Science, Faculty of
Chemistry, Department of
DSpace
UBCV
Daponte, Jordan Ashton
Master of Science - MSc
University of British Columbia
Mechanistic insight is fundamental to understanding a reaction and essential towards accessing desired product(s) in high yield, enantiopurity, and efficiency. Key to unlocking these investigations are developing tools that can monitor as many reactive species, intermediates, and products over the course of a reaction as possible. In the case of heterogeneous and biphasic systems, this analysis requires the development of new monitoring methodologies that can probe the complex equilibria, solubilities, mass transfer events, and catalytic cycles associated with the reaction. Herein, the development and deployment of reaction monitoring methods for the study of heterogeneous and biphasic reactions is discussed. These methodologies were deployed in two case studies, the first of which involved investigation of stereoselectivities of a proline catalyzed aldol reaction, while the second probed a biphasic reaction for an enantioselective spirocyclization catalyzed by a doubly quaternized cinchona alkaloid. The monitoring platforms allowed for the identification of water as the primary source of stereoselectivity in the proline-catalyzed aldol reaction, while also identifying the observed rate law, catalyst deactivation, and gaining insight into product behaviours. Investigations suggest that stereoselectivity likely originates from differences in transition states arising from the presence of water, rather than through kinetic phenomena. In the case of biphasic systems, a combined approach utilizing phase selective and heterogeneous sampling allowed for tracking of reaction species across both phases, allowing for insight into the reaction rate law, catalyst degradation, mass transfer behaviour, and temperature dependence studies. These results suggest that productive spirocyclization is balanced against inescapable catalyst degradation, with future optimization likely requiring new catalyst designs to counteract this relationship. The deployment of these monitoring methods provided the data necessary to carry out in-depth analysis of these two reactions which would not be accessible through end-point analysis. These methodologies promise excellent utility in the study of other heterogeneous and biphasic systems, with potential applications in mechanistic investigations and reaction optimizations.
Development and Deployment of Automated Monitoring Methodologies Towards Investigations of Heterogeneous and Biphasic Reactions by Jordan Ashton Daponte B.Sc., University of Toronto, 2017 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Chemistry) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) November 2019 © Jordan Ashton Daponte, 2019 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis/dissertation entitled: Development and Deployment of Automated Monitoring Methodologies Towards Investigations of Heterogeneous and Biphasic Reactions submitted by Jordan Daponte in partial fulfillment of the requirements for the degree of Master of Science in Chemistry Examining Committee: Dr. Jason E. Hein Supervisor Dr. Glenn Sammis Supervisory Committee Member Dr. Gregory Dake Supervisory Committee Member iii Abstract Mechanistic insight is fundamental to understanding a reaction and essential towards accessing desired product(s) in high yield, enantiopurity, and efficiency. Key to unlocking these investigations are developing tools that can monitor as many reactive species, intermediates, and products over the course of a reaction as possible. In the case of heterogeneous and biphasic systems, this analysis requires the development of new monitoring methodologies that can probe the complex equilibria, solubilities, mass transfer events, and catalytic cycles associated with the reaction. Herein, the development and deployment of reaction monitoring methods for the study of heterogeneous and biphasic reactions is discussed. These methodologies were deployed in two case studies, the first of which involved investigation of stereoselectivities of a proline catalyzed aldol reaction, while the second probed a biphasic reaction for an enantioselective spirocyclization catalyzed by a doubly quaternized cinchona alkaloid. The monitoring platforms allowed for the identification of water as the primary source of stereoselectivity in the proline-catalyzed aldol reaction, while also identifying the observed rate law, catalyst deactivation, and gaining insight into product behaviours. Investigations suggest that stereoselectivity likely originates from differences in transition states arising from the presence of water, rather than through kinetic phenomena. In the case of biphasic systems, a combined approach utilizing phase selective and heterogeneous sampling allowed for tracking of reaction species across both phases, allowing for insight into the reaction rate law, catalyst degradation, mass transfer behaviour, and temperature dependence studies. These results suggest that productive spirocyclization is balanced against inescapable catalyst degradation, with future optimization likely requiring new catalyst designs to counteract this relationship. The deployment of these monitoring methods provided the data necessary to carry out in-depth analysis of these two iv reactions which would not be accessible through end-point analysis. These methodologies promise excellent utility in the study of other heterogeneous and biphasic systems, with potential applications in mechanistic investigations and reaction optimizations. v Lay Summary Developing tools and techniques to study complex chemical reactions is an important part of understanding chemistry. Reaction conditions cover a wide range, with some operating at extreme pressures, temperatures, toxicity, reactivity, and various combinations of liquids, solids and gases. These conditions can make sampling a reaction difficult, and so specialized procedures must be designed to meet the unique needs of each reaction in order to learn as much as possible from them. In this work, two automated reaction monitoring procedures were developed and applied to the study of two reactions, one of which involved a liquid-solid slurry, and the other involving a biphasic liquid-liquid solvent system. The information gained from these monitoring approaches provided insight into the mechanisms of these reactions and opened up the possibility for future studies. vi Preface The “Aldol Project” as outlined in Chapter 2 was a collaborative effort undertaken by myself and Dr. Jason E. Hein at the University of British Columbia, as well as Dr. Paul Ha-Yeon Cheong and his student(s) at Oregon State University. Dr. Matthew Vetticatt and his student, Victor M. Wambua at Binghamton University were later consulted for their specialty in integrated 13C NMR experiments. I conducted all work presented in this chapter except for the experimental array outlined in section 2.8 which was conducted on an in-development robotic sampling platform with the help of Dr. Lars Yunker, Elena Liles, Henry Situ, Veronica Lai, and Dr. Sebastian Steiner, on a platform designed and built by Allan Hendry. I designed the experiments and prepared them for the platform with the help of Henry Situ. All computational and integrated 13C experiments were carried out by the groups in Oregon State University and Binghamton respectively. The work from this chapter is not yet published, with a manuscript under preparation. Chapter 3 has been submitted for publication. The project was conducted as a collaboration between myself and Dr. Jason E. Hein at the University of British Columbia, and Dr. Rebecca Ruck at Merck & Co. I conducted all experimental work surrounding the modification of an existing sampling platform to the study of a biphasic reaction, as well as the subsequent kinetic investigations into the reaction catalyzed by a doubly quaternized cinchona alkaloid phase transfer catalyst. I designed and completed all experiments surrounding solubility measurements, catalyst decomposition, and kinetic profiling. Both equipment and experimental design were decided upon by me and Dr. Jason E. Hein. Yuejun Guo determined the initial conditions for the reaction, including HPLC method development. The spirocyclic precursor, vii initial batch of phase transfer catalyst, and characterization were kindly provided by Dr. Rebecca Ruck and co-workers. The miniature reactor vial was designed by and acquired from Technobis. viii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ....................................................................................................................... viii List of Tables .............................................................................................................................. xiv List of Figures ...............................................................................................................................xv List of Schemes ...........................................................................................................................xxv List of Symbols ......................................................................................................................... xxvi List of Abbreviations .............................................................................................................. xxvii Acknowledgements .................................................................................................................. xxxi Dedication ................................................................................................................................ xxxii Chapter 1: Introduction ................................................................................................................1 1.1 Spectroscopy ................................................................................................................... 3 1.1.1 Fourier Transform Infrared Spectroscopy (FTIR) ...................................................... 4 1.1.2 Ultraviolet-Visible Spectroscopy (UV-Vis) ............................................................... 7 1.1.3 Nuclear Magnetic Resonance (NMR) ......................................................................... 8 High Performance Liquid Chromatography (HPLC) ............................................................... 12 1.2 Gas Chromatography (GC) ........................................................................................... 16 1.3 Mass Spectrometry (MS) .............................................................................................. 18 1.4 The Problem with Heterogeneous Solutions................................................................. 19 Chapter 2: Investigating the Changes in Stereoselectivity of a Proline-Catalyzed Aldol Reaction ........................................................................................................................................24 ix 2.1 Synopsis ........................................................................................................................ 24 2.2 Introduction to the Houk-List Model and the Proline-Catalyzed Aldol Reaction ........ 24 2.3 Initial Studies into Diastereoselectivity and Enantioselectivity .................................... 31 2.4 Screening a Range of Reaction Conditions .................................................................. 32 2.4.1 Probing the potential role of By-product Catalysis ................................................... 36 2.5 Development of an Autonomous Sampling Platform for a Heterogeneous Mixture .... 38 2.6 Exploring Kinetic Behavior Under the Dry and Wet DMSO conditions ..................... 42 2.6.1 Product Degradation and Epimerization studies ....................................................... 43 2.6.2 Product Inhibition and Further Decomposition Studies............................................ 49 2.7 Investigations into Solubility and the Solid Phase of the Reaction .............................. 51 2.8 Probing Reaction Behaviour Using Reaction Progress Kinetic Analysis (RPKA) and Variable Time Normalization Analysis (VTNA) ..................................................................... 52 2.8.1 Utilization of a Next Generation Kinetic Study Platform to increase monitoring capability ............................................................................................................................... 52 2.8.2 Same Excess Experiments to probe the role of catalyst deactivation or product inhibition ............................................................................................................................... 56 2.8.3 Different Excess experiment to determine rate order of reactants ............................ 59 2.8.3.1 Summary of kinetic analysis using RPKA and VTNA ..................................... 64 2.9 Water dosing experiments demonstrate the direct involvement of water in the stereochemistry determining step ............................................................................................. 65 2.9.1 13C NMR Experiments to probe kinetic isotope effects ............................................ 67 2.9.1.1 Derivatization of aldol products for NMR studies ............................................ 69 2.9.1.2 Purification and Recrystallization of aldol products for NMR studies ............. 70 x 2.10 Conclusions ................................................................................................................... 71 2.11 Experimental ................................................................................................................. 73 2.11.1 General Notes........................................................................................................ 73 2.11.2 Automated Reaction Monitoring and HPLC Analysis ......................................... 74 2.11.2.1 Instrumentation Design and Setup ................................................................ 74 2.11.2.2 General Procedure for Kinetic Experiments ................................................. 75 2.11.2.3 General Procedure for the Aldol Reaction .................................................... 75 2.11.3 General Procedure for Aldol Product (2.1) Degradation Studies ......................... 76 2.11.3.1 Product Inhibition in Dry DMSO ................................................................. 77 2.11.3.2 Product Inhibition in Wet DMSO ................................................................. 77 2.11.4 Solubility Experiments.......................................................................................... 77 2.11.5 Aldol Reaction Conditions Screen ........................................................................ 78 2.11.6 Next Generation Reaction Sampling, RPKA and VTNA Studies ........................ 78 2.11.6.1 Parallel Reaction Sampler ............................................................................. 79 2.11.6.2 General Procedure for RPKA Studies........................................................... 79 2.11.6.2.1 RPKA Plots for DMSO Only Solvent Conditions .................................... 81 2.11.6.2.2 RPKA Plots for DMSO:H2O (4:1 ratio by volume) Solvent Conditions .. 84 2.11.6.3 General Procedure for Variable Time Normalization Analysis (VTNA) ..... 87 2.11.6.3.1 VTNA Plots for DMSO Only.................................................................... 87 2.11.7 Additional Experiments ........................................................................................ 92 2.11.7.1 Monitoring Product Distribution by HPLC .................................................. 92 2.11.7.2 Monitoring 2.1 enantiomer populations using chiral HPLC. ........................ 93 2.11.7.3 Byproduct catalysis (formation of mixture of oxazolidinones) .................... 94 xi 2.11.7.4 Crystallization and X-Ray Identification of Major Stereoisomer of 2.1 (S,R) under wet DMSO conditions. ........................................................................................... 95 2.11.7.5 Calibration Plots.......................................................................................... 103 2.11.8 1H and 13C NMR Data......................................................................................... 104 Chapter 3: Investigations in a Phase Transfer Catalysis Reaction .......................................105 3.1 Phase Transfer Catalysis ............................................................................................. 105 3.2 Development of an Automated Sampling System for Biphasic Reaction Monitoring 109 3.2.1 General Monitoring of Both Phases ........................................................................ 114 3.2.2 Selective Monitoring of the Organic Phase ............................................................ 115 3.2.3 Refinement and Validation of the Sampling Method(s) ......................................... 118 3.3 Initial Studies .............................................................................................................. 121 3.3.1 The Issue of Reproducibility ................................................................................... 122 3.3.2 Control Experiments ............................................................................................... 123 3.3.3 Order of Additions .................................................................................................. 126 3.3.4 Stir-Rate and Mass Transfer ................................................................................... 127 3.3.5 Solubility ................................................................................................................. 128 3.4 Reaction Progress Kinetic Analysis (RPKA) and Variable Time Normalization Analysis (VTNA) Studies ....................................................................................................... 130 3.4.1 Same Excess............................................................................................................ 130 3.4.2 Different Excess ...................................................................................................... 131 3.4.3 VTNA ..................................................................................................................... 132 3.5 Catalyst Behaviour ...................................................................................................... 135 3.5.1 Temperature Dependence ....................................................................................... 140 xii 3.5.2 Conclusions ............................................................................................................. 143 3.6 Experimental ............................................................................................................... 143 3.6.1 General Notes.......................................................................................................... 143 3.6.2 Procedures ............................................................................................................... 146 3.6.2.1 Biphasic Reaction Sampling ........................................................................... 146 3.6.2.2 Instrumentation Design and Setup .................................................................. 146 3.6.2.3 General Procedure for the Phase Transfer Catalyzed Reaction ...................... 149 3.6.2.4 Using tetrabutylammonium bromide as catalyst............................................. 149 3.6.2.5 Synthesis of the Singly Quaternized Cinchona Alkaloid Catalyst.................. 150 3.6.2.6 Synthesis of the Doubly Quaternized Cinchona Alkaloid Catalyst ................ 151 3.6.2.7 Validation of the Sampling Methodology using Benzoic Acid and Benzyl Alcohol………………………………………………………………………………….151 3.6.2.8 Determination of Solubility via Gravimetric Analysis ................................... 152 3.6.2.9 Catalyst Decomposition Studies ..................................................................... 152 3.6.2.10 Monitoring via Selective Phase Sampling .................................................. 152 3.6.2.11 Monitoring via Heterogeneous Sampling ................................................... 153 3.6.2.12 Monitoring via 1H NMR ............................................................................. 154 3.6.3 Additional Experiments .......................................................................................... 155 3.6.4 Kinetic Studies ........................................................................................................ 159 3.6.5 General Procedure for Kinetic Studies ................................................................... 159 3.6.6 Reaction Progress Kinetic Analysis (RPKA) ......................................................... 160 3.6.6.1 Same Excess.................................................................................................... 160 3.6.6.2 Different Excess – Spirocyclic precursor (2) .................................................. 161 xiii 3.6.6.3 Different Excess - NaOH ................................................................................ 162 3.6.7 Variable Time Normalization Analysis (VTNA) ................................................... 162 3.6.8 Calibration Plots and NMR spectra ........................................................................ 163 3.6.8.1 Calibration Plots.............................................................................................. 163 3.6.8.1.1 Spirocyclic Precursor ................................................................................ 163 3.6.8.1.2 Phase Transfer Catalyst ............................................................................. 164 3.6.8.2 NMR Spectra .................................................................................................. 165 Conclusion ..................................................................................................................................168 Bibliography ...............................................................................................................................171 Appendices ..................................................................................................................................182 Appendix A ............................................................................................................................. 182 A.1 NMR spectra for Chapter 2 ..................................................................................... 182 A.2 NMR Spectra for Chapter 3 .................................................................................... 187 xiv List of Tables Table 1: Summary of a proline catalyzed aldol reaction between benzaldehyde (2.0 M), cyclohexanone (2.0 M) and (S)-proline (2.0 M) in DMSO and DMSO:H2O (4:1 volume) solvent systems. ......................................................................................................................................... 32 Table 2. Summary of reaction screen varying benzaldehyde and proline relative concentration under dry or wet conditions. ......................................................................................................... 33 Table 3. Conditions explored for detailed RPKA kinetic analysis. .............................................. 53 Table 4: Fractional Atomic Coordinates (×104) and Equivalent Isotropic Displacement Parameters (Å2×103) for jh032. Ueq is defined as 1/3 of the trace of the orthogonalised Uij. ...... 98 Table 5: Anisotropic Displacement Parameters (×104) jh032. The anisotropic displacement factor exponent takes the form: -22[h2a*2 × U11+ ... +2hka* × b* × U12] ................................. 99 Table 6: Bond Lengths in Å for jh032. ....................................................................................... 99 Table 7: Bond Angles in ° for jh032. ........................................................................................ 100 Table 8: Torsion Angles in ° for jh032. .................................................................................... 100 Table 9: Hydrogen Fractional Atomic Coordinates (×104) and Equivalent Isotropic Displacement Parameters (Å2×103) for jh032. Ueq is defined as 1/3 of the trace of the orthogonalised Uij. ..................................................................................................................... 101 Table 10: Hydrogen Bond information for jh032. ................................................................. 102 Table 11: Summary of conditions and concentrations used for RPKA and VTNA reaction concentrations and reagent amounts used. † NaOH volumes based on a 1.2 N stock solution. . 160 xv List of Figures Figure 1. Simplified scheme for a ReactIR probe. Light generated by the IR spectrometer is carried along a fibre optic cable and shone into solution (right). The light returned to the probe is recorded, compared against a reference, and processed using Fourier Transform into a spectrum.......................................................................................................................................................... 6 Figure 2. Figure outlining the Larmor Frequency of a nuclei as its precession around an axis in an external magnetic field. The gyromagnetic ratio, γ, depends on the nuclei’s charge, mass, and magnetic moment. ........................................................................................................................... 9 Figure 3. Sample 400 MHz spectrometer (left) and a cutaway of spectrometer (right)20. ........... 10 Figure 4. Sample HPLC configuration (left) and depiction of a chromatography column with a theoretical plate(s) (right).29 .......................................................................................................... 13 Figure 5. Simplified description of the Van Deemter equation terms (left) and the resulting plot (right).29,31 ..................................................................................................................................... 14 Figure 6. Schematic of a sample GC system.38 ............................................................................. 17 Figure 7. Schematic of a sample triple quadrupole (QQQ) spectrometer40. ................................. 18 Figure 8. Cutaway schematic of the Easy Sampler probe head, highlighting the internal plumbing (inflow and outflow highlighted in orange). The probe can be primed while the scoop is in solution (left), and then quench the aliquot for dispensing (right). .............................................. 22 Figure 9: Aldol condensation reaction between cyclohexanone and benzaldehyde as catalyzed by (S)-proline. ..................................................................................... Error! Bookmark not defined. Figure 10. Proposed catalytic cycle for the proline catalyzed aldol condensation reaction. ........ 26 xvi Figure 11: Schematic illustrating the four major transition states and their corresponding stereoisomer products for the S-proline catalyzed aldol condensation reaction of benzaldehyde and cyclohexanone as proposed by Houk et al48. ......................................................................... 28 Figure 12. Possible scenarios to explain observed outcome of aldol condensation reactions in the presence and absence of water. ..................................................................................................... 35 Figure 13. Preparation of oxazolidinone byproducts (top) and investigating their catalytic activity in the aldol condensation reaction................................................................................................. 37 Figure 14: Summary of changing stereoselectivities in response to solvent conditions of the proline catalyzed aldol reaction between benzaldehyde and cyclohexanone ............................... 39 Figure 15: Schematic outlining the automated sampling platform, including nitrogen line (A), quench reservoir (B), Gilson 215 Liquid Handler with mounted Valvemate 6-port, 1 position valve, (C), Valvemate 6-port, 2-position injection valve (D), Ismatec Piston Pump (E), Reaction vessel (F). ...................................................................................................................................... 40 Figure 16: Time-course profiling of the aldol condensation between dry DMSO (left) and wet DMSO (4:1 H2O, v/v) (right). [cyclohexanone]o = [benzaldehyde]o = [(S)-proline]o = 2.0 M .... 43 Figure 17: Exposure of aldol products to (S)-proline in DMSO ................................................... 44 Figure 18: Exposure of minor product diastereomer ((S,S), (R,R), 58% e.e.) to reaction conditions; [minor diastereomer]o = [proline]o = 0.1 M. Analysis by HPLC. .............................. 45 Figure 19: Exposure of major product diastereomer ((S,R), (R,S), 93% e.e.) to reaction conditions; [major diastereomer]o = [proline]o = 0.1 M ............................................................... 47 Figure 20: Monitoring enantiomer degradation upon exposure of the anti-diastereomer (93% e.e.) to dry DMSO and (S)-proline. Peak area normalized using 1,3,5-trimethoxybenzene (TMB, 0.5 equiv) as internal standard. [major diastereomer]o = [proline]o = 0.1 M. ..................................... 48 xvii Figure 21: Aldol reaction with initial 0.1 M dose of the major diastereomer (93% e.e.). [benzaldehyde]o = [cyclohexanone]o = [(S)-proline]o = 2.0 M, [major diastereomer]o = 0.10 M. 50 Figure 22. Overview of robotic sampler protocol ......................................................................... 53 Figure 23. Variable time normalization analysis with equation (top) and sample graphs below with time course plot (left) and time normalized plot (right). ...................................................... 55 Figure 24. Same excess experiments in dry DMSO (top) and wet DMSO (4:1 H2O, v/v) (bottom). [(S)-proline]o = 0.030 M. .............................................................................................. 57 Figure 25. Different excess in cyclohexanone, in dry DMSO. Series A ([cyclohexanone]o = 2.0 M; [benzaldehyde]o = 0.10 M, [(S)-proline = 0.030 M]); Series B ([cyclohexanone]o = 1.50 M; [benzaldehyde]o = 0.10 M, [(S)-proline = 0.030 M]); Series D ([cyclohexanone]o = 2.0 M; [benzaldehyde]o = 0.10 M, [(S)-proline = 0.015 M]); Series E ([cyclohexanone]o = 1.50 M; [benzaldehyde]o = 0.10 M, [(S)-proline = 0.015 M]); .................................................................. 59 Figure 26. Reaction profiles showing accumulation of products from different excess in cyclohexanone in wet DMSO. ...................................................................................................... 61 Figure 27. Variable time normalization analysis plots for determining the order of cyclohexanone in dry DMSO (top) and wet DMSO (bottom). .............................................................................. 62 Figure 28. Different excess in benzaldehyde in dry DMSO (top) and wet DMSO (bottom). ...... 63 Figure 29. Sample VTNA plots for proline in dry DMSO (left) and wet DMSO (right). ............ 64 Figure 30: Examining product inhibition by dosing water and stating material into a DMSO only system. (top left) Tracking species concentrations; (top right) tracking 2.1 diastereomers; (bottom left) Tracking enantiomeric excess; D) Tracking individual enantiomer populations via chiral HPLC. [cyclohexanone]o = [benzaldehyde]o = [(S)-proline]o = 2.0 M. .............................. 66 Figure 31. Work flow for separation and purification of aldol product 2.1 diastereomers. ......... 71 xviii Figure 32. Organic phase selective sampling configuration with quench solution (A), Gilson 215 (B), 6-port, 2-position valve (C), Ismatec Piston Pump (D) and reactor assembly (E). Nitrogen line and additional 6-port, 1-position valve not pictured. ............................................................. 74 Figure 33: Table of concentrations, volumes, and masses used for the DOE array. An identical array was conducted varying DMSO only and DMSO:H2O (4:1 ratio by volume) ..................... 78 Figure 34: Table of concentrations and reagent amounts for use in RPKA and VTNA studies .. 80 Figure 35: Reaction profiles of RPKA series under DMSO only solvent conditions .................. 83 Figure 36: Reaction profiles of RPKA series under DMSO:H2O (4:1 ratio by volume) solvent conditions ...................................................................................................................................... 85 Figure 37. Different excess plots for cyclohexanone in dry DMSO. ............................................ 85 Figure 38. Different excess plots for cyclohexanone in wet DMSO. ........................................... 86 Figure 39. Different excess plots for benzaldehyde in dry DMSO............................................... 86 Figure 40. Different excess plots for benzaldehyde in wet DMSO. ............................................. 86 Figure 41. VTNA plots for cyclohexanone in dry DMSO............................................................ 88 Figure 42. VTNA plots for benzaldehyde in dry DMSO.............................................................. 88 Figure 43. VTNA plots for (S)-proline in dry DMSO. ................................................................. 89 Figure 44. VTNA plots for benzaldehyde in wet DMSO. ............................................................ 90 Figure 45. VTNA plots for cyclohexanone in wet DMSO. .......................................................... 90 Figure 46. VTNA plots for (S)-proline in wet DMSO. ................................................................. 91 Figure 47. HPLC trace of product distributions under dry DMSO ([cyclohexanone]o = [benzaldehyde]o = [(S)-proline]o = 2.0 M). Benzoic acid = 3.624 min; benzaldehyde = 3.6943 min; 2.5 = 6.431 min, 2.1 ((S,S),(R,R)) = 6.218 min; 2.1 ((S,R),(R,S)) = 6.343 min; 2.6 = 7.236, 7.810 min (diastereomers). ........................................................................................................... 92 xix Figure 48. HPLC trace of product distributions under wet DMSO ([cyclohexanone]o = [benzaldehyde]o = [(S)-proline]o = 2.0 M). Benzaldehyde = 3.905 min; 2.1 ((S,S),(R,R)) = 6.189 min; 2.1 ((S,R),(R,S)) = 6.333 min. ............................................................................................... 92 Figure 49. Measurement of aldol product 2.1 enantiomer populations (right) and enantiomeric excess (left) via chiral HPLC. [cyclohexanone]o = [benzaldehyde]o = [(S)-proline]o = 2.0 M in dry DMSO. .................................................................................................................................... 93 Figure 50. Chiral HPLC Trace at 210 nm for dry DMSO conditions. Benzaldehyde = 1.807 min; 2.1 (R,R) = 2.697; 2.1 (S,R) = 3.324 min; 2.1 (S,R) = 4.365 min; 2.1 (S,S) = 6.585 min. ............ 93 Figure 51. Chiral HPLC Trace at 210 nm for wet DMSO (4:1 H2O, v/v) conditions. Benzaldehyde = 1.888 min; 2.1 (R,R) = 2.839; 2.1 (S,R) = 3.470 min; 2.1 (S,R) = 4.636 min; 2.1 (S,S) = 6.931 min. ......................................................................................................................... 93 Figure 52. HPLC trace of final time point of aldol reaction under dry DMSO using oxazolidinone mixture. Benzoic acid = 3.576 min; benzaldehyde = 3.997 min, 2.5 = 5.459 min; 2.6 = 7.236, 7.810 min (diastereomers). ........................................................................................................... 94 Figure 53. HPLC trace of final time point of aldol reaction under dry DMSO using oxazolidinone mixture. Benzoic acid = 3.581 min; benzaldehyde = 3.992 min, 2.5 = 5.468 min; 2.6 = 7.240, 7.817 min (diastereomers). ........................................................................................................... 95 Figure 54. Calibration plots for benzaldehyde (top) and 2.1 (bottom) ....................................... 103 Figure 55. General mechanism(s) for a simple phase transfer catalysis reactions.72 .................. 107 Figure 56: CGRP antagonist candidates.80.................................................................................. 108 Figure 57. Schematics for the sampling platform, including phase selective sampling (top) and heterogeneous sampling (bottom) configurations. A) Quench reservoir B) Gilson 215 Liquid xx Handler C) Valvemate 6-port, 2-position valve with sample loop D) Ismatec piston pump E) Reactor vessel with circulation loop F) Reactor vessel with EasySampler. ............................... 111 Figure 58: Vial assembly (left) and overhead stirrer (right) for continuous mixing of a biphasic reaction ........................................................................................................................................ 113 Figure 59. Easy Sampler schematic illustrating the extended scoop with primed lines (left) and withdrawn scoop with in-line quench of sample aliquot (right). ................................................ 115 Figure 60: Overview (left) and schematic (right) of the membrane-based continuous liquid-liquid extractor.87 ................................................................................................................................... 117 Figure 61: HPLC aliquot sample stability in methanol (left) and in methanol with 1% acetic acid (v/v) (right).................................................................................................................................. 120 Figure 62. Sampling validation of heterogeneous and phase selective sampling using benzoic acid (left) and benzyl alcohol (right) in response to the addition of base and acid. ................... 121 Figure 63: Early reproducibility issues. [3.2]o = 0.14 M in toluene, [NaOH]o = 0.3 N in water (1.1 equiv), [3.3]o = 6 μM (total reaction concentration)............................................................ 122 Figure 64. Phase transfer reaction in the absence of any catalyst (left): [3.2]o = 0.14 M in toluene, [NaOH]o = 0.3 N, 1.1 equiv. PTC using tetrabutylammonium bromide (right) [tetrabutylammonium bromide] = 0.018 M total reaction concentration. .................................. 124 Figure 65: Testing whether the reaction is base limited (top left) or catalyst limited (top right via dosing experiments. Using standard PTC conditions; addition of [3.3] = 1.8 mM and [NaOH] = 0.15 M (0.5 equiv) where listed. ................................................................................................. 