Jason Hein

Professor

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Graduate Student Supervision

Doctoral Student Supervision

Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.

Advancing benchtop nuclear magnetic resonance (NMR) spectroscopy as a tool for pharmaceutical development (2024)

The ability to quantitatively monitor chemical species through a reaction allows for insight to enhance process efficiency and/or safety. Nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical technique, known for the ability to provide structural and quantitative data in a non-destructive manner. There has been significant growth in the development and availability of benchtop NMR spectrometers in the last decade. The use of permanent magnets result in smaller applied magnetic fields, a decrease in sensitivity and signal dispersion, but a more compact size and affordable cost. Particularly, benchtop NMR can allow for the powerful analytical capabilities associated with NMR spectroscopy to enter non-traditional settings, such as a synthetic laboratory. Therefore, this thesis focuses on leveraging these systems for reaction monitoring. First, an on-line continuous-flow benchtop NMR system is explored. Particular attention is given to the impact of flow on the mixing behaviour of analyte within the flow cell, mixing/emptying behaviour, the spin-lattice relaxation time, and sensitivity of data measurement with two sets of acquisition parameters. The complex nature of continuous-flow analyses prompted the development and application of an on-line stopped-flow benchtop NMR system, with all hardware centrally controlled with a Python script. The utility of this system was showcased using difficult to monitor model reaction systems. These reactions include activation of a carboxylic acid with sulfuryl fluoride (SO₂F₂) and carbamate formation as a result of an alcohol reacting with an isocyanate resultant from a modified Curtius rearrangement. An external calibration quantitative NMR (qNMR) method is further highlighted, allowing for robust qNMR analyses without an internal standard or special hardware. The utility of the qNMR method is demonstrated by monitoring all synthetic steps of a highly relevant chemical transformation to the pharmaceutical industry: 1,1’-carbonyldiimidazole (CDI) mediated amide coupling. Lastly, on-line stopped- and continuous-flow benchtop NMR systems were compared for reaction monitoring, using two model reactions: a homogenous imination reaction and the activation of a carboxylic acid using perfluorobutanesulfonyl fluoride (PBSF). The on-line stopped-flow benchtop NMR system resulted in more robust quantitative analyses and, therefore, more easily achievable mechanistic information.

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Application of time course-based kinetic methods to complex catalytic systems (2024)

Understanding and optimizing chemical reactions is important for controlling reaction selectivity, increasing yield, reducing waste, and improving numerous other reaction parameters. Reaction optimization is often informed by mechanistic understanding, which arises from kinetic studies. Kinetic studies aim to understand what impacts the mechanism and rate of a reaction. There are many methodologies for kinetic analysis. There have been recent advances in kinetic methodologies which allow for the interrogation of systems under reaction-relevant conditions, and which require fewer experiments than traditional initial rate methods. These modern kinetic methodologies utilize temporal profiles of chemical reactions that track the course of individual reaction components over the course of a reaction. Time course reaction profiles provide invaluable reaction insight and, coupled with these new kinetic methodologies, are extremely powerful tools for mechanistic elucidation. However, chemists have been slow to onboard these powerful methodologies, which are still considered advanced and niche techniques. This thesis aims to develop protocols to make these methodologies more accessible to the general chemistry community. A set of best practices for collecting robust and high-quality time course reaction profiles for kinetic studies was developed. This guide improves the confidence chemists have in the conclusions of kinetic studies by ensuring that important control reactions have been run and proper optimization of reaction monitoring parameters has been achieved. A protocol for converting data sets of temporal peak area versus time to temporal concentration using nonlinear regression analysis was also developed. This method is rapid, facile, and broadly accessible as it can be done with any nonlinear regression tool, including the Solver plug-in in Microsoft Excel. Lastly, the presented protocols and procedures were applied to gather kinetic data in the Buchwald Hartwig amination of a polyhalogenated arene. Time course data of the amination were gathered with several commonly employed catalyst systems. The time course profiles in combination with reaction modeling enabled delineation of two previously indistinguishable mechanisms, ring walking and diffusion controlled coupling. The resulting mechanistic understanding was leveraged to achieve a specific site selectivity in the amination of the polyhalogenated arene and enabled desymmetrization of the symmetrical starting material.

