Exploration of Reaction Pathways and Chemical Transformation Networks

For the investigation of chemical reaction networks, the identification of all relevant intermediates and elementary reactions is mandatory. Many algorithmic approaches exist that perform explorations efficiently and automatedly. These approaches differ in their application range, the level of completeness of the exploration, as well as the amount of heuristics and human intervention required. Here, we describe and compare the different approaches based on these criteria. Future directions leveraging the strengths of chemical heuristics, human interaction, and physical rigor are discussed.Comment: 48 pages, 4 figure

Spectral rate theory for projected two-state kinetics

Classical rate theories often fail in cases where the observable(s) or order parameter(s) used are poor reaction coordinates or the observed signal is deteriorated by noise, such that no clear separation between reactants and products is possible. Here, we present a general spectral two-state rate theory for ergodic dynamical systems in thermal equilibrium that explicitly takes into account how the system is observed. The theory allows the systematic estimation errors made by standard rate theories to be understood and quantified. We also elucidate the connection of spectral rate theory with the popular Markov state modeling (MSM) approach for molecular simulation studies. An optimal rate estimator is formulated that gives robust and unbiased results even for poor reaction coordinates and can be applied to both computer simulations and single-molecule experiments. No definition of a dividing surface is required. Another result of the theory is a model-free definition of the reaction coordinate quality (RCQ). The RCQ can be bounded from below by the directly computable observation quality (OQ), thus providing a measure allowing the RCQ to be optimized by tuning the experimental setup. Additionally, the respective partial probability distributions can be obtained for the reactant and product states along the observed order parameter, even when these strongly overlap. The effects of both filtering (averaging) and uncorrelated noise are also examined. The approach is demonstrated on numerical examples and experimental single-molecule force probe data of the p5ab RNA hairpin and the apo-myoglobin protein at low pH, here focusing on the case of two-state kinetics

First-principles kinetic modeling in heterogeneous catalysis: an industrial perspective on best-practice, gaps and needs

Electronic structure calculations have emerged as a key contributor in modern heterogeneous catalysis research, though their application in chemical reaction engineering remains largely limited to academia. This perspective aims at encouraging the judicious use of first-principles kinetic models in industrial settings based on a critical discussion of present-day best practices, identifying existing gaps, and defining where further progress is needed

Computational Chemistry Studies of Organometallic Energy Landscapes

Computational chemistry is becoming a widely used tool to investigate the kinetics and thermodynamics of chemical transformations. These investigations are often heavily guided by experiment and require significant mechanistic insight prior to meaningful model development. Recent advances in reaction path finding and automated potential energy surface assessment have enabled faster and easier exploration of complex chemical mechanisms. In combination with mechanistic information, structure energy correspondence provides information which describes how a particular reaction mechanism energetically varies as structure is modulated. Together, the relevant reaction pathways and the structure energy relationships describe the reaction landscape for a given class of reactivity. Chapter 1 introduces the core chemical concepts needed to understand reaction landscapes. The tools and information needed to perform detailed mechanistic exploration via computation are presented and competing methods are summarized. Further discussion of reaction path finding tools is provided through an example involving the reactivity of ammonia borane and carbon dioxide. A discussion of the characteristics which connect potential energy surfaces to quantitative structure activity relationships is used to conclude this chapter. Chapter 2 details the application of an automated reaction path finding tool for the investigation of intuitive and non-intuitive pathways for C(sp3)-N reductive elimination from palladium(IV). This work demonstrates that detailed computational studies using automated reaction path investigation can be used to assess unexpected reaction pathways. These simulations predicted the relative reaction rates with various sulfonamides through consideration of both intuitive and non-intuitive reaction mechanisms. Overall, this chapter demonstrates that combinations of experimental studies and computational tools can provide fundamental mechanistic insights into complex organometallic reaction pathways. This work begins to explore relevant molecular features which appear to trend well with the experimentally observed reactivity. Chapter 3 continues the development of molecular feature based investigation. This chapter was inspired by the possibility of using computational investigations of complex organometallic reaction landscapes to describe structure energy correspondence. This section discusses the development of a thermodynamic landscape to investigate CO2 reduction from cobalt bis(diphosphine) complexes. The construction of a dataset of Co(L)(L’)H2 type complexes from set of commercially available of bis(diphosphines) covering a thermodynamic landscape of over 50 orders of magnitude acidity and hydricity is discussed. These data suggest that relationships between common steric and electronic molecular features are poorly correlated with catalyst thermodynamics. However, a strong correlation between the thermodynamics and Co—H NLMO energy is observed. The landscape provides a clear example of careful electronic balance required for catalytic relevance. The best catalyst identified for future experimental investigations was Co(dCype)H, which is expected to be more acidic and hydridic than previously reported Co(dmpe)2H. While there is still significant work remaining in the development of robust and automated computational chemistry tools, this work outlines some potential applications and details the relevant findings. The final chapter discusses the current limitations and challenges associated with computational reaction discovery. Particular attention is paid to the development of reasonable organometallic computational models for use in reaction landscape investigation.PHDChemistryUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143995/1/ipendlet_1.pd