126 Figure 66. Plotting formation of product 3.4 over time in response to changing stir-rates. [3.2]o = 0.09 M in toluene, [NaOH]o = 0.3 N (1.1 equiv), [3.3]o = 18 μM. ............................................. 127 xxi Figure 67. Examining catalyst solubility into the organic phase via heterogeneous and phase selective sampling. [3.3]o = 18 mM, [NaOH] = 0.3 N (50 equiv) .............................................. 129 Figure 68: Same excess plots with time shifts for Series B and C; Series A - [3.2]o = [NaOH]o = 0.25 M; Series B - [3.2]o = [NaOH]o = 0.15 M; Series C - [3.2]o = [NaOH]o = 0.09 M. [3.3] = 1.8 mM for all series. ........................................................................................................................ 131 Figure 69: Different excess reaction progress curves. Series A - [NaOH]o = 0.15 M; Series B - [3.2]o = 0.15 M. [3.3] = 1.8 mM for all series. ............................................................................ 132 Figure 70. Plots generated using variable time normalization analysis for 3.2 (top), NaOH (middle) and 3.3 (bottom). [3.2]o = 0.15 M, [NaOH]o = 0.15 M, [3.3]o = 18 mM unless otherwise stated. .......................................................................................................................................... 135 Figure 71: 1H NMR trace of catalyst transition (left) using [3.3]o = [NaOD]o = 28 mM. Organic phase selective sampling of catalyst transition under standard biphasic conditions using [3.3]o = 0.0018 M, [NaOH] = 0.3 N (50 equivalents). ............................................................................. 138 Figure 72. Phase selective sampling of catalyst phase transition behaviour. [3.3]o = 0.0018 M, [base] = 0.3 M (50 equivalents) as listed. ................................................................................... 140 Figure 73. Reaction profiles at high and low temperatures. [3.2]o = 0.09 M (in toluene), [NaOH]o = 0.3 N (1.1 equiv), [3.3]o = 18 mM ........................................................................................... 142 Figure 74. Heterogeneous sampling configuration with nitrogen line (A), quench solution (B), Gilson 215 Liquid Handler with added selection valve (C) EasySampler set up (D). ............... 147 Figure 75. Organic phase selective sampling configuration with quench solution (A), Gilson 215 (B), 6-port, 2-position valve (C), Ismatec Piston Pump (D) and reactor assembly (E). Nitrogen line and additional 6-port, 1-position valve not pictured. ........................................................... 148 xxii Figure 76. Time-course plot for the reaction using tetrabutylammonium bromide in place of 3.3...................................................................................................................................................... 150 Figure 77. Technobis reactor assembly schematic (left) highlighting inlet and outlets for circulation loop, as well as PTFE filter. Final setup with overhead stirrer fitted with neodymium magnet (right).............................................................................................................................. 153 Figure 78. Time course 1H NMR data for the catalyst 3.3 in triethylamine. [3.3]o = 50 mM, [Et3N]o = 50 mM. ........................................................................................................................ 154 Figure 79. Solubility measurements for catalyst 3.3 and starting material 3.2 determined gravimetrically. ........................................................................................................................... 155 Figure 80. Standard phase transfer reaction in the absence of catalyst 3.3. [3.2]o = 0.14 M, [NaOH]o = 0.3 N, 1.1 equivalent ................................................................................................ 155 Figure 81. HPLC peak area traces of starting material 3.2 enantiomers and product 3.4 enantiomers under standard phase transfer reaction conditions ................................................. 156 Figure 82. Chiral-HPLC traces at final time point (t=66) under standard phase transfer reaction conditions depicting the remaining starting material 3.2 (rt = 2.130, 2.485 min) and product 3.4 (2.130, 2.625 min) in 0% and 84% e.e respectively. Also pictured toluene (rt = 1.153 min) and benzene (rt = 1.089 min). ............................................................................................................ 156 Figure 83. Catalyst dosing experiment under standard phase transfer reaction conditions. Using 1.8 μM (total reaction concentration) for each catalyst addition ................................................ 157 Figure 84. Hydroxide dosing experiment under standard phase transfer reaction conditions. Using 0.3 N (0.5 equivalents) hydroxide per addition ................................................................ 157 xxiii Figure 85. Organic phase monitoring of catalyst 3.3 in the presence of hydroxide and phosphate. [3.3]o = 18 μM (total reaction concentration). Addition of base designated by orange bar at t=3 min. ............................................................................................................................................. 158 Figure 86. Tracing concentration of the singly quaternized cinchona alkaloid (3.3) after exposure to hydroxide after 2 hours in the organic layer (top) and in the aqueous layer (bottom). Catalyst was never observed in the organic layer. .................................................................................... 159 Figure 87. Same excess plot with time correction for series B and C. ● = replicate 1 ■ = replicate 2▲= replicate 3. Reactions series based on colour as outlined in the above table ..................... 161 Figure 88. Different excess plot with time correction for series C. ● = replicate 1 ■ = replicate 2▲= replicate 3. Reactions series based on colour as outlined in the above table ..................... 161 Figure 89. Different excess plot. ● = replicate 1 ■ = replicate 2▲= replicate 3. Reactions series based on colour as outlined in the above table ........................................................................... 162 Figure 90: Calibration plot for spirocyclic precursor 3.2. .......................................................... 164 Figure 91: Calibration plot for phase transfer catalyst 3.3.......................................................... 164 Figure 92. 1H NMR for 2.1 ((S,R),(R,S)). ................................................................................... 182 Figure 93. 13C NMR with full assignments for 2.1 ((S,R),(R,S)). ............................................... 183 Figure 94. 1H COSY NMR for 2.1 ((S,R),(R,S))......................................................................... 183 Figure 95. HSQC NMR for 2.1 ((S,R),(R,S)) .............................................................................. 184 Figure 96. 1H NMR for 2.1 ((S,S),(R,R)) .................................................................................... 184 Figure 97. 13C NMR with full assignment for 2.1 ((S,S),(R,R)) ................................................. 185 Figure 98. 1H COSY NMR for 2.1 ((S,S),(R,R))......................................................................... 185 Figure 99. HSQC NMR for 2.1 ((S,S),(R,R)). ............................................................................. 186 Figure 100. 1H NMR for 2.2. ...................................................................................................... 187 xxiv Figure 101. 13C NMR for 2.2. ..................................................................................................... 187 Figure 102. 1H NMR for 2.4. ...................................................................................................... 188 Figure 103. 13C NMR for 2.4. ..................................................................................................... 188 Figure 104. 1H NMR for 2.3. ...................................................................................................... 189 Figure 105. 13C NMR for 2.3. ..................................................................................................... 189 Figure 106. 1H NMR for 2.9. ...................................................................................................... 190 Figure 107. 1H NMR for 2.8 formed by decomposition of 2.3 by Et3N in CDCl3. .................... 191 Figure 108. 13C NMR for 2.8 formed by decomposition of 2.3 by Et3N in CDCl3. ................... 191 Figure 109. 1H COSY NMR for 2.8 formed by decomposition of 2.3 by Et3N in CDCl3. ........ 192 Figure 110. HSQC NMR for 2.8 formed by decomposition of 2.3 by Et3N in CDCl3. .............. 192 Figure 111. HMBC NMR for 2.8 formed by decomposition of 2.3 by Et3N in CDCl3. ............ 193 xxv List of Schemes Scheme 1. Synthesis of oxazolidinones from proline and benzaldehyde. .................................... 36 Scheme 2. Retro-aldol and potential equilibration of product stereoisomers. .............................. 46 Scheme 3. Catalytic cycle of the proline catalyzed aldol condensation, where formation of a product could inhibit formation of other stereoisomers. ............................................................... 49 Scheme 4. Proposed reaction mechanism for the proline catalyzed aldol condensation between cyclohexanone and benzaldehyde. ................................................................................................ 58 Scheme 5. Highlighting the carbon positions that should display differing isotope distributions after a C-C bond forming event which would reflect a KIE. ........................................................ 68 Scheme 6. Outline of the stereoselectivities in a proline-catalyzed aldol reaction. ...................... 72 Scheme 7. Reaction scheme for the enantioselective spirocyclization catalyzed by a doubly quaternized cinchona alkaloid.80 ................................................................................................. 109 Scheme 8. Possible decomposition pathways for the doubly quaternized cinchona alkaloid .... 125 Scheme 9. Proposed decomposition pathway for 3.3 based on HPLC-MS, deuterium labelling studies, and NMR........................................................................................................................ 136 Scheme 10. Singly quaternized and doubly quaternized cinchona alkaloid phase transfer catalysts. ...................................................................................................................................... 139 xxvi List of Symbols [A] = concentration of reaction species A [cat] = concentration of catalyst species [cat]t = total concentration of free/unbound catalyst species [catA] = concentration of catalyst-reagent adduct, catA krxn = spirocyclization rate constant A = Eddy diffusion (Van Deemter equation) B = Longitudinal diffusion (Van Deemter equation) C = Mass transfer (Van Deemter equation) μ = flowrate (chromatography) γ = gyromagnetic ratio (NMR) 𝐵𝑜⃗⃗⃗⃗ = external magnetic field vector xxvii List of Abbreviations © copyright µ micro µL microliter 0 degree 13C-NMR carbon nuclear magnetic resonance 1-D 1-dimensional 1H NMR proton nuclear magnetic resonance 2-D 2-dimensional Ac acetyl aq aqueous Ar aryl Bn benzyl Bu butyl Bz benzoyl cat catalyst OR catalytic d.r diastereomeric ratio DCM dichloromethane DMF N,N-dimethylformamide e.e. enantiomeric excess ELSD evaporative light scattering detector Equiv equivalents xxviii ESI electrospray ionization ESI-MS electrospray ionization tandem mass spectrometry Et ethyl EtOAc ethyl acetate EtOH ethanol FTIR Fourier transform infrared spectroscopy g gram GC gas chromatography h hour HMBC heteronuclear multiple bond coherence HPLC high performance liquid chromatography HSQC heteronuclear single quantum coherence Hz hertz iPrOH isopropanol IR infrared J coupling constant (NMR spectroscopy) KIE kinetic isotope effect L liter LC liquid chromatography M concentration (moles/liter) Me methyl MeOH methanol mg milligram xxix MHz megahertz min minute mL milliliter mM concentration (millimoles/liter) mol mole MS mass spectrometry MTBE methyl-tert-butyl ether n/a not available OR not applicable NMR nuclear magnetic resonance OMe methoxy pdt product PEEK polyether ether ketone pet ether petroleum ether Ph phenyl PTFE polytetrafluoroethylene p-TsOH para-Toluenesulfonic acid q quartet (NMR spectroscopy) RPKA reaction progress kinetic analysis rt room temperature s second OR singlet (NMR spectroscopy) t triplet (NMR spectroscopy) TFA trifluoroacetic acid THF tetrahydrofuran xxx TLC thin layer chromatography Tol toluene UHPLC ultra high performance liquid chromatography UV ultraviolet δ chemical shift in ppm (NMR spectroscopy) xxxi Acknowledgements I thank the University of British Columbia for supporting the work conducted, for providing teaching appointments and travel grants. I thank members of the Hein Lab, both past and present, for their work, support, mentorship, and consultation throughout my work and studies. To Ryan and Tom for sharing their knowledge and wisdom on all things analytical and experimental. To Dr. Shrin Pal, Dr. Carolyn Higman, and Dr. Stephanie Forget for their support, advice, and feedback on everything from chemistry to careers. To Paul for his help and teachings on everything including hardware, electrical, and technical, and Shad for his amazing edits and writing feedback. To Elena, Junliang, Maddie and Yusuke for being amazing lab mates. I thank my family for their unwavering support throughout my studies, for making sure I could always unwind a bit when I visited home, and always stocked up on Portuguese cuisine on my trips back to Vancouver. I especially thank my brother for his constant encouragement and reminding me of the simple awe and wonder of science. Last and most importantly, I am grateful to my advisor, Dr. Jason E. Hein. He is amazing mentor, a staunch defender of my work, and an unwavering source of support, guidance, knowledge, and humour. xxxii Dedication This thesis is dedicated to my parents, my grandparents, and to my brother. “The most exciting phrase in science is not ‘Eureka!’ but ‘that’s funny …” - Isaac Asimov- 1 Chapter 1: Introduction An in-depth understanding of a mechanism is crucial in order to optimize the time, costs, and applications of a reaction. A thorough understanding of its intricacies including byproduct formation, inhibitors, catalytic cycles, off-cycle reservoirs, catalyst activation and species degradation must be developed in order to tailor a chemical process to provide the desired product(s) in a robust, efficient, and safe manner.1 All chemical processes, whether in the multi-ton reactor of an industrial chemical plant or the 10 mL vial of a research laboratory, can greatly benefit from this depth of analysis in order to optimize an existing reaction and inform exploration into new ones. This fundamental insight into a reaction’s mechanism can only be unveiled by a detailed investigation into its kinetics and behaviours, which in turn requires quantitative analysis of constituent species over time. Therefore, an appropriate monitoring methodology must be established before investigating the reaction and beginning to build an understanding of its mechanisms. The abundance of variability surrounding reactions, such as air sensitivity, exothermic profiles, variable pressure, extreme temperatures, corrosive reagents, solvents, homogeneity, viscosity, and more make it nearly impossible to create a singular, unified strategy capable of adequately tracing the concentrations of reactive species over time across all reaction space. Fortunately, there exists a range of existing analytical technology, tools, and methodologies which can be leveraged to suit the needs of a particular reaction. Despite this variation in reactions and analytics, there are at least two basic principles which must be incorporated into a monitoring methodology to ensure it can adequately probe the reaction at hand. The first essential component to a reaction monitoring methodology is the ability to detect and quantify reaction species over time. While this may seem self-evident, it nonetheless represents a challenging and, oftentimes, the most time-consuming portion of building a methodology. Here is where the conditions associated with a specific reaction must in turn be matched with a set of 2 analytical tool(s) which can accurately probe the reaction matrix for the information of interest. For some reactions, this is as simple as placing a cuvette into a spectrometer, while for others, it requires the amalgamation of multiple instruments and complex data analysis.1–3 The strengths and weaknesses of various instruments, tools, and analytics must be balanced to retrieve as much information from a system as possible. For instance, what if not all reagents or products are not detectable by an instrument? What if a transient species exists that is nearly impossible to isolate, and must therefore be measured in-situ? Suppose during a reaction, a catalyst is activated, an inhibitor synthesized, or an intermediate generated in such low concentrations that it lies below the limit of detection for a methodology, and thus eludes the investigator? All these situations pose real concerns and difficulties in the attempt to build an understanding of a reaction mechanism. Thus, developing a means to detect, quantify, and track reaction species is an essential first step towards developing a methodology. The second essential component is consistency and reproducibility in the monitoring method itself. A mechanism is a model, and a well-fitting model is one which can reliably describe existing phenomena and predict future ones. To this end, a kinetic trace or reaction profile is of no help when it cannot be reproduced. However, it is essential to determine whether this irreproducibility arises from the reaction itself or the monitoring method. If the former, then there remains some hitherto unknown mechanism or reaction parameter which is not being accounted for, and which can be eventually uncovered through further investigation. If the latter, however, then there is no way to know for certain whether the irreproducibility is truly from the reaction, or inherent to the limitations of the monitoring methodology. For instance, an unstable sampling methodology can generate a low signal to noise ratio and/or a high sample deviation, making it nearly impossible to observe subtle changes or low concentrations of reaction species, which are crucial to developing more nuanced mechanistic models and building a more thorough understanding of a reaction. The 3 use of internal standards, calibration procedures, standards, and experimental replicates are powerful tools in improving and validating the reproducibility of a sampling method, ensuring that the ensuing mechanistic model is an accurate reflection of the system at hand. In order to begin designing a monitoring method, one must first understand the analytical tools and methodologies available. This can inform decisions on how and where different technologies can be best leveraged to exemplify their strengths while also accounting for their limitations. Thus, a brief review of the more versatile and widely adopted reaction monitoring methods will be discussed, covering Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance imaging (NMR), high performance liquid chromatography and mass spectrometry (HPLC-MS), as well as a general discussion of reaction aliquoting. 1.1 Spectroscopy Spectroscopy is a vital component of chemical analysis and encompasses a range of instruments spanning the entire electromagnetic spectrum. At its core, spectroscopy relies on observing how electromagnetic radiation and matter interact. This can be achieved through a variety of means, but all require the use of a detector which can themselves interact with photons of a particular wavelength(s) and generate a corresponding signal (usually electrical) which can be recorded.4–6 The quantization of energy allows for different phenomena to be studied at different wavelengths, leading to a range of experiments, equipment, and applications. These can include low energy phenomena such as spin states in nuclear magnetic resonance at long radio waves, to vibrational modes in the intermediate infrared range, to electron-interactions and scattering at the short x-ray wavelengths6. It would take an entire book on each spectroscopic technique to give them the attention they deserve. However, for the purposes of this thesis only a few will be considered and presented. These techniques represent some of the most common and powerful means to monitor the concentration of 4 reaction species over time, with each offering their own advantages and disadvantages in that regard. To this end, Fourier-transform infrared spectroscopy, UV-vis spectroscopy, and nuclear magnetic resonance spectroscopy will be discussed. 1.1.1 Fourier Transform Infrared Spectroscopy (FTIR) Infrared spectroscopy has been an integral part of characterization and identification for decades since the development of commercial spectrometers in the 1950’s.7 Its ability to quickly identify compounds based on their spectroscopic “fingerprint” has gained it wide applications ranging from food safety to material characterization.5,6 Advances in data processing and hardware design have created a slew of spectrometers which can measure entire spectra multiple times in a matter of seconds, with some even allowing for in-situ measurements of reaction solutions. This high data density per unit of time makes IR an excellent tool in reaction monitoring.8 In general, IR spectrometers measure the transmittance or absorbance of a sample in the near-, mid-, and far- infrared region, roughly encompassing the 700 nm to 1 mm wavelength region of the electromagnetic spectrum. This region encompasses both vibrational and rotational transition of molecules, with the resulting IR spectra typically reported in units of wavenumbers (cm-1).6,8 As different molecules will have different vibrational modes and energies, molecules can have unique spectroscopic “handles” which differentiate them from other species in a sample, allowing their concentration to be monitored over progressive scans. To obtain a spectra, a sample is irradiated with a monochromatic beam (narrow range of wavelengths) and the resulting transmittance recorded. To record an entire spectrum, the instrument would need to scan or “sweep” the entire range of desired wavelengths sequentially. The advent of Fourier-transform spectrometers substantially reduced the time needed for spectra acquisition by allowing a sample to be irradiated with a wide range of wavelengths repeatedly over a short period of time, and then using a computer to mathematically determine the absorbance at each wavelength. Thus, entire spectra can be 5 acquired in a matter of second.8 Furthermore with Beer-Lambert’s law allowing for direct conversion of absorption to concentration, IR-spectrometers an attractive means for applications to reaction monitoring.9 Advances in computation, fiber-optics, machining, and laser technologies have allowed versions of the spectrometer which trades the large lenses, detectors, and cuvettes for a much more compact design in the form of a probe which can be directly inserted into a reaction solution10–12. Commercially available units, such as the Mettler Toledo ReactIR uses a flexible fiber-optic cable which allows infrared light to travel from the main unit to the tip of the probe, where it is projected into the solution; the radiation which is scattered back towards the probe is then recorded, and a spectra constructed using the principles of Fourier-transform outlined earlier. This development allows for easy acquisition of IR spectra from a reaction by inserting the probe into the solution (Figure 1). The use of diamond or silicon-based coatings allows for decent compatibility across a range of chemical space without necessarily compromising signal areas of the spectral window. The use of properly fitted glassware, tubing, and connectors can even allow the probe to monitor air sensitive reactions.13 Software can facilitate data analysis by offering means to correct for peak drifts or overlap, as well as the ability to visualize and present data in a 3-dimensional plot to easily convey reaction progress. More importantly, the use of an in-situ probe can allow for the detection and observation of transient chemical species which may otherwise be destroyed upon work-up. As such, FT-IR is a powerful tool capable of delivering dense time course data desired for reaction monitoring. 6 Figure 1. Simplified scheme for a ReactIR probe. Light generated by the IR spectrometer is carried along a fiber optic cable and shone into solution (right). The light returned to the probe is recorded, compared against a reference, and processed using Fourier Transform into a spectrum. While the FT-IR probe is a particularly useful tool in reaction monitoring, it also suffers from several limitations. Reactions involving compounds with highly similar functional groups generally suffer from insufficient resolution in their signals, leading to a lack of “spectroscopic handles” and resulting in inaccurate tracking of their concentrations over time. As IR is a reflection of molecular vibrations and rotations, changes in temperature will also affect intensity and distribution of peaks in the IR spectra, making reactions which operate under fluctuating temperatures difficult to directly convert to concentration. Furthermore, while the probe can handle a range of reaction conditions, including heterogeneous solutions composed of solid-liquid slurries, it is unable to accurately monitor biphasic reactions.14,15 This is due to a constantly fluctuating background signal as a result of mixing two immiscible phases. 7 Despite these limitations, IR remains a powerful tool for use in reaction monitoring applications. Advancements in instrumentation and data processing has afforded instruments which can be easily leveraged to provide time course data with rapid data acquisition. However, it often must be supplemented with complimentary analytical techniques, such as nuclear magnetic resonance and mass spectrometry, to afford detailed information on the composition and chemical structures of a sample. 1.1.2 Ultraviolet-Visible Spectroscopy (UV-Vis) Ultraviolet-visible spectroscopy is widely employed for the detection and quantification of chemical species in a sample. Spectrometers typically operate within the 380 nm to 750 nm range of the electromagnetic spectrum, which encompasses electronic transitions (ground state to excited state electron excitation) of many compounds which typically possess aromatic, conjugated, or transition metal components.6 The basic operating principle of a UV spectrometer is similar to that of a dispersive IR, whereby a beam of monochromatic light is focused through a sample and the light transmitted then recorded by a detector. However, modern spectrometers use a lamp (tungsten filament, deuterium arc, or LED) as a photon source which, depending on its material, produces light within the range of the UV-Vis spectrum. This light is passed through a sample, where it is then split using a prism or diffraction grating into its constituent wavelengths, which will then interact with a diode array detector. Each wavelength will correspond to a different portion of the detector, allowing for simultaneous measurement of absorbances across multiple wavelengths simultaneously16. This configuration for quick, dense data acquisition makes UV-vis spectroscopy a valuable tool for reaction monitoring. 8 UV-vis spectroscopy is a versatile tool in reaction monitoring. As with IR, the Beer-Lambert Law allows for direct conversion of absorption to sample concentration, allowing for quantification of reaction species9. Consecutive sampling of a cuvette filled with a reaction solution can then provide time-course data for tracking reactive species over time. However, in order to use this technique, the sample of interest must be spectroscopically active within the UV-vis range; compounds which do not absorb strongly in this region do not generate a strong signal, and thus cannot be tracked accurately. Nonetheless, this can be worked around by introducing UV active “tags” onto reaction substrates, as is commonly used in studies involving enzyme kinetics.17 In general, UV-vis detectors are an essential component of many analytical instruments, and are deeply integrated into liquid chromatography, gas chromatography, and microscopy. 1.1.3 Nuclear Magnetic Resonance (NMR) Nuclear magnetic resonance (NMR) has established itself as an easy and reliable tool for reaction monitoring. This method offers several attractive features in terms of reaction setup, often requiring relatively small volumes of reagents and straightforward sample preparation. It can also offer a user-friendly interface with the advent of software to simplify and streamline both data acquisition and processing. In addition to kinetic data, NMR also offers the potential for some degree of characterization for both reactants, products, as well as intermediates throughout the course of a reaction.18,19 9 Figure 2. Figure outlining the Larmor Frequency of a nuclei as its precession around an axis in an external magnetic field. The gyromagnetic ratio, γ, depends on the nuclei’s charge, mass, and magnetic moment. On a fundamental level, NMR measures the response of nuclei oriented in a strong, constant magnetic field to stimulation by an external, weaker magnetic field generated by a radiofrequency pulse(s).19 Nuclei aligned along an external magnetic field will precess around an axis at a frequency related to the field strength, and the magnetic dipole moment of the atom (Figure 2). This Larmor frequency is intrinsically tied to the chemical environment that the nuclei reside in, with magnetically “shielded” environments resulting in lower frequencies, and magnetically “de-shielded” environments resulting in higher ones. What’s more, nuclei can influence the spin of their neighbours, giving rise to experiments which can provide information between covalently bonded atoms spanning entire spin systems and even through three-dimensional space. These experiments can be applied to a range of nuclei, including 1H, 13C, 14N, 15N, 19F, and 31P. Furthermore, by simply performing multiple consecutive experiments, NMR can give rise to time course data in addition to structural information.19 Thus, it is no surprise then that NMR is a quintessential tool for the characterization of compounds and is regularly employed in simple reaction monitoring approaches (Figure 3). BOLarmor Frequency:ω = -γBo10 Figure 3. Sample 400 MHz spectrometer (left) and a cutaway of spectrometer (right)20. Time course data can be acquired by simply preparing a reaction solution in an NMR tube using a deuterated solvent, and then acquiring spectra over consecutive experiments. Quantitative analysis of reaction profiles can often be accomplished without the need of an internal standard, provided experiment parameters allow sufficient relaxation times for the nucleus of interest.18,21 In some cases, one can compare differences in isotope distributions between starting material(s) and product(s) to gain insight into reaction mechanisms.22 This kinetic isotope effect can provide an additional layer of depth into kinetic analysis, in addition to acquiring rates, rate laws, and other parameters acquired through time-course analysis23. In cases where deuterated solvent is unavailable or simply unfeasible due to scale, developments in signal suppression and probe development can allow for in-situ reaction monitoring by pumping a homogenous mixture into a spectrometer. Furthermore, access to both the spectrometers and training needed to carry out these experiments has improved as NMR facilities become ever more commonplace in many academic and industrial settings. 400 MHzLiquid HeLiquid N2SuperconductingMagnetsRadiation ShieldInsulating JacketCoilsCoolantPortsSample Port11 While extremely useful, NMR has several limitations. The acquisition of these instruments poses significant upfront costs, including the specialized facilities needed to house them and the personnel needed to maintain them. Institutions with access to a spectrometer may limit their availability to ensure fair usage, which can severely limit the ability to perform experiments and their replicates, particularly for reactions with long completion times, which can make other reaction monitoring methods preferential by comparison. Thus, access to these instruments may not be feasible, although this may be circumvented to some degree via collaboration with an institution in possession of an NMR facility. Another challenge is in the case of unresolved or highly crowded spectra, whereby “peak drifting” coupled with overlapping signals can create a convoluted data set that makes it nearly impossible to accurately track a single species over the course of a reaction. At times, this problem can be mitigated if the reactive species possess moieties which would allow monitoring via another spectroscopic handle, such as 19F or 31P NMR which are typically well resolved and not as abundant in most organic molecules. Furthermore, emerging processing software and algorithms have been developed which can help deconvolute overlaying signals in a given spectra, although their success is varied and often limited.24 Perhaps the greatest drawback of NMR spectrometry is its low sensitivity in comparison with other analytical techniques, in addition to poor compatibility with certain reagents and materials. Reactions involving highly ionic species, or with material displaying ferromagnetic properties, can lead to poor spectra resolution and peak broadening, which can complicate analysis. Heterogeneous reactions and highly viscous reactions suffer from inefficient mixing and an uneven distribution of reactive species throughout the sample tube, resulting in skewed or inconsistent data.25 12 Despite its limitations, NMR remains an extremely powerful tool in reaction monitoring arsenal. Its ability to provide time-course data with structural information across a range of conditions makes it an extremely versatile and potent method when probing a reaction. High Performance Liquid Chromatography (HPLC) High-performance liquid chromatography (HPLC) and ultra-high-performance liquid chromatography (UHPLC) is a vital component of modern analytics. It provides a robust, reliable, and easy-to-use platform for identification of a sample and its components. Careful construction of response curves for individual reagents can provide quantitative data of a sample’s composition, while appending an electrospray ionization-based mass spectrometer opens the door for characterization and identification of previously unidentifiable reaction components or intermediates.26 The introduction of an evaporative light scattering detector (ELSD) in place of a conventional UV-vis detector can allow for quantitative analysis of compounds which lack sufficient UV activity.27 The use of chiral columns and corresponding methods allows for the resolution and measurement of enantiomeric excess (e.e.) without the need for optical rotation studies28. The sensitivity of the technique means that only a small amount of material in diluted samples is necessary to commit to each analysis. It is this combination of versatility, robustness, small sample volumes, and characterization potential which makes HPLC an extremely favourable method for reaction monitoring if available.26 13 Figure 4. Sample HPLC configuration (left) and depiction of a chromatography column with a theoretical plate(s) (right).29 In general, chromatography relies on the non-covalent interactions between compounds in a mobile phase and those on a stationary phase, with stronger interactions resulting in longer retention. This process can therefore separate compounds based on differences in their physical properties. The resolving power of a column to efficiently separate different molecules is described by the Van Deemter equation which relates the diffusion of eluting particles, the packing of the column, the linear velocity through the column, and the mass transfer of the particles between the stationary phase and the mobile phase.30,31 This can be further detailed in terms of additional parameters such as column diameter and particle shapes but is ultimately reliant on the concept of “theoretical plates” (Figure 4). This concept describes the equilibrium of an analyte between two distinct phases (such as the liquid and solid phases of most chromatography columns) of a fixed height and size, as designated by the physical properties of the analyte and its phases. Stacking theoretical plates can improve the efficiency of the separation, as described by the Van Deemter equation (Figure 5). Solvent ReservoirsPumps and MixerAuto SamplerColumn(s)Detector14 Figure 5. Simplified description of the Van Deemter equation terms (left) and the resulting plot (right).29,31 In practical terms, chromatography generally involves packing a stationary phase into a column for the separation of chemical species based on their inherent physical properties. For liquid chromatography, this generally refers to a hydrophilic stationary phase (such as silica) and a non-polar mobile phase, or a “reverse-phase” column packed with a hydrophobic material (such as C18 chains immobilized onto silica) and a polar mobile phase. The use of small-diameter columns which are tightly packed with particles in the micrometer scale allow for extremely efficient and reproducible separation of a range of compounds. High pressures ranging from 50-450 bar (and up to 1200 bar in the ultra-high-performance systems) allow for relatively quick flow rates through the tightly packed column beds. Affixing a detector to the column output, such as UV-diode array, or evaporative light scattering detector (ELSD) can allow for identification and quantification of eluted species, which can be even further appended with a mass spectrometer for characterization data as well.26,27 Automated control of the pumps, samplers, mixing lines, column temperature, diode array, and other parameters allows for easy creation of HPLC methods and facile acquisition of A = Eddy DiffusionB = Longitudinal DiffusionC = Mass TransferμμμVan Deemter EquationH = A + B/μ + CμMobile Phase Velocity (μ)Theoretical Plate Height (H)ACBFinal PlotOptimumConditions15 reproducible data for dozens of samples without the need for full-time supervision as with a manual column. The use of chiral columns (columns which have a stationary phase composed of immobilized chiral molecules, such as alkylated sucrose) allow for the separation of enantiomeric species, allowing for further insights into the composition of stereoisomers in a sample. Thus, HPLC has become a cornerstone in many analytical labs and applications, ranging from reaction monitoring, to quality assurance, to high-throughput screening.32,33 The ability for HPLC to separate, quantify, and characterize chemical species makes it well-suited to reaction monitoring. In a simplest scenario, a reaction in a vial can be continually sampled at regular intervals to generate time-course data. The use of an auto-sampler can facilitate this process even further, freeing a chemist to perform other tasks while data is collected. However, direct sampling from a reaction vial can be challenging, as high reaction concentrations can easily overload the column, leading to poor resolution. HPLC columns can also be sensitive to certain reaction conditions and solvents, leading to irreparable damage and poor separation efficiency.34 Furthermore, sampling frequency is limited by the duration of the method; for instance, a ten-minute HPLC method will only ever allow a minimum time interval of ten minutes between sampling events. Thus, to circumvent these issues, it is often easier to aliquot, quench, and dilute a reaction into vials which can then be analyzed offline.2,35 This allows HPLC to be amenable to generate time course data for a wide range of reactions. While the applicability of HPLC to reaction monitoring has amassed a reasonable rapport, it is not without its limitations. The ease with which quantitative data can be extracted depends heavily on the construction of well-defined response curves, as well as the reproducibility and consistency of preparation for both the HPLC run and the reaction aliquot. Thus, an extremely robust sampling and quenching protocol must be developed for quantitative HPLC reaction monitoring to be attainable.3 Furthermore, the entire principle of reaction monitoring by HPLC relies on the stability 16 of the samples once aliquoted from a reaction; that is, the reagents, intermediates, and products should be resistant to degradation or further conversion once quenched and diluted during HPLC sample preparation, or else there is an increased risk in complicating their analysis or losing them altogether. This limitation can be somewhat mitigated through the introduction of direct-inject HPLC systems, whereby aliquots of a reaction are quenched and directly loaded onto an HPLC column using a bit of automation.36,37 This technique opens the door for the monitoring of reactive intermediates which would traditionally be too air sensitive or possessing too short of a half-life to be detectable through traditional sample preparation. Despite these limitations, the overall advantages and versatility of HPLC makes it a primary candidate for monitoring most reactions. 