 (Figure 4.5). Based on the detected mass, this species was assumed as [Au14(NHC)9Cl3]Cl2. This cluster has not been isolated and characterized, due to its poor stability and transient nature. 125 Figure 4.5 Reaction spectra from both HPLC and mass spectrometry extracted of reaction time at 0 hour (top), 30 minutes (middle), and 1 hour (bottom). 4.1 (shaded in red), 4.2 (shaded in yellow) and a newly identified AuNC [Au14(NHC)9Cl3]2+ (shaded in blue) were shown in the figure. In the LC and mass spectra, I observed that the predominant peak in the medium region immediately after NaBH4 addition was the Au14 NC (Figure 4.5, blue). After 30 minutes at 0 °C, 4.1 and 4.2 peaks became larger while the Au14 NC peak diminished. This observation indicates that Au14 NC is a kinetically favored product, while 4.1 and 4.2 are thermodynamically favored products. After concentrated HCl was added and the etching process started, I observed that 4.2 disappeared after an hour while the desired product (4.1) peak remained unchanged in terms of the peak area (Figure 4.3D). 126 4.5 Optimization of the [Au13(NHC)9Cl3]Cl2 (4.1) Synthesis From the real-time reaction monitoring of the 4.1 synthesis by LC-MS, I learned that the major by-product was 4.4 and the major side product was large region AuNCs. As a result, reducing the formation of the large size NCs can potentially increase the yield of 4.1. In studies on thiol-protected nanoclusters, it has been shown that the stoichiometric addition of NaBH4 can improve selectivity and prevent the formation of larger undesired NCs.210 I hypothesized that using stepwise dosing of NaBH4 instead of dosing 1 equivalent of NaBH4 at once can reduce the formation of larger AuNCs. Not only would this limit over-reduction, but it would also allow for the effective titration of the NCs with the reducing reagent to observe intermediate AuNCs more clearly as well as monitor their formation and consumption. NaBH4 was added stepwise in 0.2 equivalent doses, and the reaction was continuously analyzed by LCMS to monitor subsequent changes (Figure 4.6). After the first NaBH4 addition, 40 % of 4.3 was consumed, and the bis-NHC Au complex 4.4 along with NHC-AuNCs in the small and medium regions quickly formed. After 15 minutes, the amount of 4.3 unexpectedly increased by about 15%. Simultaneously, the small and medium regions and 4.4 decreased. This dynamic phenomenon indicated that there was a series of transformations occurring between the 4.3, small, medium NCs and 4.4. 127 Figure 4.6 Au13 NC synthesis by sequential doses method. Reaction condition: 4 mM of 4.3 in 3 mL of DCM under r.t. 24 μL NaBH4 (100 mM, 0.2 eq) EtOH solution was dosed into the reaction successfully. Due to these changes, I hypothesized that the initially formed small and medium NCs were not thermodynamically stable, instead being kinetically formed after the generation of Au(0). As they decomposed or interconverted to the other AuNCs over a short period of time, they released Au(I) back into the solution, where the newly released Au(I) re-associated with 4.4 and reformed two molecules of 4.3. N NBn BnAuClDCMr.t.NaBH4 in EtOH(20 mM, 0.2 eq. portional dose)4.34.0 mM[Au13(NHC)9Cl3]Cl24.10400080001200016000200000.0 1.0 2.0 3.0 4.0HPLC Peak Area (mAu)Experimental Time (hour)NHC-Au(I)-Cl (4.3) [NHC-Au(I)-NHC]+ (4.4)Small regionMedium regionLarge region0.2 eq. NaBH4 addition128 Repeated dosing showed that until the total amount of NaBH4 added was 1.0 equivalents, each 0.2 equivalent addition caused similar changes in peak area in each region. Despite the reforming of 4.3 slightly after each addition of NaBH4, 4.3 was still being consumed until 0.8 equivalents of NaBH4 were added. This overall consumption of 4.3 accumulated stable AuNCs (i.e., 4.1 and 4.2) which were thermodynamically stable and survived over time. As the stable NCs accumulated so did 4.4 further supporting its role as a necessary by-product in the formation of 4.1 and 4.2. The 5th addition of 0.2 equivalents of NaBH4 completely and irreversibly consumed 4.3. At the same time, I observed the large region AuNCs formed at a higher rate than before. I hypothesize that NaBH4 preferentially reacts with 4.3 over small or medium AuNCs. Only after the full consumption of 4.3, the NaBH4 can now react with AuNCs in the small or medium region. The different aggregation paths caused larger region AuNCs formation. Using stepwise addition of NaBH4, AuNC formation in the large m/z region was successfully suppressed. However, the desired Au13 had not significantly increased in the peak area, while significant amount of Au24 and unreactive biproduct 4.4 were still formed (Section 4.13). 4.6 Reaction Monitoring of [Au24(NHC)14Cl2H3] [BF4]3 (4.2) Synthesis A recently reported Au24 nanocluster (4.2) obtained by reduction of [NHC-Au-Py]BF4 (4.6) (Py = Pyridine) bears the same NHC with a distinctly different metal core to the aforementioned Au13 NC (4.1) (Figure 4.1). The structural difference between 4.1 and 4.2 cores suggests that the reaction kinetics and mechanism of formation are distinctly 129 different. Using HPLC reaction monitoring also afforded insights into this cluster’s formation (Figure 4.7). In the synthesis of 4.2 (Figure 4.7), a lower concentration of 4.6 was used compared to the synthesis of 4.1 due to its lower solubility in toluene (1.5 mM vs. 4.0 mM previously). After taking an initial HPLC sample, 1.0 eq. of NaBH4 EtOH solution was added to the reactor. 4.6 was immediately consumed, while small region NCs and 4.4 were formed. In contrast to the synthesis of 4.1, the medium region NCs were slowly formed, and the large region NCs were not formed significantly. HPLC-MS showed that the medium region consisted primarily of 4.2 (m/z 2992) with 4.1 identified as a minor product. Instead of a single bis-NHC Au complex peak, two peaks were observed for the bis-NHC by-product in this reaction. These two peaks both had m/z 793, which indicates the two peaks correspond to [NHC-Au-NHC]+ coordinated with two different counter ions (BF4- and Cl-) (Section 4.16). 130 Figure 4.7 Analysis of the Au24 synthesis reaction over time. The total peak area of each region was analysed and monitored over the course of the reaction. Reaction conditions: 1.5 mM of 4.6 in 1 mL of toluene, cooled in ice bath for 10 mins, then the addition of 100 μL NaBH4 (15 mM, 1 eq) in EtOH dropwise and DCM (50 μL). The reaction was allowed to warm to r.t. and monitored for 2 hours. By comparing the reaction monitoring data of the synthesis of 4.2 to that of 4.1, Au3NHC3 located in the small region had a significantly higher peak area, suggesting that this intermediate is a key precursor for the formation of 4.2 (Section 4.16). N NBn BnAuPytoluene2.0 hr at r.t.[Au24(NHC)14Cl2H3][BF4]3NaBH4 in EtOH(15 mM, 1.0 eq.)50 µL DCM4.61.5 mM4.2BF4010002000300040005000-0 .5 0 0.5 1 1.5 2HPLC Peak Area (mAu)Reaction Time (hour)NaBH4 addition[NHC-Au-Py]BF4 (4.6) [NHC-Au(I)-NHC]+ (4.4)Small regionMedium regionLarge region131 The behavior of 4.4 indicated it was likely a transient intermediate. The consumption of 4.4 was only observed in the sequential experiment of the Au13 synthesis, where I hypothesized the consumption of the 4.4 was because of the release of Au(I) from the decomposition of unstable AuNCs. However, during the synthesis of 4.2, the formation of 4.6 was not observed. Thus, the net consumption of the 4.4 after its initial formation can indicate that it can be used in AuNC formation. However, the true mechanism of the fate of 4.4 needs more experimental investigation. 4.7 Conclusion In conclusion, I have demonstrated the use of HPLC-MS as an analytical tool to monitor the synthesis of NHC-AuNCs. By developing a quick HPLC eluting method by using water/MeOH with the TFA system, I enabled frequent sampling while also keeping a certain amount of resolution for NHC-AuNCs mixture. Regional analysis methodology demonstrated the successful visualization of dynamic transformation between NHC-AuNCs with small, medium, and large m/z values. The coupled ESI-MS provided concomitant information to characterize existing AuNC species in each region. 132 4.8 General Information All reagents and solvents were purchased from Millipore Sigma, Oakwood and Alfa Aesar, and used as received. 1,3-dibenzyl-1H-benzo[d]imidazol-3-ium chloride, (1,3-dibenzyl-1H-benzo[d]imidazol-2-ylidene) gold(I) chloride, and (1,3-dibenzyl-1H-benzo[d]imidazol-2-ylidene)(pyridin-2-yl)gold tetrafluoroborate were synthesized according to literature procedures. Optima-grade UHPLC solvents were purchased from Fisher. High-resolution mass spectrometry (HRMS) data was acquired by the UBC Department of Chemistry Mass Spectrometry Center. The Liquid Chromatography (LC) samples were analyzed by HPLC/MS conducted on an Agilent 1200 HPLC. HPLC data was acquired and formatted with OpenLAB ChemStation LC software. 