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The control and analysis of one-pot multistep reactions by automation and reaction monitoring technologies (2024)

The comprehension, control, and optimization of chemical reactions largely depend on the apt selection of suitable analytical methodologies. For simpler reactions, characterized by straightforward setups and a limited number of reaction components, success can typically be achieved through the combination of standard off-line analytical instruments and established workflows/methodologies.Nonetheless, the situation dramatically changes with the escalation of reaction complexity. This situation becomes particularly prominent in the context of one-pot telescoping type reactions. Such complexities necessitate the development and implementation of more advanced analytical tools and control strategies to ensure the effective study and optimization. This thesis delves into the creation of innovative platforms and methodologies to scrutinize one-pot multistep reaction systems, enabling the control and analysis of these reactions. The work is composed of three distinct studies.The first study focuses on the development of an adaptive auto-synthesizer by merging commercially accessible automated labware and programming language. This auto-synthesizer facilitates the control and standardization of one-pot multistep reactions, accomplished through the integration of orthogonal online reaction monitoring techniques to enable a feedback-control algorithm. In particular, the platform was used to investigate a one-pot two-step carbonyl diimidazole (CDI)-mediated amide bond formation reaction. By adaptively standardizing the reaction conditions, relative rates for the reaction between various carboxylic acids and amines were determined.The second study explored a reliable monitoring methodology for nanocluster (NC) synthesis. Given the complexity of NC synthesis, which usually results in mixtures comprising various species of metal clusters and ligands, existing process analytical technologies (PATs) have proven inadequate for the separation and quantification of each component within the mixture. To address this, I developed a high-performance liquid chromatography (HPLC) separation technique tailored for an N-heterocyclic carbene (NHC)-gold nanocluster (AuNC) mixture. The synthesis of [Au₁₃(NHC)₉Cl₃]Cl₂ and [Au₂₄(NHC)₁₄Cl₂H₃][BF₄]₃ was examined through HPLC monitoring. The third study focused on visualization of the process of one-pot reactions, with those involving non-UV-active and/or unstable reaction components. Two instances are presented in this research. In the first scenario, the research aimed to visualize bio-catalyzed cascade reactions. In the second instance, the study aimed to visualize unstable acyl imidazolide intermediates involved in amidation reactions.

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Development of process analytical technologies and application for complicated reaction conditions (2023)

Real-time sample analysis, including in situ analysis and automated sampling/injection, provides timely measurements of analytes and facilitates efficient reaction elucidations. In contrast to manual sampling, real-time sample analysis eliminates laborious sample preparations and increases efficiency and robustness in obtaining data-rich information. Unfortunately, many instrumental analytical tools used for real-time reaction monitoring are only applicable to homogeneous conditions, leaving heterogeneous conditions a major challenge. This thesis explores developments and applications of new heterogenous sampling platforms to investigate reaction details. Combing commercially available laboratory equipment with an in-line dynamic mixer, an online HPLC reaction monitoring system has been developed to investigate solid/liquid heterogeneous reactions. Using this platform, a slurry tetrabenazine (TBZ) synthesis has been investigated. The isolation and characterization of unseen enone and iminium intermediates proved that the reaction underwent the aza-Michael-Mannich annulation pathway. Our increased mechanistic understanding has allowed for the reaction rate to be boosted five-fold. For liquid/liquid heterogeneous reaction monitoring, a phase-selective sampling system was developed. This was achieved by developing a novel hydrophilic/oleophobic stainless steel filter. Partition coefficients of boronic acids with varying functional groups have been tested using this platform. Biphasic Suzuki-Miyaura coupling reaction was also explored. In addition to the heterogeneous conditions, nanocluster synthesis was also known to create challenging conditions to be monitored due to its complicated polydisperse cluster formations. This thesis lastly demonstrated that real-time LCMS monitoring revealed size growth of gold nanoclusters synthesis and potential intermediates.