1.2 Gas Chromatography (GC) Gas chromatography is a complimentary analytical technique to liquid chromatography and operates on similar principles. The former uses a mobile gas phase in place of a mobile liquid phase, and separates compounds based on their affinity to a stationary phase. The efficiency of this separation also relates back to the number of theoretical plates and the Van Deemter equation as described earlier.30,31 Unlike liquid chromatography, gas chromatography requires samples be vaporized before they contact the column; this is achieved by injecting the sample into a heated environment. A continuous flow of inert gas, such as argon or nitrogen, will then carry the vaporized material through the column. Due to weaker resistance encountered by gas-phase molecules with the stationary phase, a longer column is required which typically range from 15 to 60 meters (Figure 6). A GC can also be appended with a mass spectrometer to provide additional characterization data. Ionization of the vaporized material can be readily achieved through electron or chemical ionization approaches. The construction of calibrated response curves, especially with the aid of an internal standard, can help provide quantitative data on sample composition.38 Thus, GC is a popular 17 analytical method for the identification and quantification of reaction samples, with applications ranging from academic to forensic laboratories. Figure 6. Schematic of a sample GC system.38 Just as with HPLC, GC can also be used to generate time course data for a reaction, either by consecutively sampling a reaction vial or processing prepared reaction aliquots39. However, as GC relies on successful vaporization of a sample, reactions involving compounds with high molecular weights or metals are discouraged due to possible the accumulation of particulates and possible damage to the GC’s column and/or vaporization chambers. Thus, HPLC still remains a preferable choice to sample analysis due to its broader tolerance of chemical species by comparison. Nonetheless, GC, and GC-MS remain a viable strategy for reaction monitoring. Auto SamplerInjector PortColumn DetectorOven with Insulation18 1.3 Mass Spectrometry (MS) Mass spectrometry allows for the measurement of the mass to charge ratio (m/z) of an ion after the ionization of its progenitor. The means by which this mass to charge ratio is measured varies by instrumentation method including quadrupoles, time of flight (TOF), Fourier-transform ion cyclotron resonance, and ion traps (Figure 7). While the exact mechanisms vary, all operate on the basic principle of establishing conditions whereby only a particle with the correct mass-to-charge ratio can travel to and collide with a detector, which then amplifies the signal and converts it into an electric response. Ions can also be generated in a variety of ways, including electrospray ionization (ESI), matrix-assisted laser desorption ionization (MALDI), and atmospheric pressure chemical ionization (APCI) among others.40 Figure 7. Schematic of a sample triple quadrupole (QQQ) spectrometer40. In general, mass spectrometry’s utility lies in characterization rather than quantification, as different molecules across different samples will have variable ionization efficiencies, making the construction of a calibrated response curve challenging. Additionally, appending an ESI-MS after an Ionization ChamberQuadrupoleCollision Cell DetectorLow-pressureChamber19 HPLC allows for easier quantification of reaction species, while also providing m/z characterization data. Nonetheless, some methods have been developed which use mass spectrometry for time-course analysis, largely to gain insight into transient intermediates.41 In one instance, a constant stream of a reaction solution is channeled into an ESI-MS which allowed for identification and approximation of intermediates in a catalytic cycle.42 Overall however, mass spectrometry remains an excellent tool for characterization, and significantly enhances existing reaction monitoring methodologies using HPLC and GC. 1.4 The Problem with Heterogeneous Solutions As can be seen from the examples above, heterogeneous reaction monitoring can prove particularly challenging, particularly for in-situ analysis of complex mixtures. The added difficulty of insoluble particulates can pose substantial problems with regards to sample acquisition, as the exact composition of an aliquot will vary according to the distribution of both soluble and insoluble material which happened to be collected in an instance. These reactions also contain additional physical parameters, such as solubility and mass transfer, which can affect reaction behaviour in terms of rate and even stereoselectivities.43 Overall, these reactions generally require finer attention to detail and care when developing a monitoring procedure and are not easily adaptable to existing methodologies. FTIR probes can be used to study the solution phase of a heterogeneous reaction, provided that its solvent composition remains constant. This allows the technology to retain its robustness and applicability but makes it extremely difficult to leverage in cases of biphasic heterogeneous reactions. The ever-changing solvent composition makes establishing a background spectrum extremely difficult and, thus, tracing reactive species particularly inconsistent. However, even under non-biphasic heterogeneous applications, the probe is susceptible to complications. The most 20 common of these is buildup of particulate around the probe’s optical window, obstructing its ability to penetrate a reaction solution and, thus, accurately trace reactive species. NMR also tends to suffer under heterogeneous conditions, particularly in cases where excessive particulates can cause issues with sample shimming and baseline stability. However, further advances with regards to spectrometers, experiments, and data processing has allowed for limited in-situ reaction monitoring of reactions with a solid phase component, even on a bench top spectrometer.25,44 Despite this, the technology is still currently unamenable to biphasic reactions, as both solvent locking and inefficient mixing add another layer of complexity and inaccuracy for both data acquisition and interpretation. Both HPLC and ESI-MS in and of themselves are not limited in the same manner by heterogeneous slurries; as reaction aliquots often need to be heavily diluted prior to analysis, it often allows for an appropriate solvent to be selected which can solubilize all reaction components. Furthermore, in-line HPLC filters can prevent any insoluble particulates from damaging sensitive components on the instrumentation, particularly the columns or nebulizer of the HPLC and MS respectively. However, while the techniques themselves are somewhat indifferent to heterogeneous solutions, the aliquot acquisition is not. Sampling a homogeneous reaction is relatively straightforward. A syringe can be used to withdraw a predefined volume of the reaction solution, dispense it into a waiting vial, diluted and/or quenched with an appropriate solution, and then analyzed offline via HPLC-MS, GC-MS, or other analytical methods. This laborious process can be improved by substituting manual sample preparation for an automated one. Entire platforms, such as those employed in high throughput screening (HTS) are dedicated to sampling (and even preparing) hundreds of reactions autonomously.45 For labs which are not interested in purchasing these highly specialized and costly platforms, the ever-growing range of commercially available pumps, stir-plates, and dispensers, 21 coupled with a “bit” of coding knowledge can allow for the creation of their own automated sampling platforms. The use of automated hardware can provide consistent, reproducible sampling while the chemist is free to perform other tasks. Furthermore, integration of automated sampling procedures opens the possibility for direct-injection systems with an HPLC or MS, allowing for the detection of transient species which would be otherwise destroyed through conventional aliquoting. Heterogeneous reactions present additional obstacles which must be overcome for reaction sampling. Solid-liquid slurries pose added difficulties in aliquot acquisition, as the introduction of particulates can clog tubing and syringes, damage pumps, and obscure sensors. While attaching a filter to sample intake lines can mitigate this problem, it then neglects the insoluble material which also make up the reaction matrix, and thus omits an entire set of data that might be crucial towards understanding a system. Heterogeneous solutions involving two immiscible solvents can be even more complicating; these reactions are intrinsically tied to mass transfer between phases, and thus would require selective sampling of each phase in order to build a mechanism that is reflective of this biphasic system.46,47 With heterogeneous and biphasic systems constituting a wide range of chemistry, including transition-metal catalysis, aldol condensations and biphasic reactions, developing monitoring methods for these conditions is essential towards furthering the understanding of these reactions. Considerable work has already been invested in monitoring heterogeneous reactions. While some approaches have gotten by with careful use of existing tools (such as manual aliquoting of a slurry), others have sought to develop new tools to facilitate sampling and study. For instance, one such probe is the EasySampler Probe developed by Mettler Toledo in conjunction with the Hein Group at the University of British Columbia. The probe utilizes a 20 μL “scoop” which can be extended into a reaction solution and withdrawn with the help of a brushed DC-motor. The Teflon sleeve which surrounds and seals the reaction scoop is cut with premade channels to allow for the 22 flow of a quench solution in and out of the probe (Figure 8). The scoop allows for the sampling of virtually any heterogeneous solution, whether slurry, suspension, or emulsion, provided that all particulates can be solubilized in an appropriate quench solution. As with other technologies which rely on narrow tubing to carry reaction solution, insoluble particulates can quickly clog lines or wear down parts, thus bringing the sampling system offline. Such a probe has been successfully used in monitoring and studying study of several heterogeneous reactions. Figure 8. Cutaway schematic of the Easy Sampler probe head, highlighting the internal plumbing (inflow and outflow highlighted in orange). The probe can be primed while the scoop is in solution (left), and then quench the aliquot for dispensing (right). However, many reactions persist which are yet to take advantage of these new monitoring methodologies. To demonstrate their utility, a recent heterogeneous sampling method was applied to the study of a proline-catalyzed aldol reaction in order to determine and understand the source of its stereoselectivity (Chapter 2). This reaction system proposed a unique challenge, whereby a reinvestigation of computational prediction and experimental determination generated more questions than answers with respect to the proline-catalyzed aldol condensation between 23 cyclohexanone and benzaldehyde as outlined in the original Houk-List model.48 The reaction presented a complex matrix including various side-products and catalyst deactivation pathways, retro-aldol reactivity, solubility, and stereoselectivities. This presented an excellent challenge to test recent heterogeneous monitoring platform(s), as well as to resolve and perhaps further elucidate the mechanism of the reaction. Additionally, reactions exist which are still in need of an adequate monitoring methodology. For this end, an automated sampling platform for the monitoring of biphasic reactions was developed and deployed in the study of a biphasic reaction (Chapter 3). A model system was studied which involved the use of a doubly quaternized cinchona alkaloid as phase transfer catalyst in an enantioselective spirocyclization. Investigations were focused around elucidating the reaction mechanism and addressing issues such as irreproducibility through the acquisition of time-course data. 24 Chapter 2: Investigating the Changes in Stereoselectivity of a Proline-Catalyzed Aldol Reaction 2.1 Synopsis An automated sampling platform was leveraged to understand the selectivity in a proline-catalyzed aldol reaction between cyclohexanone and benzaldehyde. The platform configuration allowed for facile time-course data collection over 48-hour reaction times, allowing up to six reactions to be monitored in parallel using a next generation sampler. The stereoselectivity of the reaction was found to be significantly influenced by the presence of water in the organic solvent, with “dry” conditions yielding poor selectivity while “wet” systems yielded a predominant stereoisomer. Detailed investigations suggested that this selectivity was not driven by any kinetic phenomena, including product degradation, epimerization, inhibition, byproduct catalysis or varied mechanisms from solvent conditions, and was likely a result of differences in the transition state due to the presence or absence of water in the reaction solution. 2.2 Introduction to the Houk-List Model and the Proline-Catalyzed Aldol Reaction The reconciliation between the chemistry carried out in a flask and chemistry modelled in silico is constantly evolving. The steady improvements in computational power, software, and models have allowed computational chemists to apply their craft towards understanding reactions at a more fundamental, molecular level. While modelling known reactions with empirically determined yields can already prove an ambitious undertaking, the “holy grail” of the field aspires to predicting experimental outcomes. One such example was the work published by Houk et al., in which quantum mechanical calculations were used to predict the stereochemical product distribution of an aldol reaction, which was then confirmed by physical experimentation immediately thereafter.48 25 Among the aldol condensation reactions studied was the reaction of benzaldehyde and cyclohexanone as catalyzed by (S)-proline in DMSO (Error! Reference source not found.). This work was a landmark for the field of computational chemistry, as it demonstrated the ability of current methodology and computational power to accurately predict the outcome of a reaction prior to executing and analyzing the benchtop experiment. Scheme 1. Aldol condensation reaction between cyclohexanone and benzaldehyde as catalyzed by (S)-proline. The quantum mechanical prediction of the reaction relied upon an understanding of the reaction’s mechanism. In broad terms, the proline catalyzed aldol condensation between a ketone and aldehyde can be simplified to five steps (Figure 9). To begin, the proline catalyst (cat) can reversibly condense with either the starting ketone, A, or the starting aldehyde, B to form an iminium species. The catalyst-aldehyde adduct (catB) in some systems can undergo decarboxylation of the proline fragment, resulting in the irreversible formation of byproducts such as oxazolidinones; the specifics of this process will be discussed later, but for now, it is sufficient to represent an irreversible, non-productive pathway in the reaction’s model. If the catalyst-ketone adduct is formed (catA), it can then undergo a carbon-carbon bond formation with the aldehyde to yield a new adduct with catalyst condensed onto to the corresponding aldol condensation product 2.1. A subsequent hydrolysis step will liberate the product (P), and regenerate free catalyst to start the reaction again. 26 Figure 9. Proposed catalytic cycle for the proline catalyzed aldol condensation reaction. In order to develop a computational model, two main assumptions and manipulations needed to be made. For instance, reaction conditions should be simulated to minimize the undesired formation of catalyst-aldehyde byproducts. If the initial condensation of catalyst onto substrates is indeed reversible, then operating under a relatively high loading of ketone (A) compared with aldehyde (B) should suppress formation of the catalyst-aldehyde adduct, cat-B (thus, decreasing byproduct formation) while driving formation of the catalyst-ketone adduct, cat-A based on Le Chatelier’s principle (Figure 9). The second assumption is that the carbon-carbon bond formation between the catalyst-ketone adduct and aldehyde is an irreversible stereochemical determining step. This was necessary to ensure that the distribution of stereoisomers which were predicted computationally and determined experimentally were a direct reflection of the lowest-energy transition state, rather than equilibration to the lowest energy product in accordance with the Curtin-Hammett principle. While retro-aldol reactions are known, the assumption of an irreversible step is not unreasonable; at the start of a reaction, where there is a large excess of ketone, benzaldehyde, catalytic amounts of proline and no product yet formed, the equilibria will be heavily biased towards 27 the formation of the aldol condensation product, which allows the step to be considered irreversible for the purposes of prediction. With these assumptions in hand, quantum mechanical predictions could be carried out. However, in order to do so, another model was required which described the stereochemical determining C-C bond formation step in the mechanism. In principle, there are four possible stereoisomers which could be generated from the reaction, which could stem from at least 8 different transition state configurations. It was believed that the carboxylic acid of the proline-ketone adduct would direct the incoming aldehyde through favourable hydrogen bonding interactions, and thus limit the system to only four main “approaches” which needed to be considered. These approaches can be described by the prochirality of the two reactants, leading to four main transition states of a “re-re”, “re-si’, “si-re”, or “si-si” addition to generate the corresponding (R,R), (R,S), (S,R) and (S,S) 2.1 product configurations (Figure 10). In order to begin calculating the energies associated with these transition states, the lowest conformational energies of the approaching molecules must be determined. For a relatively rigid molecule such as benzaldehyde, this was straightforward. However, much more work was required for the cyclohexanone-proline adduct, which could adopt a variety of conformations (such as a half-chair, boat, twist-boat). Nonetheless, all the requisite calculations were performed, the lowest energy conformation(s) identified, and the transition states computed. Through this approach, Houk et al. were able to predict the stereochemical outcomes across several aldol condensation reactions, the stereoselectivities of which were then confirmed through physical experimentation.48 28 Figure 10: Schematic illustrating the four major transition states and their corresponding stereoisomer products for the S-proline catalyzed aldol condensation reaction of benzaldehyde and cyclohexanone as proposed by Houk et al48. It is worth emphasizing that the catalytic cycle and assumptions introduced previously represent a significant simplification of the proposed mechanism for the proline catalyzed aldol condensation but were necessary for the construction of a reaction model. There are additional equilibria and reaction intermediates which exist, and their brief mention would help convey the deceptive complexity of this reaction. For instance, the formation of the proline-cyclohexanone condensation product modelled earlier as simply cat-A, actually comprises 3 different species in equilibria. This includes the resulting imine 2.2, and both stereoisomers of the resulting enamine 2.3a and b. Additionally, the formation of the proline-product adduct (described as simply cat-P) actually describes 4 adducts, one for each of the possible stereoisomers of 2.1. Thus, there are four 29 distinct rates describing the formation of cat-P, each of which would also have a corresponding rate for the reverse reaction. Each of these species will also have a range of stable and unstable conformations, the energies of which will influence their transition states and, thus, the relative rates of these steps. In short, this system is non-trivial from either a kinetic or thermodynamic standpoint and required some level of simplification in order to make it feasible for computational analysis. Scheme 2. Equilibria between species from the condensation of cyclohexanone onto (L)-proline. Therefore, it was a substantial success that Houk et al. were successful in predicting the stereoselectivity of proline catalyzed aldol reactions. However, a reinvestigation of the cyclohexanone-benzaldehyde condensation led to the discovery of an error in the conformational analysis. It was found that the conformation of the proline-cyclohexanone adduct which was used in subsequent transition state calculations was not actually the lowest energy conformation that could be computed. Thus, the stereochemical predictions generated by comparing the transition state energies and utilizing the ΔΔG‡ of this transition state were not accurate reflections of the system. By recalculating the free energy difference using the new lowest energy transition state conformations, little to no stereoselectivity was predicted for the reaction outcome based on the similar energies of the relevant transition states for each stereochemical product. When this was discovered, the experimental work was also revisited in an attempt to reproduce the selectivity observed in the original report by Houk et al.48 but was also unable to replicate the high level of stereoselectivity observed previously. Thus, there was a seemingly irreparable dispute between 30 previous computation and experimentation which both found excellent stereoselectivity, in contrast to recent reinvestigations which found poor selectivity overall. The field of organocatalysis is no stranger in the struggle to both understand and control the stereoselectivities of its reactions. Proline catalyzed reactions in particular are among the oldest and most thoroughly explored, with the Hajos-Parrish-Eder-Sauer-Wichert reaction sometimes referred to as the foundation of asymmetric organocatalysis.49–51 Proline is a valuable organocatalyst as a naturally available chiral amine base, allowing it to catalyze reactions involving key enamine or imine intermediates by imparting both rate acceleration and stereoselectivity under relatively mild conditions.52 Proline-catalyzed aldol reactions are an exemplar in this regard, as they are capable of facilitating asymmetric carbon-carbon bond formations that introduce two new stereocenters with relatively high selectivity and good yields. The mechanism for these reactions was thought to be well understood, to the point where an appropriate model and corresponding transition state(s) could be proposed and, most importantly, computed using the technology available in early 2000’s.53,54 Thus, the reaction made an excellent candidate for testing the predictive capabilities of computational chemistry, as well as contemporary understanding of the reaction mechanism. The confounding inconsistency between past and present computational and experimental results sparked an interest in the re-evaluation of this system to determine the source of the apparent change in selectivity, as well as to reconcile the results with updated quantum mechanical predictions. To this end, a collaborative effort was undertaken, with work in Dr. Hein’s lab endeavoring to discover the cause behind the varying by experimental kinetic analysis, while a collaborator, Dr. Paul Ha-Yeon Cheong and his graduate student, Celine Richardson at Oregon State University lead efforts to reexamine the computational aspect of the reaction. 31 2.3 Initial Studies into Diastereoselectivity and Enantioselectivity Initial efforts were focused on elucidating the source of experimentally observed stereoselectivity first reported by Houk et al.48 The first suspicions were focused around the presence of water in the reaction solvent, as this has been observed to influence the stereoselectivity of other aldol reaction systems.55–57 Furthermore, the hygroscopicity of DMSO makes the introduction of significant water content highly plausible, especially under prolonged or improper storage conditions.58,59 Thus, the system was investigated to determine whether any such correlation between water and stereoselectivity could be observed. To test this, two standard condensation reactions were carried out, one of which was run in “dry” DMSO containing less than 2% water by weight (as determined using the refractive index of the solvent at 25 0C59), and a second “wet” DMSO solvent which had been dosed with water in a 4:1, DMSO:H2O ratio by volume. Endpoint analysis of these reactions revealed a marked difference in the distribution of the four possible stereoisomers (Table 1). The reaction under “dry” DMSO displayed modest enantioselectivity and virtually no diastereoselectivity, which was consistent with the reported recent attempts to replicate the original work. Meanwhile, the wet DMSO system exhibited the high enantioselectivity and diastereoselectivity consistent with the results originally reported by Houk et al. Between the two systems, there was a 20% improvement in the e.e. of the major diastereomer and a corresponding 21% decrease in the e.e. of the minor diastereomer when transitioning from dry to wet DMSO conditions (Table 1). Based on these results, it was concluded that water was heavily implicated in the stereoselectivity of the aldol reaction (Figure 13), with the observed variation in reproducibility likely a reflection of insufficiently dried DMSO. 32 Table 1: Summary of a proline catalyzed aldol reaction between benzaldehyde (2.0 M), cyclohexanone (2.0 M) and (S)-proline (2.0 M) in DMSO and DMSO:H2O (4:1 volume) solvent systems. Minor Diastereomeric Pair† Major Diastereomeric Pair‡ (S,S) (R,R) (S,R) (R,S) DMSO e.e. 76% 73% Relative ratio 6.1 0.80 6.4 1.0 DMSO:H2O 4:1 (v/v) e.e. 57% 93% Relative ratio 4.5 1.2 26.6 1.0 Enantiomer populations determined using chiral HPLC of aliquoted reaction samples. † Relative stereochemistry based on Houk List assignments. ‡ Absolute configuration determined using x-ray crystallography of 93% e.e. product isolate. The absolute configuration of the major product was determined using x-ray crystallography. For this purpose, the 93% e.e. product isolate were used to generate crystals containing a single product enantiomer determined to be the (S,R) product. Not only is this consistent with the previous results by Houk et al.48 but determination was performed on the native 2.1 species, without the need for derivatization to the p- toluenesulfonylhydrazide as was reported previously. 2.4 Screening a Range of Reaction Conditions The conditions used to initially probe the stereoselectivity of the proline catalyzed aldol reaction in this study used all reagents in stochiometric amounts ([cyclohexanone]o = [benzaldehyde]o = [(S)-proline]o = 2.0 M), while the original Houk-List report used catalytic conditions ([cyclohexanone]o = 2.0 M; [benzaldehyde]o = 0.1 M; [(S)-proline]o = 0.03 M). The higher material loadings used in this study were chosen to shorten reaction time from four days needed under Houk-List conditions to two days, allowing for higher experimentation throughput. However, to ensure similar behaviour within our investigated range of conditions, a screen was performed in order to determine whether water was still the primary culprit in driving 33 stereoselectivity. This involved varying the concentrations of (S)-proline and benzaldehyde, as well as performing the entire screen in duplicate, with one set using dry and the other using wet DMSO as their solvent. The reaction was then be sampled after 24 and 48 hours for analysis by HPLC-MS and chiral HPLC. Table 2. Summary of reaction screen varying benzaldehyde and proline relative concentration under dry or wet conditions. The results of the array identified the role of water as the driving force behind the stereoselectivity of the aldol condensation. Analysis by HPLC and chiral HPLC revealed that all reactions involving the use of dry DMSO resulted in a near 1:1 ratio of the syn- and anti- diastereomers and a roughly 60-70% e.e in each (where observable). This diastereomeric ratio was significantly improved when the identical reaction was run in the wet solvent system, resulting in d.r. as high as 7:1, and significant improvements in the e.e. of the major anti-diastereomer (>90%) but with a drop in the minor syn-diastereomer (50-60%). These results are consistent with the results identified in the early Concentration D.R. (Syn;Anti) 2.1Reaction ID Cyclohexanone (M) Proline (M) BnCHO (M) Dry DMSO Wet DMSO (4:1 H2O v/v)A 2.000 0.100 2.000 1.32 10.14B 2.000 2.000 0.100 1.03 >15C 2.000 0.030 0.100 0.92 6.58D 2.000 0.100 0.100 0.93 9.39E 2.000 2.000 2.000 1.44 6.06F 2.000 0.030 0.100 1.04 >15G 2.000 2.000 0.100 1.02 >15H 2.000 0.100 2.000 1.44 9.74I 2.000 2.000 2.000 1.44 6.05J 2.000 0.100 0.100 0.97 9.81K 2.000 0.030 2.000 1.47 12.90L 2.000 1.015 1.050 1.08 6.11M 2.000 0.030 2.000 1.50 11.06N 2.000 1.015 1.050 1.20 >1534 investigations of this study, as well as those reported under the original Houk-List conditions. Thus, it was found to be a general trend that water was crucial in deciding the stereoselective outcome of the aldol condensation. There are several potential phenomena which could account for different stereoselectivities observed between the two solvent systems (Figure 11). One possible cause could have been selective degradation of the major stereoisomer in dry DMSO which was slowed or suppressed in the presence of water, or the three other stereoisomers could have been degrading more rapidly in the presence of water to yield the major stereoisomer in wet DMSO. Similarly, the poor diastereoselectivity in dry DMSO could be explained by the rapid epimerization of the aldol products, resulting in a more even distribution of the stereoisomers; this epimerization could be suppressed in the wet system, which would exhibit the natively high stereoselectivity of the reaction (Situation A). Of course, the final product distribution may not even be a result of product reactivity, but of their initial formation. Inhibition-type mechanisms could suppress the formation of certain stereoisomers which could be activated or inactivated in the presence of absence of water. For instance, the formation of the major stereoisomer could inhibit formation of the minor(s) in wet DMSO, while formation of the minor(s) could inhibit the major under dry DMSO (Situation B). Other potential sources of stereoselectivity could arise from the reaction environment itself, such as formation of a catalytically active byproduct generated through the non-productive reactions between (S)-proline, benzaldehyde, and cyclohexanone. Indeed, the byproducts of proline catalyzed aldol condensations have proposed to act in this capacity in other studies (Situation C).60,61 The selectivity may also have roots in thermodynamics, whereby a surplus (or absence) of water molecules can stabilize key transition states, thereby lowering their energy and potentially favoring a stereoisomer over its counterparts (Situation D); this could potentially be identified through differences in the observed rate law between wet and dry DMSO solvent conditions, or in transition 35 state computational analysis. However, as this latter portion is better addressed by our computational collaborators, it will not be discussed in depth for now. Figure 11. Possible scenarios to explain observed outcome of aldol condensation reactions in the presence and absence of water. Situation A:Product EpimerizationThe reaction is highly stereoselective, but the major stereoisomer is decomposed or epimerized. The presence of water arrests this.ORThe reaction is poorly stereoselective,but the presence of water promotes epimerization to the major stereoisomer.Situation B:Product InhibitionThe minor stereoisomer(s) can inhibitformation of the major stereoisomer in the absence of water.ORThe major stereoisomer(s) can inhibitformation of the minor stereoisomer in the presence of water.Situation C: Byproduct CatalysisThe reaction generates byproductswhich catalyze stereoselective formation of the major diastereomer.ORThe reaction generates byproductswhich catalyze non-stereoselective formation of all possible stereoisomers.Situation D:Mechanistic or ThermodynamicsThe presence of water affects stereoselectivity by directly impacts the formation of the products due to involvement in the transition state.ORThe presence of water activates or suppresses a different mechanistic pathway.36 2.4.1 Probing the potential role of By-product Catalysis The aldol reaction is known to generate a host of side products under dry DMSO conditions, most of which originate from the condensation adduct between benzaldehyde and proline. Subsequent decarboxylation of this adduct can lead to the formation of oxazolidinones This adduct and its subsequent products have been well characterized in previous work, even going so far as to disprove the capacity for some of these by-products to catalyze the aldol reaction itself.60 Scheme 3. Synthesis of oxazolidinones from proline and benzaldehyde. Previous research had investigated the advantageous role of water in the proline catalyzed aldol reactions60. This work concluded that addition of water reduced the rate of product formation but improved catalytic performance by suppressing the formation of 2.4 and effectively arresting unproductive pathways, and thus, mitigated the decomposition of the proline catalyst. Given that the formation of decomposition products serves as a key observable difference between the two conditions under study, a study was undertaken to determine whether 2.5 or 2.6 may be catalytically active and influence the stereoselectivity of the aldol reaction. To determine whether the proline-benzaldehyde byproducts could act as catalysts in the aldol reaction, benzaldehyde (3 equiv.) and (S)-proline (1 equiv.) were mixed in DMSO, and the resulting products identified using HPLC-MS; the resulting crude isolate, containing a mixture of 2.5 and 2.6, was then used in the place of (S)-proline to investigate both the aldol condensation and retro-aldol 37 reactions (Figure 12). It was expected that if these oxazolidinones and oxazolidines could catalyze the reaction, then formation of the major aldol product 2.1 should be observed when the material is exposed to cyclohexanone and benzaldehyde. Conversely, catalytic activity could also be observed through degradation of the major 2.1 product via retro-aldol or a different degradation pathway. Figure 12. Preparation of oxazolidinone byproducts (top) and investigating their catalytic activity in the aldol condensation reaction. Analysis of the corresponding reactions showed no observable catalysis (consumption of starting material or products) in the presence of the isolate of byproducts. Treating benzaldehyde and cyclohexanone with the crude mixture containing 2.5 and 2.6 did not result in detectable aldol products. In addition, exposing syn- and anti-aldol products of 2.1 the crude mixture of 2.5 and 2.6 did not yield any notable degradation by retro-aldol pathways. These experiments conclusively demonstrate that byproducts 2.5 and 2.6 serve only to sequester catalyst and starting material, and were not directly involved in the catalytic aldol reaction, confirming previous studies.60 38 2.5 Development of an Autonomous Sampling Platform for a Heterogeneous Mixture End point analysis would be insufficient to begin investigating the other possible factors influencing stereoselectivity discussed earlier. The ability to monitor the formation of the four stereoisomer products over time, as well as any transient intermediates, would be necessary to build a full model for the reaction. Time-course reaction monitoring would be required to gain insight into the behaviour of all reaction components including starting materials, catalyst, side products, and condensation products in order to piece together a detailed description of the reaction’s mechanism. It was now known that the long four-day reaction times used under the original Houk-List conditions could be shortened to two days by increasing the starting loadings of benzaldehyde and proline without impacting product distribution. While this improved the rate of data acquisition and expediates experiment time, it also introduced heterogeneous reaction conditions. Complications introduced by heterogeneity as discussed in the introduction (page 19) made monitoring the reaction by either 1H NMR spectroscopy or in-situ FTIR further unfeasible due to the density of reaction spectra, whereby the high degree of similarity in functional groups and structures made it impossible to resolve signals and thus accurately track the concentrations of reaction species. As our studies also required insight into the populations of product diastereomers and enantiomers, HPLC and chiral-HPLC appeared best suited. A sampling protocol was therefore required which would collect and prepare aliquots for offline analysis. An automated dispensing platform was envisioned , both for the high degree of consistency, convenience and customizability it afforded, as well as the success that has been demonstrated in the study of other reactions.2,35 Furthermore, the long reaction times spanning over 24-72 hours made sampling highly undesirable for conventional protein-based samplers, and so more modern equipment was leveraged instead. 