4.9 HPLC Methods The HPLC gradient used when developing separation methods. Table 4.1. HPLC method for separation development using acetonitrile and formic acid as modifier Column: EC-C18 2.7 µm, 3.0 x 50 mm Column Temperature: 35 °C Flow Rate: 0.65 mL/min Detection: 290 nm Acquisition Time: 8.0 min run time 4.0 min post run time Mobile Phase: Solvent A = Water with 0.1% formic acid Solvent B = Acetonitrile Mobile Phase Program: Time 0.00 min 0.10 min 8.00 min B% 50 100 100 Injection Volume: 3 μL 133 Table 4.2. HPLC method for separation development using methanol and formic acid as modifier Table 4.3. HPLC method for separation development using methanol and TFA as modifier Column: EC-C18 2.7 µm, 3.0 x 50 mm Column Temperature: 35 °C Flow Rate: 0.65 mL/min Detection: 290 nm Acquisition Time: 8.0 min run time 4.0 min post run time Mobile Phase: Solvent A = Water with 0.1% formic acid Solvent B = Methanol Mobile Phase Program: Time 0.00 min 0.10 min 8.00 min B% 50 100 100 Injection Volume: 3 μL Column: EC-C18 2.7 µm, 3.0 x 50 mm Column Temperature: 35 °C Flow Rate: 0.65 mL/min Detection: 290 nm Acquisition Time: 8.0 min run time 4.0 min post run time Mobile Phase: Solvent A = Water with 0.1% TFA Solvent B = Methanal with 0.1% TFA Mobile Phase Program: Time 0.00 min 0.10 min 8.00 min B% 50 100 100 Injection Volume: 3 μL 134 Table 4.4. HPLC method for reaction monitoring Table 4.5. HPLC method for separation development using methanol and TFA as modifier Column: EC-C18 2.7 µm, 3.0 x 50 mm Column Temperature: 35 °C Flow Rate: 0.45 mL/min Detection: 210-360 nm Acquisition Time: 12.0 min run time 4.0 min post run time Mobile Phase: Solvent A = Water with 0.1% formic acid Solvent B = Acetonitrile Mobile Phase Program: Time 0.00 min 0.10 min 8.00 min 12.00 min B% 50 100 100 100 Injection Volume: 3 μL Spray chamber Method of spray chamber: API-ES Drying gas flow (l/min) 11.0 -13.0 Nebulizer pressure (psig) 35-60 Drying gas temperature (°C) 350 Capillary voltage (V) 3000 MSD signal settings Signal 1 Positive, Scan Mass range 200 - 3000 Threshold 150 Speed (u/sec) 3467 Signal 2 Positive, Scan Mass range 2500 - 3000 Threshold 150 Speed (u/sec) 1040 135 4.10 Synthetic Procedures 4.10.1 1,3-dibenzyl-1H-benzo[d]imidazolium chloride 1,3-Dibenzyl-1H-benzo[d]imidazolium chloride was prepared according to a published procedure.201 2.36 g of benzimidazole was used, and 3.25 g of the product was obtained (yield 49%). 4.10.2 (1,3-Dibenzyl-1H-benzo[d]imidazol-2-ylidene)gold(I) chloride (4.3) (1,3-Dibenzyl-1H-benzo[d]imidazol-2-ylidene)gold(I) chloride was prepared according to a published procedure.200 334.9 mg of benzimidazole was used, and 403.2 mg of the product was obtained (yield 76%). N NBn BnCl4.3N NBn BnAuCl136 4.11 General Reaction Monitoring Procedure 4.11.1 [Au13(NHC)9Cl3]Cl2 (4.1) Synthesis (Section 4.4) Monitoring Procedure In an HPLC vial, under air, 4.3 (2.12 mg, 4 μmol) was dissolved in DCM (1.0 mL), and the solution was cooled in an ice-cold water bath for ca. 10 min. This HPLC vial was constantly sampled by an Agilent HPLC/MS with a 15-minute time interval during the following steps for reaction monitoring. In another flask, 5 mL of 100 mM NaBH4 (18.9 mg) in ethanol was prepared. The NaBH4 in EtOH solution (40 μL, 1 eq.) was added into the 4.3 solution in one portion, and the solution was mixed well. The solution was left at 0 °C for 1.5 hours and then at r.t. for 1.5 hours. Concentrated hydrochloric acid (12 M, 0.33 µL, 1 eq.) was added, and the reaction was monitored for 1 hour., after which the solution changed color from dark brown to clear orange. 4.11.2 [Au13(NHC)9Cl3]Cl2 (4.3) Synthesis by Sequential Dose (Section 4.5) Monitoring Procedure In an HPLC vial, under air, 4.3 (2.12 mg, 4.0 μmol) was dissolved in DCM (1.0 mL), and the solution was cooled in an ice-cold water bath for ca. 10 min. This HPLC vial was constantly sampled by an Agilent HPLC/MS with 15-minute time interval during the following steps for N NBn BnAuClHCl (1.0 eq.)DCM1.5 hr at 0 °C1.5 hr at r.t.Polydisperse gold clusters[Au13(NHC)9Cl3]Cl2NaBH4 in EtOH(100 mM, 1.0 eq.)4.34.0mMEtching4.1N NBn BnAuClDCMr.t.NaBH4 in EtOH(20 mM, 0.2 eq. portional dose)4.34.0 mM[Au13(NHC)9Cl3]Cl24.1137 reaction monitoring. In another flask, 15 mL of 20 mM NaBH4 (11.4 mg) in ethanol was prepared. The NaBH4 in ethanol solution (40 uL, 0.20 eq.) was added into the 4.3 solution 0.2 equivalents and monitored for 30-45 minutes. Repeated the addition of 0.2 eq. NaBH4 solution until 1.0 equivalent was added. 4.11.3 [Au24(NHC)14Cl2H3] [BF4]3 (4.2) Synthesis (Section 4.6) Monitoring Procedure In an HPLC vial, [NHC-Au-Py][BF4] 4.6 (1.0 mg, 1.5 μmol) was dissolved in toluene (1.0 mL) and cooled to 0 °C. This HPLC vial was constantly sampled by an Agilent HPLC/MS with 15-minute time interval during the following steps for reaction monitoring. In another flask, prepare 10 mL of 15 mM NaBH4 (5.72 mg) in ethanol. The NaBH4 in EtOH solution (100 μL, 1 eq.) was added dropwise to the solution of 4.6. DCM (50 μL) was added, and the solution was mixed well. The solution was allowed to warm at room temperature and monitored for 2.0 hours. 4.12 MS Signal Found in Regional Analysis for Au13 Synthesis 4.12.1 Small Region In this section, the ESI-MS data was extracted for reaction monitoring trend (Section 4.4). For the small region, a retention time of 6.5-8.5 minutes was selected (Figure 4.3, highlighted in blue), and the m/z scope for these extracted data is set as m/z 1000-3000. In the 1st spectrum (Figure 4.8, only 4.3 dissolved in DCM), a massive signal of m/z 1025 was shown below. This massive N NBn BnAuPytoluene2.0 hr at r.t.[Au24(NHC)14Cl2H3][BF4]3NaBH4 in EtOH(15 mM, 1.0 eq.)50 µL DCM4.61.5 mM4.2BF4138 signal represents NHC-Au-Cl starting material dimer [NHC-Au]2Cl+. The signal of m/z 1025 disappeared after the NaBH4 addition. After the NaBH4 addition (Figure 4.9), a series of MS signals appeared in the spectrum, major ones include m/z 1517.3, 1884.3, 1991.1, 2059.6, and 2590.0. Figure 4.8. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 0 min 1st sample: NHC-Au-Cl dissolved in DCMm/z = 1025.0[NHC-Au]2Cl+ dimer (Starting material)m/z = 1203m/z = 1381139 Figure 4.9. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 1 min Figure 4.10. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 15 min 2nd sample: right after NaBH4 additionm/z = 1517.3[Au3(NHC)3MeOH]+m/z = 1991.1m/z = 2057.6m/z = 1884.3m/z = 2590.03rd sample 15 minsm/z = 1517.3[Au3(NHC)3MeOH]+m/z = 1991.1m/z = 2057.6m/z = 1884.3m/z = 2590.0140 Figure 4.11. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 30 min Figure 4.12. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 45 min 4th sample 30 minsm/z = 1517.3[Au3(NHC)3MeOH]+m/z = 1991.1m/z = 2057.6m/z = 1884.3m/z = 2590.05th sample 45 minsm/z = 1517.3[Au3(NHC)3MeOH]+m/z = 1991.1m/z = 2057.6m/z = 1884.3m/z = 2590.0141 Figure 4.13. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 60 min Figure 4.14. Small region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 75 min 6th sample 60 minsm/z = 1517.3[Au3(NHC)3MeOH]+m/z = 1991.1m/z = 2057.6m/z = 1884.3m/z = 2590.07th sample 15 after r.t.m/z = 1517.3[Au3(NHC)3MeOH]+142 4.12.2 Medium Region In this section, the ESI-MS data was extracted for reaction monitoring trend (Section 4.4) for the medium region (8.5-9.0 minutes) (Figure 4.3, highlighted in orange). The m/z scope for these extracted data is set as m/z 1000-3000. After the NaBH4 addition (Figure 4.16), a series of MS signals appeared in the spectrum, including m/z 2675.7 ([Au13(NHC)9Cl3]Cl2 (4.1)) and m/z 2774.7 [Au14(NHC)9Cl3]Cl2. The interchange between these two species can be clearly seen in the time-coursed MS spectra. As the reaction progressed, 4.1 was first formed in a relatively lower MS intensity than the Au14, but Au14 started to decrease while 3 increased, and the relative MS intensity inverted after eight samples. In addition, unlike the small region MS analysis, m/z 1000-2500 signals remained low. Figure 4.15. Medium region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 0 min 1st sample: NHC-Au-Cl dissolved in DCMm/z = 1025[NHC-Au]2Cl+ dimer (Starting material)143 Figure 4.16. Medium region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 1 min Figure 4.17. Medium region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 15 min 2nd sample: right after NaBH4 additionm/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ 3rd sample 15 minsm/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ 144 Figure 4.18. Medium region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 30 min Figure 4.19. Medium region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 45 min 4th sample 30 minsm/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ 5th sample 45 minsm/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ 145 Figure 4.20. Medium region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 60 min Figure 4.21. Medium region mass spectrometry analysis for Au13 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 75 min 6th sample 60 minsm/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ 7th sample 15 min after r.t.m/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ 146 4.13 By-/Side Product Formations in Sequential Dose Experiment It was demonstrated that the Au13 NC synthesis by sequential doses of 0.2 eq. NaBH4 solution successfully suppressed the large region AuNCs formation (Section 4.5). However, instead of an increase of the desired Au13 NC formation, a significant amount of [NHC-Au(I)-NHC]+ (4.4) and [Au24(NHC)14Cl2H3]3+ (4.2) were observed in HPLC spectra (Figure 4.22). Figure 4.22. HPLC spectrum showing a significant amount of [NHC-Au(I)-NHC]+ (4.4) and [Au24(NHC)14Cl2H3]3+ (4.2) N NBn BnAuClDCMr.t.NaBH4 in EtOH(20 mM, 0.2 eq. portional dose)4.34.0 mM[Au13(NHC)9Cl3]Cl24.1[Au24NHC14Cl2H2]3+[Au13(NHC)9Cl3]2+NNBnBnAuBnBnNN4.14.4 4.2147 4.14 MS Signal Found in Regional Analysis for Au24 Synthesis 4.14.1 Small Region In this section, the ESI-MS data was extracted for reaction monitoring trends (Section 4.6). For the small region, a retention time of 6.5-8.5 minutes was selected (Figure 4.3, highlighted in blue), and the m/z scope for these extracted data was set as m/z 1000-3000. In the 1st spectrum (Figure 4.22, only 4.6 dissolved in toluene), it was observed that the mass signal pattern was quite different, compared to 4.3 as a starting material (Figure 4.8). After the NaBH4 addition (Figure 4.24), a series of MS signals appeared in the spectrum, including a much larger peak of m/z 1517.3 than one with 4.3 as a starting material (Figure 4.9). 148 Figure 4.23. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 0 min Figure 4.24. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 1 min 1st sample: [NHC-Au-Py]BF4 dissolved in Toluenem/z = 1025[NHC-Au]2Cl+ dimer (Starting material)m/z = 10552nd sample: right after NaBH4 additionm/z = 1517.3[Au3(NHC)3MeOH]+m/z = 2057m/z = 2068.8149 Figure 4.25. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 15 min Figure 4.26. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 30 min 3rd sample 15 minsm/z = 1517.3[Au3(NHC)3MeOH]+m/z = 2057 m/z = 2068.84th sample 30 minsm/z = 1517.3[Au3(NHC)3MeOH]+m/z = 2057 m/z = 2068.8150 Figure 4.27. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 45 min Figure 4.28. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 60 min 5th sample 45 minsm/z = 2057 m/z = 2068.86th sample 60 minsm/z = 1197m/z = 2057 m/z = 2068.8151 Figure 4.29. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 75 min Figure 4.30. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 90 min 7th sample 75 minsm/z = 1197m/z = 2057 m/z = 2068.88th sample 90 minsm/z = 1197m/z = 2068.8152 Figure 4.31. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 105 min Figure 4.32. Small region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 6.5-8.5 minutes; reaction time point: 120 min 9th sample 105 minsm/z = 1197m/z = 2068.810th sample 120minsm/z = 1197m/z = 2068.8153 4.14.2 Medium Region Figure 4.33. Medium region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 0 min Figure 4.34. Medium region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 1 min 1st sample: [NHC-Au-Py]BF4 dissolved in DCM2nd sample: right after NaBH4 additionm/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2714.3m/z = 2774.7[Au14(NHC)9Cl3]2+ m/z = 2992.6[Au24(NHC)14Cl2H3]3+ (4.2) 154 Figure 4.35. Medium region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 15 min Figure 4.36. Medium region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 30 min 3rd sample 15 minsm/z = 2714.3m/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ m/z = 2992.6[Au24(NHC)14Cl2H3]3+ (4.2) 4th sample 30 minsm/z = 2714.3m/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ m/z = 2992.6[Au24(NHC)14Cl2H3]3+ (4.2) 155 Figure 4.37. Medium region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 45 min Figure 4.38. Medium region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 60 min 5th sample 45 minsm/z = 2714.3m/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ m/z = 2992.6[Au24(NHC)14Cl2H3]3+ (4.2) 6th sample 60 minsm/z = 2714.3m/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ m/z = 2992.6[Au24(NHC)14Cl2H3]3+ (4.2) 156 Figure 4.39. Medium region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 75 min Figure 4.40. Medium region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 90 min 7th sample 75 minsm/z = 2714.3m/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ m/z = 2992.6[Au24(NHC)14Cl2H3]3+ (4.2) 8th sample 90 minsm/z = 2714.3m/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ m/z = 2992.6[Au24(NHC)14Cl2H3]3+ (4.2) 157 Figure 4.41. Medium region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 105 min Figure 4.42. Medium region mass spectrometry analysis for Au24 NC synthesis, selected m/z range: 1000-3000; selected retention time range: 8.5-9.0 minutes; reaction time point: 120 min 9th sample 105 minsm/z = 2714.3m/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ m/z = 2992.6[Au24(NHC)14Cl2H3]3+ (4.2) 10th sample 120minsm/z = 2714.3m/z = 2675.7[Au13(NHC)9Cl3]2+ (4.1) m/z = 2774.7[Au14(NHC)9Cl3]2+ m/z = 2992.6[Au24(NHC)14Cl2H3]3+ (4.2) 158 4.15 High Resolution Mass Spectrometry (HRMS) Data of 4.1 Figure 4.43. HPLC spectrum of isolated [Au13(NHC)9Cl3]Cl2 at 290 nm wavelength Figure 4.44. HRMS data and a predicted mass pattern of isolated [Au13(NHC)9Cl3]2+ 159 4.16 HPLC Spectra Comparison between Synthesis of 4.1 and 4.2 Figure 4.45. HPLC spectra comparison between synthesis of 4.1 and 4.2. Reaction samples at 1 minute point from each reaction (Figure 4.4 and 4.7) were compared using 290 nm wavelength. The HPLC spectrum of the synthesis of 4.2 showed two peaks with m/z 793, which is the same as the mass of bis-NHC complex byproduct 4.4. Since [NHC-Au-Py]BF4 4.6 was used as starting material, the two peaks indicated [NHC-Au-NHC]+ coordinated with two different counter ions (BF4- and Cl-). The HPLC spectrum of the synthesis of 4.2 also showed a significant amount of a peak with m/z 1517.3. To identify this compound, all species with the chemical formula [Aux(NHC)yClz] were compared, but none of these had the same m/z value. Since HPLC mobile phase used MeOH, this species was estimated as [Au3(NHC)3MeOH]+. 1 min Sample of synthesis of [Au24(NHC)14Cl2H3][BF4]31 min Sample of synthesis of [Au13(NHC)9Cl3]Cl2m/z = 1517.3[Au3(NHC)3MeOH]+2 peaks with m/z = 793NNBnBnAuBnBnNN160 Chapter 5: Conclusions and Outlook Real-time analysis is essential to understand the details of reactions. However, while existing PATs quantitatively monitored ideal homogeneous conditions, solid/liquid heterogeneous conditions, liquid/liquid heterogeneous conditions, and nanocluster synthesis have suffered from a lack of meaningful quantitative analysis. This thesis has provided new methodologies to expand the monitoring tools to monitor such challenging conditions. The development of new analytical tools allow for monitoring more practical reactions seen in industrial and academic chemistry, which increases the utility of such reactions by understanding the reaction mechanism and optimizing the reaction conditions. To demonstrate their efficacy in reaction analysis and optimization, these tools were applied to three practical reactions that researchers in industry-academia collaborators faced difficulties in quantifying. To collect these reaction profiles, various reaction monitoring techniques were utilized simultaneously. Chapter 2 explored the development and application of a solid/liquid heterogeneous online HPLC platform. Solid-liquid slurries are challenging to monitor as many PATs are solution phase-specific, including in situ spectroscopic techniques such as NMR or IR, and very few techniques are capable of obtaining real-time solid phase composition information. However, if an aliquot is taken, dissolved, and then analyzed ex situ, the total composition of such systems can be determined. Using Mettler-Toledo’s EasySampler probe, a liquid handler, an in-line mixer and a custom series of pumps and valves, I created a sampling platform capable of sampling slurries and delivering them immediately to an HPLC for real-time component quantitation. The robustness of the new platform was demonstrated by the linear calibration curve of the slurry tetrabenazine (TBZ) mixture. I applied this system to study the synthesis of TBZ. Combining online HPLC with 161 pH and particle microscopy measurements, the orthogonal PATs provided data-rich information, including component concentration vs. time profile, pH change, and real-time image of crystallization. Specifically, intermediate trends were one of the most critical pieces of information to delineate the reaction path from starting materials to the products. The identification of two key intermediates, the enone and the iminium, revealed that the reaction occurred through the first elimination step and the second aza-Michael addition respectively. Chapter 3 discussed the liquid/liquid biphasic mixture. Similar to slurries, biphasic mixtures can be difficult to analyze due to the distribution of species between organic and aqueous phases and/or solvent mixtures, impeding background subtraction from spectroscopic techniques. The new methodologies selectively sample organic and aqueous layers from the mixing liquid/liquid biphasic mixture. New surface modification of a stainless steel (SS) filter for selective aqueous layer sampling was achieved by simply immersing in a basic K2CO3 solution. With the modified SS filter and a polyethylene filter, an automated sampling platform which selectively samples both the aqueous and organic layers was developed. The sampling platform circulates the single phase of the biphasic mixture through the line by a peristaltic pump. Therefore, the platform was readily applicable to existing flow NMR instruments and HPLC for real-time monitoring. To demonstrate the capabilities of the two platforms, partition tests of boronic acid and biphasic Suzuki Miyaura cross-coupling reactions were investigated. Chapter 4 explored a reliable monitoring technique for a nanocluster (NC) synthesis. Given that an NC synthesis is formed as mixtures of species with varying numbers of metal atoms and ligands, the existing PATs have fallen short in regards to separating and quantifying each component in the mixture. I developed an HPLC separation method for an NHC-AuNC mixture. First, [Au13(NHC)9Cl3]Cl2 synthesis was investigated by real-time HPLC monitoring. By 162 investigating the spectra of AuNC synthesis samples, three different AuNC size regimes are identified from elution profiles. By tracking these size regimes, I have been able to identify specific processes such as AuNC nucleation, aggregation, and size-focusing. Furthermore, the coupled MS suggested unstable Au14 NC formation. The broad applicability of LCMS to monitoring AuNCs synthesis was demonstrated by monitoring of another AuNC, [Au24(NHC)14Cl2H3][BF4]3, synthesis. Having developed these reaction monitoring platforms, future work could involve their further application to monitor other challenging systems. Reactive crystallization,219–223 in which products crystallize into solids during the reaction, is a logical application of the newly developed solid/liquid heterogeneous sampling platform. These reactions involve at least one component increasing in supersaturation until it crystallizes and desaturates, which makes monitoring this process extremely challenging without systems like mine. Furthermore, in addition to the high resolution capabilities demonstrated in the TBZ synthesis (Chapter 2), online HPLC is capable of separating chiral compounds via a chiral stationary phase. The new platform could therefore be further applied to monitor a racemization reaction in solid/liquid heterogeneous