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Leveraging novel process analytical technologies to access chiral small molecule drug precursors via dynamic crystallization (2023)

Dynamic crystallizations can drive the formation of enantiopure solid phases but require significant process understanding to achieve the necessary levels of control. Phase-specific data that sheds light on the solution and solid phases of crystallizations can facilitate this understanding and enable the development of such dynamic crystallizations. Building off previous work in the Hein Lab, this Thesis explores the development of two new phase-specific analytical tools for monitoring crystallizations and their application to dynamic crystallization development. A filter modification for Mettler-Toledo’s EasySampler probe is presented. This filter is capable of selectively sampling the solution phase of crystallizations, and its efficacy is demonstrated in a variety of crystallization tests. A complementary solid phase tool is developed using a webcam to monitor the turbidity of solutions, providing a solid phase monitoring tool and allowing automated solubility and nucleation measurements to be performed. These two tools were used in combination to investigate, optimize, and demonstrate the dynamic crystallizations of two unique small molecule drug precursors, each of which is currently isolated via crystallization. The first molecule was discovered to form an undesired racemic solid phase. As such, a multi-well continuous crystallization setup with dissolution, crystallization and inline racemization was used to kinetically control its dynamic crystallization. Based on this success, the crystallization of a second molecule was investigated in partnership with Genentech. Mechanistic understanding was achieved using our novel process analytical technology tools and traditional offline sampling, allowing a similar inline racemization approach to that used with the first molecule to be applied and optimized for the second molecule’s crystallization.

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The development and applications of autonomous process optimization systems (2023)

Autonomous process optimization involves the human-intervention free search of an input parameter space in order to minimize or maximize output parameters of interest. These systems automate the repetitive and manual approach to process optimization that currently dominates the field. The field of autonomous process optimization is in its infancy and a majority of examples have focused on flow reactor-based systems, however, not all processes can be executed in flow reactors due to heterogeneity or long reaction times. We extended this novel technology to high-throughput microscale batch reactors through the integration of commercial Chemspeed robotics platforms with online analytical instruments and optimization algorithms using a Python interface. The first system was applied to the optimization of a stereoselective Suzuki-Miyaura process, and the second to the optimization of a Wohl-Ziegler photobromination process. We found that optimization performance was impacted by the definition of the search space, the appropriate representation of chemical structure, the optimization algorithm, the acquisition function and the selection of the appropriate reactor and analysis technology. These aspects are discussed in detail for each case study. Finally, the analysis of multivariate optimization data proved to be a challenging proposition, and we found that qualitative machine learning approaches such as random forest modeling allowed for the determination of parameter influences in an effective way. The strategy that we have implemented for autonomous process optimization has the potential to be scaled to additional robotic and analytical instruments, as well as optimization algorithms, through its modular Python interface. We envision a future where the utilization of such systems is commonplace.

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Synthesis and characterisation of platinum(II) methyl complexes and their reactivity towards carbon-hydrogen (C-H) and carbon-halogen bonds (C-X) (2022)

Within this thesis, the syntheses of novel Pt⁽ᴵᴵ⁾ complexes that show reactivity towards carbon-hydrogen and carbon-halogen bonds is explored. Understanding the nuances of fundamental reactivity is important for catalyst design. These nuances allow for the development of novel systems capable of tackling challenging reactions such as alkane activation and functionalisation. Chapter 1 gives an overview of the current understanding of the mechanisms for C-H activation of alkanes and how the communities understanding has changed over the last 20 years. In chapter 2 the intermolecular oxidative addition of aryl halides to Pt⁽ᴵᴵ⁾ complexes is presented. The work in chapter 2 forms part of a proposed catalytic cycle for methane functionalisation, using aryl halides as oxidants. The oxidative addition of aryl halides to Pt⁽ᴵᴵ⁾ complexes has so far only been reported for aryl halides that are tethered to the ligand backbone. The work in chapter 2 therefore constitutes a significant advance in the reactivity of aryl halide chemistry with platinum. Novel ligand design and synthesis of new platinum complexes targeted towards small molecule activation is presented in chapter 3. The new ligands provide an entry into the synthesis of (hetero)bimetallic complexes that could show activity in cascade or tandem reactions. The use of bimetallic complexes is important for tailoring the reactivity of two catalysts simultaneously in the same molecule allowing for a higher degree of control over a reaction or multiple reactions in the same flask. The C-H activation of pyridine via the formation of Pt-Pt bonded bimetallic species is shown in chapter 4. Furthermore, a detailed computational and experimental study into the donor-acceptor nature of the Pt-Pt bond shows how bimetallic complexes of platinum could be used in challenging C-H activation reactions. Chapter 5 provides a summary of the work in this thesis and gives new avenues for the continued development of new platinum compounds for small molecule activation reactions.