39 Figure 13: Summary of changing stereoselectivities in response to solvent conditions of the proline catalyzed aldol reaction between benzaldehyde and cyclohexanone In summary, a system was required that could handle the heterogeneous conditions of the aldol condensation reaction. The system required the capability for automatically sampling a heterogeneous reaction over 24 to 72 hours, without stalling, and in a highly reproducible manner. To accomplish this goal, modifications were carried out on an automated sampling platform developed by our group which had been successfully deployed for the study of other reactions.2,3,35 The platform was built around a Gilson 215 Liquid Handler as its foundation, which could dispense controlled volumes into waiting vial racks. Two intake lines to the Gilson would be required, and selected for using a 6-port, 1 position valve; these would be a nitrogen line (to purge and dry the lines between sampling events) and a quench reservoir (for quenching, diluting, and dispensing samples). These components (Gilson 215, 6-port-1-position valve, nitrogen line and quench reservoir) constituted the sampler liner of the sampling platform. The second section involved a reaction circulation loop which used an Ismatec piston pump to continually cycled material to and from the reaction vessel. A 0.2 μM PTFE filter added to the intake line of the circulation loop ensured only the liquid phase (and thus, fully solubilized material) would be pumped through the resulting tubing, minimizing the chances of clogs or damage to the pump due to the accumulation of insoluble particulates. Both the sampler line and the reaction circulation were connected to a 6-port-40 2-position valve fitted with a 20 μL sample loop. These three components (the sample line, sample loop, and reaction circulation loop and their respective hardware) constituted the main apparatuses of the sampling platform. Figure 14: Schematic outlining the automated sampling platform, including nitrogen line (A), quench reservoir (B), Gilson 215 Liquid Handler with mounted Valvemate 6-port, 1 position valve, (C), Valvemate 6-port, 2-position injection valve (D), Ismatec Piston Pump (E), Reaction vessel (F). To carry out a sampling sequence, Gilson’s Trilution software was used to coordinate and program the various components of the platform, including the Gilson 215 Liquid Handler and respective valves. A sampling event began with the 6-port-1-position valve of the sampler loop aligning with the methanol quench solution. Concurrently, the 6-port-2-position valve aligned to the reaction circulation loop (green), allowing the 20 μL sample loop (red) to be filled with the reaction solution. While this happens, the Gilson will begin pumping a methanol quench through the sampler lines (orange) to prime them. When triggered again, the 6-port-2-position valve will then align the sample loop (now filled with 20 μL of the reaction solution) with the sampler line, which would then be quenched in line, dispensed and diluted into a waiting vial. After dispensing the sample, an DE F`B CA41 additional volume (approximately 1 mL) of the methanol quench solution is pumped through the sampler line and sample loop to clean the needle of the Liquid Handler (which would be maneuvered over a rinsing station). The 6-port-1-position valve would then align from the quench reservoir to the nitrogen line, purging the sampling tubing and sample of any residual solvent, and drying them in preparation for the next sampling event. In total, a sampling event required 90 seconds from priming to final drying of the lines. This was more than sufficient to accommodate the 24-48 hour reaction times and provided a robust, reproducible platform for sampling of the aldol condensation. High-performance liquid chromatography with tandem mass spectrometry (HPLC-MS) was selected as the preferred analytical method for the identification and quantification of reaction species. The structural similarity in chemical structure for starting material and products created a lack of distinct handles for techniques such as FTIR spectroscopy, while the heterogeneous nature of the reaction made others such as 1H NMR spectroscopy challenging. Furthermore, obtaining time-course data of the reaction’s stereochemical product accumulation was essential, and could be easily obtained through chiral HPLC. Calibration plots would allow for quantification of reaction species, while mass spectrometry would allow for the identification of the species, potentially including any stable intermediates. Thus, as HPLC-MS provided the best data density per sample, it was selected as the principle analytical method to the monitoring procedure. In all, the development of the platform proceeded well, requiring only two to three weeks of work to assemble into a finalized version. The greatest difficulty came from ensuring platform stability, that it could run without supervision over the 48-hour blocks required for reaction monitoring. The most common issues encountered surrounded clogs and valve leaks, which caused system failures midway through reactions. Adjusting tubing diameter, filters, pump type and 42 replacing valve fittings remedied these issues, and the platform was capable of running uninterrupted for weeks at a time with minimal maintenance between experiments. 2.6 Exploring Kinetic Behavior Under the Dry and Wet DMSO conditions The proline catalyzed aldol reaction displayed notable differences in both kinetic behaviours and product distribution between dry and wet DMSO (Figure 15). Under dry conditions, roughly 0.5 M of the initial benzaldehyde is immediately consumed upon addition of (S)-proline, presumably due to rapid condensation between the two; these adducts can then undergo reversible hydrolysis to give back starting material, or proceed through an irreversible decarboxylation to yield a mixture of products including oxazolidinones. This rapid initial consumption was not observed under the wet conditions, likely due to the excess water suppressing the formation of these adducts and their eventual products, as has been proposed in similar reactions.60 Furthermore, the dry system exhibited poor enantioselectivity, and virtually no diastereoselectivity of the desired 2.1 product(s), with a near 1:1 ratio of the anti- and syn diastereomers observed throughout the reaction and an e.e. of approximately 73% for both sets of enantiomers. End point analysis of the product e.e. revealed approximately 75% average between both major and minor diastereomers in dry DMSO, while the 4:1 DMSO water system boasted an improved 93% e.e for the (S,R) stereoisomer and with a concomitant reduction in selectivity for syn aldol products 56% e.e. respectively. The time-course analysis between these systems reveal an extreme bias towards the formation of a single product throughout the entire observed duration of the wet DMSO conditions, which suggests some fundamental difference exists in the kinetics between the two systems. 43 Figure 15: Time-course profiling of the aldol condensation between dry DMSO (< 2% water by weight) (left) and wet DMSO (4:1 H2O, v/v) (right). [cyclohexanone]o = [benzaldehyde]o = [(S)-proline]o = 2.0 M 2.6.1 Product Degradation and Epimerization studies To investigate the possibility of selective product decomposition, the products isolated from a reaction run in wet DMSO (75% e.e. of anti-, 76% e.e. of syn-diastereomers) were re-exposed to (S)-proline in dry DMSO in a 0.6:1 ratio of major to minor diastereomer (Figure 16). The purpose of the experiment was to observe whether product interconversion would occur and, if so, to gauge its extent. It was expected that if product epimerization was occurring, then the concentration of a reaction beginning with one diastereomer decrease, while the concentration of the other would increase stoichiometrically. In essence, a reaction starting with only the syn-diastereomer of 2.1 would exhibit gradual formation of the anti-diastereomer once reposed to proline. If the rates of this epimerization are sufficiently differentiated between dry and wet solvent conditions, then the stereoselectivity observed is due in part to product epimerization. DMSO:H2O (4:1, v/v)DMSO00.20.40.60.811.21.41.61.820 10 20 30 40Concentration (M)Time (h)00.20.40.60.811.21.41.61.820 10 20 30 40Concentration (M)Time (h)44 For these experiments, a lower catalyst and diastereomer loading was used to ensure a homogenous solution, and thus eliminate any influence from solubility. The ratio of diastereomers was observed to change over the course of 48 hours was observed, with the syn-product decreasing at a faster rate than that of the anti. This suggested some form of product epimerization and/or degradation was possible, and so further studies were conducted to examine product behaviour under the varying solvent conditions. Figure 16: Exposure of aldol products to (S)-proline in DMSO To further study the extent of product degradation and/or epimerization, isolated diastereomeric products were isolated from the wet DMSO system (93% e.e. of anti- and 52% e.e. of syn-diastereomers) were exposed to (S)-proline in either dry or wet DMSO (Figure 16). For these reactions, a lower concentration (0.1 M) was selected, providing homogenous reaction conditions, to negate the effect solubility may exert on the system and its equilibria. To also investigate the influence of the geometry of the proline catalyst may have on degradation, the isolated products were exposed to both (S)- and (R)-proline. 0.50.540.580.620.660.70 10 20 30 40Ratio of 2.1 Diastereomers (syn/anti)Time (h)45 Figure 17: Exposure of minor product diastereomer ((S,S), (R,R), 58% e.e.) to reaction conditions; [minor diastereomer]o = [proline]o = 0.1 M. Analysis by HPLC. The minor diastereomer products ((S,S), (R,R), 53% e.e.) remained stable over a 30-hour observation period when re-exposed to all reaction-like conditions. (Figure 17). The product displayed similar rates of degradation of approximately 3 mM/hour across both solvent conditions and in the presence of both proline enantiomers, with a maximum of 10% material lost. The accumulation of benzaldehyde was detected over the course of the reaction(s), suggesting that the decomposition of the products was likely proceeding through a retro-aldol mechanism. However, as 00.020.040.060.080.10.120 5 10 15 20 25 30[syn-diastereomer] (M)Time (hour)00.020.040.060.080.10.120 5 10 15 20 25 30[syn-diastereomer] (M)Time (hour)00.020.040.060.080.10.120 5 10 15 20 25 30[syn-diastereomer] (M)Time (hour)00.020.040.060.080.10.120 5 10 15 20 25 30[syn-diastereomer] (M)Time (hour)DMSO Only DMSO:H2O (4:1)(S)-proline(R)-proline46 its concentrations lay near to the limit of detection for the HPLC method, it was not plotted in the figure above. No significant differentiation in product behaviour or rates of degradation was observed across solvent conditions, which suggests that selective degradation of the minor diastereomer product is unlikely to be the source of stereoselectivity observed for this system. Scheme 4. Retro-aldol and potential equilibration of product stereoisomers. A parallel reaction series was conducted in which the major anti-diastereomer (93% e.e.) was also exposed to both dry and wet DMSO, as well as to both enantiomers of proline (Figure 18). Unlike the minor syn-diastereomer (e.e. = 52%), the major anti-diastereomer (e.e. = 93%) exhibited a difference in the rate of its decomposition whether it was in the presence of (S)-proline or (R)-proline. We observed a decomposition rate of approximately 6 mM/hour when the anti-diastereomer (93% e.e. in favor of S,R) is treated with (S)-proline and no discernable decomposition when treated with (R)-proline . This suggests the mechanism of their degradation, and presumably their formation, is stereoselective. Indeed, observation of decomposition by additional chiral-HPLC analysis illustrated preferential degradation of the abundant enantiomer, (S,R), over its minor (Figure 18). This behaviour suggests that decomposition of the product occurs by stereoselective pathway catalyzed by (S)-proline, and not via a Bronsted acid or base mechanism. This matched/mismatched behavior can be further observed when monitoring enantiomer populations over the course of the degradation (Figure 19). As noted in the degradation studies of the minor diastereomer, benzaldehyde accumulation was also detected throughout these reactions 47 which suggested a retro-aldol type mechanism as the primary pathway of product loss for both product diastereomers. Figure 18: Exposure of major product diastereomer ((S,R), (R,S), 93% e.e.) to reaction conditions; [major diastereomer]o = [proline]o = 0.1 M 00.020.040.060.080.10.120 5 10 15 20 25 30[anti-diastereomer] (M)Time (hour)00.020.040.060.080.10.120 5 10 15 20 25 30[anti-diastereomer] (M)Time (hour)00.020.040.060.080.10.120 5 10 15 20 25 30[anti-diastereomer] (M)Time (hour)00.020.040.060.080.10.120 5 10 15 20 25 30[anti-diastereomer] (M)Time (hour)DMSO Only DMSO:H2O (4:1)(S)-proline(R)-proline48 Figure 19: Monitoring enantiomer degradation upon exposure of the anti-diastereomer (93% e.e.) to dry DMSO and (S)-proline. Peak area normalized using 1,3,5-trimethoxybenzene (TMB, 0.5 equiv) as internal standard. [major diastereomer]o = [proline]o = 0.1 M. While these studies did reveal a previously unknown stereoselective decomposition pathway, which primarily impacts the major (S,R) stereoisomeric product, our result further indicates that the rate of decomposition is invariant to solvent conditions. Figure 17 and Figure 18 illustrate the near identical rates of product decomposition across both dry and wet DMSO conditions, meaning that this decomposition pathway is not responsible for the observed variation in diastereoselectivity for the proline-catalyzed aldol reaction in these two different solvent systems. In summary, both the major and minor diastereomer products of the aldol reaction displayed slow rates of decomposition when re-exposed to reaction conditions. The accumulation of benzaldehyde during these reactions suggests that this decomposition likely proceeds through a retro-aldol type mechanism, and not involve isomerization or degradation to aldol condensation products. There is minimal variation in the rates of product decomposition when comparing the minor diastereomer and major diastereomer in both dry and wet DMSO solvent systems, which 00.20.40.60.811.21.40 10 20 30 40Normalized Peak AreaTime (h)(S,R)(R,S)49 cannot adequately account for the stereoselectivity observed in the forward reaction. The relative rates of decomposition for both major and minor diastereomers individually did not vary between solvent systems, which makes it unlikely that selective degradation could be the source of the stereoselectivity observed in the original reaction. However, the results do support the highly stereoselective nature of the reaction, as only the “matched” chirality of proline (S) could degrade an enantioenriched product, whereas the opposite chirality (R) did not cause any detectable degradation over the course of the experiment(s). The complimentary diastereomer was not observed to be produced in any of the degradation experiments which provides additional evidence that stereoselectivity does not arise from a product epimerization route. 2.6.2 Product Inhibition and Further Decomposition Studies Scheme 5. Catalytic cycle of the proline catalyzed aldol condensation, where formation of a product could inhibit formation of other stereoisomers. With product degradation eliminated as a possible source of stereoselectivity, our attention turned to whether product inhibition could also be a factor. In wet DMSO, this could occur when formation of the major (S,R) stereoisomer suppressed the formation of the others ((R,S), (S,S), (R,R)), leading to the high stereoselectivity observed (Scheme 5). To investigate this potential 50 phenomenon, a dosing experiment could be conducted whereby a standard aldol reaction was run, but with an additional initial loading of the or major diastereomer. Observation and comparison of the resulting reaction profiles should then reveal whether any form of product inhibition is taking place. It was expected that if product inhibition was occurring, then the addition of the major anti-diastereomer of product 2.1 would cause a suppression of the formation of the minor syn-diastereomer. If no inhibition was occurring, then the reaction should maintain a difference in concentration between the major and minor diastereomers equal to the concentration of the initial dose. Figure 20: Aldol reaction with initial 0.1 M dose of the major diastereomer (93% e.e.). [benzaldehyde]o = [cyclohexanone]o = [(S)-proline]o = 2.0 M, [major diastereomer]o = 0.10 M. To determine whether the major diastereomer exhibited product inhibition, a dosing experiment was performed whereby the major diastereomer (S,R), (R,S) in 93% e.e. was added at the onset of a standard aldol condensation reaction in dry DMSO (Figure 20). If product inhibition was occurring, then the reaction was expected to produce the major ((S,R),(R,S) and minor ((S,S), (R,R)) diastereomers at different rates compared with native reaction under these conditions. This was not the case however, with the reaction producing both diastereomers at commensurate rates which maintained the 0.1 M differential introduced at the start throughout the entire course of the reaction. 00.050.10.150.20.250.30.350.40 10 20 30 40Concentration (M)Time (h)SS, RR SR RS51 This result also further supports the lack of epimerization or degradation as the source of stereoselectivity, as no decrease in the concentration of the major diastereomer. Thus, it did not appear that stereoselectivity was driven by inhibition of the minor diastereomer due to the presence of the major. 2.7 Investigations into Solubility and the Solid Phase of the Reaction Product solubility was investigated to determine its effect, if any, on the diastereoselectivity of the reaction. It is possible that the major anti-diastereomer product of 2.1 was being sequestered into the solid phase of the reaction, and thus would not observable by liquid phase sampling. However, workup of the reaction under both wet and dry DMSO systems revealed a distribution of 2.1 stereoisomers consistent with what was observed over the course of reaction monitoring. To prove this further, an aliquot was taken representing a) the solid phase (acquired by filtering off the solid phase) b) the liquid phase (acquired through a filtered syringe) and c) a heterogenous mixture of both phases were taken from both dry and wet DMSO reaction conditions. Only trace quantities of aldol products could be observed within the solid phase, and the products observed existed in the diastereomeric ratio expected for that reaction. This eliminated the possibility that a product was selectively transferring into the solid phase of the reaction mixture. The concentration of proline in solution was also obtained using gravimetric analysis to determine its solubility in both solvent systems. Aliquots of filtered solution from both 1.0 M solutions of (S)-Proline in dry and wet DMSO of a known volume were dispensed into pre-weighed LC vials. The samples were then stripped of solvent using a freeze-pump drier, and the vials weighed again to determine the proline content. The solubility of (S)-proline was determined to be 1.7 mg/mL in dry DMSO, and 42.2 mg/mL in DMSO:H2O (4:1 v/v). 52 2.8 Probing Reaction Behaviour Using Reaction Progress Kinetic Analysis (RPKA) and Variable Time Normalization Analysis (VTNA) In order to further probe the rate law and kinetic behaviour, a series of reactions were needed which would systematically vary the starting concentrations of benzaldehyde, cyclohexanone, and (S)-proline. Such a series would also require duplicates to ensure reproducibility and accuracy in the subsequent analysis. This reaction series of at least nine experiments would also need to be carried out in parallel with an identical reaction set, where one is run under dry and wet DMSO respectively (Table 3). If run in series using the established reaction platform, this would entail over 800 hours (36 days) of non-stop experimentation and require over 50 grams of each reagent. A parallel reaction sampling approach with smaller reaction volumes was desired to expedite the process and reduce the amount of materials needed. 2.8.1 Utilization of a Next Generation Kinetic Study Platform to increase monitoring capability The aldol reaction was set to be monitored using a robotic system capable of high throughput kinetic analysis under development between the Hein Lab and North Robotics. This platform takes advantage of modern robotics to facilitate reaction manipulation on a modular deck, with handling operations performed by a two joint robotic arm equipped with a variable gripper. The platform also incorporates the use of direct inject capabilities for online HPLC analysis, similar to those utilized in other kinetic monitoring studies. The goal of the platform was to combine a modular handling system with direct inject HPLC capabilities with a machine learning program capable of generating the experimental parameters needed to study a particular system, as well as process the acquired results in a self-driven loop. However, before the integration of mind and machine could be undertaken, it was necessary to prove the robustness and consistency of the platform’s hardware for 53 kinetic analysis; to this end, the proline-catalyzed aldol reaction’s rate law derivation was undertaken. Figure 21. Overview of robotic sampler protocol With the assistance of Elena Liles, Dr. Sebastian Steiner, Henry Situ, Dr. Lars Yunker, and Sean Clarke, a deck configuration and sampling script was built to carry out the desired experiments (Figure 21). Samples were prepared manually, and then handed to the robotic platform for online HPLC analysis via a direct inject system. With the platform, up to six experiments could be run in parallel with sampling events taking place every 90 minutes, which could generate adequate data density over the 48-hour reaction periods. Several duplicates were built into the experimental set up to ensure reproducibility both within and between experiment batches. The HPLC data, including retention time, sampling interval, and peak areas, were compiled using Python based scripts prepared by the aforementioned robotics team, and were processed manually using Excel. Table 3. Conditions explored for detailed RPKA kinetic analysis. Series B and G used identical conditions to validate the monitoring method between experiment sets RoboticsN9HPLC Mass SpecReactionsConcentration(s) (M)Reaction ID Cyclohexanone Benzaldehyde ProlineA 2.0 0.10 0.030B 1.5 0.10 0.030C 1.5 0.20 0.030D 2.0 0.10 0.015E 1.5 0.10 0.015F 1.5 0.20 0.015G 1.5 0.10 0.030H 1.47 0.07 0.030I 1.47 0.07 0.01554 The series of experiments conducted systematically varied the starting concentrations of each reagent based on the principles of reaction progress kinetic analysis (RPKA).62 In one set, the concentration of a single reagent was changed. These “different excess” experiments allowed for insight into parameters such as the order of a species and rate constants. The use of variable time normalization analysis (VTNA) allows for facile determination of the order of a reagent.63,64 As the only change between the two experiments was the concentration of one species, the difference in the rate of product formation is directly related to the difference in the concentration of that species, [A]. Mathematically, the change in [A] is integrated iteratively for each time point, and then plotted against [P] (Figure 22). This effectively removes the time component of the reaction’s progress, such as the formation of [P] is directly proportional to the change in [A] and its order in the reaction. The two reaction profiles in the resulting graph will overlap seamlessly when they are raised to the correct power, which identifies the order for that reagent. This approach, while relying on the qualitative overlay of kinetic curves, enabled the determination of the observed rate law for the reaction when used in conjunction with RPKA. 55 Figure 22. Variable time normalization analysis with equation (top) and sample graphs below with time course plot (left) and time normalized plot (right). A second set of experiments has the starting concentrations of all starting materials changed proportionally such that stoichiometric ratio remains constant; however, the concentration of catalyst is kept constant. For instance, in a system where species A and B react in a 1:1 ratio, a reaction begun with [A]o = 2.0 M and [B]o = 0.10 M and another begun with [A]o = 1.97 M and [B]o = 0.07 M differ by the “same excess” of 0.03 M in both starting materials. However, the reaction begun at [A]o = 2.0 M and [B]o = 0.10 M will at some point reach [A]t = 1.97 M and [B]t = 0.07 M, effectively where the second reaction was started. With the catalyst concentration held constant between these two reactions, a comparison of their profiles can provide insight into possible catalyst deactivation, activation, and product inhibition mechanisms. 00.20.40.60.80 5 10[Product]∑[A]1Δt A=1.0 MA=0.600.20.40.60.811.20 10 20 30[A]TimeA=1.0 MA=0.6Δ[A]Δt56 2.8.2 Same Excess Experiments to probe the role of catalyst deactivation or product inhibition A set of experiments differing by a total of 0.03 M of starting material was conducted in which the resulting plots of Series B ([cyclohexanone] = 1.50 M; [benzaldehyde] = 0.10 M; [(S)-proline] = 0.030 M) and Series H ([cyclohexanone] = 1.47 M; [benzaldehyde] = 0.07 M; [(S)-proline] = 0.030 M) were overlaid using an appropriate time shift. A second set involving Series D ([cyclohexanone] = 1.50 M; [benzaldehyde] = 0.10 M; [(S)-proline] = 0.015 M) and Series I ([cyclohexanone] = 1.47 M; [benzaldehyde] = 0.07 M; [(S)-proline] = 0.015 M) was also conducted to exaggerate any potential catalyst deactivation that may be occurring. These two experimental sets were duplicated for dry and wet DMSO solvent systems. Additionally, Series A was further conducted in duplicate (for both wet and dry solvent) to ensure accuracy and reproducibility in both the sampling method and subsequent reaction kinetics. A standard deviation of less than 1% between these duplicates confirmed the robustness of the platform and the observed reaction profiles. 57 Figure 23. Same excess experiments in dry DMSO (top) and wet DMSO (4:1 H2O, v/v) (bottom). [(S)-proline]o = 0.030 M. It was observed that the reaction run under dry DMSO conditions experienced mild catalyst deactivation (Figure 23). The deviation in overlays between the two same excess reactions indicates different active catalyst concentrations at each time point, whereby the system which has been running longer ([cyclohexanone]o = 1.50 M, [benzaldehyde]o = 0.10 M] proceeds more slowly due to catalyst degradation. By comparison, the reaction run under wetter solvent did not experience any loss of catalyst even after nearly 24 hours into the reaction. These results are also consistent with lower catalyst loadings (Figure 34), suggesting that this phenomenon is likely a direct result of 00.020.040.060.080.10.120 10 20 30 40 50[Benzaldehyde] (M)Time (h)[Cyclohexanone] = 1.47 M; [Benzaldehyde] = 0.07 M[Cyclohexanone] = 1.50 M; [Benzaldehyde] = 0.10 M00.020.040.060.080.10.120 10 20 30 40 50[Benzaldehyde] (M)Time (h)[Cyclohexanone] = 1.47 M; [Benzaldehyde] = 0.07 M[Cyclohexanone] = 1.50 M; [Benzaldehyde] = 0.10 M58 solvent conditions rather than catalyst concentration (within the examined range). It was also noted that the rate of benzaldehyde consumption was significantly slower under wet conditions rather than dry, with only 30% and 80% respectively consumed in the first 24 hours. Scheme 6. Proposed reaction mechanism for the proline catalyzed aldol condensation between cyclohexanone and benzaldehyde. Both observations are consistent with the proposed mechanism for the reaction. The presence of excess water can suppress the formation of cat-B by driving the equilibria back to free catalyst. By extension, this also slows the formation of the subsequent oxazolidinone byproducts (2.5, 2.6) by lowering the amount of cat-B available under reaction conditions. However, while the presence of water slows the non-productive pathways stemming from the condensation of (S)-proline and benzaldehyde, it also slows the productive formation of the cyclohexanone-proline condensation adducts by a similar mechanism. It is such that byproduct formation (and thus catalyst deactivation) can be suppressed at the cost of also slowing the aldol condensation reaction itself. This is reflective of the beneficial role of water in some aldol reactions, whereby the reaction is made “cleaner” rather than “faster.” In these systems, reactions in dry solvents generate can generate less product than those with a more aqueous environment, despite the former being “complete” in a shorter amount of time.60 59 2.8.3 Different Excess experiment to determine rate order of reactants A series of different excess experiments were conducted in which the concentration of one species was systematically changed while the others were held constant. As discussed previously, these experiments serve to provide insight into the order of a substrate and potentially elucidate its role in the reaction’s mechanism. Figure 24. Different excess in cyclohexanone, in dry DMSO. Series A ([cyclohexanone]o = 2.0 M; [benzaldehyde]o = 0.10 M, [(S)-proline = 0.030 M]); Series B ([cyclohexanone]o = 1.50 M; [benzaldehyde]o = 0.10 M, [(S)-proline = 0.030 M]); Series D ([cyclohexanone]o = 2.0 M; [benzaldehyde]o = 0.10 M, [(S)-proline = 0.015 M]); Series E ([cyclohexanone]o = 1.50 M; [benzaldehyde]o = 0.10 M, [(S)-proline = 0.015 M]); 00.010.020.030.040.050.060 10 20 30 40Concentration (M)Time (h)Series A: [(S,S),(R,R)] Series A: [(S,R),(R,S)]Series B: [(S,S),(R,R)] Series B: [(S,R),(R,S)]00.010.020.030.040.050.060 10 20 30 40Concentration (M)Time (h)Series D: [(S,S),(R,R)] Series D: [(S,R),(R,S)]Series E: [(S,S),(R,R)] Series E: [(S,R),(R,S)]60 Cyclohexanone in dry DMSO displayed two distinct profiles (Figure 24); under relatively higher catalyst loadings (0.030 M), the reaction displayed a positive order in cyclohexanone, whereby a larger starting concentration of the reagent (2.0 M versus 1.5 M) resulted in faster rates of product formation. However, under lower catalyst loadings (0.015 M), the rate of product formation remained constant, suggesting the reaction is zero order in cyclohexanone. Despite their apparent disunity, both results are consistent with the proposed mechanism for the aldol condensation. Reactions with large excesses of cyclohexanone are expected to operate under saturating conditions, where increasing the starting concentration of the reagent would not drive the equilibria towards formation of the cyclohexanone-proline imine/enamine by any discernable amount, as the rate of condensation k1 is already substantially larger than that of the reverse hydrolysis k-1. Thus, the reaction transitions between saturating and non-saturating behaviour somewhere within the examined experiment range. Indeed, the application of VTNA to this experiment set confirmed the reaction was zero order in cyclohexanone under low proline loadings, but first order under higher ones. 00.010.020.030.040.050.060 10 20 30 40Concentration (M)Time (h)Series A: [(S,S),(R,R)] Series A: [(S,R),(R,S)]Series B: [(S,S),(R,R)] Series B: [(S,R),(R,S)]61 Figure 25. Reaction profiles showing accumulation of products from different excess in cyclohexanone in wet DMSO. The wet DMSO solvent system exhibited faster rates of product formation under higher initial loadings of cyclohexanone suggesting that the reaction is of positive order in this reagent. This rate improvement was observed under both catalyst loadings tested, suggesting the reaction is not operating under saturating conditions as in the case of dry DMSO. The presence of water was expected to slow the rate of imine formation, and thus, adding additional cyclohexanone into the reaction would be consistent with also improving the rate of productive aldol condensation. 00.0050.010.0150.020.0250.030.0350 10 20 30 40Concentration (M)Time (h)Series D: [(S,S),(R,R) Series D: [(S,R),(R,S)]Series E: [(S,S),(R,R)] Series E: [(S,R),(R,S)]00.0050.010.0150.020.0250.030.0350 10000 20000 30000[(S,S),(R,R)] (M)∑[Cyclohexanone]0Δt 00.0050.010.0150.020.0250.030.0350.040 10000 20000 30000[(S,R),(R,S)] (M)∑[Cyclohexanone]0Δt 62 Figure 26. Variable time normalization analysis plots for determining the order of cyclohexanone in dry DMSO (top) and wet DMSO (bottom). A similar set of same-excess experiments were conducted for benzaldehyde. The reaction appeared positive order under both dry and wet DMSO systems, with higher loadings of the reagent resulting in faster rates of product formation (Figure 27). This behaviour was consistent, irrespective of catalyst loading. Application of variable time normalization analysis confirmed that the reaction was indeed first order in benzaldehyde across both solvent systems. This observation is consistent with the proposed mechanism and the conditions, where additional benzaldehyde can drive the formation of the resulting aldol product in the key C-C bond forming step (k2). Under all investigated reaction conditions, benzaldehyde remained the limiting reagent by as much as 20 orders of magnitude; thus, it being first order was consistent with expectations. 00.00050.0010.00150.0020.00250.0030 20000 40000 60000[(S,S),(R,R)] (M)∑[Cyclohexanone]1Δt 00.0050.010.0150.020.0250.030.0350 20000 40000 60000[(S,R),(R,S)] (M)∑[Cyclohexanone]1Δt 63 Figure 27. Different excess in benzaldehyde in dry DMSO (top) and wet DMSO (bottom). A final set of experiments investigated the order of (S)-proline using VTNA. The reaction was determined to be first order in catalyst across both solvent systems. Once again, this was consistent with expectations, as proline is necessary to catalyze the reaction. It should be noted that, to carry out VTNA, the concentration of proline was assumed to be fairly constant throughout the course of the reaction; it is known from both RPKA and previous observations that proline will be irreversibly consumed upon reaction with benzaldehyde, resulting in loss of catalyst over the course of the reaction. Thus, if catalyst degradation was significant, VTNA would not be able to cleanly identify the order, and would require further analysis.64 However, the fact that this was unnecessary confirms that there is insignificant catalyst deactivation observed under these conditions, whereby 00.010.020.030.040.050.060.070 10 20 30 40Concentration (M)Time (h)Series E: [(S,S),(R,R)] Series E: [(S,R),(R,S)]Series F: [(S,S),(R,R)] Series F: [(S,R),(R,S)]00.010.020.030.040.050.060 10 20 30 40Concentration (M)Time (h)Series E: [(S,S),(R,R)] Series E: [(S,R),(R,S)]Series F: [(S,S),(R,R)] Series F: [(S,R),(R,S)]64 the large excess of cyclohexanone (and especially water) can suppress non-productive pathways for the aldol condensation reaction. Figure 28. Sample VTNA plots for proline in dry DMSO (left) and wet DMSO (right). 