conditions, especially if it were combined with a reactive crystallization. Crystallization-induced diastereomer transformation (CIDT) is one such reaction, where a solution phase stereoisomerization reaction occurs and one component crystallizes out of the solution, driving a single diastereomer formation from a mixture. The importance of liquid/liquid biphasic conditions is also increasing along with the growth in organic synthesis in the biphasic system, including the Buchwald-Hartwig amination, the Suzuki-Miyaura cross-coupling, and phase transfer catalysis (PTC) reactions. Though the post-reaction outcomes (yield, selectivity, and catalytic efficiency) have shown significant benefits 163 from the biphasic system, the time course profiles have typically not been reported due to the lack of a sampling/monitoring platform. The new sampling platform both for organic and aqueous layers could be a simple solution, and readily amenable to inline/online sensors224,225 (IR, Raman, NMR and HPLC) which have rapidly developed along with the importance of flow chemistry.226,227 The variety of amenable PATs with the new material implies a large potential to delineate the broad scope of chemical transformations in a biphasic system. Beyond the reaction monitoring, this convenient modification method for a stainless steel material may help solve an oil spill issue. Surface-coated stainless steel mesh has been used in biomimetic and environmental chemistry due to its hydrophilic surface and has previously been demonstrated to efficiently separate oil-water emulsions in gravity-drive separations of oil contaminated industrial water.173,228 However, the modification required more complicated reactions to coat the surface with hydrophilic polymeric or the other hydrophilic material layer. The newly developed modification with the inorganic base can be a simple and fast methodology. While monitoring the formation of two AuNCs (Au13 and Au24 NCs), other previously unobserved NCs were also separated and detected by LCMS. Au14 and Au3 showed intriguing behaviour over time, which indicates they may be intermediates for Au13 and Au24 formation, respectively. However, insufficient characterization of nanoclusters has historically led to many NCs being misidentified.190 Therefore, additional experiments would be desired to further investigate these two key intermediates, such as 13C labelled NMR, X-ray crystallography and computational calculations. Since HPLC can also separate a variety of NCs, including Ag, Cu, Si, and MoS2 NCs,229–231 my new methodology for NC synthesis monitoring has the potential to be readily applied to monitor other NC syntheses. 164 References (1) Harvey, D. Analytical Chemistry 2.1. http://dpuadweb.depauw.edu/harvey_web/eTextProject/version_2.1.html (accessed Oct 7, 2022). (2) Oldroyd, D. R. Some Eighteenth Century Methods for the Chemical Analysis of Minerals. J. Chem. Educ. 1973, 50 (5), 337–340. (3) Simon, J. Analysis and the Hierarchy of Nature in Eighteenth-Century Chemistry. Br. J. Hist. Sci. 2002, 35 (1), 1–16. (4) Homburg, E. The Rise of Analytical Chemistry and Its Consequences for the Development of the German Chemical Profession (1780–1860). Ambix 1999, 46 (1), 1–32. (5) Beck, C. M. Classical Analysis: A Look at the Past, Present, and Future. Anal. Chem. 1991, 63 (20), 993A-1003A. (6) Lawless, P. A.; Rodes, C. E. Maximizing Data Quality in the Gravimetric Analysis of Personal Exposure Sample Filters. J. Air Waste Manage. Assoc. 1999, 49 (9), 1039–1049. (7) Sherman, G.; Shenoy, S.; Weiss, R. A.; Erkey, C. A Static Method Coupled with Gravimetric Analysis for the Determination of Solubilities of Solids in Supercritical Carbon Dioxide. Ind. Eng. Chem. Res. 2000, 39 (3), 846–848. (8) Phillips, K. M.; Tarragó-Trani, M. T.; Grove, T. M.; Grün, I.; Lugogo, R.; Harris, R. F.; Stewart, K. K. Simplified Gravimetric Determination of Total Fat in Food Composites after Chloroform-Methanol Extraction. J. Am. Oil Chem. Soc. 1997, 74 (2), 137–142. (9) Tantray, A. K.; Dar, S. A.; Ahmad, S.; Aabid, C.; Tantray, K.; Bhat, S. A. Spectrophotometric and Titrimetric Analysis of Phytoascorbate. J. Pharmacogn. 165 Phytochem. 2017, 6 (61), 27–31. (10) Licht, S.; Naschitz, V.; Halperin, L.; Halperin, N.; Lin, L.; Chen, J.; Ghosh, S.; Liu, B. Analysis of Ferrate(VI) Compounds and Super-Iron Fe(VI) Battery Cathodes: FTIR, ICP, Titrimetric, XRD, UV/VIS, and Electrochemical Characterization. J. Power Sources 2001, 101 (2), 167–176. (11) Epton, S. R. A New Method for the Rapid Titrimetric Analysis of Sodium Alkyl Sulphates and Related Compounds. Trans. Faraday Soc. 1948, 44 (226), 226–230. (12) Mitić, Ž.; Stolić, A.; Stojanović, S.; Najman, S.; Ignjatović, N.; Nikolić, G.; Trajanović, M. Instrumental Methods and Techniques for Structural and Physicochemical Characterization of Biomaterials and Bone Tissue: A Review. Mater. Sci. Eng. C 2017, 79, 930–949. (13) Swager, T. M.; Mirica, K. A. Introduction: Chemical Sensors. Chem. Rev. 2019, 119 (1), 1–2. (14) Galli, S. X-Ray Crystallography: One Century of Nobel Prizes. J. Chem. Educ. 2014, 91 (12), 2009–2012. (15) Boesch, C. Nobel Prizes for Nuclear Magnetic Resonance: 2003 and Historical Perspectives. J. Magn. Reson. Imaging 2004, 20 (2), 177–179. (16) Chung, J.-H.; Kim, H. M. The Nobel Prize in Chemistry 2017: High-Resolution Cryo-Electron Microscopy. Appl. Microsc. 2017, 47 (4), 218–222. (17) Singh, R. C. V. Raman and the Discovery of the Raman Effect. Phys. Perspect. 2002, 4 (4), 399–420. (18) Smith, W. D.; Felton, M. J. People: Analytical Chemists Win Nobel Prize. Anal. Chem. 2002, 74 (21), 567 A. 166 (19) Flato, J. B. Renaissance in Polarographic and Voltammetric Analysis. Anal. Chem. 1972, 44 (11), 75A-87A. (20) McKelvy, G. M. Flame Tests That Are Portable, Storable, and Easy To Use. J. Chem. Educ. 1998, 75 (1), 55. (21) Pearson, R. S. An Improved Calcium Flame Test. J. Chem. Educ. 1985, 62 (7), 622. (22) Sanger, M. J.; Phelps, A. J.; Catherine Banks. Simple Flame Test Techniques Using Cotton Swabs. J. Chem. Educ. 2004, 81 (7), 969. (23) Landis, A. M.; Davies, M. I.; Landis, L.; Nicholas C. Thomas. “Magic Eraser” Flame Tests. J. Chem. Educ. 2009, 86 (5), 577. (24) Böttcher, T. From Molecules to Life: Quantifying the Complexity of Chemical and Biological Systems in the Universe. J. Mol. Evol. 2018, 86 (1), 1–10. (25) Li, J.; Eastgate, M. D. Current Complexity: A Tool for Assessing the Complexity of Organic Molecules. Org. Biomol. Chem. 2015, 13 (26), 7164–7176. (26) Nováková, L.; Vlčková, H. A Review of Current Trends and Advances in Modern Bio-Analytical Methods: Chromatography and Sample Preparation. Anal. Chim. Acta 2009, 656 (1–2), 8–35. (27) Nawrocki, J. The Silanol Group and Its Role in Liquid Chromatography. J. Chromatogr. A 1997, 779 (1–2), 29–71. (28) Herrero, M.; Ibáñez, E.; Cifuentes, A.; Bernal, J. Multidimensional Chromatography in Food Analysis. J. Chromatogr. A 2009, 1216 (43), 7110–7129. (29) Ackers, G. K. Analytical Gel Chromatography of Proteins. In Advances in Protein Chemistry; 1970; Vol. 24, pp 343–446. (30) Hemström, P.; Irgum, K. Hydrophilic Interaction Chromatography. J. Sep. Sci. 2006, 29 167 (12), 1784–1821. (31) Downes, A.; Mouras, R.; Elfick, A. Optical Spectroscopy for Noninvasive Monitoring of Stem Cell Differentiation. J. Biomed. Biotechnol. 2010, 2010, 1–10. (32) Lucas, M.; Riedo, E. Invited Review Article: Combining Scanning Probe Microscopy with Optical Spectroscopy for Applications in Biology and Materials Science. Rev. Sci. Instrum. 2012, 83 (6), 061101. (33) Wolfbeis, O. S. Fiber-Optic Chemical Sensors and Biosensors. Anal. Chem. 2006, 78 (12), 3859–3873. (34) Bloch, F. Nuclear Induction. Phys. Rev. 1946, 70 (7–8), 460–474. (35) Purcell, E. M.; Torrey, H. C.; Pound, R. V. Resonance Absorption by Nuclear Magnetic Moments in a Solid. Phys. Rev. 1946, 69 (1–2), 37–38. (36) Bifulco, G.; Dambruoso, P.; Gomez-Paloma, L.; Riccio, R. Determination of Relative Configuration in Organic Compounds by NMR Spectroscopy and Computational Methods. Chem. Rev. 2007, 107 (9), 3744–3779. (37) Palmer, A. G. NMR Characterization of the Dynamics of Biomacromolecules. Chem. Rev. 2004, 104 (8), 3623–3640. (38) Kwan, E. E.; Huang, S. G. Structural Elucidation with NMR Spectroscopy: Practical Strategies for Organic Chemists. European J. Org. Chem. 2008, No. 16, 2671–2688. (39) Lucier, B. E. G.; Chen, S.; Huang, Y. Characterization of Metal–Organic Frameworks: Unlocking the Potential of Solid-State NMR. Acc. Chem. Res. 2018, 51 (2), 319–330. (40) Pellecchia, M.; Sem, D. S.; Wüthrich, K. NMR in Drug Discovery. Nat. Rev. Drug Discov. 2002, 1 (3), 211–219. (41) Pauli, W. Writings on Physics and Philosophy; Enz, C. P., von Meyenn, K., Eds.; Springer 168 Berlin Heidelberg, 1994. (42) Belloni, L. Pauli’s 1924 Note on Hyperfine Structure. Am. J. Phys. 1982, 50 (5), 461–464. (43) Atta-ur-Rahman; Choudhary, M. I. Important 2D NMR Experiments. In Solving Problems with NMR Spectroscopy; Elsevier, 1996; pp 213–343. (44) Atta-ur-Rahman; Choudhary, M. I. The Third Dimension. In Solving Problems with NMR Spectroscopy; 1996; pp 345–363. (45) Rogalski, A. Infrared Detectors: An Overview. Infrared Phys. Technol. 