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Leveraging automation to elucidate reaction mechanisms (2020)

Understanding chemical processes facilitates reaction optimization to make synthetic procedures more efficient while also enabling reaction discovery. Temporal profiling of chemical reactions provides the gold standard for increasing mechanistic understanding. Unfortunately, obtaining time-course information reproducibly, accurately, and also minimizing analyst intervention is a significant challenge. Combining in situ spectroscopic methods with automated sampling techniques provides a robust method to generate kinetic profiles enabling increased mechanistic understanding. This thesis explores the development and application of online HPLC as an analytical technique to obtain concentration data while minimizing workload for the analyst. By utilizing commercially available laboratory equipment and software we have created a sampling device capable of automatically monitoring both homogeneous and heterogeneous reactions, as well as those performed under an inert atmosphere. The ability of the platform to sample, dilute, mix, and analyze reaction aliquots reproducibly has been validated, thereby ensuring accuracy of acquired time-course data. This automated reaction monitoring device has been used to delineate reaction mechanisms for a series of chemically distinct transformations. The Kinugasa reaction for the synthesis of beta-lactams was investigated. A novel retrocycloaddition step accounts mechanistically for byproducts associated with the transformation. A telescoped synthesis yielding cyanoimidazoles via combining an imidazole forming condensation annulation with a functional group conversion was also investigated. A series of Buchwald-Hartwig aminations performed within a glovebox using various aryl halide components were explored. Lastly, the mechanism of a synthetic procedure to synthesize Spiro-OMeTAD, a state-of-the-art organic material used in modern solar cells, was probed. By leveraging automated reaction monitoring devices, mechanistic understanding for each transformation was increased, ultimately making these transformations more efficient.

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Solving difficult problems with automated technology: new tools to understand complex chemical and physical processes (2020)

The desire for cheaper, faster, energy-conscious, and more sustainable chemical processes often necessitates the design and development of new catalytic methods. Once a catalytic transformation is conceived, the reaction conditions must be optimized to maximize yield and selectivity. Traditional optimization protocols stipulate the correlation of these end-metrics at a fixed time point to variable reaction parameters such as temperature, time, concentration, stoichiometry, etc. By systematically varying these parameters, researchers hope to develop empirical trends relating properties of the chemical species involved to the observed reactivity. What underpins these efforts is an attempt to account for and control the complex, dynamic, and numerous chemical equilibria within a catalytic environment. However, while idealized catalytic mechanisms can be easily envisioned, the reality is that these processes are often plagued by off-cycle equilibria and decomposition pathways that lead to reduced yield and efficiency. In order to rapidly assess what inhibits productive chemistry, focus must be redirected towards scrutinizing the mechanisms within a catalytic environment. To facilitate this, the acquisition of high-density, trustworthy, and time-resolved reaction progress information for all observable species present within a chemical transformation (starting reagents, intermediates, by-products, products, etc.) by modern in situ reaction monitoring tools offers unmatched opportunities for mechanistic understanding. Ultimately, these time-course profiles provide temporal signatures of dynamic processes active during the chemical transformation that inform process development. This Thesis reports on case studies in which the construction and application of automated technology enabled the solution to difficult problems in complex chemical and physical processes.

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Development and mechanistic analysis of n-heterocyclic carbene-catalyzed reactions (2018)

A new class of N-heterocyclic carbene (NHC) organocatalysts were developed based on the 1,2,3-triazolium core architecture. These catalysts were found to facilitate the oxidative esterification of aromatic aldehydes, and a small substrate scope was examined. Using reaction progress monitoring by HPLC, a detailed kinetic analysis was performed. Mechanistic studies showed the reaction to be positive order in both aldehyde and base, and zero order in oxidant and methanol. A key carbene-aldehyde adduct was isolated and characterized by X-ray crystallography, and it was shown to exhibit catalytic activity.The NHC-catalyzed oxidative acylation of electron-poor nucleophiles was also developed, using a 1,2,4-triazolium salt precatalyst. A brief substrate scope was examined, and a kinetic analysis was performed using ¹H NMR reaction monitoring. The mechanistic analysis revealed that the reaction is positive order in aldehyde and base, and zero order in catalyst, oxidant, and sulfonamide nucleophile. In addition, the origin of catalyst deactivation was investigated in the NHC-catalyzed oxidative amidation of aldehydes with amines. Two carbene-amine adducts were discovered, and they were characterized by 1-D and 2-D NMR techniques. A minor carbene-carbene condensation product was also discovered, and characterized by X-ray crystallography.Finally, a new method of synthesizing dihydropyrimidone precursors for isothiourea organocatalysts was developed, and a brief substrate scope was examined. Experimental and computational results showed that the cyclization reaction proceeds through an alpha,beta-unsaturated mixed imide intermediate, rather than by direct conjugate addition to the alpha,beta-unsaturated amide starting material. These computational results also revealed a 7.6 kcal/mol difference between the imide cyclization pathway and the direct acrylamide cyclization pathway. Using HPLC reaction monitoring methods, a preliminary mechanistic analysis was performed. These preliminary results showed that electron-withdrawing substituents on the benzothiazole ring slow down the reaction, while electron-donating substituents do not enhance the reaction rate.