2.8.3.1 Summary of kinetic analysis using RPKA and VTNA In summary, the aldol reaction in both dry and wet DMSO solvent exhibited mild degrees of catalyst deactivation, with more deactivation observed when using dry DMSO. This result is consistent with the proposed mechanism, where the presence of excess water can suppress formation of benzaldehyde-proline condensation adducts, and thus, slow down the rate of subsequent degradation pathways. However, while water helps to prevent these side products, it also slows the rate of productive aldol condensation by the same principle. Analysis by VTNA revealed that the reaction, under both solvent systems, is first order in catalyst, cyclohexanone, and benzaldehyde. In the case of dry DMSO, cyclohexanone can exhibit saturation behaviour under systems with small catalyst loadings, and thus appear zero order. However, results from this investigation did not observe any changes in reaction mechanism based upon the observed rate law under the range of conditions examined. All observations to this point suggest that the stereoselectivity of the reaction is not arising from phenomena outside of the accepted catalytic cycle for the reaction. Stereoselectivity is not observed due to product epimerization, degradation, inhibition, or formation by another catalytically 00.010.020.030.040.050 200 400 600 800 1000[(S,R),(R,S)] (M)∑[Proline]1Δt 00.010.020.030.040.050 100 200 300 400[(S,R),(R,S)] (M)∑t[Proline]1.265 active species. Furthermore, it has been demonstrated that the presence of water that determines the distribution of product stereoisomers across a range of starting material loadings. Investigation of the reaction by RPKA and VTNA revealed identical observed rate laws between solvent conditions, which suggests a common reaction pathway and rate limiting step. We therefore propose that the source of stereoselectivity likely resides in the transition state of the key C-C bond formation step of the reaction’s mechanism. 2.9 Water dosing experiments demonstrate the direct involvement of water in the stereochemistry determining step Following all other experiments, a definitive test to demonstrate the solvent’s dynamic impact on the stereoselectivity of the catalytic system was carried out. First, the standard aldol reaction in dry DMSO was initiated, resulting in the expected 1:1 diastereomeric product ratio over the first 6.5 hrs. Then, 3 mL of water was added, and the reaction allowed to continue. This dosing event effectively transitioned the reaction from dry to wet conditions (4:1 DMSO:water, as previously investigated) ( 00.511.520 5 10 15Concentration (M)Time (h)BenzaldehydeSS, RRSR, RS00.050.10.150.20.250.30 5 10 15 20Concentration (M)Time (h)SS, RRSR, RS010002000300040005000600070005 10 15 20Peak AreaTime (h)(R,R) (S,R) (R,S) (S,S)0.00%20.00%40.00%60.00%80.00%100.00%0 20 40e.e.Time (h)(S,R)(R,S) ee(S,S)(R,R) ee66 Figure 29). How the system transitioned from operating under dry conditions to wet would give further insight into the phenomena at play. Figure 29: Examining product inhibition by dosing water and stating material into a DMSO only system. (top left) Tracking species concentrations; (top right) tracking 2.1 diastereomers; (bottom left) Tracking enantiomeric excess; D) Tracking individual enantiomer populations via chiral HPLC. [cyclohexanone]o = [benzaldehyde]o = [(S)-proline]o = 2.0 M. 00.511.520 5 10 15Concentration (M)Time (h)BenzaldehydeSS, RRSR, RS00.050.10.150.20.250.30 5 10 15 20Concentration (M)Time (h)SS, RRSR, RS010002000300040005000600070005 10 15 20Peak AreaTime (h)(R,R) (S,R) (R,S) (S,S)0.00%20.00%40.00%60.00%80.00%100.00%0 20 40e.e.Time (h)(S,R)(R,S) ee(S,S)(R,R) ee67 The addition of water into this system effectively made the entire reaction respond as if it had been running under wet DMSO conditions. This suppression of the three minor stereoisomers suggests that water is involved in the stereochemical-determining step by either altering the associated transition states or somehow allowing the reaction to proceed through a slightly different mechanism. A further addition of benzaldehyde and cyclohexanone (0.33 equiv) made just prior to the 22.5 hour mark confirmed that this selectivity was maintained even in the presence of new starting materials, and that some proline had remained catalytically active. Thus, this experiment provides further support that the source of the stereoselectivity did not arise from product inhibition due to reaction conditions. 2.9.1 13C NMR Experiments to probe kinetic isotope effects In order to further elucidate whether the potential source for differing diastereoselectivity and enantioselectivity between solvent conditions arose from a different mechanism, 13C studies were proposed in collaboration with Dr. Mathew Vetticatt and his graduate student, Victor M. Wambua at Binghamton University. They proposed that a kinetic isotope effect could be interpreted through the integration of carbon-13 abundance of select carbons in the product.22,65 Based on the assumption of an equal initial distribution of 13C throughout the alpha carbons of cyclohexanone, and that a C-C bonding formation event would result in a skewed distribution based on kinetic isotope effects, then it should be possible to acquire insight into such a measurement by integrating the appropriate 13C NMR signals arising from each diastereomeric product (Scheme 7). 68 Scheme 7. Highlighting the carbon positions that should display differing isotope distributions after a C-C bond forming event which would reflect a KIE. With this in mind, work was begun to prepare adequate samples for the corresponding NMR experiment(s). The first matter involved validating whether the 13C signals of interest were adequately resolved from one another in a deuterated solvent. This was performed using isolated material from previous reactions. The initial 13C spectrum obtained confirmed that all the main carbons involved in the products were sufficiently resolved from one another to allow for integration experiments. A series of 2-D NMR experiments (HSQC, HMBC, COSY) were used to identify the signals corresponding to the two carbons of interest. NMR experiments on the diastereomers up to this stage revealed two potential issues; the first was apparent degradation of one diastereomer and corresponding generation of its counterpart in CDCl3 over time. This was attributed to acid catalyzed epimerization enabled by trace HCl in the deuterated solvent. This process could be minimized using newly purchasedchloroform-d3 stored over molecular sieves; use of this method allowed sufficient sample stability (i.e., no detectable epimerization) during the acquisition time for NMR spectra. The second issue concerned impurities whose 13C signals were close to those of interest, and would potential interfere in attempts to integrate the latter. This was largely addressed through purification techniques to eliminate most impurities to either trace levels or altogether. 69 Work was performed to generate and purify sufficient quantities of the diastereomers needed for quantitative 13C NMR experiments; this involved acquiring both diastereomer products generated under both solvent conditions (four product samples in total). Crude recrystallization and further refinement using flash column chromatography proved sufficient to fully resolve the diastereomers and eliminate most impurities. The samples were then sent to Dr. Mathew J. Vetticatt and his graduate student, Victor M. Wambua for the corresponding quantitative 13C NMR experiments. While initial experiments provided tentative KIE values for two of the four samples provided (the minor diastereomer), impurities causing signal overlap in the other two prevented an accurate KIE from being measured. In this systems, impurity 13C peaks resolved too closely to those of interest, skewing the integration values. As a result, work was necessary to either further purify the material to allow for quantitative 13C experimentation or derivatize the products further in the hopes of obtaining isolated 13C signals of interest. 2.9.1.1 Derivatization of aldol products for NMR studies Work was undertaken to explore the possibility of derivatizing the aldol condensation products into a form where the carbon peaks of interest would no longer be in proximity with that of an impurity. It was reasoned that a KIE could still potentially be obtained relating back to the original aldol condensation provided that a) the reaction proceeded to completion, b) no retro-aldol reaction was observable and c) the derivatization did not yield any product mixtures (such as diastereomers) or side products. Developing a synthetic strategy which would satisfy all of those demands proved difficult and, ultimately, unfruitful. Early attempts at converting the diastereomers to their corresponding elimination product using catalytic acid (TsOH) were ineffective, as the reactions could not be pushed to completion and, more troubling, appeared to be undergoing a retro-70 aldol reaction based on the generation of benzaldehyde during the process. Another attempt was made at reducing the ketone to help reduce epimerization at the carbon of interest. Early work using a mild reducing agent such as sodium borohydride (NaBH4) proved unsuccessful, as the reaction’s displayed a propensity to produce multiple side products, regardless of stoichiometric control, in addition to incomplete reduction to the desired alcohol. The use of stronger reducing agents was considered but were ultimately not attempted due to the concern of product decomposition, as well as promising results generated by purification attempts carried out concurrently with derivatization studies. 2.9.1.2 Purification and Recrystallization of aldol products for NMR studies Purification of the diastereomers to remove the impurities causing signal overall in the 13C- NMR spectra was undertaken concurrently with derivatization efforts. Flash column chromatography proved adept at both isolating dominant reaction species as well as resolving the diastereomers from one another. This purification approach was only mildly effective at reducing residual impurities that could be detected by 1H and 13C NMR experiments. Further product isolation using chromatographic separation proved challenging, as the relatively low concentration of the remaining impurities made them difficult to track by TLC staining methods, as well as insufficient resolution from the retention factor of the desired product(s) across several solvent systems. As a result, work was also undertaken to explore crystallization as a complimentary technique to achieve the required purity of products. A brief solvent screen quickly identified PET ether as a promising candidate for recrystallization; solubility of the major and minor diastereomers were then investigated using gravimetric measurements over a 10 oC range, showed that the solubility (JD-EX-115) changed by nearly 20 mg/mL. Efforts were undertaken to recrystallize the diastereomers from previous flash column chromatography runs. It was found that recrystallization of the diastereomers in PET Ether, 71 followed by trituration, could substantively reduce the impurities observed by both HPLC, and in 1H and 13C NMR spectra. As a result, material isolated by flash column chromatography was subsequently subjected to the recrystallization and trituration protocol before being sent to Dr. Mathew Vetticatt at Binghamton University for further study. Despite significant improvements to sample purity, small impurities were still observed near the 13C peaks of interest during prolonged acquisition and KIE values could still not be generated for the major diastereomers. Work is still ongoing to determine the KIE’s for both the minor and major diastereomers with higher confidence. Figure 30. Work flow for separation and purification of aldol product 2.1 diastereomers. 2.10 Conclusions The use of an automated monitoring methodology allowed for in-depth studies into the stereoselectivity of a proline catalyzed aldol reaction between benzaldehyde and cyclohexanone. It was discovered that the presence of water drastically improved the stereoselectivity of the reaction, generating a single stereoisomer as the dominant product (93% e.e., 7:1 d.r) (Scheme 8). It was found that water was the primary driver of this product distribution across a range of concentrations, prompting further investigation into the phenomena by which this was occurring. 72 Scheme 8. Outline of the stereoselectivities in a proline-catalyzed aldol reaction. Detailed studies into the potential sources of this stereoselectivity found that it was unlikely to proceed via product epimerization or degradation routes. While both the syn- and anti-diastereomers 2.1 were observed to degrade via a retro-aldol type mechanism when re-exposed to reaction conditions, their rates amongst each other and the different solvent conditions were insufficiently differentiated to account for the stereoselectivity observed in the reaction. Investigations into potential byproduct catalysis also proved unfruitful, and is consistent with previous observations on these oxazolidinone species.60 Product inhibition was also disproven through dosing experiments; these experiments also demonstrated the instantaneous “switch” in reaction selectivity once water was added to the system, which suggests the answer to the stereoselectivity may lie in the transition state. We are awaiting the results of computational studies, performed by our collaborators, to further explore the role of water on the transition state in this system, in addition to acquiring KIE values for the products under the differing conditions. 73 2.11 Experimental 2.11.1 General Notes Cyclohexanone was acquired from Sigma Aldrich and used without further purification. Benzaldehyde was acquired from Sigma Aldrich and distilled (70oC, high vacuum) prior to use. (S)-proline and (R)-proline was acquired from TCI Canada and used without further modification. DMSO solvent for use in “dry” conditions was sourced from HPLC grade DMSO from Fisher Scientific. All HPLC-MS analysis was carried out on an Agilent HPLC 1200 system with the following configuration: Agilent G1379B degasser, G1312A binary pump, G1316A thermal column compartment, G1315 DAD, and a 6120 single quad mass spectrometer. Analytical settings for the detectors are: DAD – 200-400 nm collected at 20 Hz storing all spectra for offline analysis. ESI-MSD – positive mode scan for m/Z 110–1500 running at 0.8sec/cycle. drying gas = 7.0 l/min, nebulizer pressure = 20 psi, gas temperature = 300 °C, capillary voltage = 4000 VHPLC column. General HPLC conditions were as follows: Column: Poroshell 120 (SB-C18, 2.7 µm, 2.1 mm x 100 mm); Temperature (column): ambient; Flow rate: 0.650 mL/min; Detection: 210 and 254 nm DAD; Mobile Phase A: 0.05% formic acid in water; Mobile Phase B: acetonitrile; Starting conditions 90% A, 10% B; 0.0-10.00 min linear gradient to 50%, 50%. Run Time: 10.00 min; Post Time: 2.50 min. Retention Times: benzaldehyde 3.89; oxazolidinones (2.5, 2.6) 4.2-5.4 min; 2.1 ((S,S),(R,R)) 6.20; 2.1 ((S,R),(R,S)) 6.32 min. Chiral HPLC conditions were as follows: Column: ChiralPak® IA-3 (3 µm, 2.1 mm x 150 mm); Temperature (column): ambient; Flow rate: 0.500 mL/min; Detection: 210 and 254 nm DAD; Mobile Phase A: 0.05% formic acid in water; Mobile Phase B: acetonitrile; Starting conditions 60% A 40% B isocratic. Run Time: 10.00 min; Post 74 Time: 1.00 min. Retention Time: [(S,S) 2.1] 2.66; [(S,R) 2.1] .277; [(R,S) 2.1] 4.26; [(R,R) 2.1] 6.42 min. All 1H and 13C NMR spectra were recorded on a Bruker AV III HD 400 MHz spectrometer equipped with a Bruker BBFO smart probe with ATMA using Topspin 3.2 on CentOS 5. Collected spectra were processed using MestreNova 12.0. For 1H NMR, chemical shifts are reported relative to residual protiated solvent peaks (δ7.27, 1.56 and 2.50 ppm for CDCl3, D2O, and (CD3)2SO respectively). 13C NMR spectra were measured at either 125 MHz or 100 MHz on the same instrument noted above for recording 1H NMR spectra. Chemical shifts were again reported in accordance to residual protiated solvent peaks (δ 77.23 and 39.51ppm for CDCl3 and (CD3)2SO respectively). 2.11.2 Automated Reaction Monitoring and HPLC Analysis 2.11.2.1 Instrumentation Design and Setup Figure 31. Organic phase selective sampling configuration with quench solution (A), Gilson 215 (B), 6-port, 2-position valve (C), Ismatec Piston Pump (D) and reactor assembly (E). Nitrogen line and additional 6-port, 1-position valve not pictured. DE F`B CA75 2.11.2.2 General Procedure for Kinetic Experiments A septum capped vial containing the reaction to be studied was attached to the circulation loop of the sampling platform (yellow) with an HPLC filter frit fitted onto the input Peek tubing and circulated using an Ismatec REGLO-CPF Digital piston pump (4 mL/min flow rate). The sampling protocol was controlled by Gilson’s Trilution Software, which executed commands to the corresponding hardware components. The sampling sequence begins with the Gilson 6-port, 2-position valve switching to its first position, which allows the reaction mixture to flow through the sample loop (orange); following this valve switch, the Gilson 215 Liquid Handler begins priming its solvent lines with the methanol quench solution (1.5 mL passed through). Once primed, the Gilson 6-port, 2-position valve switches to its second position, which connects the sample loop with the Gilson solvent line (cyan). At this point, the Gilson 215 Liquid Handler is triggered to push 1.5 mL of the methanol solution through the sample loop (quenching the reaction) and dispense it into the corresponding LC vial on the sample tray. The Gilson 215 Liquid Handler then executes a rinse cycle, pushing through 1.5 mL through the dispensing loop to flush the lines and clean the syringe head (both interior and exterior). A second Gilson 6-port, 6-position valve is triggered, which blows nitrogen gas through the dispensing loop (cyan) for 30 seconds to clear the lines of any residual solvent. This valve then returns to its original position, resetting the system for the next sampling sequence. The total sampling procedure consistently takes approximately 1.5 minutes, which is taken into consideration when defining the sampling interval. 2.11.2.3 General Procedure for the Aldol Reaction To a glass vial fitted with a PTFE septum cap was added benzaldehyde (4.1 mL, 40 mmol), cyclohexanone (4.1 mL, 40 mmol) in DMSO (20 mL total volume). The septum was pierced to 76 allow PEEK tubing lines into the vial, connecting the reaction solution with the circulation loop of the automated sampler. To this was then added (S)-proline (4.6 gram, 30 mmol). The filtered reaction slurry was then cycled through the reaction circulation loop, with periodic sampling every 30 minutes over a 48-hour period. The solution was then quenched with 150 mL of distilled water, and extracted with EtOAc (3 x 50 mL). The combined organic fractions were then washed with brine (50 mL), dried over MgSO4, filtered, and concentrated under vacuum. The crude mixture was then purified via flash column chromatography (Stationary Phase: silica, Mobile Phase: 10% EtOAc in PET Ether to 25% EtOAc in PET Ether after elution of the first species, Visualization: UV). The isolated products were then analyzed by HPLC-MS using Method A and Chiral Method A, as well as by 1H NMR and 13C NMR. An identical procedure was used for the water dosed system, whereby DMSO was replaced with a DMSO:H2O (4:1 ratio by volume). The procedure generated the identical products of (ID) with yields of respectively. 2.11.3 General Procedure for Aldol Product (2.1) Degradation Studies To a vial was added the major diastereomer isolated from the standard aldol reaction conditions in dry DMSO (102 mg, 0.5 mmol) and (S)-proline (57.5 mg, 0.5 mmol) in dry DMSO (5 mL). The reaction was monitored using the reaction monitoring method outlined previously, with results analyzed using offline HPLC. This procedure was repeated for the following reaction sets: Minor Diastereomer ((S,S),(R,R)) in (S)-proline and dry DMSO; Minor Diastereomer ((S,S),(R,R)) in (R)-proline and dry DMSO; Minor Diastereomer ((S,S),(R,R)) in (S)-proline and wet DMSO; Minor Diastereomer ((S,S),(R,R)) in (R)-proline and wet DMSO; Major Diastereomer ((S,R),(R,S)) in (S)-proline and dry DMSO; Major Diastereomer ((S,R),(R,S))in (R)-proline and dry DMSO; Major Diastereomer ((S,R),(R,S))in (S)-proline and wet DMSO; Major Diastereomer ((S,R),(R,S))in (R)-proline and wet DMSO. 77 2.11.3.1 Product Inhibition in Dry DMSO To a round bottomed flask containing benzaldehyde, cyclohexanone, prepared under standard aldol conditions was also added the anti-diastereomer ((S,R),(R,S), 93% e.e., 408.25 mg, 2 mmol). To this was added the requisite amount of (S)-proline under standard aldol reaction conditions, and the reaction monitoring using the general monitoring methodology, with samples analyzed by offline HPLC-MS. 2.11.3.2 Product Inhibition in Wet DMSO To a round bottomed flask containing benzaldehyde, cyclohexanone, and (S)-proline under standard aldol reaction conditions, and the reaction monitoring using the general monitoring methodology, with samples analyzed by offline HPLC-MS. After 6.5 hours, water was added into the system (5 mL) to generate a 4:1 DMSO:H2O (v/v) solvent system, and the reaction subsequently monitored for an addition 38 hours. 2.11.4 Solubility Experiments The solubility of (S)-proline in DMSO and DMSO:H2O (4:1 ratio by volume) was determined gravimetrically. To a solution of vigorously stirred DMSO (10 mL) at 22oC was added (S)-proline until a slurry was achieved (approximately 1-2 grams). Aliquots (0.5 mL) of the solution were obtained via a syringe fitted with a PTFE filter (0.2 μm), and dispensed into pre-weighed HPLC vials. Solvent was removed by freezing samples in solid CO2, and then exposing the samples to a freeze-pump dryer. The vials were then reweighed to determine their proline content. An identical procedure was carried out using DMSO:H2O (4:1 ratio by volume) in place of DMSO. 78 2.11.5 Aldol Reaction Conditions Screen Experimental space was selected to cover the range between the 2.0 M, 2.0 M, 2.0 M of cyclohexanone, benzaldehyde, and (S)-proline respectively used in this experimental study and the 2.0 M, 0.1 M, and 0.03 M of cyclohexanone, benzaldehyde and (S)-proline respectively used in the original report by Houk et al48. To a vial was added benzaldehyde, cyclohexanone, DMSO and (S)-proline according to the amounts outlined for the respective reaction vial (Figure 32). The vials were then stirred over 48 hours, with aliquots taken at both the 24-hour and 48-hour mark respectively. These samples were then diluted with methanol, and analyzed by HPLC (Method A for d.r., and Chiral Method A for e.e.) to determine the diastereomeric ratio and enantiomeric excess of the products formed. An identical array was prepared and conducted, substituting DMSO for DMSO:H2O (4:1 ratio by volume). Duplicates were built into the array to ensure reproducibility. Figure 32: Table of concentrations, volumes, and masses used for the DOE array. An identical array was conducted varying DMSO only and DMSO:H2O (4:1 ratio by volume) 2.11.6 Next Generation Reaction Sampling, RPKA and VTNA Studies 79 2.11.6.1 Parallel Reaction Sampler The reaction sampler used for the kinetic studies of the aldol reaction was sampler the culmination of collaboration between North Robotics, which provided the hardware and robotics platform, members of the Hein Lab, as well as the Aspuru-Guzik Group. The platform used a robotic arm to manipulate reaction vials on a modular bed equipped with a needle rack, vial gripper, 6 vial array equipped with magnetic stirring, and fitted with a direct inject valve assembly to a neighbouring HPLC. During a sampling sequence, the arm would move the target vial to the gripper, equip itself with a needle, pull an aliquot of the reaction to be sent to HPLC via direct inject, and then returned the vial to the rack. 2.11.6.2 General Procedure for RPKA Studies Two vials were prepared per reaction, with all reagent amounts added outlined in the reaction ID (Figure 33); to the first vial equipped with a micro stirbar was added (S)-proline. To the second vial was added benzaldehyde, cyclohexanone, DMSO with 10 mM TMB, and DMSO. Directly prior to handling by the sampling platform, 1600 μL of the second solution was added to the first vial containing the pre-weighed (S)-proline. The vial was then placed into a corresponding location on the vial array, whereby subsequent handling and sampling was carried out by the automated sampler. Samples were analyzed via direct-inject to an HPLC. An identical array was carried out for DMSO:H2O (4:1 ratio by volume) in place of DMSO. As the sampler, at the time of this experiment, could only accommodate six vials in a stirrer, reactions were conducted in batches of 6 (A-F) and 3 (G-I) respectively, using a duplicate (C and G) to ensure consistency and reproducibility between trials. 80 Figure 33: Table of concentrations and reagent amounts for use in RPKA and VTNA studies Processing of the data was handled through a series of steps. Firstly, raw HPLC data from each sampling sequence were compiled into an automatically generated report based on Agilent’s OpenLab software. The sample time, retention times, and peak areas were then extracted from the report files using a Python based script gratefully created by Henry Situ and Dr. Sebastian Steiner and compiled into a single Excel spreadsheet. The spreadsheet was then processed to ultimately organize the data to yield the peak areas for a species over time for a respective reaction. In order to process the data into concentrations, the peak areas for all reaction species was normalized against the 1,3,5-trimethoxybenzene used as internal standard. Subsequent processing relied on several assumptions, which have been outlined where applicable. The first assumption was that the concentration of benzaldehyde sampled at t = 0 is given accurately by the volume of benzaldehyde dispensed for that vial. Thus, the peak area for the first time point, t = 0, is directly proportional to the concentration of benzaldehyde in the vial. Thus, the concentration of benzaldehyde at any point in the reaction can be given by Equation 1. The concentration of cyclohexanone at a given point in the reaction was determined using two assumptions; firstly, that the initial concentration of cyclohexanone in the vial was accurate based on the volumes added to that reaction vial and secondly, that the amount of cyclohexanone consumed is directly proportional (1:1) to that of benzaldehyde for a given time interval, as based on the current understanding of the aldol condensation reaction mechanism. As such, the concentration of cyclohexanone at a given time, t, can be expressed as Equation 2. 81 Equation 1: Concentration of Benzaldehyde Benzaldehyde 𝑡 Peak Area 𝑡𝜀 where 𝜀 Peak Area 𝑡 0 Benzaldehyde 𝑡 0 Equation 2: Concentration of Cyclohexanone Cyclohexanone 𝑡 Cyclohexanone 0 Benzaldehyde 0 Benzaldehyde 𝑡 The concentration of products at a given point in the reaction was determined based on the consumption of benzaldehyde and maintaining the corresponding mass balance. It was also assumed that both diastereomers had near identical response factors on the LC (based upon actual response factors determined via calibration curves. Thus, the relationship between product peak area and its concentration could be given by Equation 3, while a simplified mass balance could be given by Equation 4. The value of F was altered until a consistent mass balance was achieved throughout the course of the reaction. Equation 3: Concentration of Minor and Major Diastereomers Minor Diastereomer 𝑡 Minor Diastereomer Peak Area 𝑡𝐹 Major Diastereomer 𝑡 Major Diastereomer Peak Area 𝑡𝐹 Equation 4: Mass Balance Mass Balance 𝑡 Benzaldehyde 𝑡 + Minor Diastereomer 𝑡 + Major Diastereomer 𝑡 2.11.6.2.1 RPKA Plots for DMSO Only Solvent Conditions 82 00.020.040.060.080.10.120 10 20 30 40Concentration (M)Time (h)[Benzaldehyde] [Minor] [Major]Series A00.010.020.030.040.050.060.070.080.090.10 10 20 30 40Concentration (M)Time (h)Benzaldehyde [Minor] [Major]Series B00.050.10.150.20.250 10 20 30 40Concentration (M)Time (h)Benzaldehyde [Minor] [Major]Series C00.020.040.060.080.10.120 10 20 30 40Concentration (M)Time (h)Benzaldehyde [Minor] [Major]Series D00.020.040.060.080.10.120 10 20 30 40Concentration (M)Time (h)Benzaldehyde [Minor] [Major]Series E00.050.10.150.20.250 10 20 30 40Concentration (M)Time (h)Benzaldehyde [Minor] [Major]Series F83 Figure 34: Reaction profiles of RPKA series under DMSO only solvent conditions 00.020.040.060.080.10.120 10 20 30 40 50Concentration (M)Time (h)[Benzaldehyde] [Minor] [Major]Series G00.010.020.030.040.050.060.070.080 10 20 30 40 50Concentration (M)Time (h)[Benzaldehyde] [Minor] [Major]Series H00.010.020.030.040.050.060.070.080 10 20 30 40 50Concentration (M)Time (h)[Benzaldehyde] [Minor] [Major]Series I84 2.11.6.2.2 RPKA Plots for DMSO:H2O (4:1 ratio by volume) Solvent Conditions 00.020.040.060.080.10.120 10 20 30 40Concentration (M)Time (h)[Benzaldehyde] [Minor] [Major]Series A00.020.040.060.080.10.120 10 20 30 40Concentration (M)Time (h)Benzaldehyde [Minor] [Major]Series B00.050.10.150.20.250 10 20 30 40Concentration (M)Time (h)Benzaldehyde [Minor] [Major]Series C00.020.040.060.080.10.120 10 20 30 40Concentration (M)Time (h)Benzaldehyde [Minor] [Major]Series D00.020.040.060.080.10.120 10 20 30 40Concentration (M)Time (h)Benzaldehyde [Minor] [Major]Series E00.020.040.060.080.10.120.140.160.180.20 10 20 30 40Concentration (M)Time (h)Benzaldehyde [Minor] [Major]Series F85 Figure 35: Reaction profiles of RPKA series under DMSO:H2O (4:1 ratio by volume) solvent conditions Figure 36. Different excess plots for cyclohexanone in dry DMSO. 00.020.040.060.080.10.120 10 20 30 40Concentration (M)Time (h)[Benzaldehyde] [Minor] [Major]Series G00.010.020.030.040.050.060.070.080 10 20 30 40Concentration (M)Time (h)[Benzaldehyde] [Minor] [Major]Series H00.010.020.030.040.050.060.070.080 10 20 30 40Concentration (M)Time (h)[Benzaldehyde] [Minor] [Major]Series I00.010.020.030.040.050.060 10 20 30 40Concentration (M)Time (h)Series A: [(S,S),(R,R)] Series A: [(S,R),(R,S)]Series B: [(S,S),(R,R)] Series B: [(S,R),(R,S)]00.010.020.030.040.050.060 10 20 30 40Concentration (M)Time (h)Series D: [(S,S),(R,R)] Series D: [(S,R),(R,S)]Series E: [(S,S),(R,R)] Series E: [(S,R),(R,S)]86 Figure 37. Different excess plots for cyclohexanone in wet DMSO. Figure 38. Different excess plots for benzaldehyde in dry DMSO. Figure 39. Different excess plots for benzaldehyde in wet DMSO. 00.010.020.030.040.050.060 10 20 30 40Concentration (M)Time (h)Series A: [(S,S),(R,R)] Series A: [(S,R),(R,S)]Series B: [(S,S),(R,R)] Series B: [(S,R),(R,S)]00.0050.010.0150.020.0250.030.0350 10 20 30 40Concentration (M)Time (h)Series D: [(S,S),(R,R) Series D: [(S,R),(R,S)]Series E: [(S,S),(R,R)] Series E: [(S,R),(R,S)]00.010.020.030.040.050.060.070.080.090.10 10 20 30 40Concentration (M)Time (hour)Series B: [(S,S),(R,R)] Series B: [(S,R),(R,S)]Series C: [(S,S),(R,R)] Series C: [(S,R),(R,S)]00.010.020.030.040.050.060.070 10 20 30 40Concentration (M)Time (h)Series E: [(S,S),(R,R)] Series E: [(S,R),(R,S)]Series F: [(S,S),(R,R)] Series F: [(S,R),(R,S)]00.010.020.030.040.050.060.070.080.090 10 20 30 40Concentration (M)Time (h)Series B: [(S,S),(R,R)] Series B: [(S,R),(R,S)]Series C: [(S,S),(R,R) Series C: [(S,R),(R,S)]00.010.020.030.040.050.060 10 20 30 40Concentration (M)Time (h)Series E: [(S,S),(R,R)] Series E: [(S,R),(R,S)]Series F: [(S,S),(R,R)] Series F: [(S,R),(R,S)]87 2.11.6.3 General Procedure for Variable Time Normalization Analysis (VTNA) Variable time normalization analysis was applied on the reaction series acquired for reaction progress kinetic analysis studies. To carry out the analysis, two main assumptions were made. Firstly, that the consumption of the spirocyclic starting material had a 1:1 proportionality to formation of the spirocyclic product. Essentially, it was assumed that if 0.01 M of the precursor was consumed, then 0.01 M of the product was formed. Similarly, it was assumed that the consumption of hydroxide (which was not directly monitored) also had a 1:1 proportional rate of consumption to that of the spirocyclic precursor, based on the 1:1 mole ratio of reactivity required to form the corresponding spirocyclic product. With these two assumptions, the time scale for all reaction series were normalized and plotted to determine the reagent order based on optimal overlay according to the equation below, where [A]i is the concentration of the species of interest t is time, and α is the order of the reagent63. 2.11.6.3.1 VTNA Plots for DMSO Only ( ) 88 Figure 40. VTNA plots for cyclohexanone in dry DMSO Figure 41. VTNA plots for benzaldehyde in dry DMSO. 00.010.020.030.040.050.060.070.080 500 1000 1500 2000[(S,S),(R,R)] (M)∑[Benzaldehyde]1.2Δt Series B Series C00.010.020.030.040.050.060.070.080.090.10 500 1000 1500 2000[(S,R),(R,S)] (M)∑[Benzaldehyde]1.2Δt Series B Series C00.010.020.030.040.050.060 500 1000 1500 2000 2500 3000[(S,S),(R,R)] (M)∑[Benzaldehyde]1.2Δt Series E Series F00.010.020.030.040.050.060.070 500 1000 1500 2000 2500 3000[(S,R),(R,S)] (M)∑[Benzaldehyde]1.2Δt Series E Series F00.0050.010.0150.020.0250.030.0350 5000 10000 15000 20000 25000 30000[(S,S),(R,R)] (M)∑[Cyclohexanone]1Δt Series D Series E00.0050.010.0150.020.0250.030.0350.040 5000 10000 15000 20000 25000 30000[(S,R),(R,S)] (M)∑[Cyclohexanone]1Δt Series D Series E00.0050.010.0150.020.0250.030.0350.040.0450.050 10000 20000 30000 40000 50000 60000 70000[(S,S),(R,R)] (M)∑[Cyclohexanone]0Δt Series A Series B00.010.020.030.040.050.060 10000 20000 30000 40000 50000 60000 70000[(S,R),(R,S)] (M)∑[Cyclohexanone]0Δt Series A Series B89 Figure 42. VTNA plots for (S)-proline in dry DMSO. 00.0050.010.0150.020.0250.030.0350.040.0450.050 50 100 150[(S,S),(R,R)] (M)∑[Proline]1Δt Series A Series D00.010.020.030.040.050.060 50 100 150[(S,R),(R,S)] (M)∑[Proline]1Δt Series A Series D00.0050.010.0150.020.0250.030.0350.040.0450 100 200 300 400[(S,S),(R,R)] (M)∑[Proline]1Δt Series B Series E00.0050.010.0150.020.0250.030.0350.040.0450.050 100 200 300 400[(S,R),(R,S)] (M)∑[Proline]1Δt Series B Series E00.010.020.030.040.050.060.070.080 50 100 150 200 250 300[(S,S),(R,R)] (M)∑[Proline]1Δt Series C Series F00.010.020.030.040.050.060.070.080.090.10 50 100 150 200 250 300[(S,R),(R,S)] (M)∑[Proline]1Δt Series C Series F90 Figure 43. VTNA plots for benzaldehyde in wet DMSO. Figure 44. VTNA plots for cyclohexanone in wet DMSO. 00.0010.0020.0030.0040.0050.0060.0070 1000 2000 3000[(S,S),(R,R)] (M)∑[Benzaldehyde]1Δt Series B Series C00.010.020.030.040.050.060.070.080.090 500 1000 1500 2000 2500 3000[(S,R),(R,S)] (M)∑[Benzaldehyde]1Δt Series B Series C00.00050.0010.00150.0020.00250.0030.00350.0040 1000 2000 3000 4000[(S,S),(R,R)] (M)∑[Benzaldehyde]1Δt Series E Series F00.010.020.030.040.050.060 500 1000 1500 2000 2500 3000[(S,R),(R,S)] (M)∑[Benzaldehyde]1Δt Series E Series F00.00050.0010.00150.0020.00250.0030.00350.0040.00450 20000 40000 60000 80000[(S,S),(R,R)] (M)∑[Cyclohexanone]1Δt Series A Series B00.010.020.030.040.050.060 10000 20000 30000 40000 50000 60000[(S,R),(R,S)] (M)∑[Cyclohexanone]1Δt Series A Series B00.00050.0010.00150.0020.00250.0030 20000 40000 60000[(S,S),(R,R)] (M)∑[Cyclohexanone]1Δt Series D Series E00.0050.010.0150.020.0250.030.0350 10000 20000 30000 40000 50000 60000[(S,R),(R,S)] (M)∑[Cyclohexanone]1Δt Series D Series E91 Figure 45. VTNA plots for (S)-proline in wet DMSO. 00.00050.0010.00150.0020.00250.0030.00350.0040.00450 200 400 600 800 1000[(S,S),(R,R)] (M)∑[Proline]1Δt Series A Series D00.010.020.030.040.050.060 200 400 600 800[(S,R),(R,S)] (M)∑[Proline]1Δt Series A Series D00.00050.0010.00150.0020.00250.0030.00350.0040 200 400 600 800 1000[(S,S),(R,R)] (M)∑[Proline]1Δt Series B Series E00.0050.010.0150.020.0250.030.0350.040.0450 200 400 600 800[(S,R),(R,S)] (M)∑[Proline]1Δt Series B Series E00.0010.0020.0030.0040.0050.0060.0070 100 200 300 400 500[(S,S),(R,R)] (M)∑[Proline]1Δt Series C Series F00.010.020.030.040.050.060.070.080.090 100 200 300 400[(S,R),(R,S)] (M)∑[Proline]1Δt Series C Series F92 2.11.7 Additional Experiments 2.11.7.1 Monitoring Product Distribution by HPLC Figure 46. HPLC (general method) trace of product distributions under dry DMSO ([cyclohexanone]o = [benzaldehyde]o = [(S)-proline]o = 2.0 M). Benzoic acid = 3.624 min; benzaldehyde = 3.6943 min; 2.5 = 6.431 min, 2.1 ((S,S),(R,R)) = 6.218 min; 2.1 ((S,R),(R,S)) = 6.343 min; 2.6 = 7.236, 7.810 min (diastereomers). Figure 47. HPLC (general method) trace of product distributions under wet DMSO ([cyclohexanone]o = [benzaldehyde]o = [(S)-proline]o = 2.0 M). Benzaldehyde = 3.905 min; 2.1 ((S,S),(R,R)) = 6.189 min; 2.1 ((S,R),(R,S)) = 6.333 min. 93 2.11.7.2 Monitoring 2.1 enantiomer populations using chiral HPLC. Figure 48. Measurement of aldol product 2.1 enantiomer populations (right) and enantiomeric excess (left) via chiral HPLC (chiral method). [cyclohexanone]o = [benzaldehyde]o = [(S)-proline]o = 2.0 M in dry DMSO. Figure 49. Chiral HPLC Trace at 210 nm for dry DMSO conditions. Benzaldehyde = 1.807 min; 2.1 (R,R) = 2.697; 2.1 (S,R) = 3.324 min; 2.1 (S,R) = 4.365 min; 2.1 (S,S) = 6.585 min. Figure 50. Chiral (chiral method) HPLC Trace at 210 nm for wet DMSO (4:1 H2O, v/v) conditions. Benzaldehyde = 1.888 min; 2.1 (R,R) = 2.839; 2.1 (S,R) = 3.470 min; 2.1 (S,R) = 4.636 min; 2.1 (S,S) = 6.931 min. 00.20.40.60.810 10 20 30 40e.e.Time (hour)(S,R) (R,S) (S,S) (R,R)02000400060008000100000 10 20 30 40Peak AreaTime (hour)(R,R) (S,R) (R,S) (S,S)94 2.11.7.3 Byproduct catalysis (formation of mixture of oxazolidinones) To a vial was added was added benzaldehyde (0.5 mL 4.5 mmol), and (S)-proline (172 mg, 1.5 mmol) in DMSO (15 mL). After 24 hours and observation of byproduct formation via HPLC-MS, the mixture was diluted with water (100 mL), extracted with EtOAc (3 x 50 mL), the combined organic fractions washed with brine (1 x 50 mL), dried over MgSO4, filtered, and concentrated under vacuum to yield a viscous yellow oil (250 mg). This oil in its entirety was then used in the place of proline in a standard aldol reaction (see above) in both dry DMSO and wet DMSO (4:1 H2O v/v). No product formation was observed after 4, 24, or 48 hours of mixture. Figure 51. HPLC trace of final time point of aldol reaction under dry DMSO using oxazolidinone mixture. Benzoic acid = 3.576 min; benzaldehyde = 3.997 min, 2.5 = 5.459 min; 2.6 = 7.236, 7.810 min (diastereomers). 95 Figure 52. HPLC trace of final time point of aldol reaction under dry DMSO using oxazolidinone mixture. Benzoic acid = 3.581 min; benzaldehyde = 3.992 min, 2.5 = 5.468 min; 2.6 = 7.240, 7.817 min (diastereomers). 2.11.7.4 Crystallization and X-Ray Identification of Major Stereoisomer of 2.1 (S,R) under wet DMSO conditions. Experimental. Single colourless irregular-shaped crystals of jh032 (major product diastereomer isolated from standard aldol reaction under wet DMSO conditions, 93% e.e.) were recrystallized from PET ether by slow evaporation. A suitable crystal 0.61×0.31×0.20 mm3 was selected and mounted on a mylar loop in oil on an Bruker APEX II area detector diffractometer. The crystal was kept at a steady T = 90(2) K during data collection. The structure was solved with the XT66 structure solution program using the Intrinsic Phasing solution method and by using Olex267 as the graphical interface. The model was refined with version 2017/1 of XL68 using Least Squares minimization. 