2002, 43 (3–5), 187–210. (46) Stuart, B. Infrared Spectroscopy. In Kirk-Othmer Encyclopedia of Chemical Technology; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2005; pp 1–20. (47) Yu, P.; Kirkpatrick, R. J.; Poe, B.; McMillan, P. F.; Cong, X. Structure of Calcium Silicate Hydrate (C-S-H): Near-, Mid-, and Far-Infrared Spectroscopy. J. Am. Ceram. Soc. 2004, 82 (3), 742–748. (48) Werle, P.; Slemr, F.; Maurer, K.; Kormann, R.; Mücke, R.; Jänker, B. Near- and Mid-Infrared Laser-Optical Sensors for Gas Analysis. Opt. Lasers Eng. 2002, 37 (2–3), 101–114. (49) Jiang, W.; Saxena, A.; Song, B.; Ward, B. B.; Beveridge, T. J.; Myneni, S. C. B. Elucidation of Functional Groups on Gram-Positive and Gram-Negative Bacterial Surfaces Using Infrared Spectroscopy. Langmuir 2004, 20 (26), 11433–11442. (50) Ostrowska, J.; Narebska, A. Infrared Study of Hydration and Association of Functional Groups in a Perfluorinated Nafion Membrane, Part 1. Colloid Polym. Sci. 1983, 261 (2), 93–98. (51) Duley, W. W.; Williams, D. A. The Infrared Spectrum of Interstellar Dust: Surface 169 Functional Groups on Carbon. Mon. Not. R. Astron. Soc. 1981, 196 (2), 269–274. (52) Hastings, S. H.; Watson, A. T.; Williams, R. B.; Anderson, J. A. Determination of Hydrocarbon Functional Groups by Infrared Spectroscopy. Anal. Chem. 1952, 24 (4), 612–618. (53) Haris, P. I.; Chapman, D. The Conformational Analysis of Peptides Using Fourier Transform IR Spectroscopy. Biopolymers 1995, 37 (4), 251–263. (54) Skoog, D. A.; Hokker, F. J.; Crouch, S. R. Principles of Instrumental Analysis, 7th ed.; Cengage Learning, 2017. (55) Diffey, B. L. Sources and Measurement of Ultraviolet Radiation. Methods 2002, 28 (1), 4–13. (56) Nielsen, S. S. Food Analysis, 5th ed.; Food Science Texts Series; Springer US, 2010. (57) Alaoui Tahiri, A.; El Bali, B.; Lachkar, M.; Wilson, C.; Bauer, D.; Haisch, C. Crystal Structure, IR, Raman and UV–Vis Studies of [Co(H2P2O7)2(H2O)2][CH3)3C-NH3)]2·2H2O. Inorg. Chem. Commun. 2021, 128 (February), 108541. (58) Tan, B.; Soderstrom, D. N. Qualitative Aspects of UV-Vis Spectrophotometry of β-Carotene and Lycopene. J. Chem. Educ. 1989, 66 (3), 258–260. (59) Brown, J. Q.; Vishwanath, K.; Palmer, G. M.; Ramanujam, N. Advances in Quantitative UV-Visible Spectroscopy for Clinical and Pre-Clinical Application in Cancer. Curr. Opin. Biotechnol. 2009, 20 (1), 119–131. (60) Behzadi, S.; Ghasemi, F.; Ghalkhani, M.; Ashkarran, A. A.; Akbari, S. M.; Pakpour, S.; Hormozi-Nezhad, M. R.; Jamshidi, Z.; Mirsadeghi, S.; Dinarvand, R.; Atyabi, F.; Mahmoudi, M. Determination of Nanoparticles Using UV-Vis Spectra. Nanoscale 2015, 7 (12), 5134–5139. 170 (61) Gaur, K.; Cruz, Y. M.; Santiago Espinoza, J. A.; Morales Rueda, C. A.; Loza-Rosas, S. A.; Fernández-Vega, L.; Benjamín-Rivera, J. A.; Álvarez, A.; Tinoco, A. D. Exploring the pH Dependent Aqueous Speciation of Metal Complexes through UV-Vis Spectroscopy. J. Chem. Educ. 2020, 97 (7), 1970–1975. (62) Brian W. Pfennig. Principles of Inorganic Chemistry; John Wiley & Son, 2015. (63) Chakraborty, I.; Pradeep, T. Atomically Precise Clusters of Noble Metals: Emerging Link between Atoms and Nanoparticles. Chem. Rev. 2017, 117 (12), 8208–8271. (64) Jayawardena, H. S. N.; Liyanage, S. H.; Rathnayake, K.; Patel, U.; Yan, M. Analytical Methods for Characterization of Nanomaterial Surfaces. Anal. Chem. 2021, 93 (4), 1889–1911. (65) Kang, X.; Zhu, M. Transformation of Atomically Precise Nanoclusters by Ligand-Exchange. Chem. Mater. 2019, 31 (24), 9939–9969. (66) Brown, P.; Djerassi, C. Electron‐Impact Induced Rearrangement Reactions of Organic Molecules. Angew. Chemie Int. Ed. English 1967, 6 (6), 477–496. (67) Vikse, K. L.; Woods, M. P.; McIndoe, J. S. Pressurized Sample Infusion for the Continuous Analysis of Air- and Moisture-Sensitive Reactions Using Electrospray Ionization Mass Spectrometry. Organometallics 2010, 29 (23), 6615–6618. (68) Ho, C. S.; Lam, C. W. K.; Chan, M. H. M.; Cheung, R. C. K.; Law, L. K.; Lit, L. C. W.; Ng, K. F.; Suen, M. W. M.; Tai, H. L. Electrospray Ionisation Mass Spectrometry: Principles and Clinical Applications. Clin. Biochem. Rev. 2003, 24 (1), 3–12. (69) Yunker, L. P. E.; Stoddard, R. L.; McIndoe, J. S. Practical Approaches to the ESI-MS Analysis of Catalytic Reactions. J. Mass Spectrom. 2014, 49 (1), 1–8. (70) Hawkes, J. A.; Kew, W. High-Resolution Mass Spectrometry Strategies for the 171 Investigation of Dissolved Organic Matter; Elsevier Inc., 2020. (71) Roberts, K. M.; Fitzpatrick, P. F. Measurement of Kinetic Isotope Effects in an Enzyme-Catalyzed Reaction by Continuous-Flow Mass Spectrometry, 1st ed.; Elsevier Inc., 2017; Vol. 596. (72) Das, R.; Mitra, A.; Bhat, V.; Mandal, A. K. Application of Isotope Exchange Based Mass Spectrometry to Understand the Mechanism of Inhibition of Sickle Hemoglobin Polymerization upon Oxygenation. J. Struct. Biol. 2017, 199 (1), 76–83. (73) Oxgaard, J.; Tenn, W. J.; Nielsen, R. J.; Periana, R. A.; Goddard, W. A. Mechanistic Analysis of Iridium Heteroatom C-H Activation: Evidence for an Internal Electrophilic Substitution Mechanism. Organometallics 2007, 26 (7), 1565–1567. (74) Owen, J. S.; Labinger, J. A.; Bercaw, J. E. Kinetics and Mechanism of Methane, Methanol, and Dimethyl Ether C-H Activation with Electrophilic Platinum Complexes. J. Am. Chem. Soc. 2006, 128 (6), 2005–2016. (75) Northcutt, T. O.; Wick, D. D.; Vetter, A. J.; Jones, W. D. Investigation of the Mechanism of Alkane Reductive Elimination and Skeletal Isomerization in Tp′Rh(CNneopentyl)(R)H Complexes: The Role of Alkane Complexes. J. Am. Chem. Soc. 2001, 123 (30), 7257–7270. (76) Schaller, C. P.; Cummins, C. C.; Wolczanski, P. T. Hydrocarbon Activation via Reversible 1,2-RH-Elimination from (tBu3SiNH)3ZrR: Synthetic, Structural, and Mechanistic Investigations. J. Am. Chem. Soc. 1996, 118 (3), 591–611. (77) Malig, T. C.; Koenig, J. D. B.; Situ, H.; Chehal, N. K.; Hultin, P. G.; Hein, J. E. Real-Time HPLC-MS Reaction Progress Monitoring Using an Automated Analytical Platform. React. Chem. Eng. 2017, 2 (3), 309–314. 172 (78) Chung, R.; Hein, J. E. Automated Solubility and Crystallization Analysis of Non-UV Active Compounds: Integration of Evaporative Light Scattering Detection (ELSD) and Robotic Sampling. React. Chem. Eng. 2019. (79) Lindon, J. C.; Nicholson, J. K.; Wilson, I. D. Directly Coupled HPLC-NMR and HPLC-NMR-MS in Pharmaceutical Research and Development. J. Chromatogr. B Biomed. Sci. Appl. 2000, 748 (1), 233–258. (80) Ansori. Chapter 2 The Ultraviolet Absorption Detector. In Paper Knowledge . Toward a Media History of Documents; 1977; Vol. 3, pp 109–120. (81) Da Rocha, M. S.; Silva, L. da; Sena, R. C. de; Araújo, T. de O.; Almeida, M. D. de; Sánchez, M. L. F.; Medel, A. S. Single Point Calibration for Quantitative Speciation of Selenomethionine in Yeast Saccharomyces Cerevisiae by HPLC-ICP-MS: Using Reliable, Traceable and Comparable Measurements. J. Mex. Chem. Soc. 2018, 62 (2), 334–347. (82) Bánfai, B.; Kemény, S. Estimation of Bias for Single-Point Calibration. J. Chemom. 2012, 26 (3–4), 117–124. (83) Sulistyaningrum, I.; Utami, M. P. G.; Istiningrum, R. B.; Siregar, I. M. Comparison Between the Calibration and the Standard Addition Methods in Determining Dissolved Lead in Borobudur’s Control Tanks Water by Flame Atomic Absorption Spectrophotometry (F-AAS). Procedia Chem. 2015, 17, 70–74. (84) Rybak, M. E.; Calvey, E. M.; Harnly, J. M. Quantitative Determination of Allicin in Garlic: Supercritical Fluid Extraction and Standard Addition of Alliin. J. Agric. Food Chem. 2004, 52 (4), 682–687. (85) Hutchinson, G.; Welsh, C. D. M.; Burés, J. Use of Standard Addition to Quantify In-Situ FTIR Reaction Data. J. Org. Chem. 2021, 86 (2), 2012–2016. 173 (86) Liu, J.; Sato, Y.; Yang, F.; Kukor, A. J.; Hein, J. E. An Adaptive Auto‐Synthesizer Using Online PAT Feedback to Flexibly Perform a Multistep Reaction. Chemistry–Methods 2022, 2 (8), 1–9. (87) Harris, C. D. Quantitative Chemical Analysis, 9th ed.; W. H. Freeman, 2016. (88) Malig, T. C.; Koenig, J. D. B.; Situ, H.; Chehal, N. K.; Hultin, P. G.; Hein, J. E. Real-Time HPLC-MS Reaction Progress Monitoring Using an Automated Analytical Platform. React. Chem. Eng. 2017, 2 (3), 309–314. (89) Annesley, T. M. Ion Suppression in Mass Spectrometry. Clin. Chem. 2003, 49 (7), 1041–1044. (90) Furey, A.; Moriarty, M.; Bane, V.; Kinsella, B.; Lehane, M. Ion Suppression; A Critical Review on Causes, Evaluation, Prevention and Applications. Talanta 2013, 115, 104–122. (91) Sterner, J. L.; Johnston, M. V.; Nicol, G. R.; Ridge, D. P. Signal Suppression in Electrospray Ionization Fourier Transform Mass Spectrometry of Multi-Component Samples. J. Mass Spectrom. 2000, 35 (3), 385–391. (92) Bonfiglio, R.; King, R. C.; Olah, T. V.; Merkle, K. The Effects of Sample Preparation Methods on the Variability of the Electrospray Ionization Response for Model Drug Compounds. Rapid Commun. Mass Spectrom. 1999, 13 (12), 1175–1185. (93) Bharti, S. K.; Roy, R. Quantitative 1H NMR Spectroscopy. TrAC Trends Anal. Chem. 2012, 35, 5–26. (94) Wang, H.; Zhao, M.; Ackerman, J. L.; Song, Y. Saturation-Inversion-Recovery: A Method for T1 Measurement. J. Magn. Reson. 2017, 274, 137–143. (95) Popper, K. The Logic of Scientific Discovery, 2nd ed.; Taylor & Francis, 2005. (96) Blackmond, D. G. Kinetic Profiling of Catalytic Organic Reactions as a Mechanistic Tool. 174 J. Am. Chem. Soc. 2015, 137 (34), 10852–10866. (97) Blackmond, D. G. Reaction Progress Kinetic Analysis: A Powerful Methodology for Mechanistic Studies of Complex Catalytic Reactions. Angew. Chemie Int. Ed. 2005, 44 (28), 4302–4320. (98) Malig, T. C.; Yu, D.; Hein, J. E. A Revised Mechanism for the Kinugasa Reaction. J. Am. Chem. Soc. 2018, 140 (29), 9167–9173. (99) Burés, J. Variable Time Normalization Analysis: General Graphical Elucidation of Reaction Orders from Concentration Profiles. Angew. Chemie Int. Ed. 2016, 55 (52), 16084–16087. (100) Burés, J. A Simple Graphical Method to Determine the Order in Catalyst. Angew. Chemie Int. Ed. 2016, 55 (6), 2028–2031. (101) Nielsen, C. D. T.; Burés, J. Visual Kinetic Analysis. Chem. Sci. 2019, 10 (2), 348–353. (102) Maschmeyer, T.; Yunker, L. P. E.; Hein, J. E. Quantitative and Convenient Real-Time Reaction Monitoring Using Stopped-Flow Benchtop NMR. React. Chem. Eng. 2022, 7 (5), 1061–1072. (103) Foley, D. A.; Bez, E.; Codina, A.; Colson, K. L.; Fey, M.; Krull, R.; Piroli, D.; Zell, M. T.; Marquez, B. L. NMR Flow Tube for Online NMR Reaction Monitoring. Anal. Chem. 2014, 86 (24), 12008–12013. (104) Friebel, A.; Von Harbou, E.; Münnemann, K.; Hasse, H. Reaction Monitoring by Benchtop NMR Spectroscopy Using a Novel Stationary Flow Reactor Setup. Ind. Eng. Chem. Res. 2019, 58 (39), 18125–18133. (105) Ahuja, S.; Diehl, D. Chapter 2 Sampling and Sample Preparation. In Comprehensive Analytical Chemistry; Elsevier, 2006; Vol. 47, pp 15–40. 