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Development of mechanistic tools for understanding organic reactions: from manual to automated sampling (2017)

Kinetic studies were conducted on three unrelated reaction types using traditional and modified reaction monitoring tools. The Aza-Piancatelli rearrangement was studied through ReactIR and HPLC-MS to obtain a better understanding of why the substrate scope was limited. It was found that the Lewis acid catalyzed reaction is often zero-order, dependent on the lanthanide metal used. Off-cycle binding of the nucleophile to the Lewis acid was proposed to help explain the zero-order profile. Differences between Lewis and Brønsted acid catalysts were found through subsequent experiments assessing catalyst deactivation and the chemoselectivity of the products in the Aza-Piancatelli rearrangement. An automated sampling system was created for hands-free reaction monitoring and offline analysis by HPLC-MS to provide detailed information about more complicated reactions. The automated sampling system was modified for the study of microwave assisted reactions. This application allowed for more information to be derived from the field of poorly-understood microwave chemistry than allowed by previous technology. Comparisons were made between microwave-assisted and conventionally heated reactions, using a Claisen rearrangement as a model reaction. As expected, it was found that the Claisen rearrangement of allylphenyl ethers displayed similar kinetics between the two heating modes. The technology was also used briefly to search for the existence of non-thermal effects. It was shown that the sampling apparatus could be useful for collecting data observed from microwave-specific effects. Mechanistic studies were also conducted on the Kinugasa reaction to obtain a better understanding of why the reaction generally behaves poorly in regards to the formation of β-lactam product. To study the reaction, samples for HPLC-MS analysis were taken manually, then by a liquid handler, and then through direct-injection to the HPLC. It was found that its side-product formation was directly coupled to the desired product formation, suggesting that both the product and imine side-product stem from a common intermediate. Another little-known side-product was isolated, suggesting the common intermediate could be intercepted by select nucleophiles to form an amide. This finding will direct future attempts to find conditions to favor either β-lactam or amide formation.

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Master's Student Supervision

Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.

Developing a self-driving robotic platform for rapid screening of solid purification methods (2024)

Crystallization is a highly effective method of both isolating and purifying a compound of interest following synthesis. In industry, the development of a crystallization method is a time and labor-intensive process, often requiring a significant amount of impure solid and a strong understanding of the many factors that complicate crystallization processes. Due to these limitations, crystallization design may not be feasible in time or material-limited situations.In this thesis, I outline the development of a self-driving platform that can rapidly screen purification attempts on an impure solid. The platform autonomously collects solubility information and conducts crystallization and washing experiments on the solid, evaluating the yield, purity, and impurity rejection from each attempt. The solvent system is the primary variable screened by the platform. Following a decision tree, a user will arrive at a potential purification method for the process solid, requiring minimal characterization of impurities and using significantly less material than a traditional high-throughput screen. The platform itself is highly modular and reconfigurable; important considerations for integrating filtration, agitation and analytical modules are discussed in detail. Three industry-relevant solids were used to demonstrate the ability of the platform to model solubility data and acquire reproducible data on crystallizations and washing experiments. In one of these case studies, the full decision tree was used to successfully find high-purity crystallization conditions.Information about the impurity profile of the solid is another important factor in designing a purification. The platform is able to autonomously conduct powder dissolution studies on a solid, identifying the retention mechanism for each impurity. This was successfully demonstrated on one test system and three industry-relevant solids, identifying impurity retention mechanisms across a range of categories. Development of the platform is still in progress; future directions are outlined for integrating machine learning abilities, fully automating all decision points, and increasing robustness and accessibility.

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Development and deployment of automated monitoring methodologies mowards investigations of heterogeneous and biphasic reactions (2020)

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.

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