96 Crystal Data. C13H16O2, Mr = 204.26, monoclinic, P21 (No. 4), a = 9.9143(3) Å, b = 11.5946(3) Å, c = 10.5477(3) Å,  = 115.2980(10)°,  =  = 90°, V = 1096.20(5) Å3, T = 90(2) K, Z = 4, Z' = 2, (CuK) = 0.652, 24430 reflections measured, 3972 unique (Rint = 0.0384) which were used in all calculations. The final wR2 was 0.0705 (all data) and R1 was 0.0278 (I > 2(I)). Compound JD-EX-096-Major Formula C13H16O2 Dcalc./ g cm-3 1.238 /mm-1 0.652 Formula Weight 204.26 Colour colourless Shape irregular Size/mm3 0.61×0.31×0.20 T/K 90(2) Crystal System monoclinic Flack Parameter -0.02(6) Hooft Parameter 0.01(6) Space Group P21 a/Å 9.9143(3) b/Å 11.5946(3) c/Å 10.5477(3) /° 90 /° 115.2980(10) /° 90 V/Å3 1096.20(5) Z 4 Z' 2 Wavelength/Å 1.54178 Radiation type CuK min/° 4.637 max/° 68.437 Measured Refl. 24430 Independent Refl. 3972 Reflections with I > 2(I) 3858 Rint 0.0384 Parameters 280 Restraints 1 Largest Peak 0.151 Deepest Hole -0.136 GooF 1.036 wR2 (all data) 0.0705 wR2 0.0698 R1 (all data) 0.0288 R1 0.0278 97 Structure Quality Indicators Reflections: Refinement: A colourless irregular-shaped crystal with dimensions 0.61×0.31×0.20 mm3 was mounted on a mylar loop in oil. Data were collected using an Bruker APEX II area detector diffractometer equipped with an Oxford Cryosystems low-temperature device operating at T = 90(2) K. Data were measured using  and  scans of 2.0 ° per frame for 2 s using CuK radiation (microfocus sealed X-ray tube, 45 kV, 0.60 mA). The total number of runs and images was based on the strategy calculation from the program APEX3. The maximum resolution that was achieved was  = 68.437° (0.83 Å). The diffraction pattern was indexed and the unit cell was refined using SAINT (Bruker, V8.38A, after 2013) on 8916 reflections, 36% of the observed reflections. Data reduction, scaling and absorption corrections were performed using SAINT (Bruker, V8.38A, after 2013). The final completeness is 100.00 % out to 68.437° in . A multi-scan absorption correction was performed using SADABS-2016/2 (Bruker, 2016/2) was used for absorption correction. wR2(int) was 0.0743 before and 0.0556 after correction. The ratio of minimum to maximum transmission is 0.9197. The /2 correction factor is not present. The absorption coefficient  of this material is 0.652 mm-1 at this wavelength ( = 1.542Å) and the minimum and maximum transmissions are 0.807 and 0.878. The structure was solved and the space group P21 (# 4) determined by the XT66 structure solution program using Intrinsic Phasing and refined by Least Squares using version 2017/1 of XL.68 All non-hydrogen atoms were refined anisotropically. Hydrogen atom positions were calculated geometrically and refined using the riding model. Most hydrogen atom positions were calculated geometrically and refined using the riding model, but all O—H hydrogen atoms were refined freely. 98 The value of Z' is 2. This means that there are two independent molecules in the asymmetric unit. The Flack parameter was refined to -0.02(6). Determination of absolute structure using Bayesian statistics on Bijvoet differences using the Olex2 results in 0.01(6). The configurations of C7 and C20 were determined to be (R), while C8 and C21 are both (S). Note: The Flack parameter is used to determine chirality of the crystal studied, the value should be near 0, a value of 1 means that the stereochemistry is wrong and the model should be inverted. A value of 0.5 means that the crystal consists of a racemic mixture of the two enantiomers. Table 4: Fractional Atomic Coordinates (×104) and Equivalent Isotropic Displacement Parameters (Å2×103) for jh032. Ueq is defined as 1/3 of the trace of the orthogonalised Uij. Atom x y z Ueq O1 2232.8(17) 10074.8(13) 8029.7(16) 29.1(3) O2 1752.7(15) 8766.7(12) 5705.6(15) 25.8(3) C1 69(2) 10265.1(16) 9276(2) 19.7(4) C2 -302(2) 10497.1(17) 10376(2) 22.1(4) C3 290(2) 9839.5(17) 11588(2) 20.6(4) C4 1237(2) 8935.2(17) 11687(2) 20.4(4) C5 1601.8(19) 8691.4(16) 10584.4(19) 18.3(4) C6 1022(2) 9353.7(16) 9366.9(19) 17.2(4) C7 1428(2) 9099.4(16) 8166.3(19) 18.0(4) C8 67(2) 8809.1(16) 6796.6(19) 16.9(4) C9 -786(2) 7779.0(19) 6997(2) 24.4(4) C10 -2078(2) 7385(2) 5640(2) 28.2(5) C11 -1508(2) 7069.8(18) 4554(2) 25.7(5) C12 -694(2) 8089.5(18) 4284(2) 24.8(4) C13 507(2) 8565.3(16) 5605.6(19) 18.3(4) O3 2324.2(14) 5809.0(13) 6920.7(15) 26.2(3) O4 3731.8(15) 6274.9(13) 9770.0(14) 26.6(3) C14 3353(2) 6385.5(18) 4801(2) 22.6(4) C15 3581(2) 6283.7(19) 3597(2) 26.6(4) C16 4520(2) 5446.9(18) 3489(2) 25.9(4) C17 5232(2) 4698.3(19) 4600(2) 27.5(5) C18 4999(2) 4796.4(18) 5801(2) 23.5(4) C19 4072.1(19) 5638.7(16) 5924.0(19) 17.6(4) C20 3894.2(19) 5763.5(16) 7272.0(19) 17.9(4) C21 4690(2) 6835.5(16) 8113.3(19) 16.6(4) C22 6362(2) 6861.2(18) 8458.0(19) 19.7(4) C23 7140(2) 7914.2(18) 9330.7(19) 20.7(4) C24 6962(2) 7952.4(18) 10693.1(19) 20.7(4) C25 5314(2) 7927.6(19) 10408(2) 23.6(4) C26 4503(2) 6941.2(17) 9467(2) 19.4(4) 99 Table 5: Anisotropic Displacement Parameters (×104) jh032. The anisotropic displacement factor exponent takes the form: -22[h2a*2 × U11+ ... +2hka* × b* × U12] Atom U11 U22 U33 U23 U13 U12 O1 33.2(8) 29.5(8) 30.6(8) -7.0(6) 19.3(7) -14.8(7) O2 28.6(8) 26.6(8) 31.4(8) -1.5(6) 21.6(6) -3.2(6) C1 19.9(10) 17.8(9) 17.6(9) -0.7(7) 4.4(7) 1.3(7) C2 19.9(9) 19.7(10) 25.1(10) -5.0(8) 8.1(8) 2.2(8) C3 19.4(9) 23.4(10) 21.1(9) -6.3(8) 10.7(8) -3.4(8) C4 20.1(9) 21.7(10) 17.5(9) 0.6(8) 6.0(7) -1.9(7) C5 14.7(8) 17.7(9) 21.7(9) -1.0(7) 6.9(7) 0.1(7) C6 13.9(9) 17.5(9) 18.9(9) -4.4(7) 5.8(7) -4.6(7) C7 17.5(9) 18.3(9) 19.7(9) -0.4(7) 9.4(7) -2.3(7) C8 17.1(9) 17.9(9) 16.5(9) 0.3(7) 7.9(7) 1.2(7) C9 28.0(11) 30.7(11) 18.4(9) -3.9(8) 13.8(8) -10.6(9) C10 25.9(11) 36.5(12) 22.8(10) -7.7(9) 11.0(9) -11.7(9) C11 30.4(11) 27.9(11) 17.6(9) -5.3(8) 9.2(8) -5.6(9) C12 30.3(11) 30.0(11) 16.4(9) 1.2(8) 12.0(8) 1.4(9) C13 24.1(10) 14.3(9) 19.6(9) 5.4(7) 12.3(8) 2.7(7) O3 17.5(7) 33.7(8) 29.4(8) -7.9(6) 12.0(6) -7.1(6) O4 25.9(7) 32.3(8) 28.0(7) -0.7(6) 17.5(6) -6.9(6) C14 21.3(9) 21.6(10) 22.1(9) -3.2(8) 6.8(8) 4.2(8) C15 30.4(11) 26.1(11) 18.0(9) -0.9(8) 5.2(8) 2.2(9) C16 28.1(10) 28.8(11) 23.2(10) -10.0(8) 13.3(8) -7.3(9) C17 23.7(10) 27.4(11) 34.2(11) -5.0(9) 15.2(9) 3.7(8) C18 21.1(10) 21.7(10) 26.2(10) 1.7(8) 8.8(8) 3.6(8) C19 14.3(8) 16.2(9) 20.6(9) -5.4(7) 5.7(7) -3.9(7) C20 15.5(9) 17.0(9) 21.3(9) 0.8(7) 8.0(7) -0.2(7) C21 15.9(9) 18.4(9) 16.1(9) 0.6(7) 7.4(7) -0.6(7) C22 16.6(9) 27.0(10) 17.2(9) -2.6(8) 8.9(7) -2.5(8) C23 17.3(9) 27.0(10) 18.1(9) -2.0(8) 7.9(7) -5.8(8) C24 18.9(9) 26.2(10) 15.7(9) -1.9(8) 6.2(7) -3.0(8) C25 22.6(10) 29.5(11) 21.4(10) -5.8(9) 11.9(8) -2.7(9) C26 14.4(9) 23.6(10) 21.2(9) 0.1(8) 8.6(7) 2.1(8) Table 6: Bond Lengths in Å for jh032. Atom Atom Length/Å O1 C7 1.427(2) O2 C13 1.216(2) C1 C2 1.385(3) C1 C6 1.393(3) C2 C3 1.385(3) C3 C4 1.381(3) C4 C5 1.387(3) C5 C6 1.392(3) C6 C7 1.513(2) C7 C8 1.535(2) C8 C9 1.530(3) C8 C13 1.522(2) C9 C10 1.527(3) C10 C11 1.522(3) C11 C12 1.525(3) C12 C13 1.499(3) Atom Atom Length/Å O3 C20 1.439(2) O4 C26 1.221(2) C14 C15 1.386(3) C14 C19 1.393(3) C15 C16 1.383(3) C16 C17 1.385(3) C17 C18 1.386(3) C18 C19 1.385(3) C19 C20 1.513(2) C20 C21 1.535(3) C21 C22 1.538(3) C21 C26 1.522(2) C22 C23 1.525(3) C23 C24 1.521(2) C24 C25 1.530(3) C25 C26 1.503(3) 100 Table 7: Bond Angles in ° for jh032. Atom Atom Atom Angle/° C2 C1 C6 120.29(18) C1 C2 C3 120.45(18) C4 C3 C2 119.61(18) C3 C4 C5 120.23(18) C4 C5 C6 120.55(17) C1 C6 C7 120.35(17) C5 C6 C1 118.85(17) C5 C6 C7 120.80(17) O1 C7 C6 106.88(15) O1 C7 C8 112.56(15) C6 C7 C8 112.93(14) C9 C8 C7 110.90(15) C13 C8 C7 111.76(14) C13 C8 C9 109.86(15) C10 C9 C8 113.30(16) C11 C10 C9 110.19(17) C10 C11 C12 110.49(17) C13 C12 C11 112.67(15) O2 C13 C8 122.10(17) O2 C13 C12 121.69(16) C12 C13 C8 116.19(15) Atom Atom Atom Angle/° C15 C14 C19 120.11(18) C16 C15 C14 120.95(19) C15 C16 C17 119.19(18) C16 C17 C18 119.87(19) C19 C18 C17 121.34(18) C14 C19 C20 121.14(16) C18 C19 C14 118.53(17) C18 C19 C20 120.29(17) O3 C20 C19 108.02(14) O3 C20 C21 110.60(14) C19 C20 C21 112.52(15) C20 C21 C22 112.86(15) C26 C21 C20 111.63(15) C26 C21 C22 109.16(15) C23 C22 C21 111.96(16) C24 C23 C22 111.15(16) C23 C24 C25 111.02(15) C26 C25 C24 111.70(16) O4 C26 C21 122.37(17) O4 C26 C25 121.83(17) C25 C26 C21 115.80(16) Table 8: Torsion Angles in ° for jh032. Atom Atom Atom Atom Angle/° O1 C7 C8 C9 -178.57(15) O1 C7 C8 C13 58.5(2) C1 C2 C3 C4 -1.1(3) C1 C6 C7 O1 63.9(2) C1 C6 C7 C8 -60.4(2) C2 C1 C6 C5 -0.6(3) C2 C1 C6 C7 180.00(17) C2 C3 C4 C5 0.5(3) C3 C4 C5 C6 0.1(3) C4 C5 C6 C1 0.0(3) C4 C5 C6 C7 179.40(16) C5 C6 C7 O1 -115.47(19) C5 C6 C7 C8 120.23(18) C6 C1 C2 C3 1.1(3) C6 C7 C8 C9 -57.4(2) C6 C7 C8 C13 179.62(15) C7 C8 C9 C10 -175.16(17) C7 C8 C13 O2 -10.9(3) C7 C8 C13 C12 170.56(16) C8 C9 C10 C11 57.9(2) 101 Atom Atom Atom Atom Angle/° C9 C8 C13 O2 -134.49(19) C9 C8 C13 C12 47.0(2) C9 C10 C11 C12 -57.2(2) C10 C11 C12 C13 53.0(2) C11 C12 C13 O2 132.33(19) C11 C12 C13 C8 -49.2(2) C13 C8 C9 C10 -51.1(2) O3 C20 C21 C22 -177.27(15) O3 C20 C21 C26 59.34(19) C14 C15 C16 C17 0.4(3) C14 C19 C20 O3 51.6(2) C14 C19 C20 C21 -70.8(2) C15 C14 C19 C18 -0.5(3) C15 C14 C19 C20 177.37(18) C15 C16 C17 C18 -0.1(3) C16 C17 C18 C19 -0.5(3) C17 C18 C19 C14 0.8(3) C17 C18 C19 C20 -177.09(18) C18 C19 C20 O3 -130.58(18) C18 C19 C20 C21 107.05(19) C19 C14 C15 C16 -0.1(3) C19 C20 C21 C22 -56.36(19) C19 C20 C21 C26 -179.75(15) C20 C21 C22 C23 -178.29(15) C20 C21 C26 O4 -3.9(2) C20 C21 C26 C25 176.68(15) C21 C22 C23 C24 58.0(2) C22 C21 C26 O4 -129.4(2) C22 C21 C26 C25 51.2(2) C22 C23 C24 C25 -56.1(2) C23 C24 C25 C26 52.1(2) C24 C25 C26 O4 129.35(19) C24 C25 C26 C21 -51.3(2) C26 C21 C22 C23 -53.5(2) Table 9: Hydrogen Fractional Atomic Coordinates (×104) and Equivalent Isotropic Displacement Parameters (Å2×103) for jh032. Ueq is defined as 1/3 of the trace of the orthogonalised Uij. Atom x y z Ueq H1A -328.82 10729.43 8455.24 24 H2 -966.95 11111.34 10298.49 27 H3 45.98 10009.6 12346.09 25 H4 1639.4 8478.54 12513.9 25 H5 2252.89 8067.32 10660.51 22 H7 2113.96 8419.45 8432.85 22 H8 -615.64 9491.37 6527.02 20 102 Atom x y z Ueq H9A -85.09 7127.64 7393.82 29 H9B -1181.33 7989.22 7684.17 29 H10A -2570.71 6707.53 5830.26 34 H10B -2824.5 8011.51 5270.8 34 H11A -2358.42 6842.74 3667.52 31 H11B -821.21 6403.85 4893.3 31 H12A -245.82 7841.35 3651.13 30 H12B -1424.61 8707.04 3803.77 30 H14 2705.64 6965.62 4859.56 27 H15 3084.84 6796.2 2835.89 32 H16 4675.36 5386.36 2662.85 31 H17 5879.15 4118.5 4538.89 33 H18 5485.93 4275.32 6555.08 28 H20 4325.89 5064.99 7863.22 21 H21 4217.93 7528.29 7526.4 20 H22A 6842.66 6153.11 8980.18 24 H22B 6482.74 6867.82 7573.49 24 H23A 8213.86 7890.03 9545.22 25 H23B 6710.35 8623.1 8783.39 25 H24A 7430.6 8663.93 11214.2 25 H24B 7480.86 7283.35 11283.36 25 H25A 5233.79 7856.6 11308.49 28 H25B 4837.98 8662.76 9963.62 28 H3A 2260(30) 5850(30) 7720(30) 43(8) H1 2440(40) 9920(30) 7300(30) 62(10) Table 10: Hydrogen Bond information for jh032. D H A d(D-H)/Å d(H-A)/Å d(D-A)/Å D-H-A/deg O3 H3A O4 0.88(3) 2.08(3) 2.773(2) 135(2) O1 H1 O2 0.90(3) 2.02(3) 2.746(2) 137(3) 103 2.11.7.5 Calibration Plots A standard solution (2 mL) was prepared containing benzaldehyde (2.0 M), 2.1 ((S,S),(R,R), 0.5 M), and 2.1 ((S,R),(R,S) 0.6 M). The solution was sampled in triplicate using the automated sampling platform outlined previously. The solution was serially diluted, with each standard sampled as outlined to generate calibration plots between the HPLC peak area of a particular species and its corresponding concentration in the parent solution (Figure 53) . Figure 53. Calibration plots for benzaldehyde (top) and 2.1 (bottom) y = 5351.1x + 811.63R² = 0.9778020004000600080001000012000140000 0.5 1 1.5 2HPLC Peak AreaConcentration (M)Benzaldehydey = 16964x + 133.3R² = 0.9948y = 18025x + 76.908R² = 0.9970200040006000800010000120000 0.1 0.2 0.3 0.4 0.5 0.6 0.7HPLC Peak AreaConcentration (M)((S,R),(R,S))((S,S),(R,R))104 2.11.8 1H and 13C NMR Data 1H NMR (300 MHz, Chloroform-d) δ 7.33 – 7.18 (m, 5H), 4.72 (dd, J = 8.8, 2.6 Hz, 1H), 3.89 (d, J = 2.8 Hz, 1H), 2.55 (dddd, J = 12.7, 8.8, 5.5, 1.2 Hz, 1H), 2.42 (dddd, J = 13.7, 4.6, 3.1, 1.7 Hz, 1H), 2.29 (tdd, J = 13.6, 6.0, 1.2 Hz, 1H), 2.02 (ddt, J = 12.3, 6.0, 3.0 Hz, 1H), 1.78 – 1.40 (m, 4H), 1.31 – 1.14 (m, 1H). 13C NMR (75 MHz, CDCl3) δ 215.7, 141.1, 128.5, 128.0, 127.2, 74.9, 57.6, 42.8, 31.0, 27.9, 24.9. 1H NMR (300 MHz, Chloroform-d) δ 7.32 – 7.15 (m, 5H), 5.34 (t, J = 2.9 Hz, 1H), 2.95 (d, J = 3.2 Hz, 1H), 2.60 – 2.48 (m, 1H), 2.45 – 2.24 (m, 2H), 2.03 (ddd, J = 15.6, 5.5, 2.7 Hz, 1H), 1.85 – 1.37 (m, 6H). 13C NMR (75 MHz, CDCl3) δ 215.0, 141.6, 128.3, 127.1, 125.9, 70.8, 57.3, 42.8, 28.1, 26.1, 25.0. 105 Chapter 3: Investigations in a Phase Transfer Catalysis Reaction 3.1 Phase Transfer Catalysis Biphasic reactions involving a phase transfer catalyst compose a unique subcategory of heterogeneous reaction mixtures. They have displayed excellent utility, both on the lab bench and in the industrial reactor, with certain instances boasting high yields, enhanced stereoselectivity, as well their potential for use in continuous operations, solvent reduction and solvent recycling.69 The origins of phase transfer catalysis, or at least the first formal discussion of the term, originated in the 1970’s where it was applied to the use of tetraalkylammonium or tetraalkylphosphonium salts to facilitate a cyanide displacement reaction.46,70 Since then, phase transfer catalysts have expanded both in variety of their structures and the reactions they catalyze. By 1986, phase transfer catalysts were involved in numerous reactions such as aromatic substitutions, dehydrohalogenations, and oxidations, and were involved in numerous industrial scale preparations of polymers, pesticides, and pharmaceuticals.71 Asymmetric phase transfer catalysts were particularly attractive as they offered routes for the enantioselective preparations of complex molecules with environmental and cost-friendly benefits such as catalyst recovery, solvent recycling, and mild reaction conditions.47,72 Catalytic systems have been developed which offer access to enantioselectiveepoxidations,73,74 alkylations, rearrangements,75 aziridinations,76 dihydroxylations,77 fluorinations,78 cyanations,79 and even spirocyclizations80 to name a few. At its core, asymmetric phase transfer catalysis operates and benefits by many of the same principles of general catalysis, with improved atom economy, faster rates, and often milder conditions than stoichiometric systems. Biphasic reactions can also allow two or more substrates 106 with vastly different solubilities to interact. For instance, in many systems, a phase transfer catalyst allows for the use of a simple aqueous base, such as hydroxide or phosphate, rather than a stoichiometric equivalent of a chiral organic base or other auxiliary. Moreover, catalysts in these systems are typically readily derived from the existing chiral pool of natural products such as cinchona alkaloids. These compounds, such as quinidine, cinchonine, and dihydroquinine, have formed the backbone of many asymmetric phase transfer catalysts through relatively simple preparative procedures, with their relative abundance making them generally affordable and accessible.81 Phase transfer catalysis reactions are generally accepted to operate by one of three main mechanisms; the catalyst can shuttle material from one phase to the other (organic to aqueous or aqueous to organic) where it then mediates the reaction, or it mediates the reaction at the interface of the immiscible phases.72 Reactions which involve the movement of material between solvents have an additional mass transfer and solubility component as an added complexity to their system. In general, most catalysts are believed to operate via ion-pairing, with catalyst-substrate complexes allowing transition between phases. Non-covalent interactions, such as hydrogen bonding, π-stacking, and Van-der-Waals forces are believed to determine the stereoselectivity of the resulting reaction.82 In several cases, mass transfer between phases has been identified as the limiting step for the reaction, thus efficient mixing is vital to achieving efficient catalytic reactivity.83 Understanding how to optimize these systems requires the knowledge of several rates, including that of mass transfer (ktransfer), and the productive reaction (krxn). However, obtaining these data is often non-trivial. 107 Figure 54. General mechanism(s) for a simple phase transfer catalysis reactions.72 Monitoring biphasic reactions poses significant challenges over that of heterogenous solid-liquid slurries. The inherent dependence of biphasic systems on interfacial interactions between the two immiscible solvent phases requires most phase transfer reactions to occur under an extremely high stir rate in order to effectively to maximize the interfacial area. This renders many common analytical techniques ineffective to monitor the reaction such means as NMR and FTIR.84 In these cases, the ever-fluctuating solution phase prevents a suitable solvent lock for magnetic resonance studies or a stable background spectrum for use in infrared spectroscopy. Aliquot sampling to access time-course data is also not straightforward. To fully understand a biphasic reaction, direct insight into what is occurring in each phase at a given time is crucial to building a model that adequately describes the system. To get around this issue, traditional reaction monitoring often involves “stopping” the reaction by stopping any stirring and then carefully sampling the respective layers once they separate. However, this approach relies heavily on two assumptions; first, that the rate of reaction is largely mass-transfer limited, and so OrganicAqueousCatalyst brings reagent from the Organic Phase to the Aqueous PhaseCatalyst brings reagent from the Aqueous Phase to the Organic PhaseCatalyst mediates reaction(s) at the interface of the solvent layer108 the reaction should crawl to a stop once mixing is stopped. While this assumption holds true for many systems, it may not work for all. The second assumption asserts that there is no background reactivity such as catalyst deactivation which occurs independently of phase transfer. whereby as the solubilities of reactive species, catalysts, intermediates, and products would need to be known for every stage in the reaction; such analysis would prove even more difficult in cases where additives and catalytic species can drastically alter the solubility of a given component85. As a result, many biphasic reactions, particularly those involving a phase transfer catalyst, are poorly understood and less well developed as compared to their homogeneous counterparts.86 A relatively recent application of phase transfer catalysis involves the potential industrial scale application of a drug candidate for a calcitonin gene-related peptide (CGRP) receptor antagonist.80 This class of compounds has shown promise for the treatment of migraines and headaches. As such, work has been undertaken by Xiang et al80 to explore the synthesis of these compounds on larger scales. Figure 55: CGRP antagonist candidates.80 One proposed route in the synthesis of these compounds is the use of a doubly quaternized cinchona alkaloid to generate one of the spirocyclic center in an enantioselective manner (Figure 55). Early screening attempts of suitable candidates were promising, whereby a 109 catalyst 3.3 was identified which could carry out the spirocyclization in near quantitative yields and with high enantioselectivity (93% e.e.). However, reproducibility issues plagued attempts to refine the catalyst and improve the yield of the desired product.80 Thus, the project was proposed as a suitable candidate to develop a sampling protocol for the study of biphasic reactions. Scheme 9. Reaction scheme for the enantioselective spirocyclization catalyzed by a doubly quaternized cinchona alkaloid.80 3.2 Development of an Automated Sampling System for Biphasic Reaction Monitoring In order to study the phase transfer catalyzed reaction, an automated sampling platform was developed which could selectively sample the organic layer, aqueous layer, or both in a reliable, robust, and reproducible fashion. As described above, the biphasic nature of the reaction created a limitation in the ability to acquire robust and reproducible kinetic data on such a reaction. To overcome this, a monitoring methodology using phase selective solution sampling coupled with HPLC-MS would be leveraged. To accomplish the Gilson215 liquid handler was selected to prepare vials for HPLC analysis based on its successful deployment in the study of other reactions.2,3,35 This would then be configured into one of two potential sampling methods; the first would use heterogeneous sampling to aliquot the organic and aqueous layer 110 simultaneously, while the second would achieve selective sampling from either the organic or aqueous layer independently. As was used previously, the Gilson 215 Liquid Handler was selected to form the foundation of the sampler and would handle the final dilution and dispensing of reaction aliquots into vials for offline HPLC analysis. Gilson’s Trilution software was used to coordinate the liquid handler and ancillary equipment to carry out a sampling event, while PEEK tubing (0.040 ID) was used to connect them together. A sample of the reaction mixture is withdrawn and loaded into a sample loop of known volume. This sample is subsequently quenched with a MeOH (1% AcOH modifier) and dispensed into HPLC vials via the Gilson liquid handler. Heterogeneous sampling was envisioned with the use of a Mettler Toledo EasySampler probe. The small 20 μL “scoop” and accompanying tubing has been used to great effect in the study of liquid-solid heterogeneous reactions, and was expected to translate well to biphasic systems2. Assuming a well-mixed and behaved emulsion, the sampler was expected to withdraw consistent volumes of the biphasic reaction with a near constant composition of organic-to-aqueous phases. However, this composition was expected to have some degree of variability in practice and needed to be accounted for. For instance, if some reactive species A had near complete solubility in toluene, its concentration would appear to be 50% higher if the Easy Sampler happened to aliquot a solution containing 45% toluene than one containing 30% based on raw peak HPLC area alone. Thus, an internal standard would be necessary to more accurately determine the concentration of reaction species. For this reaction, benzene was selected due to its high solubility in toluene compared with water, as well as being easily separable from other reaction species via HPLC. 111 Figure 56. Schematics for the sampling platform, including phase selective sampling (top) and heterogeneous sampling (bottom) configurations. A) Quench reservoir B) Gilson 215 Liquid Handler C) Valvemate 6-port, 2-position valve with sample loop D) Ismatec piston pump E) Reactor vessel with circulation loop F) Reactor vessel with EasySampler. The selective sampling of the organic phase was more challenging. The limitations discussed previously regarding sampling phases by letting them resolve without stirring encouraged the development instead of a continuous flow approach. This was originally envisioned with the use of a membrane-based liquid-liquid separator for continuous flow operations.87 A continuous circulation loop could be set up which continually pumped the A B C D EA B F112 toluene-water slurry through the membrane separator before returning both lines into the reaction vessel. An HPLC injector loop could be introduced to either the organic or aqueous outflow lines to then sample aliquots of the corresponding phase for offline HPLC analysis via the Gilson liquid handler. These two proposals served as the base for the development of the sampling platform. Another design criterion which needed to be considered was the reactor design itself. A traditional round-bottomed flask with a stir-bar would not be able to provide the mixing efficiency or rotations per minute needed to sufficiently mix the biphasic reaction. As illustrated previously, the reliance of biphasic reactions on mass transfer between or at the interface of its immiscible solvents necessitates efficient and consistent stirring in order to ensure reproducible and consistent reactions. Generally speaking, these reactions are not amenable to conventional round bottomed flasks nor stir-plates due to poor mixing and relatively low stirring speeds, and often need dedicated reactor designs particularly on scale.88,89 Attempts to recreate the stirring efficiencies of large reactors on the bench-top scale originally focused on using narrow vials with long stir bars which could sit “upright” in the vial and “tumble” when placed over a rotating stir-plate. The idea was that the tumbling motion could mix the solution more efficiently than simple stirring at low rpm. However, while this mode allowed for better mixing at comparatively lower speeds, the propensity of the stir-bar to decouple from the stir-plate magnet along with inconsistent tumbling made it a poor contender for use in a reaction which already had issues with reproducibility. It became apparent that a new reactor design was necessary; one which would allow for highly efficient stirring, stay coupled with the stirrer’s magnet, while accommodating the equipment needed to monitor the reaction, such as the EasySampler and circulation tubing. 113 Figure 57: Vial assembly (left) and overhead stirrer (right) for continuous mixing of a biphasic reaction The solution to reaction stirring came in the form of a “miniature” industrial reactor design using an aluminum/stainless steel impeller assembly which could be inductively coupled to an external magnetic to drive its motion developed by Technobis. This assembly allowed for versatility in propeller design and allowed for easy adaptation to threading found on common glass vials. To drive the propeller, a neodymium magnet was fixed to an overhead stirrer in order to inductively couple with a second neodymium magnet embedded in the vial’s propeller assembly (Figure 57). Channels built into the aluminum housing allowed for PEEK tubing to be fed directly into the vial to allow for both withdrawal and return lines to be installed to establish 114 a circulation loop of the reaction solution. Furthermore, O-rings built into the assembly in addition to the low tolerance of the tubing channels allows for the vial to, in principle, be sealed as an atmospherically isolated system. This opens the possibility for reactions to be carried out under an inert atmosphere, provided an initial seal can be established. 3.2.1 General Monitoring of Both Phases Simultaneous sampling of all reaction components in the biphasic reaction was achieved using a Mettler-Toledo EasySampler Probe. The probe, while originally designed for sampling of homogenous or heterogenous slurries, was found adaptable to the sampling of a heterogeneous biphasic reaction. Its basic operating principal involved the use of a “sample scoop” of fixed volume which could be extended into solution or withdrawn into the probe head on command; channels built into the probe head allows for the priming of internal plumbing with a diluent and/or quench solution, which can be immediately applied to the reaction aliquot once it has been retracted into the probe, and then dispensed into a vial for offline analysis. This tool proved useful in acquiring an overview of the phase transfer reaction at a given point in time. However, in order to study the reaction in greater depth, a method needed to be developed which could observe reactive species in either the organic or aqueous phase in a selective manner. 115 Figure 58. Easy Sampler schematic illustrating the extended scoop with primed lines (left) and withdrawn scoop with in-line quench of sample aliquot (right). 3.2.2 Selective Monitoring of the Organic Phase The development of a method capable of selectively sampling either the organic or aqueous phase was crucial to further the understanding of phase transfer catalysis reactions. As these reactions are dependent on the shuttling of reagents between solvent layers, observations of exactly what species are present in which layer at a given point in time is imperative to developing models, furthering mechanistic understanding, and directing optimization efforts. Equation 5. Minimal partial pressure required to drive separation of two immiscible phases. 𝑷𝒑𝒆𝒓 𝟖𝝁𝑸𝑳 𝝅𝑹𝟒 116 The area of liquid-liquid extraction has undergone impressive advancements in recent years due to interest in continuous flow operations for industrial applications. One such emergent technique came in the form of a membrane-based liquid-liquid separator for continuous separation of immiscible solvents.87 It exploits the minimum membrane pressure, Pper required to drive complete separation of two immiscible phases as dictated by the viscosity of the permeate phase, μ, and the volumetric flowrate of the entering permeate liquid, Q. The other parameters are dictated by the membrane properties, including the membrane thickness, L ¸the number of pores, n, and their corresponding radii R (Equation 5). In practical terms, the separation of a biphasic mixture could be accomplished by either adjusting the flow rate to the separator or swapping the membranes in use until sufficient separation is achieved. In effect, the “wetting” of the membrane occurs due to favourable interactions between one of the solvent phases and the material of the membrane; this “wetting” and surface interaction(s) allows for only one phase to permeate through the membrane, thus separating the immiscible solvents. A diaphragm introduced downstream of this membrane allowed for integrated pressure control to ensure consistent separation in the face of continually fluctuating pressures during operation (Figure 59). Its ability to separate immiscible phases under continuous flow has already been exploited in syntheses involving flow reactors.90 The ability of this device for the continuous liquid-liquid separation made it an ideal candidate for separation and selective sampling of either the aqueous or organic phase of the reaction. 117 Figure 59: Overview (left) and schematic (right) of the membrane-based continuous liquid-liquid extractor.87 Initial attempts to integrate the continuous flow separator proved particularly challenging. Efforts to obtain and optimize flow rates and pressures necessary to establish complete separation were initially unsuccessful. Concerns surrounding the substantial dead-volume of the separator and its tubing further cast doubt on the easy application of the tool to selectively sample both phases of the reaction. Nonetheless, parameters were found which consisted of a 0.2 μm PTFE membrane and 5 mL/min pump rate which could adequately separate the toluene and aqueous solvents for continuous phase-selective sampling. Work on addressing other issues with the sampling assembly led to a serendipitous discovery. The aluminum-based casing which capped the reactor vial gradually generated insoluble aluminum hydroxide particulate during the phase transfer reaction(s) due to the use of hydroxide. Over time, this particulate accumulated in tubing and within the pump head, causing obstructions which had the potential to arrest circulation or damage the pump itself. To minimize this particulate build-up, a 0.2 μm PTFE HPLC filter was placed onto the start of the “intake” line for the circulation loop. After installing this filter, it was observed that less water was being partitioned by the membrane-based separator. Upon closer inspection, it was found that the small PTFE filter appeared to be selectively withdrawing toluene from the reaction mixture. It was 118 then realized that the filter chosen to prevent particulate intake to the circulation loop was of the same material and porosity used in the membrane separator. In effect, the pore size and material of the HPLC -inline filter appeared to have the capability of satisfying the minimum differential pressure, Pper, required to drive separation of the phases. As with the membrane filter, the parameters concerning the viscosity of the permeate phase, μ, the membrane thickness, L ¸the number of pores, n, and their corresponding radii R were fixed properties of the filter, and so flow-rate was varied until complete separation was achieved. Thus, it appeared that the addition of the filter adequately emulated the action of the continuous membrane separator, allowing for a compacted sampler design, smaller reaction volumes, and easier maintenance. The utilization of both the Easy-Sampler, and PTFE membrane allowed for heterogeneous (simultaneous organic and aqueous) sampling, as well as phase-selective sampling of the toluene layer. Although the method lacked a direct way to sample the aqueous phase without the use of the membrane separator, insight into the reaction space was still easily accessible with the existing method. One could subtract the chemistry observed in the organic phase via the phase selective sampling (toluene only) from what is observed in both phases via heterogeneous sampling (toluene and water), with the difference accounting for any species residing in the aqueous layer. Thus, a sampling method had been created which could, in principle, study the three major facets of a biphasic reaction. 3.2.3 Refinement and Validation of the Sampling Method(s) Further refinement of the sampling platform and its method, as well as its validation, proceeded following its assembly. As with previous work, a calibration plot for optimal sample concentration and push volume(s) was constructed to acquire the highest response factor per sample, and to do so consistently between samples. In essence, there exists a minimum volume 119 of solvent that must be pushed through the lines to deliver all of the reaction aliquot to the waiting HPLC vial. This volume is referred to herein as the push or dilution volume. If the liquid handler pushes less than this volume, then not all of the reaction aliquot will reach the waiting HPLC vial, leading to low HPLC traces and inconsistent tracking of reaction species. Conversely, employing a push volume which is to large is equally problematic producing reduced HPLC signal due to dilution. Thus, there exists an optimal “Goldilocks” push volume range which can deliver the entire reaction aliquot to the waiting vial without excessively diluting it, giving the highest response factor per sample, while being highly consistent between samples. For this system, 1.0 mL was determined to be the optimal dilution volume. The relatively short reaction time under the previously reported optimized conditions necessitated a condensed sampling sequence. Several adjustments were made to the system in order to reduce the time needed to complete a single sampling interval, which included shortening tubing (reducing the optimized push volume(s) required to prime, dispense, and rinse lines), as well as decreasing the time required to dry the lines (tubing) by increasing the pressure of nitrogen gas which could be passed through the system. This resulted in a substantive decrease of the sampling interval to just under 90 seconds, compared with the 176 seconds required previously. This nearly doubled the sampling frequency of the platform, and was better suited to increasing the number of samples which could be acquired in each interval of time. The reaction quench and resulting sample stability was tested by sampling a phase transfer reaction under the previously reported optimized conditions (Figure 62Error! Reference source not found.). In some systems, reactivity is not stopped once the sample is diluted, resulting in inaccurate sampling and necessitating specialized quenches which can fully arrest the reaction.35 As the phase transfer reaction operates under basic conditions, the need for 120 an acid-modified quench was investigated. To do so, a standard phase transfer reaction was quenched using the automated sampling platform with either unmodified methanol or methanol with a 1% acetic acid modifier (v/v). It was found that there was negligible conversion of 3.2 to 3.4 whether the aliquot had been quenched with or without the presence of acid modifier, even after 12 hours (Figure 60). Thus, it did appear that methanol itself was enough to both dilute and quench the reaction. However, to ensure a full arrest of the sampled reaction, all subsequent quenches contained the acid modifier as a precaution. Figure 60: HPLC aliquot sample stability in methanol (left) and in methanol with 1% acetic acid (v/v) (right). Validation of the heterogeneous and phase selective sampling was achieved by sampling a stirred solution of water and toluene, which contained both benzoic acid and benzyl alcohol, and monitoring their relative concentrations using HPLC. It was expected that the solubility of these species could be tracked using data acquired from the heterogeneous and toluene-selective sampling. The content of the unsampled aqueous phase can be deduced by subtraction of 0100200300400500600700Toluene 3.2 3.4Peak AreaTime (0 hour) Time (12 hour)0100200300400500600700Toluene 3.2 3.4Peak AreaTime (0 hour) Time (12 hour)121 material detected in the organic phase from that of the heterogeneous mixture. To demonstrate this approach, the phase preference of benzoic acid was monitored under basic and acidic conditions. Upon addition of base, benzoate formed and was observed to partition to the aqueous layer (Figure 61). The addition of acid regenerated benzoic acid, which was observed in the organic layer. In contrast, the benzyl alcohol concentration in the organic layer remained constant throughout the experiment, as expected (Figure 61). Heterogeneous sampling of both species displayed constant concentrations throughout. An average standard deviation of less than 2% was calculated for sampling, demonstrating good reproducibility. Figure 61. Sampling validation of heterogeneous and phase selective sampling using benzoic acid (left) and benzyl alcohol (right) in response to the addition of base and acid. 3.3 Initial Studies Initial studies focused on establishing a basic understanding of the reaction behaviour, including profile(s), time, and conversion. Efforts also centered on testing the robustness and reproducibility of both the sampling method and the reaction itself. These experiments laid the foundation for further in-depth analysis of the reaction in later studies. 