175 (106) Smith, B. C. Fundamentals of Molecular Absorption Spectroscopy. Quant. Spectrosc. Theory Pract. 2002, 1–41. (107) Blum, M. M.; John, H. Historical Perspective and Modern Applications of Attenuated Total Reflectance - Fourier Transform Infrared Spectroscopy (ATR-FTIR). Drug Test. Anal. 2012, 4 (3–4), 298–302. (108) Foley, D. A.; Doecke, C. W.; Buser, J. Y.; Merritt, J. M.; Murphy, L.; Kissane, M.; Collins, S. G.; Maguire, A. R.; Kaerner, A. 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 (23), 9630–9640. (109) Grabow, K.; Bentrup, U. Homogeneous Catalytic Processes Monitored by Combined in Situ ATR-IR, UV-VIS, and Raman Spectroscopy. ACS Catal. 2014, 4 (7), 2153–2164. (110) Nödling, A. R.; Müther, K.; Rohde, V. H. G.; Hilt, G.; Oestreich, M. Ferrocene-Stabilized Silicon Cations as Catalysts for Diels-Alder Reactions: Attempted Experimental Quantification of Lewis Acidity and ReactIR Kinetic Analysis. Organometallics 2014, 33 (1), 302–308. (111) Leadbeater, N. E. In Situ Reaction Monitoring of Microwave-Mediated Reactions Using IR Spectroscopy. Chem. Commun. 2010, 46 (36), 6693–6695. (112) Epifanov, M.; Foth, P. J.; Gu, F.; Barrillon, C.; Kanani, S. S.; Higman, C. S.; Hein, J. E.; Sammis, G. M. One-Pot 1,1-Dihydrofluoroalkylation of Amines Using Sulfuryl Fluoride. J. Am. Chem. Soc. 2018, 140 (48), 16464–16468. (113) Guerrero-Pérez, M. O.; Bañares, M. A. From Conventional in Situ to Operando Studies in Raman Spectroscopy. Catal. Today 2006, 113 (1–2), 48–57. (114) Schwolow, S.; Braun, F.; Rädle, M.; Kockmann, N.; Röder, T. Fast and Efficient 176 Acquisition of Kinetic Data in Microreactors Using In-Line Raman Analysis. Org. Process Res. Dev. 2015, 19 (9), 1286–1292. (115) Bai, R.; Zhang, G.; Yi, H.; Huang, Z.; Qi, X.; Liu, C.; Miller, J. T.; Kropf, A. J.; Bunel, E. E.; Lan, Y.; Lei, A. Cu(II)-Cu(I) Synergistic Cooperation to Lead the Alkyne C-H Activation. J. Am. Chem. Soc. 2014, 136 (48), 16760–16763. (116) Maschmeyer, T.; Prieto, P. L.; Grunert, S.; Hein, J. E. Exploration of Continuous-Flow Benchtop NMR Acquisition Parameters and Considerations for Reaction Monitoring. Magn. Reson. Chem. 2020, 58 (12), 1234–1248. (117) Dalitz, F.; Maiwald, M.; Guthausen, G. 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. (118) Hall, A. M. R.; Chouler, J. C.; Codina, A.; Gierth, P. T.; Lowe, J. P.; Hintermair, U. Practical Aspects of Real-Time Reaction Monitoring Using Multi-Nuclear High Resolution FlowNMR Spectroscopy. Catal. Sci. Technol. 2016, 6 (24), 8406–8417. (119) Christensen, M.; Yunker, L. P. E.; Shiri, P.; Zepel, T.; Prieto, P. L.; Grunert, S.; Bork, F.; Hein, J. E. Automation Isn’t Automatic. Chem. Sci. 2021, 12 (47), 15473–15490. (120) Yang, Y. Side Reactions Upon Amino Acid/Peptide Carboxyl Activation. Side React. Pept. Synth. 2016, 95–118. (121) MacLeod, B. P.; Parlane, F. G. L.; Brown, A. K.; Hein, J. E.; Berlinguette, C. P. Flexible Automation Accelerates Materials Discovery. Nat. Mater. 2021, 9–11. (122) Shiri, P.; Lai, V.; Zepel, T.; Griffin, D.; Reifman, J.; Clark, S.; Grunert, S.; Yunker, L. P. E.; Steiner, S.; Situ, H.; Yang, F.; Prieto, P. L.; Hein, J. E. Automated Solubility Screening Platform Using Computer Vision. iScience 2021, 24 (3), 102176. 177 (123) Malig, T. C.; Tan, Y.; Wisniewski, S. R.; Higman, C. S.; Carrasquillo-Flores, R.; Ortiz, A.; Purdum, G. E.; Kolotuchin, S.; Hein, J. E. Development of a Telescoped Synthesis of 4-(1H)-Cyanoimidazole Core Accelerated by Orthogonal Reaction Monitoring. React. Chem. Eng. 2020, 5 (8), 1421–1428. (124) Daponte, J. A.; Guo, Y.; Ruck, R. T.; Hein, J. E. Using an Automated Monitoring Platform for Investigations of Biphasic Reactions. ACS Catal. 2019, 9 (12), 11484–11491. (125) Christensen, M.; Adedeji, F.; Grosser, S.; Zawatzky, K.; Ji, Y.; Liu, J.; Jurica, J. A.; Naber, J. R.; Hein, J. E. Development of an Automated Kinetic Profiling System with Online HPLC for Reaction Optimization. React. Chem. Eng. 2019, 4 (9), 1555–1558. (126) Haer, M.; Strahlendorf, K.; Payne, J.; Jung, R.; Xiao, E.; Mirabel, C.; Rahman, N.; Kowal, P.; Gemmiti, G.; Cronin, J. T.; Gable, T.; Park-Lee, K.; Drolet-Vives, K.; Balmer, M.; Kirkitadze, M. PAT Solutions to Monitor Adsorption of Tetanus Toxoid with Aluminum Adjuvants. J. Pharm. Biomed. Anal. 2021, 198, 114013. (127) Rougeot, C.; Situ, H.; Cao, B. H.; Vlachos, V.; Hein, J. E. Automated Reaction Progress Monitoring of Heterogeneous Reactions: Crystallization-Induced Stereoselectivity in Amine-Catalyzed Aldol Reactions. React. Chem. Eng. 2017, 2 (2), 226–231. (128) Rodríguez, B.; Bruckmann, A.; Bolm, C. A Highly Efficient Asymmetric Organocatalytic Aldol Reaction in a Ball Mill. Chem. - A Eur. J. 2007, 13 (17), 4710–4722. (129) Martínez-Castañeda, Á.; Poladura, B.; Rodríguez-Solla, H.; Concellón, C.; Del Amo, V. Direct Aldol Reactions Catalyzed by a Heterogeneous Guanidinium Salt/Proline System under Solvent-Free Conditions. Org. Lett. 2011, 13 (12), 3032–3035. (130) Wolfe, J. P.; Singer, R. A.; Yang, B. H.; Buchwald, S. L. Highly Active Palladium Catalysts for Suzuki Coupling Reactions. J. Am. Chem. Soc. 1999, 121 (41), 9550–9561. 178 (131) Fuentes-Rivera, J. J.; Zick, M. E.; Düfert, M. A.; Milner, P. J. Overcoming Halide Inhibition of Suzuki-Miyaura Couplings with Biaryl Monophosphine-Based Catalysts. Org. Process Res. Dev. 2019, 23 (8), 1631–1637. (132) Molloy, J. J.; Clohessy, T. A.; Irving, C.; Anderson, N. A.; Lloyd-Jones, G. C.; Watson, A. J. B. Chemoselective Oxidation of Aryl Organoboron Systems Enabled by Boronic Acid-Selective Phase Transfer. Chem. Sci. 2017, 8 (2), 1551–1559. (133) Lima, C. F. R. A. C.; Rodrigues, A. S. M. C.; Silva, V. L. M.; Silva, A. M. S.; Santos, L. M. N. B. F. Role of the Base and Control of Selectivity in the Suzuki-Miyaura Cross-Coupling Reaction. ChemCatChem 2014, 6 (5), 1291–1302. (134) Sato, Y.; Liu, J.; Kukor, A. J.; Culhane, J. C.; Tucker, J. L.; Kucera, D. J.; Cochran, B. M.; Hein, J. E. Real-Time Monitoring of Solid-Liquid Slurries: Optimized Synthesis of Tetrabenazine. J. Org. Chem. 2021, 86 (20), 14069–14078. (135) Bordawekar, S.; Chanda, A.; Daly, A. M.; Garrett, A. W.; Higgins, J. P.; LaPack, M. A.; Maloney, T. D.; Morgado, J.; Mukherjee, S.; Orr, J. D.; Reid, G. L.; Yang, B.-S.; Ward, H. W. Industry Perspectives on Process Analytical Technology: Tools and Applications in API Manufacturing. Org. Process Res. Dev. 2015, 19 (9), 1174–1185. (136) Gherras, N.; Fevotte, G. On the Use of Process Analytical Technologies and Population Balance Equations for the Estimation of Crystallization Kinetics. A Case Study. AIChE J. 2011, 58 (9), 2650. (137) Yu, L. X.; Lionberger, R. A.; Raw, A. S.; Costa, R. D.; Wu, H.; Hussain, A. S. Applications of Process Analytical Technology to Crystallization Processes. Adv. Drug Deliv. Rev. 2004, 56 (3), 349–369. (138) Chen, Z.; Lovett, D.; Morris, J. Process Analytical Technologies and Real Time Process 179 Control a Review of Some Spectroscopic Issues and Challenges. J. Process Control 2011, 21 (10), 1467–1482. (139) Gomez, M. V.; De La Hoz, A. NMR Reaction Monitoring in Flow Synthesis. Beilstein J. Org. Chem. 2017, 13, 285–300. (140) Foth, P. J.; Malig, T. C.; Yu, H.; Bolduc, T. G.; Hein, J. E.; Sammis, G. M. Halide-Accelerated Acyl Fluoride Formation Using Sulfuryl Fluoride. Org. Lett. 2020, 22 (16), 6682–6686. (141) Barrios Sosa, A. C.; Conway, R.; Williamson, R. T.; Suchy, J. P.; Edwards, W.; Cleary, T. Application of PAT Tools for the Safe and Reliable Production of a Dihydro-1 H -Imidazole. Org. Process Res. Dev. 2011, 15 (6), 1458–1463. (142) Johansen, L. N.; Kloster, L.; Andreasen, A.; Kucheryavskiy, S.; Nielsen, R. P.; Maschietti, M. Raman Spectroscopy for Monitoring Aqueous Phase Hydrogen Sulphide Scavenging Reactions with Triazine: A Feasibility Study. Chem. Eng. Trans. 2019, 74, 541–546. (143) Hamlin, T. A.; Leadbeater, N. E. Raman Spectroscopy as a Tool for Monitoring Mesoscale Continuous-Flow Organic Synthesis: Equipment Interface and Assessment in Four Medicinally-Relevant Reactions. Beilstein J. Org. Chem. 2013, 9, 1843–1852. (144) Ray, A.; Bristow, T.; Whitmore, C.; Mosely, J. On-Line Reaction Monitoring by Mass Spectrometry, Modern Approaches for the Analysis of Chemical Reactions. Mass Spectrom. Rev. 2018, 37 (4), 565–579. (145) Cho, D. S.; Gibson, S. C.; Bhandari, D.; McNally, M. E.; Hoffman, R. M.; Cook, K. D.; Song, L. Evaluation of Direct Analysis in Real Time Mass Spectrometry for Onsite Monitoring of Batch Slurry Reactions. Rapid Commun. Mass Spectrom. 2011, 25 (23), 3575–3580. 180 (146) Görög, S. The Changing Face of Pharmaceutical Analysis. Trends Anal. Chem. 2007, 26 (1), 12–17. (147) Christensen, M.; Adedeji, F.; Grosser, S.; Zawatzky, K.; Ji, Y.; Liu, J.; Jurica, J. A.; Naber, J. R.; Hein, J. E. Development of an Automated Kinetic Profiling System with Online HPLC for Reaction Optimization. React. Chem. Eng. 2019, 4 (9), 1555–1558. (148) Chung, R.; Vo, A.; Hein, J. E. Copper-Catalyzed Hydrogen/Iodine Exchange in Terminal and 1-Iodoalkynes. ACS Catal. 2017, 7 (4), 2505–2510. (149) Mestre, T.; Ferreira, J.; Coelho, M. M.; Rosa, M.; Sampaio, C. Therapeutic Interventions for Symptomatic Treatment in Huntington’s Disease. Cochrane Database Syst. Rev. 2009, 3, CD006456. (150) Skor, H.; Smith, E. B.; Loewen, G.; O’Brien, C. F.; Grigoriadis, D. E.; Bozigian, H. Differences in Dihydrotetrabenazine Isomer Concentrations Following Administration of Tetrabenazine and Valbenazine. Drugs R D 2017, 17 (3), 449–459. (151) Grigoriadis, D. E.; Smith, E.; Hoare, S. R. J.; Madan, A.; Bozigian, H. Pharmacologic Characterization of Valbenazine (NBI-98854) and Its Metabolites. J. Pharmacol. Exp. Ther. 2017, 361 (3), 454–461. (152) Paek, S. M. Synthesis of Tetrabenazine and Its Derivatives, Pursuing Efficiency and Selectivity. Molecules 2020, 25 (5), 1175. (153) Yao, Z.; Wei, X.; Wu, X.; Katz, J. L.; Kopajtic, T.; Greig, N. H.; Sun, H. Preparation and Evaluation of Tetrabenazine Enantiomers and All Eight Stereoisomers of Dihydrotetrabenazine as VMAT2 Inhibitors. Eur. J. Med. Chem. 2011, 46 (5), 1841–1848. (154) Brossi, A.; Lindlar, H.; Walter, M.; Schnider, O. Syntheseversuche in Der Emetin-Reihe. 