The Design and Application of Enzyme Inter-residue Interaction Networks Towards Quantum Mechanical Modeling

The Design and Application of Enzyme Inter-residue Interaction Networks Towards Quantum Mechanical Modelin

Non-Steady-State Catalyst Characterization with Thin-Zone TAP Experiments

Rational catalyst design must be advanced beyond its state-of-the-art given the significant economic and environmental relevance of catalytic technologies. To address this challenge, precise kinetic characterization of industrial catalysts is required for elucidating complex reaction mechanisms, establishing structure-activity relationships, and building scientifically-sound microkinetic models of catalytic processes. In this thesis, a novel framework for non-steady-state high-throughput kinetic characterization of complex catalytic reactions is theoretically developed, experimentally validated, and applied to a catalytic reaction of considerable interest. This novel framework of catalyst characterization is based on Temporal Analysis of Products: TAP) experiments. These pulse-response experiments employ Knudsen diffusion as a reliable standard process of gas transport to measure intrinsic rates of chemical transformations on catalysts. Specifically, this work focuses on the Thin- Zone: TZ) configuration of the TAP microreactor which allows monitoring of reaction kinetics for a well-defined and spatially uniform catalyst state with resolution on the millisecond scale. In the TZ TAP reactor, a narrow catalytic sample is packed between two inert zones in order to minimize macroscopic concentration and temperature non-uniformities across the catalyst. Unlike traditional kinetic testing devices such as well-mixed or tubular reactors, the TZ TAP reactor maintains the catalyst in a highly uniform state for an extended range of reactant conversions. One of the main implications of maintaining TZ uniformity is the ability to effectively decouple reaction kinetics from external transport in the microreactor. Typically, TAP data analysis relies on a set of mechanistic assumptions about a reaction in order to obtain kinetic information from coupled reaction-diffusion data. In our framework, intra-pulse kinetic characteristics in the TZ including reaction rates, gaseous concentrations, and surface concentrations are reconstructed from exit flows via the \u27model free\u27 Y-Procedure and then used for elucidating the reaction mechanism and estimating kinetic parameters. The core idea of the data analysis framework developed in this thesis is that the network of elementary steps behind a catalytic reaction can be revealed by examining how reconstructed kinetic characteristics evolve in relation to each other during a pulse-response experiment. Our results suggest, for example, that the temporal coherence between reactant consumption and product generation rates can provide compelling arguments in favor of one potential reaction mechanism over another. The analysis of rate-concentration data can also be used to estimate intrinsic kinetic parameters once the network of reaction steps is identified. These theoretical developments have been translated into a viable experimental methodology which has been validated using well-characterized oxygen uptake on polycrystalline platinum as a benchmark problem. Finally, the Y-Procedure was applied to study CO oxidation and oxygen storage on the Au/SiO2 catalyst prepared by magnetron sputtering. Oxygen was introduced to the catalyst during ow pretreatments under elevated pressure and then titrated o the catalyst by multi-pulse CO sequences under TAP vacuum conditions. The data indicate that oxygen is stored on the catalyst in two kinetically distinct reservoirs. Both reservoirs get filled with oxygen under ow pretreatment, but only one of them directly contributes oxygen for CO oxidation under vacuum. The two reservoirs exchange oxygen between each other and after one of them is depleted by the oxidation reaction during a CO pulse, the second reservoir resupplies oxygen before the next CO pulse arrives. Further research is needed to identify the chemical nature of the second oxygen reservoir. However, our findings testify to the utility of the Y-Procedure as an advanced tool for mechanistic research in catalysis. The thesis outlook section suggests several research directions which will be facilitated by the systematic application of the Y-Procedure

Kinetic Intersections as a Source of Information on Rate Coefficients

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