00.20.40.60.81Initial NaOHAddition2nd NaOHAdditionAcOHAdditionPeak Area/Internal StandardBnOHHeterogeneous Sampling Organic Sampling00.10.20.30.40.5Initial NaOHAddition2nd NaOHAdditionAcOHAdditionPeak Area/Internal StandardBzOHHeterogeneous Sampling Organic Sampling122 3.3.1 The Issue of Reproducibility The first major challenge to address was the matter of robustness and reproducibility in both the sampling method and the reaction itself. At this stage, the automated sampling platform had displayed satisfactory levels of reproducibility in its sampling protocol, and as such, attention was directed towards addressing those same issues with the biphasic reaction itself. Figure 62: Early reproducibility issues. [3.2]o = 0.14 M in toluene, [NaOH]o = 0.3 N in water (1.1 equiv), [3.3]o = 6 μM (total reaction concentration). Attempts to repeat the experiment using the optimized conditions reported previously80 resulted in an array of reaction profiles. Running the reaction under the minimized catalyst loading of 0.003 equivalents (3 μM total reaction volume concentration) exhibited reaction profiles with varying degrees of product conversion. Initiating the reaction by adding either 00.10.20.30.40.50.60.70.80 50 100 150Normalized Peak AreaTime (min)00.10.20.30.40.50.60.70.80 50 100 150Normalized Peak AreaTime (min)123 hydroxide or catalyst as the final reagent had no improvement on the reproducibility; initiating the reaction with the spirocyclic precursor was not attempted, as these quaternized cinchona alkaloids are known to be unstable when exposed to strong base.91 Caution was taken during these experiments to ensure consistency in the sampling method itself across several reaction replicates; this included maintaining flow rates, stir rates, dilution volumes, and order of addition. It was found, however, that increasing the catalyst loading of 3.3 to 0.01 equivalents (9 μM total reaction volume concentration) could reliably reproduce near identical reaction profiles. While this did not satisfy the answer for why the reaction was irreproducible, it provided a system with the reproducibility necessary for further investigations, while also casting suspicion onto the catalyst as the likely culprit. 3.3.2 Control Experiments Several control experiments were examined to begin probing reaction behaviour. The first examined the role of each reagent (3.2, 3.3, and NaOH) and their impact on reaction progress. It was found that conversion of the spirocyclic precursor 3.2 to 3.4 did not occur in the presence of base without the doubly quaternized cinchona alkaloid 3.3. Meanwhile it proceeded exceedingly slow when in the presence of another phase transfer catalyst such as tetrabutylammonium bromide 3.7 and generated 3.4 as a racemic mixture (Figure 63). The use of chiral HPLC afforded insight into the enantioselectivity of the reaction, with formation of 3.4 proceeding at approximately 85% e.e. throughout the course of the reaction, as well as equal rates of consumption for the racemic starting material 3.2. 124 Figure 63. Phase transfer reaction in the absence of any catalyst (left): [3.2]o = 0.14 M in toluene, [NaOH]o = 0.3 N, 1.1 equiv. PTC using tetrabutylammonium bromide (right) [tetrabutylammonium bromide] = 0.018 M total reaction concentration. Several additional control experiments were carried out to investigate how the reagents affected reaction progress or rate. To do so, reactions were dosed with additional catalyst or hydroxide to test which, if either, would promote further conversion to 3.4. It was found that additional hydroxide had no effect on the system, while the addition of “fresh” catalyst spurred further conversion to the desired product (Figure 64). This result, in addition to reproducibility issues observed at the low 0.003 equivalents loadings strongly suggested catalyst deactivation or death occurs over the course of the reaction. These suspicions were confirmed when it was observed that exposing an aqueous solution of the 3.3 to sodium hydroxide caused a near instantaneous degradation of the catalyst as observed by HPLC. This is consistent with other systems that employ the doubly quaternized cinchona alkaloid motif, which also reported catalyst degradation upon prolonged exposure to a strong base.91 In these systems, the strong base induces a Hoffman elimination on the quinuclidine ring, removing the quaternary nature of the catalyst and, in many cases, deactivating it. The doubly quaternized cinchona alkaloid is expected to go through a similar mechanism, whereby four possible elimination products can be formed, as well as direct dealkylation of the catalyst under strong base. Investigations of the 00.10.20.30.40.50.60.70.80 10 20 30 40 50 60Peak Area 3.4 over Internal StandardTime (min)00.10.20.30.40.50.60.70.80 10 20 30 40 50 60Peak Area 3.4 over Internal StandardTime (min)125 catalyst in previous mass spectrometry studies and computations suggest that the Hoffman elimination product can even be created under electrospray ionization conditions, which is indeed observable as the singly charged m/z = 723 ion in addition to the m/z = 362 corresponding to the doubly quaternized catalyst (Scheme 9).92 Thus, it appeared that catalyst deactivation was likely connected to the irreproducibility observed under low catalyst loadings. Scheme 10. Possible decomposition pathways for the doubly quaternized cinchona alkaloid 00.10.20.30.40.50.60 20 40 60 80[3.4] Time (min)cat addition cat addition00.10.20.30.40.50.60 10 20 30 40 50[3.4] Time (min)NaOH additionNaOH addition126 Figure 64: Testing whether the reaction is base limited (top left) or catalyst limited (top right via dosing experiments. Using standard PTC conditions; addition of [3.3] = 1.8 mM and [NaOH] = 0.15 M (0.5 equiv) where listed. 3.3.3 Order of Additions In order to observe potential effects on reactivity and conversion, the order of reagent addition was systematically altered. The two main variations examined involved the addition of sodium hydroxide or catalyst 3.3 as the final reagent to stimulate the reaction. The addition of 3.2 as the last reagent was not attempted, as it was already known that the catalyst degraded in the presence of hydroxide. Results indicated no significant variation in conversion or reactivity when varying the order of additions. However, the combination of heterogeneous and phase selective sampling did reveal an interesting behaviour during these experiments. It was noted that reactions which began with catalyst 3.3 and starting material 3.2, only the latter was observed in the organic layer in the first few time points. However, once hydroxide was added to initiate the reaction, 3.3 was observed rapidly transitioning into the organic phase, before slowly decomposing. Further experimentation confirmed that the catalyst could only become detectable and, thus, soluble in the organic layer when in the presence of hydroxide. These experiments also affirmed that both 3.2 and 3.4 remained solubilized exclusively to the toluene only layer, while the catalyst could be observed transitioning between the two phases over the course of the reaction. In effect, the catalytic mode of the doubly quaternized cinchona alkaloid appeared to be shuttling base into the organic layer, where it then facilitated the reaction via an enantioselective spirocyclization. As a result, subsequent experiments focused almost exclusively on observation of the toluene layer via phase 127 selective sampling, in order to most adequately capture catalyst behaviour and product formation behaviour. 3.3.4 Stir-Rate and Mass Transfer The effect of stir-rate on reaction progress was investigated. In biphasic reactions, stir-rate is intrinsically tied to reaction rate, with mass-transfer between the immiscible phases being limiting under poorly mixed systems.83,93 As expected, there was a positive correlation between stir-speed and reaction rate (Figure 65). Increasing the stir-rate by 1.8 times from 950 rpm to 1700 rpm increased the initial reaction rate from 45 nM s-1 to 208 nM s-1, a nearly 5-fold improvement. This, along with the catalyst’s solubility into the organic phase, suggest that the reaction is likely mass-transfer limited under the investigated conditions, with 3.3 shuttling base into the organic layer where it then catalyzed the resulting spirocyclization. Figure 65. Plotting formation of product 3.4 over time in response to changing stir-rates. [3.2]o = 0.09 M in toluene, [NaOH]o = 0.3 N (1.1 equiv), [3.3]o = 18 μM. 00.010.020.030.040.050.060.070.080.090 10 20 30 40 50[3.4]Time (min)1700 rpm 950 rpm 300 rpm128 Studying the effects of stir-speed on the reaction’s profile also revealed additional information of the underlying kinetics of the system. For instance, in an ideal system, whereby the reaction is solely dependent on stir-rate, all three reactions should eventually generate the same amount of product albeit at different times. However, the plot suggests that this is not the case, with the slowest stir-speed of 300-rpm generating only a maximum of about 5 μM of product. Similarly, the 950-rpm trial generated approximately 0.1 M less of the spirocyclic product than the highest stir-rate. This is consistent with the previous observations surrounding catalyst decomposition, whereby the productive formation of 3.4 is competing against the unproductive degradation of 3.3 This suggests that the observed rate, kobs, is the net result of several other rates including that of mass transfer, ktransfer, catalyst decomposition, kdecomp, and the product forward reaction krxn at minimum. Thus, any attempt to optimize the system is a careful balancing act of trying to maximize ktransfer and krxn, while trying to minimize kdecomp. This network of interconnected rates is likely a large reason why the rational optimization of the cinchona alkaloid phase transfer catalysts is such a challenge. Any modification to the catalyst will not only affect how it interacts with substrate, but also how efficiently it can solubilize into the organic layer and how resistant it is to degradation. A phase selective monitoring system should, in theory, provide insights on these various competing facets in a straightforward manner. Thus, the correct monitoring system should be able to gather insight into these various facets. 3.3.5 Solubility Solubility measurements were carried out in order to further validate the partition of the reaction components across the two phases (Figure 78Error! Reference source not found.). 129 Results confirmed that 3.2 was insoluble in water, further supporting the notion that it remained fully partitioned into the organic phase throughout the course of the reaction. Indeed, the solubility of 3.2 very likely exceeded that of 100 mg/mL, as that was the maximum upper range examined for solubility measurements due to starting material availability. Conversely, it was observed that the catalyst 3.3 was not detectable in toluene in its native form, further confirming the phase transition behaviour observed via heterogeneous and phase selective sampling previously. The solubility of hydroxide was obtained from existing literature, which lists its solubility in highly polar solvents such as water, ethanol, methanol, and glycerol94. Similarly, the solubility of 3.4 was not examined due to no observable difference in mass balance between heterogeneous and phase selective sampling, suggesting that it too partitioned exclusively into the organic phase throughout the course of the reaction. Figure 66. Examining catalyst solubility into the organic phase via heterogeneous and phase selective sampling. [3.3]o = 18 mM, [NaOH] = 0.3 N (50 equiv) 00.20.40.60.811.20 5 10 15 20 25 30[3.3] Normalized Peak AreaTime (min)Heterogeneous SamplingOrganic Phase Selective Sampling130 As it was observed that the entirety of the catalyst transitioned into the organic phase upon addition of base (Figure 66), and that both the precursor 3.2 and product 3.4 were solubilized within the organic layer, phase selective sampling was conducted henceforth to continue investigating reaction behaviour. 3.4 Reaction Progress Kinetic Analysis (RPKA) and Variable Time Normalization Analysis (VTNA) Studies Similar to work undertaken for the proline-catalyzed aldol reaction discussed in Chapter 2, the principles of reaction progress kinetic analysis were applied towards the spirocyclization reaction to begin probing the reaction’s mechanism. 3.4.1 Same Excess Same excess experiments were conducted to probe the robustness of the experiment, as well as to begin probing catalyst behaviour. To do so, the concentration of catalyst 3.3 was held constant across a series, while the concentration of both the spirocyclic precursor 3.2 and sodium hydroxide were increased by identical amounts. In this way, the profile of a reaction which operated at a lower loading of starting material can be overlaid with one which began at a comparatively higher loading when an appropriate time shift is applied. For the series studied (Figure 67), it was found that systems with relatively low starting material loadings in 3.2 and NaOH did not exhibit significant deviations in their reaction profiles once both had reached approximately 0.09 M in both starting materials. However, exaggerating the relative starting material loading caused a different reaction profile to be observed which did not overlay with those of the previous reaction series at 0.09 M of starting material. This decrease in the rate of 131 product formation at this point in the reaction is strongly indicative of catalyst deactivation. This is consistent with previous observations for catalyst degradation once exposed to hydroxide. It was further noted that initial rates of product formation were consistent across all reaction series, and only appeared to taper off after approximately 15 minutes of reaction time. Figure 67: Same excess plots with time shifts for Series B and C; Series A - [3.2]o = [NaOH]o = 0.25 M; Series B - [3.2]o = [NaOH]o = 0.15 M; Series C - [3.2]o = [NaOH]o = 0.09 M. [3.3] = 1.8 mM for all series. 3.4.2 Different Excess Further experiments were conducted to focus on the impact of individual reagents on reaction progress. To do so, the starting concentration of each reagent was systematically altered to observe its effect (Figure 68). It was found that varying the initial concentration of both the spirocyclic precursor 3.2 and NaOH had no impact on the reaction’s behaviour. Under both instances, the rate of product formation was identical, as were the profiles generated for the consumption of starting material. This suggested both exhibit zero-order behaviour on the 00.050.10.150.20.250 5 10 15 20 25 30 35[2]Time (min)Series A Series B Series C132 reaction. These reactions laid the groundwork for the use of variable time normalization analysis, which could be used to formally assign reaction orders to the respective reaction components. Figure 68: Different excess reaction progress curves. Series A - [NaOH]o = 0.15 M; Series B - [3.2]o = 0.15 M. [3.3] = 1.8 mM for all series. 3.4.3 VTNA Variable time normalization analysis was applied to the data acquired for reaction profile kinetic analysis. This enabled the normalization of the time-domain for each reaction, followed by subsequent comparison across similar reaction sets as a function of potential order. The results confirmed the reaction to be zero order in both 3.2 and NaOH, while it was found to be first order in catalyst 3.3 (Figure 69). However, it was observed in previous experiments using relatively higher starting material loadings that the reaction deviated from its first order behaviour in catalyst as the reaction progressed. This, coupled with the observations of 00.050.10.150 5 10 15 20[3.2]Time (min)[NaOH] = 0.09 M[NaOH] = 0.15 M00.050.10.150 5 10 15 20[3.2]Time (min)[2] = 0.09 M[2] = 0.15 M133 catalyst decomposition in the presence of hydroxide, led to the understanding that deviation from the expected reaction profile during extended reactions was due to the reduced concentration of active catalyst. These conditions, which utilized a relative catalyst loading of approximately 0.7%, are more reflective of the 0.3% catalyst loadings originally reported under the optimized conditions80. These conditions, which demand nearly 6-fold improved catalyst turnover number to reach full conversion rather than the 50 observed in these present studies, would be far more susceptible to any perturbations which resulted in increased levels of catalyst deactivation. Such perturbations or variability could easily be encountered in a biphasic or heterogeneous reaction environment, whereby the rate of catalyst degradation may outpace the rate of product formation; for instance, inefficient mixing or low stir-speeds was observed previously to result in less product formation, presumably due to catalyst degradation. Lowering the concentration of available catalyst not only demands a higher turnover number but makes the system far more susceptible to any fluctuations in the rate of catalyst degradation. This may have served as a major source of the irreproducibility observed under the low catalyst loadings reported. With catalyst identified as the primary driving force of the reaction, and with deactivation proposed as its main limitations, work began on studying catalyst behaviour. 134 00.010.020.030.040.050.060.070.080.090 5 10 15[3.4] (M)∑[3.2]0Δt [2] = 0.09 M[2] = 0.09 M[2] = 0.09 M[2] = 0.15 M[2] = 0.15 M[2] = 0.15 M00.020.040.060.080.10.120.140.160 5 10 15[3.4] (M)∑[NaOH]0Δt [NaOH] = 0.09 M[NaOH] = 0.09 M[NaOH] = 0.09 M[NaOH] = 0.15 M[NaOH] = 0.15 m135 Figure 69. Plots generated using variable time normalization analysis for 3.2 (top), NaOH (middle) and 3.3 (bottom). [3.2]o = 0.15 M, [NaOH]o = 0.15 M, [3.3]o = 18 mM unless otherwise stated. 3.5 Catalyst Behaviour Investigations into catalyst deactivation were carried out following the insight provided by previous kinetic analysis. It was observed that the doubly quaternized catalyst 3.3 began to decompose in the presence of hydroxide into a single major product as observable by HPLC (Figure 84). The use of tandem mass spectrometry identified the major decomposition species as possessing a m/z of 723, corresponding to a Hoffman elimination product. The catalyst 3.3 itself displays a mixture of m/z signals corresponding to an m/z of 2 (362) and 1 (723), with the latter signal likely due to Hoffman-type eliminations occurring during ionization of the molecule prior to entering the mass spectrometer92, which causes the doubly cationic species to become singly cationic (Scheme 11). However, the Hoffman elimination product can also appear as a doubly cationic species with m/z of 362 due to protonation of the piperidine fragment under acid HPLC conditions. 00.020.040.060.080.10.120.140.160 1 2 3[3.4] (M)∑[3.3]1Δt (1) = 0.0032 M(1) = 0.0018 M(1) = 0.0018 M(1) = 0.0018 M136 Scheme 11. Proposed decomposition pathway for 3.3 based on HPLC-MS, deuterium labelling studies, and NMR Isolation of this degradation byproduct proved non-trivial; separation by trituration, distillation, or column chromatography proved unfruitful due to the highly polar nature of the byproducts, or due to possessing a near identical retention factor to the bulk catalyst across a range of conditions. However, a combination of HPLC-MS, deuterium incorporation, and NMR studies allowed for a byproduct to be proposed. Degradation of the catalyst in the presence of deuterium oxide and sodium deuteroxide revealed the incorporation of two deuterium atoms into a product which displayed a native m/z of 723 (shifted to 725 in deuterium), which corresponded to the mass of the expected Hoffman elimination products. The incorporation of two deuterium atoms suggested that the product possessed some enol-character, which could be made possible from the Hoffman elimination product (3.8). 13C NMR studies confirmed a new carbonyl at 220 ppm, along with the loss of the geminal proton the hydroxyl group. Subsequent 2-D NMR, namely HSQC, HMBC, and COSY confirmed the overall connectivity of the molecule had remained intact, leading to the proposal of (3.8) as the major product of catalyst decomposition. 137 Catalyst decomposition was investigated by 1H NMR in order to potentially monitor and elucidate the mechanism by which it occurred. To do so, solutions of the doubly quaternized cinchona alkaloid dissolved in D2O was exposed to a solution of NaOD in D2O and then monitored in a 400 MHz Bruker spectrometer. Attempts to monitor the reaction via this approach proved highly irreproducible. The addition of hydroxide caused the catalyst to precipitate out of solution almost immediately. Furthermore, the insolubility of the catalyst and its decomposition product(s) in D2O produced a solution with a thick, gel like consistency which caused compounding shimming errors throughout the course of the experiments. Despite these difficulties, a select few profiles can illustrate how quickly, relatively speaking, the catalyst both decomposes and transitions out of the aqueous environment even in the presence of stoichiometric hydroxide. It was observed through both 1H NMR and phase selective sampling that the rate of catalyst transition into the organic phase appeared to be second order overall, with a rate constant of approximately 4 mM-1s-1. This suggests that the rapid transition into the organic phase observed under standard phase transfer reaction conditions is due to the extreme excess of hydroxide. Similarly, the rate of decomposition appeared first order under standard phase transfer reaction conditions, with an approximate rate constant of 1 x 10-4 s-1. Thus, the rate of catalyst solubilization into the organic phase is considerably faster than the rate of its degradation with a first-order dependence on catalyst under standard reaction conditions. 138 Figure 70: 1H NMR trace of catalyst transition (left) using [3.3]o = [NaOD]o = 28 mM. Organic phase selective sampling of catalyst transition under standard biphasic conditions using [3.3]o = 0.0018 M, [NaOH] = 0.3 N (50 equivalents). The phase-transition behaviour of the catalyst was probed further to elucidate its mechanism. It was known that the singly quaternized cinchona alkaloid 3.9 (Scheme 12) was not catalytically active, and so its behaviour was investigated for comparison against the active doubly quaternized species. It was observed that 3.9 remained insoluble in toluene even in the presence of hydroxide. Additionally, the catalyst appeared stable to base, with minimal degradation observed over two hours, far longer than the lifetime observed for the doubly quaternized species 3.3. This insolubility potentially explains the inactivity of the singly quaternized material, whereby it is unable to mediate the spirocyclization if it cannot transition into the organic phase where the reaction takes place. This result is also consistent with computational analysis for the stereoselectivity of the reaction, whereby it has been proposed that a doubly cationic catalyst is essential for interactions with a bromide counterion, which helps to stabilize one of the transition states of the spirocyclization.82 0510152025300 500 1000 1500 2000[3.3] (mM)Time (sec)00.00020.00040.00060.00080.0010.00120.00140 5 10 15 20[3.3] (M)Time (min)139 Scheme 12. Singly quaternized and doubly quaternized cinchona alkaloid phase transfer catalysts. The specificity of the base needed to induce the phase transition behaviour was also briefly explored. Phosphate in particular has been reported in a phase transfer reaction also catalyzed by a doubly quaternized cinchona alkaloid, albeit with different alkylating groups.95 Indeed, it was observed that phosphate could induce the same phase transition behaviour in the doubly quaternized species 3.3. However, hydroxide was over six times more effective than phosphate at inducing the phase transition behaviour based on the maximum concentration of catalyst observed in the organic phase. Similarly, phosphate was also observed to degrade the catalyst to the same Hoffman elimination product 3.8 observed in other bases such as hydroxide and triethylamine. The role of base, the mechanism of phase transition and its relationship to catalyst structure will be studied in greater detail in future studies. 140 Figure 71. Phase selective sampling of catalyst phase transition behaviour. [3.3]o = 0.0018 M, [base] = 0.3 M (50 equivalents) as listed. 3.5.1 Temperature Dependence The final investigation conducted on the system focused on examining the impact of temperature on the reaction profile. Given the different rates for catalyst solubilization, ktransfer, the rate of catalyst degradation, kdecomp, and the rate of spirocyclization, krxn, it was hypothesized that operating at lower temperatures may be able to slow the rate of catalyst degradation more than the rate of product formation depending on the temperature dependence of the respective reactions. If true, then there exists the possibility to optimize the reaction in order to improve the catalyst turnover number by reducing the rate of catalyst decomposition relative to the rate of product formation, provided that the rates are sufficiently differentiable. In effect, operating at a lower temperature might slow the rate of catalyst decomposition, mimicking a slow addition protocol, more than the rate of productive spirocyclization, thus allowing for higher catalyst turnover. 00.00020.00040.00060.00080.0010.00120.00140 5 10 15 20 25 30[3.3] (M)Time (min)[1] in 0.3 M NaOH[1] in 0.3 M K PO141 As anticipated, the rate of both catalyst degradation and spirocyclization proceeded much slower at -5 oC than at room temperature, requiring nearly 2 hours for completion. However, both reactions afforded the spirocyclic product 3.3 in approximately 82% yield, and a corresponding catalyst turnover number of 50 that suggested no improvement in efficiency. It was observed that the lower temperature decreased not only the rates, but the solubility of the catalyst in the organic phase. This highlights the complexity and potentially underscores the challenge in rational optimization of these phase transfer catalyzed reactions. Altering any parameter, whether temperature or catalyst structure, inevitably affects multiple rates simultaneously. In the case of temperature, a lower temperature appears to affect not only the rate of catalyst decomposition, but also the rate of product formation, and both the rate of solubilization and maximum solubility of the catalyst in the organic phase. However, the insight afforded by the monitoring methodology discussed herein may be able to help direct these efforts, by allowing direct insight into these rates and solubilities as the system is optimized. 142 Figure 72. Reaction profiles at high and low temperatures. [3.2]o = 0.09 M (in toluene), [NaOH]o = 0.3 N (1.1 equiv), [3.3]o = 18 mM 00.010.020.030.040.050.060.070.080.090.10 20 40 60 80 100 120Concentration (M)Time (min)[3] at -5 C [2] at -5 C [3] at 22 C [2] at 22 Co o o o00.00020.00040.00060.00080.0010.00120.00140 20 40 60 80 100 120[3.3]Time (min)-5 C 25 Co o143 3.5.2 Conclusions The development of an automated sampling methodology for the study of biphasic systems allowed for detailed study into a phase transfer reaction catalyzed by a doubly quaternized cinchona alkaloid. The combination of heterogeneous (organic and aqueous phases) and phase selective sampling (organic layer only) allowed for insight into various reaction phenomena including product formation, solubilization of the catalyst, mass transfer behaviour, and catalyst degradation. For this reaction, a rate law was determined which was found to be first order in catalyst, and zero order in starting materials, with mass transfer being a limiting step in the formation of product. Subsequent reaction profiling revealed catalyst degradation as the primary source of poor turnover and irreproducibility at low catalyst loadings, with the primary product of this degradation identified as the Hoffman elimination product caused by reaction of the catalyst with strong base. While base caused catalyst degradation, it also was responsible for inducing a phase transition behaviour in the catalyst to the organic phase where it could mediate the spirocyclization. Attempts to optimize the reaction must take into account the various rates and equilibria, including the rate of product formation, mass transfer, and catalyst degradation, as well as the solubility of the catalyst which will likely be affected by any change to the catalyst itself. These rates and equilibria can be observed using the automated reaction monitoring method described herein. 3.6 Experimental 3.6.1 General Notes Spirocyclic precursor and doubly quaternized cinchona alkaloid used for initial studies graciously provided by Dr. Rebecca Ruck and Merck. All subsequent kinetic studies utilized 144 synthesized catalyst, with precursors purchased from Sigma Aldrich and used without further modification/purification. Reactions used distilled water which had been degassed by bubbling nitrogen through the solvent for 120 minutes with intermittent sonication. Toluene used was degassed using an MBraun Solvent Purification System (SPS) and dispensed as needed for each reaction. All HPLC-MS analysis was carried out on an Agilent HPLC 1200 system with the following configuration: Agilent G1379B degasser, G1312A binary pump, G1316A thermal column compartment, G1315 DAD, and a 6120 single quad mass spectrometer. Analytical settings for the detectors are: DAD – 200-400 nm collected at 20 Hz storing all spectra for offline analysis. ESI-MSD – positive mode scan for m/Z 110–1500 running at 0.8sec/cycle. drying gas = 7.0 l/min, nebulizer pressure = 20 psi, gas temperature = 300 °C, capillary voltage = 4000 VHPLC column. General HPLC conditions were as follows: Column: InfinityLab Poroshell 120 2.7 μm SB-C18 column (2.1 mm x 50 mm); Temperature (column): ambient; Flow rate: 0.500 mL/min; Detection: 210 and 254 nm DAD; Mobile Phase A: 0.05% formic acid in water; Mobile Phase B: acetonitrile; Starting conditions 90% A, 10% B; 0.0-0.10 min linear gradient to 80%, 20% B; 0.10-2.30 min linear gradient to 0% A, 100% B; 2.30-3.00 min hold at 0% A, 100% B. Run Time: 3.00 min; Post Time: 1.00 min. Retention 145 Times: doubly quaternized cinchona alkaloid 3.3 (0.874 min); benzene (1.25 min); toluene (1.54 min); spirocyclic product 3.4 (1.78 min); spirocyclic precursor 3.2 (2.01 min). Chiral HPLC-MS Conditions were as follows: Column: CHIRALPAK IC-3 3μm (4.6 mm x 100 mm); Temperature (column): ambient; Flow rate: 0.500 mL/min; Detection: 210 and 254 nm DAD; Mobile Phase A: 0.05% formic acid in water; Mobile Phase B: acetonitrile; Starting conditions 30% A, 70% B; 0.00-1.00 min linear gradient to 20% A, 80% B; 1.00-3.00 min hold at 20% A, 80% B. Run Time: 3.00 min; Post Time: 1.00 min. Retention Time: spirocyclic precursor enantiomer (2.110); spirocyclic product minor enantiomer (2.396); spirocyclic enantiomer (2.467); spirocyclic product major enantiomer (2.621). All 1H and 13C NMR spectra were recorded on a Bruker AV III HD 400 MHz spectrometer equipped with a Bruker BBFO smart probe with ATMA using Topspin 3.2 on CentOS 5. Collected spectra were processed using MestreNova 12.0. For 1H NMR, chemical shifts are reported relative to residual protiated solvent peaks (δ7.27, 1.56 and 2.50 ppm for CDCl3, D2O, and (CD3)2SO respectively). 13C NMR spectra were measured at either 125 MHz or 100 MHz on the same instrument noted above for recording 1H NMR spectra. Chemical shifts were again reported in accordance to residual protiated solvent peaks (δ 77.23 and 39.51ppm for CDCl3 and (CD3)2SO respectively). 146 3.6.2 Procedures 3.6.2.1 Biphasic Reaction Sampling The following details the general instrumentation, assembly, and usage of the automated sampling platform for the study of biphasic reaction sampling. 3.6.2.2 Instrumentation Design and Setup The instrumentation was selected and configured similar to the assembly used in other reaction monitoring projects35,1,3. The platform is centered around a Gilson 215 Liquid Handler which manages the final dilution and dispensing of reaction samples into waiting HPLC vials. All samples were quenched and diluted using 1% acetic acid in methanol (v/v). The base platform was also fitted with a 6-port distribution valve to select for either the quench, as aforementioned, or for a nitrogen line which was used to forcibly evacuate the contents of the sampler’s plumbing lines and dry them before the next sampling instance. Heterogeneous sampling configuration: To monitor both phases, a Mettler Toledo EasySampler probe was attached in-line between the 6-port distribution valve and the dispensing needle of the Gilson 215 Liquid Handler. A sampling sequence begins with the triggering of the EasySampler probe, which then extends into solution to fill its sample scoop. While this occurs, a quench solution of MeOH (1% AcOH) primes the sampling lines. When triggered a second time, the EasySampler scoop is reintroduced to the sampling line flow path, quenched by the MeOH solution as it is flushed out to a waiting HPLC vial A flush is then performed to clean the lines of any residual material using the MeOH quench solution. The 6-port distribution valve then switches to allow the pressurized nitrogen line to evacuate residual solvent and dry out the sampling line. 147 Figure 73. Heterogeneous sampling configuration with nitrogen line (A), quench solution (B), Gilson 215 Liquid Handler with added selection valve (C) EasySampler set up (D). Configuring the liquid handler for phase-selective sampling, involved removing the EasySampler and installing an Ismatec Piston pump and 6-port, 2-position valve fitted with a 20 μL sample loop in its place. The new valve (6-port, 2-position) is installed between the dispensing pump and dispensing head of the Gilson 215 liquid handler, along with the tubing needed to create a discreet dispensing loop, sample loop, and circulation loop. The circulation loop is connected into the reaction vial, with the intake fitted with a PTFE (0.2 μm) HPLC filter. When in operation, reaction solution is continually circulated through the circulation loop under the power of an Ismatec Piston Pump, with the HPLC filter providing selective withdrawal of the toluene (organic) reaction layer. When triggered, the 6-port, 2-position valve actuates to align the sample loop with the reaction circulation loop, thus filling the sample loop with an aliquot of the organic reaction layer. The Gilson215 simultaneously primes the dispensing loop with the MeOH (1% AcOH) quench solution. When actuated again, the sample loop of the 6-port, 2-B C DA`148 position to become aligned with the dispensing loop. At this time, the Gilson215 then quenches the reaction aliquot and dispenses it into a waiting HPLC vial. Once complete, a flush of quench solution, after which the 6-port distribution valve then aligns to allow the pressurized nitrogen line to blow out any residual solvent in the tubing, and to dry it before the next sampling event. Figure 74. Organic phase selective sampling configuration with quench solution (A), Gilson 215 (B), 6-port, 2-position valve (C), Ismatec Piston Pump (D) and reactor assembly (E). Nitrogen line and additional 6-port, 1-position valve not pictured. In both systems, priming, dispensing, and flushing volumes all varied according to need. In general, a prime volume of 1.0 mL, dispense volume of 1.5 mL, and a flush volume of 1.5 mL were utilized for both systems. Gilson’s Trilution software was used to control all pieces of sampling apparatuses as well as to program all sampling protocols. A B C D E149 3.6.2.3 General Procedure for the Phase Transfer Catalyzed Reaction To a vial was added a toluene solution containing 6% benzene (v/v, 5 mL total volume) along with the spirocyclic precursor 3.2 (248 mg, 0.67 mmol), catalyst 3.3 (12.5 mg, 14.1 μmol), and deionized water (1.94 mL). The vial was sealed and vigorously stirred using the miniaturized reactor assembly, and the reaction solution circulated and sampled by the automated sampling platform to acquire a starting point for the reaction (taken in triplicate). To this was then added 1.2 N NaOH (0.56 mL, 0.67 mmol), and the reaction sampled every 60 seconds for the course of approximately 48 minutes. Upon completion, the organic layer was separated, washed with brine, and then concentrated under vacuum to yield a viscous yellow-brown oil. The crude sample was then purified via flash column chromatography (solid phase: silica, mobile phase: 90:10 PET Ether:EtOAc, visualization: UV) to yield 3.4 as a yellow solid. 3.6.2.4 Using tetrabutylammonium bromide as catalyst To a vial was added a toluene solution containing 6% benzene (v/v, 5 mL total volume) was added to a vial, along with the spirocyclic precursor 3.2 (248 mg, 0.67 mmol), tetra-n-butylammonium bromide (4.31 mg, 14.0 μmol), and deionized water (1.94 mL). The vial was sealed and vigorously stirred using the miniaturized reactor assembly, and the reaction solution circulated and sampled by the automated sampling platform to acquire a starting point for the reaction (taken in triplicate). To this was then added 1.2 N NaOH (0.56 mL, 0.67 mmol), and the reaction sampled every 60 seconds for the course of approximately 48 minutes. Upon 150 completion, the organic layer was separated, washed with brine, and then concentrated under vacuum to yield a viscous yellow/brown oil. Figure 75. Time-course plot for the reaction using tetrabutylammonium bromide in place of 3.3. 3.6.2.5 Synthesis of the Singly Quaternized Cinchona Alkaloid Catalyst To an oven dried flask was added quinidine (200 mg, 1 Eq, 616 µmol) and 1-bromo-2-(bromomethyl)-4-methoxybenzene (173 mg, 1 Eq, 616 µmol). The flask was then placed under nitrogen, charged with 2-propanol (2.0 mL) and then degassed. The reaction mixture was maintained at 70 °C until completion (approximately 3 hours). The crude mixture was reduced under vacuum (0.5 mL), and then diluted with EtOAc (20 mL) and stirred for an hour. The resulting was filtered, rinsed with cold IPA/hexanes (1:1, 2 mL) and then dried overnight to yield an off-white powder (84% yield). Based on the procedure outlined by Xiang et al80. 