1. Mitteilung. 2-Oxo-Hydrobenzo[a]Chinolizine. Helv. Chim. Acta 1958, 41 (1), 119–139. 181 (155) Openshaw, H. T.; Whittaker, N. The Synthesis of Emetine and Related Compounds. Part IV. A New Synthesis of 3-Substituted 1,2,3,4,6,7-Hexahydro-9,10-Dimethoxy-2-Oxo-11bH-Benzo[a]Quinolizines. J. Chem. Soc. 1963, 1449. (156) Ding, H.; Liu, H.; Yin, Y.; Ding, Y.; Jia, Y.; Chen, Q.; Zou, G.; Zheng, Z. Insights into the Modulation of Optimum pH by a Single Histidine Residue in Arginine Deiminase from Pseudomonas Aeruginosa. Biol. Chem. 2012, 393 (9), 1013–1024. (157) Xu, Z.; Li, S.; Feng, X.; Zhan, Y.; Xu, H. Function of Aspartic Acid Residues in Optimum pH Control of L-Arabinose Isomerase from Lactobacillus Fermentum. Appl. Microbiol. Biotechnol. 2014, 98 (9), 3987–3996. (158) Hofer, F.; Kraml, J.; Kahler, U.; Kamenik, A. S.; Liedl, K. R. Catalytic Site pKa Values of Aspartic, Cysteine, and Serine Proteases: Constant PH MD Simulations. J. Chem. Inf. Model. 2020, 60 (6), 3030–3042. (159) Hyde, A. M.; Zultanski, S. L.; Waldman, J. H.; Zhong, Y.-L.; Shevlin, M.; Peng, F. General Principles and Strategies for Salting-Out Informed by the Hofmeister Series. Org. Process Res. Dev. 2017, 21 (9), 1355–1370. (160) Yu, Q. S.; Luo, W.; Deschamps, J.; Holloway, H. W.; Kopajtic, T.; Katz, J. L.; Brossi, A.; Greig, N. H. Preparation and Characterization of Tetrabenazine Enantiomers against Vesicular Monoamine Transporter 2. ACS Med. Chem. Lett. 2010, 1 (3), 105–109. (161) Cormier, R. A.; Schreiber, W. L.; Agosta, W. C. Photochemical Rearrangements of .Alpha.-Methylene Ketones. J. Am. Chem. Soc. 1973, 95 (15), 4873–4884. (162) Hailes, H. C. Reaction Solvent Selection: The Potential of Water as a Solvent for Organic Transformations. Org. Process Res. Dev. 2007, 11 (1), 114–120. (163) Piradashvili, K.; Alexandrino, E. M.; Wurm, F. R.; Landfester, K. Reactions and 182 Polymerizations at the Liquid-Liquid Interface. Chem. Rev. 2016, 116 (4), 2141–2169. (164) Pithani, S.; Malmgren, M.; Aurell, C. J.; Nikitidis, G.; Friis, S. D. Biphasic Aqueous Reaction Conditions for Process-Friendly Palladium-Catalyzed C-N Cross-Coupling of Aryl Amines. Org. Process Res. Dev. 2019, 23 (8), 1752–1757. (165) Miyaura, N.; Yamada, K.; Suzuki, A. A New Stereospecific Cross-Coupling by the Palladium-Catalyzed Reaction of 1-Alkenylboranes with 1-Alkenyl or 1-Alkynyl Halides. Tetrahedron Lett. 1979, 20 (36), 3437–3440. (166) Zaitsev, A.; Adolfsson, H. Recent Developments in Asymmetric Dihydroxylations. Synthesis (Stuttg). 2006, 1725–1756. (167) Bhushan, B. Bioinspired Oil-Water Separation Approaches for Oil Spill Clean-up and Water Purification. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 2019, 377 (2150). (168) Bhushan, B. Biomimetics and Green Science and Technology Biomimetics, 3rd ed.; Springer, 2018. (169) Celia, E.; Darmanin, T.; Taffin de Givenchy, E.; Amigoni, S.; Guittard, F. Recent Advances in Designing Superhydrophobic Surfaces. J. Colloid Interface Sci. 2013, 402, 1–18. (170) Kota, A. K.; Mabry, J. M.; Tuteja, A. Superoleophobic Surfaces: Design Criteria and Recent Studies. Surf. Innov. 2013, 1 (2), 71–83. (171) Law, K.-Y. Definitions for Hydrophilicity, Hydrophobicity, and Superhydrophobicity: Getting the Basics Right. J. Phys. Chem. Lett. 2014, 5 (4), 686–688. (172) Gao, S. J.; Shi, Z.; Zhang, W. Bin; Zhang, F.; Jin, J. Photoinduced Superwetting Single-Walled Carbon Nanotube/TiO2 Ultrathin Network Films for Ultrafast Separation of Oil-in-Water Emulsions. ACS Nano 2014, 8 (6), 6344–6352. 183 (173) Jiang, L.; Tang, Z.; Park-Lee, K. J.; Hess, D. W.; Breedveld, V. Fabrication of Non-Fluorinated Hydrophilic-Oleophobic Stainless Steel Mesh for Oil-Water Separation. Sep. Purif. Technol. 2017, 184, 394–403. (174) Daponte, J. A.; Guo, Y.; Ruck, R. T.; Hein, J. E. Using an Automated Monitoring Platform for Investigations of Biphasic Reactions. ACS Catal. 2019, 9 (12), 11484–11491. (175) Silva Elipe, M. V.; Donovan, N.; Krull, R.; Pooke, D.; Colson, K. L. Performance of New 400-MHz HTS Power-Driven Magnet NMR Technology on Typical Pharmaceutical API, Cinacalcet HCl. Magn. Reson. Chem. 2018, 56 (9), 817–825. (176) Quasdorf, K.; Murray, J. I.; Nguyen, H.; Silva Elipe, M. V.; Ericson, A.; Kircher, E.; Guan, L.; Caille, S. Development of a Continuous Photochemical Bromination/Alkylation Sequence En Route to AMG 423. Org. Process Res. Dev. 2022, 26 (2), 458–466. (177) Silva Elipe, M. V.; Cherney, A.; Krull, R.; Donovan, N.; Tedrow, J.; Pooke, D.; Colson, K. L. 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 (8), 1428–1434. (178) Maschmeyer, T.; Prieto, P. L.; Grunert, S.; Hein, J. E. Exploration of Continuous-Flow Benchtop NMR Acquisition Parameters and Considerations for Reaction Monitoring. Magn. Reson. Chem. 2020, 58 (12), 1234–1248. (179) Hall, D. G. Structure, Properties, and Preparation of Boronic Acid Derivatives. Overview of Their Reactions and Applications. In Boronic Acids; Wiley-VCH Verlag GmbH & Co. KGaA: Weinheim, FRG, 2006; pp 1–99. (180) Silva, M. P.; Saraiva, L.; Pinto, M.; Sousa, M. E. Boronic Acids and Their Derivatives in 184 Medicinal Chemistry: Synthesis and Biological Applications. Molecules 2020, 25 (18), 4323. (181) Gozdalik, J. T.; Marek, P. H.; Madura, I. D.; Gierczyk, B.; Popenda, Ł.; Schroeder, G.; Adamczyk-Woźniak, A.; Sporzyński, A. Structures and Properties of Trifluoromethylphenylboronic Acids. J. Mol. Struct. 2019, 1180, 237–243. (182) Pace, V.; Holzer, W.; Hoyos, P.; Hernáiz, M. J.; Alcántara, A. R. 2-Methyltetrahydrofuran. In Encyclopedia of Reagents for Organic Synthesis; John Wiley & Sons, Ltd: Chichester, UK, 2014; pp 1–6. (183) Chaudhari, S. R.; Suryaprakash, N. Three-Component Chiral Derivatizing Protocols for NMR Spectroscopic Enantiodiscrimination of Hydroxy Acids and Primary Amines. J. Org. Chem. 2012, 77 (1), 648–651. (184) Carrow, B. P.; Hartwig, J. F. Distinguishing Between Pathways for Transmetalation in Suzuki−Miyaura Reactions. J. Am. Chem. Soc. 2011, 133 (7), 2116–2119. (185) Amatore, C.; Le Duc, G.; Jutand, A. Mechanism of Palladium-Catalyzed Suzuki-Miyaura Reactions: Multiple and Antagonistic Roles of Anionic “Bases” and Their Countercations. Chem. - A Eur. J. 2013, 19 (31), 10082–10093. (186) García-Melchor, M.; Braga, A. A. C.; Lledós, A.; Ujaque, G.; Maseras, F. Computational Perspective on Pd-Catalyzed C–C Cross-Coupling Reaction Mechanisms. Acc. Chem. Res. 2013, 46 (11), 2626–2634. (187) Jin, R. Atomically Precise Metal Nanoclusters: Stable Sizes and Optical Properties. Nanoscale 2015, 7 (5), 1549–1565. (188) Qian, H.; Zhu, M.; Wu, Z.; Jin, R. Quantum Sized Gold Nanoclusters with Atomic Precision. Acc. Chem. Res. 2012, 45 (9), 1470–1479. 185 (189) Du, Y.; Sheng, H.; Astruc, D.; Zhu, M. Atomically Precise Noble Metal Nanoclusters as Efficient Catalysts: A Bridge between Structure and Properties. Chem. Rev. 2020, 120 (2), 526–622. (190) Jin, R.; Zeng, C.; Zhou, M.; Chen, Y. Atomically Precise Colloidal Metal Nanoclusters and Nanoparticles: Fundamentals and Opportunities. Chem. Rev. 2016, 116 (18), 10346–10413. (191) Zhou, M.; Du, X.; Wang, H.; Jin, R. The Critical Number of Gold Atoms for a Metallic State Nanocluster: Resolving a Decades-Long Question. ACS Nano 2021, 15 (9), 13980–13992. (192) Cui, M.; Zhao, Y.; Song, Q. Synthesis, Optical Properties and Applications of Ultra-Small Luminescent Gold Nanoclusters. TrAC Trends Anal. Chem. 2014, 57, 73–82. (193) Zeng, C.; Chen, Y.; Zhao, S.; Jin, R. Atomically Precise Gold and Bimetal Nanoclusters as New Model Catalysts. Stud. Surf. Sci. Catal. 2017, 177 (8), 359–408. (194) Gao, Y.; Shao, N.; Pei, Y.; Zeng, X. C. Icosahedral Crown Gold Nanocluster Au43Cu12 with High Catalytic Activity. Nano Lett. 2010, 10 (3), 1055–1062. (195) Aiken, J. D.; Finke, R. G. Polyoxoanion- and Tetrabutylammonium-Stabilized Rh(0) n Nanoclusters: Unprecedented Nanocluster Catalytic Lifetime in Solution. J. Am. Chem. Soc. 1999, 121 (38), 8803–8810. (196) Aiken, J. D.; Lin, Y.; Finke, R. G. A Perspective on Nanocluster Catalysis: Polyoxoanion and (n-C4H9)4N+ Stabilized Ir(0)∼300 Nanocluster ‘Soluble Heterogeneous Catalysts.’ J. Mol. Catal. A Chem. 1996, 114 (1–3), 29–51. (197) Wang, Y.; Liu, X.; Wang, Q.; Quick, M.; Kovalenko, S. A.; Chen, Q.; Koch, N.; Pinna, N. Insights into Charge Transfer at an Atomically Precise Nanocluster/Semiconductor 186 Interface. Angew. Chemie Int. Ed. 2020, 59 (20), 7748–7754. (198) Liu, J.; Lee, T.; Janes, D. B.; Walsh, B. L.; Melloch, M. R.; Woodall, J. M.; Reifenberger, R.; Andres, R. P. Guided Self-Assembly of Au Nanocluster Arrays Electronically Coupled to Semiconductor Device Layers. Appl. Phys. Lett. 2000, 77 (3), 373–375. (199) Hesari, M.; Ding, Z. A Grand Avenue to Au Nanocluster Electrochemiluminescence. Acc. Chem. Res. 2017, 50 (2), 218–230. (200) Narouz, M. R.; Takano, S.; Lummis, P. A.; Levchenko, T. I.; Nazemi, A.; Kaappa, S.; Malola, S.; Yousefalizadeh, G.; Calhoun, L. A.; Stamplecoskie, K. G.; Häkkinen, H.; Tsukuda, T.; Crudden, C. M. Robust, Highly Luminescent Au13 Superatoms Protected by N-Heterocyclic Carbenes. J. Am. Chem. Soc. 2019, 141 (38), 14997–15002. (201) Narouz, M. R.; Osten, K. M.; Unsworth, P. J.; Man, R. W. Y.; Salorinne, K.; Takano, S.; Tomihara, R.; Kaappa, S.; Malola, S.; Dinh, C.-T.; Padmos, J. D.; Ayoo, K.; Garrett, P. J.; Nambo, M.; Horton, J. H.; Sargent, E. H.; Häkkinen, H.; Tsukuda, T.; Crudden, C. M. N-Heterocyclic Carbene-Functionalized Magic-Number Gold Nanoclusters. Nat. Chem. 2019, 11 (5), 419–425. (202) Ramsay, H.; Simon, D.; Steele, E.; Hebert, A.; Oleschuk, R. D.; Stamplecoskie, K. G. The Power of Fluorescence Excitation–Emission Matrix (EEM) Spectroscopy in the Identification and Characterization of Complex Mixtures of Fluorescent Silver Clusters. RSC Adv. 2018, 8 (73), 42080–42086. (203) Wan, X.