024681012140 10 20 30 40 50 60Peak Area 1 Over Internal StandardTime (min)151 3.6.2.6 Synthesis of the Doubly Quaternized Cinchona Alkaloid Catalyst A slurry of (S)-(6-methoxyquinolin-4-yl)((1S,2R,4S,5R)-5-vinylquinuclidin-2-yl)methanol (2.000 g, 1 Eq, 6.165 mmol) and 1-bromo-2-(bromomethyl)-4-methoxybenzene (4.315 g, 2.5 Eq, 15.41 mmol) in 2-propanol (1.0 mL) and DMF (7.0 mL) was placed under nitrogen atmosphere and degassed . The slurry was then heated to 70oC and stirred vigorously for five hours until clear. The solution was then cooled to ambient temperature (approximately 22 oC), and EtOAc was added (80 mL) over 20 minutes with vigorous stirring. The resulting slurry was then stirred for an additional two hours, after which the precipitate was then filtered, rinsed with EtOAc (2 x 6 mL), hexanes (2 x 6 mL) and then dried under vacuum overnight to yield a yellow precipitate (80% yield). Based on the procedure outlined by Xiang et al80. 3.6.2.7 Validation of the Sampling Methodology using Benzoic Acid and Benzyl Alcohol To a vial containing toluene (5 mL) and water (5 mL) was added benzoic acid (0.12 g, 1.0 mmol) and benzyl alcohol (0.11 g, 1.0 mmol). The sample was stirred vigorously and sampled using both the heterogeneous and organic phase-selective sampling methods (each point in triplicate). To this was made three additions; the first used NaOH (0.5 mL of a 0.6 N solution), followed by another addition of NaOH (1.0 mL of a 0.6 N solution), and finishing with AcOH (1.0 mL, 90% in water). Triplicate measurements using both the heterogeneous and organic phase selective sampling were performed after each addition. The vials were then submitted for 152 HPLC analysis, with corrections made to raw peak areas to account for dilutions during the additions. 3.6.2.8 Determination of Solubility via Gravimetric Analysis A solution of 3.3 in toluene was prepared until the reagent was no longer soluble (present as precipitate in solution). The solution was then heated and/cooled to the target temperature (5 oC and 22 oC). A 0.5 mL aliquot was withdrawn using a syringe fitted with a 0.2 μm PTFE filter and dispensed into a pre-weighed vial. The solution was allowed to evaporate in air, and the vial reweighed until a consistent mass was obtained. This procedure was repeated to determine the solubility of 3.3 in water, as well as 3.2 in toluene, 3.2 in water at the target temperatures of 5 oC and 22 oC (Figure 78). 3.6.2.9 Catalyst Decomposition Studies The following details the general procedure and reaction conditions for the study of catalyst decomposition studies. 3.6.2.10 Monitoring via Selective Phase Sampling To a vial was added catalyst (25.0 mg, 28.5 μmol), water (2.05 mL), and toluene (5 mL, 6% benzene internal standard). The reaction vial was sealed using the Technobis vial assembly, and attached to the circulation loop of the automated sampling platform as outlined previously Error! Reference source not found.. The reaction was sampled in triplicate to obtain an initial time point. To the reaction vial was then added 1.2 N NaOH (0.45 mL, 280.5 μmol), and the reaction sampled every 60 seconds over the course of approximately one hour. 153 Figure 76. Technobis reactor assembly schematic (left) highlighting inlet and outlets for circulation loop, as well as PTFE filter. Final setup with overhead stirrer fitted with neodymium magnet (right). 3.6.2.11 Monitoring via Heterogeneous Sampling To a vial was added catalyst (25.0 mg, 28.5 μmol), water (2.05 mL), and toluene (5 mL, 6% benzene internal standard). The reaction vial was sealed with a septum cap, fitted with the Mettler Toledo EasySampler probe, and attached to the circulation loop of the automated sampling platform as outlined in Section 3.6.2.3. The reaction was sampled in triplicate to obtain an initial time point. To the reaction vial was then added 1.2 N NaOH (0.45 mL, 280.5 μmol), and the reaction was sampled every 60 seconds over the course of approximately one hour. 154 3.6.2.12 Monitoring via 1H NMR Attempts to gain insight by NMR into the structure of the catalyst degradation product(s) using D2O and NaOD resulted in the immediate precipitation of the catalyst. Subsequent trials attempted to recreate the decomposition under homogeneous conditions using CDCl3 and an organic base (triethylamine). The resulting product from this homogeneous method was identical to the one produced under standard phase transfer reaction conditions based on HPLC-MS co-injection and mass fragmentation. To an NMR tube was added 0.8 mL of a solution of the doubly quaternized cinchona alkaloid catalyst dissolved in 50 mM CDCl3 (44 mg, 50 μmol,). To this was added triethylamine (7 μL, 50 μmol) and the resulting solution monitored by 1H NMR. Upon completion, the resulting solution was analyzed via NMR. Figure 77. Time course 1H NMR data for the catalyst 3.3 in triethylamine. [3.3]o = 50 mM, [Et3N]o = 50 mM. 155 3.6.3 Additional Experiments Figure 78. Solubility measurements for catalyst 3.3 and starting material 3.2 determined gravimetrically. Figure 79. Standard phase transfer reaction in the absence of catalyst 3.3. [3.2]o = 0.14 M, [NaOH]o = 0.3 N, 1.1 equivalent 0204060801001202.3 2.2bSolubility (mg/mL)Water 5C Toluene 5C Water 22C Toluene 22C00.10.20.30.40.50.60.70.80 10 20 30 40 50 60Peak Area 3.4 over Internal StandardTime (min)156 Figure 80. HPLC peak area traces of starting material 3.2 enantiomers and product 3.4 enantiomers under standard phase transfer reaction conditions Figure 81. Chiral-HPLC traces at final time point (t=66) under standard phase transfer reaction conditions depicting the remaining starting material 3.2 (rt = 2.130, 2.485 min) and product 3.4 (2.130, 2.625 min) in 0% and 84% e.e respectively. Also pictured toluene (rt = 1.153 min) and benzene (rt = 1.089 min). 02004006008001000120014000 20 40 60Peak AreaTime (min)SM Enantiomer 1 Prod MinorSM Enantiomer 2 Prod Major157 Figure 82. Catalyst dosing experiment under standard phase transfer reaction conditions. Using 1.8 μM (total reaction concentration) for each catalyst addition Figure 83. Hydroxide dosing experiment under standard phase transfer reaction conditions. Using 0.3 N (0.5 equivalents) hydroxide per addition 00.10.20.30.40.50.60.70.80.910 20 40 60 80[3]Time (min)cat addition cat addition00.10.20.30.40.50.60.70.80.910 10 20 30 40 50[3]Time (min)NaOH additionNaOH addition158 Figure 84. Organic phase monitoring of catalyst 3.3 in the presence of hydroxide and phosphate. [3.3]o = 18 μM (total reaction concentration). Addition of base designated by orange bar at t=3 min. 00.00020.00040.00060.00080.0010.00120.00140 5 10 15 20 25 30[3.3] (M)Time (min)[1] in 0.3 M NaOH[1] in 0.3 M K PO159 Figure 85. Tracing concentration of the singly quaternized cinchona alkaloid (3.3) after exposure to hydroxide after 2 hours in the organic layer (top) and in the aqueous layer (bottom). Catalyst was never observed in the organic layer. 3.6.4 Kinetic Studies 3.6.5 General Procedure for Kinetic Studies All kinetic runs for application of RPKA and VTNA methodology utilized selective sampling of the organic (toluene) layer and followed the following general procedure. For Series 1; to a vial was added a toluene solution containing 6% benzene by volume (5 mL) was added to a vial, along with the spirocyclic precursor (248 mg, 0.67 mmol), catalyst (12.5 mg, 14.1 μmol), and deionized water (1.94 mL). The vial was sealed and vigorously stirred using the miniaturized reactor assembly, and the reaction solution circulated and sampled by the automated sampling platform to acquire a starting point for the reaction (taken in triplicate). To this was then added 1.2 N NaOH (0.56 mL, 0.67 mmol), and the reaction sampled every 60 seconds for the course of approximately 48 minutes. Upon completion, the organic layer was separated, washed with 160 brine, and then concentrated under vacuum. The crude sample was combined with that of other trials, and then purified using flash chromatography (silica stationary phase, 90:10 PET Ether:EtOAc mobile phase, UV visualization). Each kinetic series was performed in triplicate, except for Series 5 and 6. 3.6.6 Reaction Progress Kinetic Analysis (RPKA) A series of experiments were conducted utilizing the principles of reaction progress kinetic analysis, with replicates for each reaction series shown where relevant (Table 11)62. Table 11: Summary of conditions and concentrations used for RPKA and VTNA reaction concentrations and reagent amounts used. † NaOH volumes based on a 1.2 N stock solution. 3.6.6.1 Same Excess Concentration (M) Reagent Amounts3.2 NaOH 3.3 3.2 (mg) NaOH† (mL) 3.3 (mg)Series 1 0.09 0.09 0.0018 248 0.56 12.5Series 2 0.15 0.15 0.0018 412 0.94 12.5Series 3 0.15 0.09 0.0018 412 0.56 12.5Series 4 0.09 0.09 0.0032 248 0.56 25Series 5 0.15 0.15 0.0032 412 0.64 25Series 6 0.25 0.25 0.0018 686 1.024 12.53.2 (M) NaOH (M) 3.3 (M)Series A 0.25 0.25 0.0018Series B 0.15 0.15 0.0018Series C 0.09 0.09 0.0018161 Figure 86. Same excess plot with time correction for series B and C. ● = replicate 1 ■ = replicate 2▲= replicate 3. Reactions series based on colour as outlined in the above table 3.6.6.2 Different Excess – Spirocyclic precursor (2) Figure 87. Different excess plot with time correction for series C. ● = replicate 1 ■ = replicate 2▲= replicate 3. Reactions series based on colour as outlined in the above table 00.050.10.150.20.250 5 10 15 20 25 30 35[2]Time (min)Series A Series B Series C3.2 (M) NaOH (M) 3.4 (M)Series D 0.15 0.09 0.0018Series C 0.09 0.09 0.001800.020.040.060.080.10.120.140.160 5 10 15 20[3.2]Time (min)y = -12.0121x +0.2495 R2 = 0.9881 162 3.6.6.3 Different Excess - NaOH Figure 88. Different excess plot. ● = replicate 1 ■ = replicate 2▲= replicate 3. Reactions series based on colour as outlined in the above table 3.6.7 Variable Time Normalization Analysis (VTNA) Variable time normalization analysis was applied on the reaction series acquired for reaction progress kinetic analysis studies. To carry out the analysis, two main assumptions were made. Firstly, that the consumption of the spirocyclic starting material 3.2 had a 1:1 proportionality to formation of the spirocyclic product 3.4. Essentially, it was assumed that if 0.01 M of the precursor was consumed, then 0.01 M of the product was formed. Similarly, it was assumed that the consumption of hydroxide (which was not directly monitored) also had a 1:1 proportional rate of consumption to that of 3.2, based on the 1:1 mole ratio of reactivity required to form the corresponding spirocyclic product. With these two assumptions, the time scale for all reaction series were normalized and plotted to determine the reagent order based on optimal 3.2 (M) NaOH (M) 3.3 (M)Series B 0.15 0.15 0.0018Series E 0.15 0.09 0.001800.020.040.060.080.10.120.140.160 5 10 15 20[3.2]Time (min)163 overlay according to the equation below, where [A]i is the concentration of the species of interest t is time, and α is the order of the reagent63. 3.6.8 Calibration Plots and NMR spectra 3.6.8.1 Calibration Plots 3.6.8.1.1 Spirocyclic Precursor Calibration plots for the spirocyclic precursor starting material were generated as follows: a 5 mL standard solution of the precursor (515 mg, 0.280 M) was prepared in toluene containing 6% benzene (v/v). The solution was then sampled by the automated sampling platform in triplicate, with the resulting samples analyzed by HPLC. Sequential 50% serial dilutions yielded a range of concentrations from 0.0044 M to 0.2800 M. In order to maintain mass balance, and given the lack of evidence suggesting byproduct formation, a one to one relationship was assumed between spirocyclic precursor consumed and spirocyclic product formed. ( ) 164 Figure 89: Calibration plot for spirocyclic precursor 3.2. 3.6.8.1.2 Phase Transfer Catalyst Figure 90: Calibration plot for phase transfer catalyst 3.3. y = 107.51x - 0.4081R² = 0.9973051015202530350 0.05 0.1 0.15 0.2 0.25 0.3Peak Area/Internal StandardConcentration (M)y = 403.15x - 0.0229R² = 0.9999012345670 0.005 0.01 0.015 0.02Peak Area/Internal StandardConcentration (M)165 3.6.8.2 NMR Spectra 1H NMR (400 MHz, Chloroform-d) δ 8.37 (t, J = 1.8 Hz, 1H), 8.14 (d, J = 5.2 Hz, 1H), 7.67 (t, J = 1.9 Hz, 1H), 7.29 (s, 1H), 7.20 (dd, J = 7.4, 1.7 Hz, 1H), 6.79 (ddd, J = 7.0, 5.2, 1.3 Hz, 1H), 4.59 (t, J = 2.0 Hz, 2H), 4.09 – 4.02 (m, 1H), 3.64 (dd, J = 16.4, 4.7 Hz, 1H), 3.35 (dd, J = 16.4, 7.4 Hz, 1H), 1.83 (d, J = 1.3 Hz, 9H). 13C NMR (101 MHz, CDCl3) δ 178.05, 159.44, 154.57, 147.38, 145.72, 136.88, 132.49, 130.43, 130.12, 123.77, 117.03, 77.34, 77.02, 76.70, 58.52, 43.41, 42.24, 33.71, 28.83. 1H NMR (400 MHz, DMSO-d6) δ 9.32 (d, J = 6.2 Hz, 1H), 8.45 (d, J = 6.1 Hz, 1H), 8.36 (d, J = 9.8 Hz, 1H), 7.76 (dd, J = 19.2, 8.9 Hz, 2H), 7.58 (t, J = 4.3 Hz, 1H), 7.43 (d, J = 3.3 Hz, 1H), 7.16 (dd, J = 8.9, 3.0 Hz, 1H), 7.02 (dd, J = 8.9, 3.0 Hz, 1H), 6.91 (d, J = 3.2 Hz, 1H), 6.49 (d, J = 3.0 Hz, 1H), 6.33 (s, 2H), 6.04 (ddd, J = 17.4, 10.5, 7.1 Hz, 1H), 5.35 – 5.09 (m, 3H), 4.93 (d, J = 13.0 Hz, 1H), 4.36 (ddd, J = 11.6, 8.2, 2.7 Hz, 1H), 4.21 (s, 4H), 4.11 (t, J = 7.6 Hz, 2H), 3.87 (s, 3H), 3.67 (s, 3H), 3.51 (s, 2H), 3.21 (d, J = 10.9 Hz, 2H), 2.89 (s, 3H), 2.31 (t, J = 11.4 Hz, 1H), 1.92 (d, J = 8.7 Hz, 1H), 1.80 (d, J = 9.1 Hz, 2H), 1.21 – 1.03 (m, 1H). 13C NMR (101 MHz, DMSO-d6) δ 162.81, 159.60, 159.22, 146.60, 137.58, 135.26, 134.86, 133.74, 133.50, 128.65, 128.53, 127.92, 122.62, 122.40, 121.79, 118.58, 118.04, 117.65, 116.26, 113.18, 67.31, 66.06, 60.73, 57.21, 56.40, 56.03, 37.36, 36.28, 31.25, 26.43, 23.62, 21.25. 166 1H NMR (400 MHz, DMSO-d6) δ 8.83 (d, J = 4.5 Hz, 1H), 8.03 (d, J = 9.2 Hz, 1H), 7.83 – 7.74 (m, 2H), 7.50 (dq, J = 5.2, 2.8 Hz, 2H), 7.44 (d, J = 2.7 Hz, 1H), 7.15 (dd, J = 8.9, 3.0 Hz, 1H), 6.85 (d, J = 2.8 Hz, 1H), 6.57 (s, 1H), 6.04 (ddd, J = 17.4, 10.5, 7.0 Hz, 1H), 5.29 – 5.12 (m, 3H), 4.83 (d, J = 13.2 Hz, 1H), 4.38 (d, J = 9.4 Hz, 1H), 4.07 (s, 3H), 3.92 (d, J = 9.5 Hz, 1H), 3.86 (s, 3H), 3.48 (t, J = 11.4 Hz, 1H), 3.16 (p, J = 9.9 Hz, 1H), 2.67 (q, J = 8.8, 8.0 Hz, 1H), 2.42 – 2.32 (m, 1H), 1.90 (s, 1H), 1.81 (dd, J = 18.7, 10.1 Hz, 2H), 1.07 (s, 1H). 1H NMR (400 MHz, Chloroform-d) δ 8.42 – 8.37 (m, 1H), 8.17 (dd, J = 5.2, 1.7 Hz, 1H), 7.54 (dt, J = 2.4, 1.1 Hz, 1H), 7.09 (dd, J = 7.3, 1.7 Hz, 1H), 6.81 (dd, J = 7.3, 5.2 Hz, 1H), 3.67 – 3.55 (m, 1H), 3.53 (d, J = 1.3 Hz, 1H), 3.11 (d, J = 16.8 Hz, 1H), 3.04 (d, J = 16.4 Hz, 1H), 1.81 (s, 9H). 13C NMR (101 MHz, CDCl3) δ 179.43, 160.53, 157.82, 147.39, 146.54, 145.73, 136.84, 135.82, 132.18, 130.61, 130.40, 129.30, 128.37, 117.69, 117.02, 77.41, 77.10, 76.78, 58.81, 51.92, 44.33, 43.38, 42.23, 41.56, 33.69, 29.69, 28.83. 167 1H NMR (400 MHz, Chloroform-d) δ 10.11 (d, J = 6.0 Hz, 1H), 8.45 (d, J = 5.9 Hz, 1H), 8.30 – 8.25 (m, 1H), 7.75 (d, J = 2.1 Hz, 2H), 7.53 (d, J = 8.9 Hz, 2H), 7.43 – 7.33 (m, 2H), 7.15 (s, 1H), 7.00 (d, J = 2.9 Hz, 1H), 6.83 (dd, J = 8.9, 3.0 Hz, 1H), 6.66 (dd, J = 8.8, 3.2 Hz, 2H), 6.39 – 6.20 (m, 2H), 5.14 – 5.11 (m, 1H), 4.65 (d, J = 7.9 Hz, 1H), 3.98 (s, 3H), 3.53 (dd, J = 13.8, 7.7 Hz, 2H), 3.20 (t, J = 7.4 Hz, 2H), 2.95 (s, 3H), 2.87 (s, 3H), 2.39 (dd, J = 22.4, 10.1 Hz, 2H), 1.77 – 1.70 (m, 3H). DMF δ 8.01 (s, 1H), 2.95 (s, 3H), 2.87 (s, 3H). Et3N δ 3.14 (q, J = 7.3 Hz, 6H), 1.42 (t, J = 7.3 Hz, 8H). 13C NMR (101 MHz, CDCl3) δ 201.97, 162.58, 161.01, 159.81, 158.97, 149.64, 147.61, 137.86, 134.82, 134.32, 133.06, 131.91, 128.60, 121.36, 120.65, 117.42, 116.57, 115.34, 114.50, 113.50, 105.62, 77.30, 64.48, 61.77, 61.34, 61.32, 56.35, 55.55, 53.90, 43.30, 40.51, 37.63, 36.52, 31.44, 28.19, 28.16. DMF δ 36.52, 31.44. Et3N δ 46.10, 8.69. 168 Conclusion The development of monitoring methods is essential towards furthering the understanding of heterogenous reactions. The limitations of contemporary methodologies can be overcome with careful modification of existing technologies but can sometimes require the creation of new approaches to truly glimpse into the mechanisms of these reactions. Herein, the application and development of such approaches were discussed in relation to a proline catalyzed aldol condensation and a phase transfer reaction catalyzed by a doubly quaternized cinchona alkaloid. The application of a heterogeneous sampling protocol to the study of a proline-catalyzed aldol condensation allowed for a great deal of insight into the reaction. After identifying water as the primary source of stereoselectivity, subsequent time-course data allowed for insight into the mechanism by which this occurred. While these studies may not have identified a kinetic root for this phenomenon, it did rule out many possibilities. It is now known that the presence or absence of water does not influence stereoselectivity by inducing epimerization, generating new catalytically active species, inhibiting product formation, sequester material due to solubility, or proceed through a completely novel mechanism across a range of reaction conditions. These results are consistent with those observed across other aldol reactions. As a result, water is believed to be involved in the transition state of the stereoselective step in the reaction’s mechanism, whereby the introduction (or removal) of hydrogen bonding could influence the relative energies, affording the distribution of stereoisomers observed. Subsequent computational studies can further investigate the role of water in the transition state, and postulate as to the importance of solvent composition in the quantum mechanical predictions of reaction selectivity, 169 The successful development and deployment of an automated sampling platform for the study of biphasic reactions allowed for valuable insight into the mechanism of a phase transfer catalyzed reaction. The combination of heterogeneous (organic and water) and phase selective sampling (organic) allowed for insight into phase transfer behaviour, catalyst decomposition, and rate laws which would not have been accessible through conventional monitoring methods. It was discovered that the reaction was mass transfer limited, with catalyst identified as the primary culprit for the irreproducible profiles generated under low (0.3 mol%) loadings. The doubly quaternized cinchona alkaloid was observed to solubilize into the organic layer upon addition of base but would also begin to undergo decomposition likely via a Hoffman elimination. Attempting to run the reaction at lower temperatures in a bid to have productive spirocyclization further outpace the rate of catalyst degradation was unsuccessful, as lower temperatures affected multiple other physical processes (solubility, mass transfer) which ultimately had no improvement on reaction yield. However, the development of this monitoring methodology coupled with the new knowledge surrounding these cinchona alkaloid phase transfer catalysts can be applied to future studies. These can explore some of the remaining questions surrounding these systems, such as the exact mechanism by which the catalyst is able to solubilize into the organic layer, or whether a new catalyst can be designed which is resistant to degradation but still retains respectable stereoselectivity and reactivity. Overall, both sampling methodologies were successful in the study of their respective reactions. However, neither were able to offer definitive answers for some of their observed phenomena, such as the exact source of stereoselectivity in the proline catalyzed aldol condensation or the phase transfer behaviour of the doubly quaternized cinchona alkaloid catalyst in the biphasic reaction. Further creative experimentation and monitoring designs may 170 be required to probe these systems even deeper, as well as employing the help of other chemical analysis, such as computational chemistry, to provide further answers. Additionally, while most of the platforms used commercially available equipment, the use of some specialized hardware such as the Gilson 215 liquid handler or EasyMax can present a substantial challenge in the adoption of such a protocol in other laboratories, which may not have the funds nor the access to such tools. The spread of 3-D printing, affordable electronics (such as motors, LED’s, wiring etc.) may present an opportunity to develop a buildable sample aliquoting platform, which may improve the availability of these methods to other researchers both in the academic and industrial realms. Indeed, the development of compact, user-buildable analytics increasingly popular, particularly as processors and cameras become more powerful and wide-spread, even in a smartphone. Thus, while the methods discussed can be refined, they provided reliable, robust platforms with which to study two heterogeneous reactions. The insights afforded by these methodologies provided valuable insight into the mechanisms and behaviours of these systems and can be leveraged in the future investigations of biphasic and heterogeneous reactions. 171 Bibliography (1) Chung, R.; Hein, J. E. The More, The Better: Simultaneous In Situ Reaction Monitoring Provides Rapid Mechanistic and Kinetic Insight. Top. Catal. 2017, 60 (8), 594–608. (2) Malig, T. C.; Yu, D.; Hein, J. E. A Revised Mechanism for the Kinugasa Reaction. J. Am. Chem. Soc. 2018, 140 (29), 9167–9173. (3) 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. (4) Chimrca, C. INTERNATIONAL CLINICAL FEDERATION CHEMISTRY OF IFCC Section 1 . Quantities and Units in Clinical Flame Emission and Absorption R . Herrmann and C . Onkelinx Chemistry : Nebulizer and Flame Properties in Spectrometry , Published by on Behalf of FEDERATION. Clin. Chim. Acta 1985, 148, 277F-285F. (5) Suzanne, N. Food Analysis - Book; 2015; Vol. 119. (6) Jespersen, N. Chapter 5 General Principles of Spectroscopy and Spectroscopic Analysis. Compr. Anal. Chem. 2006, 47 (06), 111–155. (7) The Infracord® Double Beam Spectrophotometer. Chem. Eng. News 1957, 35 (33), 74. (8) Ismail, A. A.; van de Voort, F. R.; Sedman, J. Chapter 4 Fourier Transform Infrared Spectroscopy: Principles and Applications. Tech. Instrum. Anal. Chem. 1997, 18 (C), 93–139. (9) Clark, J. Absorbance The Beer-Lambert Law. 2016, 39 (7), 1–8. (10) Ye, J. Y.; Jiang, Y. X.; Sheng, T.; Sun, S. G. In-Situ FTIR Spectroscopic Studies of Electrocatalytic Reactions and Processes. Nano Energy 2016, 29, 414–427. (11) Nakamura, R.; Imanishi, A.; Murakoshi, K.; Nakato, Y. In Situ FTIR Studies of Pimary 172 Intermediates of Photocatalytic Reactions on Nanocrystalline TiO2 Films in Contact with Aqueous Solutions. J. Am. Chem. Soc. 2003, 125 (24), 7443–7450. (12) Vrancken, N.; Li, J.; Sergeant, S.; Vereecke, G.; Doumen, G.; Holsteyns, F.; Chen, C.; Terryn, H.; De Gendt, S.; Xu, X. M. In-Situ ATR-FTIR for Dynamic Analysis of Superhydrophobic Breakdown on Nanostructured Silicon Surfaces. Sci. Rep. 2018, 8 (1), 1–12. (13) Drexler, M. T.; Foley, D. A.; Ward, H. W.; Clarke, H. J. IR and NMR Reaction Monitoring Techniques for Nucleophilic Addition Reactions: In Situ Monitoring of the Addition of Benzimidazole to a Pyridinium Salt. Org. Process Res. Dev. 2015, 19 (9), 1119–1127. (14) Roberts, J. E.; Zeng, G.; Maron, M. K.; Mach, M.; Dwebi, I.; Liu, Y. Measuring Heterogeneous Reaction Rates with ATR-FTIR Spectroscopy to Evaluate Chemical Fates in an Atmospheric Environment: A Physical Chemistry and Environmental Chemistry Laboratory Experiment. J. Chem. Educ. 2016, 93 (4), 733–737. (15) Zaera, F. New Advances in the Use of Infrared Absorption Spectroscopy for the Characterization of Heterogeneous Catalytic Reactions. Chem. Soc. Rev. 2014, 43 (22), 7624–7663. (16) Sánchez Rojas, F.; Bosch Ojeda, C. Recent Development in Derivative Ultraviolet/Visible Absorption Spectrophotometry: 2004-2008. A Review. Anal. Chim. Acta 2009, 635 (1), 22–44. (17) Acker, M. G.; Auld, D. S. Considerations for the Design and Reporting of Enzyme Assays in High-Throughput Screening Applications. Perspect. Sci. 2014, 1 (1–6), 56–73. (18) Bernstein, M. A. Reaction Monitoring Using NMR. Magn. Reson. Chem. 2016, 54 (6), 173 422. (19) Diehl, B. Principles in NMR Spectroscopy. NMR Spectrosc. Pharm. Anal. 2008, 1–41. (20) Huber, L. M.; Haeberlen, U.; Andrew, R.; Lee, M.; Fukushima, E.; Way, H.; Alto, P. 5.2. Nuclear Magnetic Resonance Spectrometer Design. 1976. (21) Gomez, M. V.; De La Hoz, A. NMR Reaction Monitoring in Flow Synthesis. Beilstein J. Org. Chem. 2017, 13, 285–300. (22) Singleton, D. A.; Hang, C. 13C and 2H Kinetic Isotope Effects and the Mechanism of Lewis Acid- Catalyzed Ene Reactions of Formaldehyde. J. Org. Chem. 2000, 65 (3), 895–899. (23) Westaway, K. C. Using Kinetic Isotope Effects to Determine the Structure of the Transition States of SN2 Reactions. Adv. Phys. Org. Chem. 2006, 41 (1), 217–273. (24) Romano, R.; Santini, M. T.; Indovina, P. L. A Time-Domain Algorithm for NMR Spectral Normalization. J. Magn. Reson. 2000, 146 (1), 89–99. (25) Shi, F.; Coffey, A. M.; Waddell, K. W.; Chekmenev, E. Y.; Goodson, B. M. Heterogeneous Solution NMR Signal Amplification by Reversible Exchange. Angew. Chemie - Int. Ed. 2014, 53 (29), 7495–7498. (26) Snyder, L. R. Peer Reviewed: HPLC: Past and Present. Anal. Chem. 2000, 72 (11), 412 A-420 A. (27) Mourey, T. H.; Oppenheimer, L. E. Principles of Operation of an Evaporative Light-Scattering Detector for Liquid Chromatography. Anal. Chem. 1984, 56 (13), 2427–2434. (28) Okamoto, Y.; Ikai, T. Chiral HPLC for Efficient Resolution of Enantiomers. Chem. Soc. Rev. 2008, 37 (12), 2593–2608. (29) Gritti, F.; Guiochon, G. The van Deemter Equation: Assumptions, Limits, and Adjustment 174 to Modern High Performance Liquid Chromatography. J. Chromatogr. A 2013, 1302, 1–13. (30) Klinkenberg, A.; Zuiderweg, F. J. Longitudinal Diffusion and Resistance to Mass Transfer as Causes of Nonideality in Chromatography. Chem. Eng. Sci. 1956, 5 (6), 271–289. (31) Knox, J. H.; Scott, H. P. B and C Terms in the Van Deemter Equation for Liquid Chromatography. J. Chromatogr. A 1983, 282 (C), 297–313. (32) Gerber, F.; Krummen, M.; Potgeter, H.; Roth, A.; Siffrin, C.; Spoendlin, C. Practical Aspects of Fast Reversed-Phase High-Performance Liquid Chromatography Using 3 Μm Particle Packed Columns and Monolithic Columns in Pharmaceutical Development and Production Working under Current Good Manufacturing Practice. J. Chromatogr. A 2004, 1036 (2), 127–133. (33) Yashin, Y. I.; Yashin, A. Y. Analysis of Food Products and Beverages Using High-Performance Liquid Chromatography and Ion Chromatography with Electrochemical Detectors. J. Anal. Chem. 2004, 59 (12), 1121–1127. (34) Kim, E.; Engineer, A. Troubleshooting of HPLC Columns Goals for This Presentation : Engineer 2008, 1–52. (35) Chung, R.; Vo, A.; Fokin, V. V.; Hein, J. E. Catalyst Activation, Chemoselectivity, and Reaction Rate Controlled by the Counterion in the Cu(I)-Catalyzed Cycloaddition between Azide and Terminal or 1-Iodoalkynes. ACS Catal. 2018, 8 (9), 7889–7897. (36) Pistos, C.; Stewart, J. T. Direct Injection HPLC Method for the Determination of Selected Benzodiazepines in Plasma Using a Hisep Column. J. Pharm. Biomed. Anal. 2003, 33 (5), 1135–1142. (37) Anderson, D. J. High-Performance Liquid Chromatography (Direct Injection Techniques). 175 Anal. Chem. 1993, 65 (12), 434–443. (38) Khimii, Z. A. Basic Principles of Gas Chromatography. 2007, No. Cc, 12–30. (39) Krupčík, J.; Mydlová, J.; Májek, P.; Šimon, P.; Armstrong, D. W. Methods for Studying Reaction Kinetics in Gas Chromatography, Exemplified by Using the 1-Chloro-2,2-Dimethylaziridine Interconversion Reaction. J. Chromatogr. A 2008, 1186 (1–2), 144–160. (40) Glish, G. L.; Vachet, R. W. The Basics of Mass Spectrometry in the Twenty-First Century. Nat. Rev. Drug Discov. 2003, 2 (2), 140–150. (41) 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. (42) Yunker, L. P. E.; Ahmadi, Z.; Logan, J. R.; Wu, W.; Li, T.; Martindale, A.; Oliver, A. G.; McIndoe, J. S. Real-Time Mass Spectrometric Investigations into the Mechanism of the Suzuki-Miyaura Reaction. Organometallics 2018, 37 (22), 4297–4308. (43) 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. (44) Leutzsch, M.; Sederman, A. J.; Gladden, L. F.; Mantle, M. D. In Situ Reaction Monitoring in Heterogeneous Catalysts by a Benchtop NMR Spectrometer. Magn. Reson. Imaging 2019, 56 (September 2018), 138–143. (45) 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, 1555–1558. 176 (46) Starks, C. M. Phase-Transfer Catalysis. I. Heterogeneous Reactions Involving Anion Transfer by Quaternary Ammonium and Phosphonium Salts. J. Am. Chem. Soc. 1971, 93 (1), 195–199. (47) Shirakawa, S.; Maruoka, K. Recent Developments in Asymmetric Phase-Transfer Reactions Angewandte. 2013, 4312–4348. (48) Bahmanyar, S.; Houk, K. N.; Martin, H. J.; List, B. Quantum Mechanical Predictions of the Stereoselectivities of Proline-Catalyzed Asymmetric Intermolecular Aldol Reactions. J. Am. Chem. Soc. 2003, 125 (9), 2475–2479. (49) Hajos, Z. G.; Parrish, D. R. Asymmetric Synthesis of Bicyclic Intermediates of Natural Product Chemistry. J. Org. Chem. 1974, 39 (12), 1615–1621. (50) Eder, B. U.; Sauer, G.; Wiechert, R. New Type of Asymmetric Cyclization to Optically Active Steroid CD Partial Structures. Angew. Chemie 1971, 10 (7), 496–497. (51) List, B.; Hoang, L.; Martin, H. J. New Mechanistic Studies on the Proline-Catalyzed Aldol Reaction. 2004, 101 (16), 5839–5842. (52) Mase, N. 6.4 C-C Bond Formation: Aldol Reaction with Proline Derivatives; Elsevier Ltd., 2012; Vol. 6. (53) Bahmanyar, S.; Houk, K. N.; Martin, H. J.; List, B. Quantum Mechanical Predictions of the Stereoselectivities of Proline-Catalyzed Asymmetric Intermolecular Aldol Reactions. 2003, No. 14, 2475–2479. (54) Bahmanyar, S.; Houk, K. N. The Origin of Stereoselectivity in Proline-Catalyzed Intramolecular Aldol Reactions. J. Am. Chem. Soc. 2001, 123 (51), 12911–12912. (55) Hayashi, Y.; Sumiya, T.; Takahashi, J.; Gotoh, H.; Urushima, T.; Shoji, M. Highly Diastereo- and Enantioselective Direct Aldol Reactions in Water. Angew. Chemie - Int. 177 Ed. 2006, 45 (6), 958–961. (56) Sz, G. Tuning the Sense of Product Stereochemistry in Aldol Reactions of Acetone and Aromatic Aldehydes in the Presence of Water with a Single Chiral Catalyst. 2015, 56, 7201–7205. (57) Yang, H.; Mahapatra, S.; Cheong, P. H. Y.; Carter, R. G. Highly Stereoselective and Scalable Anti-Aldol Reactions Using N-(p-Dodecylphenylsulfonyl)-2-Pyrrolidinecarboxamide: Scope and Origins of Stereoselectivities. J. Org. Chem. 2010, 75 (21), 7279–7290. (58) R. Ellson; R. Stearns; M. Mutz; C. Brown; B. Browning; D. Harris; S. Qureshi; J. Shieh; D. Wold. In Situ DMSO Hydration Measurements of HTS Compound Libraries. Comb. Chem. High Throughput Screen. 2005, 8 (6), 489–498. (59) Lebel, G.; Goring, D. A. I. Density , Viscosity , Refractive Index , and Hygroscopicity of Mixtures of Water and Dimethyl Sulfoxide. 100–101. (60) Zotova, N.; Franzke, A.; Armstrong, A.; Blackmond, D. G. Clarification of the Role of Water in Proline-Mediated Aldol Reactions. J. Am. Chem. Soc. 2007, 129 (49), 15100–15101. (61) Seebach, D.; Beck, A. K.; Badine, D. M.; Limbach, M.; Eschenmoser, A.; Treasurywala, A. M.; Hobi, R. Are Oxazolidinones Really Unproductive , Parasitic Species in Proline Catalysis ? – Thoughts and Experiments Pointing to an Alternative View. 2007, 90 (December 1975), 425–471. (62) 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. 178 (63) Burés, J. Variable Time Normalization Analysis: General Graphical Elucidation of Reaction Orders from Concentration Profiles. Angew. Chemie - Int. Ed. 2016, 55 (52), 16084–16087. (64) Burés, J. A Simple Graphical Method to Determine the Order in Catalyst. Angew. Chemie - Int. Ed. 2016, 55 (6), 2028–2031. (65) Ashley, M. A.; Hirschi, J. S.; Izzo, J. A.; Vetticatt, M. J. Isotope Effects Reveal the Mechanism of Enamine Formation in l -Proline-Catalyzed α-Amination of Aldehydes. J. Am. Chem. Soc. 2016, 138 (6), 1756–1759. (66) Sheldrick, G. M. Crystal Structure Refinement with SHELXL. Acta Crystallogr. Sect. C Struct. Chem. 2015, 71 (Md), 3–8. (67) Dolomanov, O. V.; Bourhis, L. J.; Gildea, R. J.; Howard, J. A. K.; Puschmann, H. OLEX2: A Complete Structure Solution, Refinement and Analysis Program. J. Appl. Crystallogr. 2009, 42 (2), 339–341. (68) Sheldrick, G. M. SHELXT - Integrated Space-Group and Crystal-Structure Determination. Acta Crystallogr. Sect. A Found. Crystallogr. 2015, 71 (1), 3–8. (69) Makosza, M. Phase-Transfer Catalysis. A General Green Methodology in Organic Synthesis. Pure Appl. Chem. 2007, 72 (7), 1399–1403. (70) Starks, C. M.; Owens, R. M. Phase-Transfer Catalysis. II. Kinetic Details of Cyanide Displacement on 1-Halooctañes. J. Am. Chem. Soc. 1973, 95 (11), 3613–3617. (71) Freedman, H. H. Industrial Applications of Phase Transfer Catalysis (Ptc): Past, Present and Future. Pure Appl. Chem. 1986, 58 (6), 857–868. (72) Ooi, T.; Maruoka, K. Recent Advances in Asymmetric Phase-Transfer Catalysis. Angew. Chemie - Int. Ed. 2007, 46 (23), 4222–4266. 179 (73) Arai, S.; Shirai, Y.; Ishida, T.; Shioiri, T. Phase-Transfer-Catalyzed Asymmetric Darzens Reaction. Tetrahedron 1999, 55 (20), 6375–6386. (74) Ye, J.; Wang, Y.; Liu, R.; Zhang, G.; Zhang, Q.; Chen, J.; Liang, X. A Highly Enantioselective Phase-Transfer Catalyzed Epoxidation of Enones with a Mild Oxidant, Trichloroisocyanuric Acid. Chem. Commun. 2003, 9 (21), 2714–2715. (75) Ooi, T.; Takahashi, M.; Doda, K.; Maruoka, K. Asymmetric Induction in the Neber Rearrangement of Simple Ketoxime Sulfonates under Phase-Transfer Conditions: Experimental Evidence for the Participation of an Anionic Pathway. J. Am. Chem. Soc. 2002, 124 (26), 7640–7641. (76) Aires-De-Sousa, J.; Lobo, A. M.; Prabhakar, S. A New Enantioselective Synthesis of N-Arylaziridines by Phase-Transfer Catalysis †. Tetrahedron Lett. 1996, 37 (18), 3183–3186. (77) Bhunnoo, R. A.; Hu, Y.; Lain??, D. I.; Brown, R. C. D. An Asymmetric Phase-Transfer Dihydroxylation Reaction. Angew. Chemie - Int. Ed. 2002, 41 (18), 3479–3480. (78) Kim, D. Y.; Park, E. J. Catalytic Enantioselective Fluorination of β-Keto Esters by Phase-Transfer Catalysis Using Chiral Quaternary Ammonium Salts. Org. Lett. 2002, 4 (4), 545–547. (79) Juliá, S.; Ginebreda, A. Asymmetric Induction by Phase-Transfer Catalysis Using Chiral Catalysts. Synthesis of 1,2-Dichloroalkanes and Acetylcyanohydrins. Tetrahedron Lett. 1979, 20 (23), 2171–2174. (80) Xiang, B.; Belyk, K. M.; Reamer, R. A.; Yasuda, N. Discovery and Application of Doubly Quaternized Cinchona-Alkaloid-Based Phase-Transfer Catalysts. Angew. Chemie - Int. Ed. 2014, 53 (32), 8375–8378. 180 (81) Jew, S. S.; Park, H. G. Cinchona-Based Phase-Transfer Catalysts for Asymmetric Synthesis. Chem. Commun. 2009, No. 46, 7090–7103. (82) He, C. Q.; Simon, A.; Lam, Y. H.; Brunskill, A. P. J.; Yasuda, N.; Tan, J.; Hyde, A. M.; Sherer, E. C.; Houk, K. N. Model for the Enantioselectivity of Asymmetric Intramolecular Alkylations by Bis-Quaternized Cinchona Alkaloid-Derived Catalysts. J. Org. Chem. 2017, 82 (16), 8645–8650. (83) von Keutz, T.; Cantillo, D.; Kappe, C. O. Enhanced Mixing of Biphasic Liquid-Liquid Systems for the Synthesis of Gem-Dihalocyclopropanes Using Packed Bed Reactors. J. Flow Chem. 2019, 9 (1), 27–34. (84) Manley, G. Origin and Correction of Magnetic Field Inhomogeneity at TheInterface in Biphasic NMR Samples. J. Magn. Reson. 2013, 71 (2), 233–236. (85) Shirakawa, S.; Yamamoto, K.; Kitamura, M.; Ooi, T.; Maruoka, K. Dramatic Rate Enhancement of Asymmetric Phase-Transfer-Catalyzed Alkylations. Angew. Chemie - Int. Ed. 2005, 44 (4), 625–628. (86) Keim, W. Multiphase Catalysis and Its Potential in Catalytic Processes: The Story of Biphasic Homogeneous Catalysis. Green Chem. 2003, 5 (2), 105–111. (87) Adamo, A.; Heider, P. L.; Weeranoppanant, N.; Jensen, K. F. Membrane-Based, Liquid-Liquid Separator with Integrated Pressure Control. Ind. Eng. Chem. Res. 2013, 52 (31), 10802–10808. (88) Mandrelli, F.; Buco, A.; Piccioni, L.; Renner, F.; Guelat, B.; Martin, B.; Schenkel, B.; Venturoni, F. The Scale-up of Continuous Biphasic Liquid/Liquid Reactions under Super-Heating Conditions: Methodology and Reactor Design. Green Chem. 2017, 19 (6), 1425–1430. 181 (89) Samant, K. D.; Singh, D. J.; Ng, K. M. Design of Liquid-Liquid Phase Transfer Catalytic Processes. AIChE J. 2001, 47 (8), 1832–1848. (90) Nieves-Remacha, M. J.; Torres, M.; Ruiz-Abad, M.; Rincón, J. A.; Cumming, G. R.; Garcia-Losada, P. Scale-up of N-Alkylation Reaction Using Phase-Transfer Catalysis with Integrated Separation in Flow. React. Chem. Eng. 2019, 4 (2), 334–345. (91) Patterson, D. E.; Xie, S.; Jones, L. A.; Osterhout, M. H.; Henry, C. G.; Roper, T. D. Synthesis of 4-Fluoro-β(4-Fluorophenyl)-l-Phenylalanine by an Asymmetric Phase-Transfer Catalyzed Alkylation: Synthesis on Scale and Catalyst Stability. Org. Process Res. Dev. 2007, 11 (3), 624–627. (92) Yang, R. S.; Sheng, H.; Lexa, K. W.; Sherer, E. C.; Zhang, L. K.; Xiang, B.; Helmy, R.; Mao, B. Mechanistic Study of the Gas-Phase In-Source Hofmann Elimination of Doubly Quaternized Cinchona-Alkaloid Based Phase-Transfer Catalysts by (+)-Electrospray Ionization/Tandem Mass Spectrometry. J. Am. Soc. Mass Spectrom. 2017, 28 (3), 452–460. (93) Jezorek, R. L.; Enayati, M.; Smail, R. B.; Lejnieks, J.; Grama, S.; Monteiro, M. J.; Percec, V. The Stirring Rate Provides a Dramatic Acceleration of the Ultrafast Interfacial SET-LRP in Biphasic Acetonitrile-Water Mixtures. Polym. Chem. 2017, 8 (22), 3405–3424. (94) The Merck Index - An Encyclopedia of Chemicals, Drugs, and Biologicals; O’Neil, M J. (Merck and Co., I. ., Ed.; Whitehouse Station, NJ, 2006. (95) Chung, C. K.; Liu, Z.; Lexa, K. W.; Andreani, T.; Xu, Y.; Ji, Y.; Dirocco, D. A.; Humphrey, G. R.; Ruck, R. T. Asymmetric Hydrogen Bonding Catalysis for the Synthesis of Dihydroquinazoline-Containing Antiviral, Letermovir. J. Am. Chem. Soc. 2017, 139 (31), 10637–10640. 182 Appendices Appendix A A.1 NMR spectra for Chapter 2 Figure 91. 1H NMR for 2.1 ((S,R),(R,S)). 183 Figure 92. 13C NMR with full assignments for 2.1 ((S,R),(R,S)). Figure 93. 1H COSY NMR for 2.1 ((S,R),(R,S)) 184 Figure 94. HSQC NMR for 2.1 ((S,R),(R,S)) Figure 95. 1H NMR for 2.1 ((S,S),(R,R)) 185 Figure 96. 13C NMR with full assignment for 2.1 ((S,S),(R,R)) Figure 97. 1H COSY NMR for 2.1 ((S,S),(R,R)). 186 Figure 98. HSQC NMR for 2.1 ((S,S),(R,R)). 187 A.2 NMR Spectra for Chapter 3 Figure 99. 1H NMR for 2.2. Figure 100. 13C NMR for 2.2. 188 Figure 101. 1H NMR for 2.4. Figure 102. 13C NMR for 2.4. 189 Figure 103. 1H NMR for 2.3. Figure 104. 13C NMR for 2.3. 190 Figure 105. 1H NMR for 2.9. 191 Figure 106. 1H NMR for 2.8 formed by decomposition of 2.3 by Et3N in CDCl3. Figure 107. 13C NMR for 2.8 formed by decomposition of 2.3 by Et3N in CDCl3. 192 Figure 108. 1H COSY NMR for 2.8 formed by decomposition of 2.3 by Et3N in CDCl3. Figure 109. HSQC NMR for 2.8 formed by decomposition of 2.3 by Et3N in CDCl3. 193 Figure 110. HMBC NMR for 2.8 formed by decomposition of 2.3 by Et3N in CDCl3.
Thesis/Dissertation
eng
Chemistry
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Development and deployment of automated monitoring methodologies mowards investigations of heterogeneous and biphasic reactions
Text