-K.; Guan, Z.-J.; Wang, Q.-M. Homoleptic Alkynyl-Protected Gold Nanoclusters: Au44(PhC≡C)28 and Au36 (PhC≡C)24. Angew. Chemie Int. Ed. 2017, 56 (38), 11494–11497. (204) Liao, L.; Chen, J.; Wang, C.; Zhuang, S.; Yan, N.; Yao, C.; Xia, N.; Li, L.; Bao, X.; Wu, 187 Z. Transition-Sized Au92 Nanoparticle Bridging Non-Fcc-Structured Gold Nanoclusters and Fcc-Structured Gold Nanocrystals. Chem. Commun. 2016, 52 (81), 12036–12039. (205) Han, X.; Luan, X.; Su, H.; Li, J.; Yuan, S.; Lei, Z.; Pei, Y.; Wang, Q. Structure Determination of Alkynyl‐Protected Gold Nanocluster Au22(tBuC≡C)18 and Its Thermochromic Luminescence. Angew. Chemie 2020, 132 (6), 2329–2332. (206) Agrachev, M.; Ruzzi, M.; Venzo, A.; Maran, F. Nuclear and Electron Magnetic Resonance Spectroscopies of Atomically Precise Gold Nanoclusters. Acc. Chem. Res. 2019, 52 (1), 44–52. (207) Sato, Y.; Liu, J.; Kukor, A. J.; Culhane, J. C.; Tucker, J. L.; Kucera, D. J.; Cochran, B. M.; Hein, J. E. Real-Time Monitoring of Solid–Liquid Slurries: Optimized Synthesis of Tetrabenazine. J. Org. Chem. 2021, 86 (20), 14069–14078. (208) Cook, A. W.; Hayton, T. W. Case Studies in Nanocluster Synthesis and Characterization: Challenges and Opportunities. Acc. Chem. Res. 2018, 51 (10), 2456–2464. (209) Yousefalizadeh, G.; Stamplecoskie, K. G. Norrish Type I Photochemistry as a Powerful Tool in the Isolation of Thiol Protected Au25SR18 Clusters. J. Photochem. Photobiol. A Chem. 2018, 353, 251–254. (210) Chen, T.; Fung, V.; Yao, Q.; Luo, Z.; Jiang, D.; Xie, J. Synthesis of Water-Soluble [Au25(SR)18]− Using a Stoichiometric Amount of NaBH 4. J. Am. Chem. Soc. 2018, 140 (36), 11370–11377. (211) Negishi, Y.; Hashimoto, S.; Ebina, A.; Hamada, K.; Hossain, S.; Kawawaki, T. Atomic-Level Separation of Thiolate-Protected Metal Clusters. Nanoscale 2020, 12 (15), 8017–8039. (212) Niihori, Y.; Uchida, C.; Kurashige, W.; Negishi, Y. High-Resolution Separation of 188 Thiolate-Protected Gold Clusters by Reversed-Phase High-Performance Liquid Chromatography. Phys. Chem. Chem. Phys. 2016, 18 (6), 4251–4265. (213) Zhang, Y.; Hu, Q.; Paau, M. C.; Xie, S.; Gao, P.; Chan, W.; Choi, M. M. F. Probing Histidine-Stabilized Gold Nanoclusters Product by High-Performance Liquid Chromatography and Mass Spectrometry. J. Phys. Chem. C 2013, 117 (36), 18697–18708. (214) Xie, S.; Paau, M. C.; Zhang, Y.; Shuang, S.; Chan, W.; Choi, M. M. F. High-Performance Liquid Chromatographic Analysis of as-Synthesised N,N′-Dimethylformamide-Stabilised Gold Nanoclusters Product. Nanoscale 2012, 4 (17), 5325. (215) Kulkarni, V. K.; Khiarak, B. N.; Takano, S.; Malola, S.; Albright, E. L.; Levchenko, T. I.; Aloisio, M. D.; Dinh, C.; Tsukuda, T.; Häkkinen, H.; Crudden, C. M. N-Heterocyclic Carbene-Stabilized Hydrido Au24 Nanoclusters: Synthesis, Structure, and Electrocatalytic Reduction of CO2. J. Am. Chem. Soc. 2022, 144 (20), 9000–9006. (216) Shichibu, Y.; Suzuki, K.; Konishi, K. Facile Synthesis and Optical Properties of Magic-Number Au13 Clusters. Nanoscale 2012, 4 (14), 4125–4129. (217) Shichibu, Y.; Konishi, K. HCl-Induced Nuclearity Convergence in Diphosphine-Protected Ultrasmall Gold Clusters: A Novel Synthetic Route to “Magic-Number” Au13 Clusters. Small 2010, 6 (11), 1216–1220. (218) Negishi, Y.; Nobusada, K.; Tsukuda, T. Glutathione-Protected Gold Clusters Revisited: Bridging the Gap between Gold(I)-Thiolate Complexes and Thiolate-Protected Gold Nanocrystals. J. Am. Chem. Soc. 2005, 127 (14), 5261–5270. (219) Teychené, S.; Rodríguez-Ruiz, I.; Ramamoorthy, R. K. Reactive Crystallization: From Mixing to Control of Kinetics by Additives. Curr. Opin. Colloid Interface Sci. 2020, 46, 1–19. 189 (220) Kelkar, V. V.; Ng, K. M. Design of Reactive Crystallization Systems Incorporating Kinetics and Mass-Transfer Effects. AIChE J. 1999, 45 (1), 69–81. (221) Ståhl, M.; Rasmuson, Å. C. Towards Predictive Simulation of Single Feed Semibatch Reaction Crystallization. Chem. Eng. Sci. 2009, 64 (7), 1559–1576. (222) Torbacke, M.; Rasmuson, Å. C. Mesomixing in Semi-Batch Reaction Crystallization and Influence of Reactor Size. AIChE J. 2004, 50 (12), 3107–3119. (223) Berry, D. A.; Ng, K. M. Synthesis of Reactive Crystallization Processes. AIChE J. 1997, 43 (7), 1737–1750. (224) Rodriguez-Zubiri, M.; Felpin, F.-X. Analytical Tools Integrated in Continuous-Flow Reactors: Which One for What? Org. Process Res. Dev. 2022, 26 (6), 1766–1793. (225) Li, J.; Šimek, H.; Ilioae, D.; Jung, N.; Bräse, S.; Zappe, H.; Dittmeyer, R.; Ladewig, B. P. In Situ Sensors for Flow Reactors – a Review. React. Chem. Eng. 2021, 6 (9), 1497–1507. (226) Plutschack, M. B.; Pieber, B.; Gilmore, K.; Seeberger, P. H. The Hitchhiker’s Guide to Flow Chemistry. Chem. Rev. 2017, 117 (18), 11796–11893. (227) Hartman, R. L.; McMullen, J. P.; Jensen, K. F. Deciding Whether To Go with the Flow: Evaluating the Merits of Flow Reactors for Synthesis. Angew. Chemie Int. Ed. 2011, 50 (33), 7502–7519. (228) Bhushan, B. Bioinspired Oil–Water Separation Approaches for Oil Spill Clean-up and Water Purification. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 2019, 377 (2150), 20190120. (229) Black, D. M.; Robles, G.; Lopez, P.; Bach, S. B. H.; Alvarez, M.; Whetten, R. L. Liquid Chromatography Separation and Mass Spectrometry Detection of Silver-Lipoate Ag29(LA)12 Nanoclusters: Evidence of Isomerism in the Solution Phase. Anal. Chem. 190 2018, 90 (3), 2010–2017. (230) Baghdasaryan, A.; Grillo, R.; Roy Bhattacharya, S.; Sharma, M.; Reginato, E.; Theraulaz, H.; Dolamic, I.; Dadras, M.; Rudaz, S.; Varesio, E.; Burgi, T. Facile Synthesis, Size-Separation, Characterization, and Antimicrobial Properties of Thiolated Copper Clusters. ACS Appl. Nano Mater. 2018, 1 (8), 4258–4267. (231) Wilcoxon, J. P.; Craft, S. A. Liquid Chromatographic Analysis and Characterization of Inorganic Nanoclusters. Nanostructured Mater. 1997, 9 (1–8), 85–88. 191 Appendix A NMR Spectra for Chapter 2 A.1 Tetrabenazine (TBZ) ((rac)-2.1) 1H NMR (400 MHz, CDCl3) 13C {1H} NMR (101 MHz, CDCl3) NMeOMeOOH(rac)-2.1NMeOMeOOH(rac)-2.1192 A.2 3-[(dimethylamino)methyl]-5-methylhexan-2-one (2.12) 1H NMR (400 MHz, CDCl3) 13C {1H} NMR (101 MHz, CDCl3) OMe2Ni-Bu2.12OMe2Ni-Bu2.12193 A.3 5-methyl-3-methylidenehexan-2-one (2.14) 1H NMR (400 MHz, CDCl3) 13C {1H} NMR (101 MHz, CDCl3) i-BuO2.14i-BuO2.14194 A.4 trimethyl-[2-(2-methylpropyl)-3-oxobutyl]-azanium iodide 1H NMR (400 MHz, CDCl3) OMe3NI195 A.5 TBZ diastereomers ((rac)-2.22) 1H NMR (400 MHz, CDCl3) 13C {1H} NMR (101 MHz, CDCl3) NMeOMeOOi-BuH(rac)-2.22NMeOMeOOi-BuH(rac)-2.22196 A.6 6,7-dimethoxy-2-[2-(2-methylpropyl)-3-oxobutyl]-3,4-dihydroisoquinolin-2-ium (2.23) 1H NMR (400 MHz, CDCl3) 13C {1H} NMR (101 MHz, CDCl3) NMeOMeOOi-Bu2.23NMeOMeOOi-Bu2.23197 1H-1H COSY (400 MHz, CDCl3) According to COSY NMR, H11-H12 and H3-H4 were observed. Diastereotpic protons at C15 were confirmed to be at 1.37 and 1.67 ppm separately. 1 11 12 3 11,12 3-4 15,16 17,18 15 12-15 12-15 15,16 16-17,18 4 134514N8910MeO11MeO1215161718O8NMeOMeOOi-Bu2.23198 1H-13C HMQC (400/101 MHz, CDCl3) According to HMQC NMR, carbons possessing protons peaks in 13C NMR were identified: C17, 18 (23.0, 23.1), C15 (39.0), C16 (either 26.1 or 26.2), C14 (29.8), C4 (either 26.1 or 26.2), C12 (either 49.9 or 50.8), C9,10 (56.9, 57.0), C3 (either 49.9 or 50.8), C11 (60.0), C5 (110.8), C8 (116.1), and C1 (165.6). 1 11 12 4 3 15,16 17,18 15 5 8 9,10 14 134514N8910MeO11MeO1215161718O8NMeOMeOOi-Bu2.23199 1H-13C HMBC (400/101 MHz, CDCl3) According to HMBC NMR, C1 has no correlation with H14 but H11 shown above, which corresponds to the iminium intermediate 6. 1 11 12 4 3 15,16 17,18 15 5 8 9,10 14 1 11 14 134514N8910MeO11MeO1215161718O8NMeOMeOi-Bu2.23200 Appendix B NMR Spectra for Chapter 3 B.1 2-Fluoro-5-pyridyl-boronic acid (Partition Test Section 3.4, Figure 3.5 B) (3.1) 1H NMR (400 MHz, 2-MeTHF) 19F NMR (377 MHz, 2-MeTHF) NB(OH)2F3.1NB(OH)2F3.1201 11B NMR (128 MHz, 2-MeTHF) NB(OH)2F3.1202 B.2 2-Fluoro-5-pyridyl-boronate (Partition Test Section 3.4, Figure 3.5 F) (3.1) 1H NMR (400 MHz, water) 19F NMR (377 MHz, water) NB(OH)3FNB(OH)3F203 11B NMR (128 MHz, water) NB(OH)3F204 B.3 3-Fluoro-5-hydroxyphenyl-boronic acid (Partition Test Section 3.4, Figure 3.6 B) (3.2) 1H NMR (400 MHz, 2-MeTHF) 19F NMR (377 MHz, 2-MeTHF) B(OH)2OHF3.2B(OH)2OHF3.2205 11B NMR (128 MHz, 2-MeTHF) B(OH)2OHF3.2206 B.4 4-(trifluoromethyl)phenyl-boronic acid (Partition Test Section 3.4, Figure 3.7 B) (3.3) 1H NMR (400 MHz, 2-MeTHF) 19F NMR (377 MHz, 2-MeTHF) BF3COHOH3.3BF3COHOH3.3207 11B NMR (128 MHz, 2-MeTHF) B.5 4-(trifluoromethyl)phenyl-boronate (Partition Test Section 3.4, Figure 3.7 F) (3.3) 1H NMR (400 MHz, water) BF3COHOH3.3208 19F NMR (377 MHz, water) 209 11B NMR (128 MHz, water) 210 B.6 NMR spectra of reaction monitoring with 2-fluoro-5-pyridyl-boronic acid (organic) Starting materials: 1H NMR (400 MHz, 2-MeTHF) During reaction: 1H NMR (400 MHz, 2-MeTHF) 211 Starting materials: 19F NMR (377 MHz, 2-MeTHF) During reaction: 19F NMR (377 MHz, 2-MeTHF) 212 Starting materials: 11B NMR (128 MHz, 2-MeTHF) During reaction: 11B NMR (128 MHz, 2-MeTHF) 213 B.7 NMR spectra of reaction monitoring with 2-fluoro-5-pyridyl-boronic acid (aqueous) During reaction: 1H NMR (400 MHz, water) Over the course of the reaction, only F-Pyridyl BA peak was observed with the decreasing trend. 214 During reaction: 19F NMR (377 MHz, water) Over the course of the reaction, only F-Pyridyl BA peak was observed with the decreasing trend. 215 Starting materials: 11B NMR (128 MHz, water) During reaction: 11B NMR (128 MHz, water)
Thesis/Dissertation
eng
Chemistry
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Hein, Jason
Development of process analytical technologies and application for complicated reaction conditions
Text