The Impact of Computational Uncertainties on the Enantioselectivity Predictions: A Microkinetic Modeling of Ketone Transfer Hydrogenation with a Noyori-type Mn-diamine Catalyst

Selectivity control is one of the most important functions of a catalyst. In asymmetric catalysis the enantiomeric excess (e.e.) is a property of major interest, with a lot of effort dedicated to developing the most enantioselective catalyst, understanding the origin of selectivity, and predicting stereoselectivity. Herein, we investigate the relationship between predicted selectivity and the uncertainties in the computed energetics of the catalytic reaction mechanism obtained by DFT calculations in a case study of catalytic asymmetric transfer hydrogenation (ATH) of ketones with an Mn-diamine catalyst. Data obtained from our analysis of DFT data by microkinetic modeling is compared to results from experiment. We discuss the limitations of the conventional reductionist approach of e.e. estimation from assessing the enantiodetermining steps only. Our analysis shows that the energetics of other reaction steps in the reaction mechanism have a substantial impact on the predicted reaction selectivity. The uncertainty of DFT calculations within the commonly accepted energy ranges of chemical accuracy may reverse the predicted e.e. with the non-enantiodetermining steps contributing to e.e. deviations of up to 25 %.ChemE/Inorganic Systems EngineeringChemE/Algemee

Operando Modeling of Multicomponent Reactive Solutions in Homogeneous Catalysis: From Non-standard Free Energies to Reaction Network Control

Optimization and execution of chemical reactions are to a large extend based on experience and chemical intuition of a chemist. The chemical intuition is rooted in the phenomenological Le Chatelier's principle that teaches us how to shift equilibrium by manipulating the reaction conditions. To access the underlying thermodynamic parameters and their condition-dependencies from the first principles is a challenge. Here, we present a theoretical approach to model non-standard free energies for a complex catalytic CO2 hydrogenation system under operando conditions and identify the condition spaces where catalyst deactivation can potentially be suppressed. Investigation of the non-standard reaction free energy dependencies allows rationalizing the experimentally observed activity patterns and provides a practical approach to optimization of the reaction paths in complex multicomponent reactive catalytic systems.ChemE/AlgemeenChemE/Inorganic Systems Engineerin

The Nature and Catalytic Function of Cation Sites in Zeolites: a Computational Perspective

Zeolites have a broad spectrum of applications as robust microporous catalysts for various chemical transformations. The reactivity of zeolite catalysts can be tailored by introducing heteroatoms either into the framework or at the extraframework positions that gives rise to the formation of versatile Brønsted acid, Lewis acid and redox-active catalytic sites. Understanding the nature and catalytic role of such sites is crucial for guiding the design of new and improved zeolite-based catalysts. This work presents an overview of recent computational studies devoted to unravelling the molecular level details of catalytic transformations inside the zeolite pores. The role of modern computational chemistry in addressing the structural problem in zeolite catalysis, understanding reaction mechanisms and establishing structure-activity relations is discussed. Special attention is devoted to such mechanistic phenomena as active site cooperativity, multifunctional catalysis as well as confinement-induced and multisite reactivity commonly encountered in zeolite catalysis.ChemE/Catalysis EngineeringChemE/Inorganic Systems Engineerin

Metal containing nanoclusters in zeolites

The molecular-sized void space of the zeolitic micropores is perfect matrices to encapsulate and stabilize multicomponent and multifunctional complexes that can be used as active sites for a wide range of important catalytic transformations. In this article, we discuss and analyze the key developments of the last decade in the catalytic chemistry of metal-containing nanoclusters confined in zeolite micropores. We will present a concise summary of the recent developments in the tailored synthesis strategies, the advanced in-situ and operando characterization techniques, the enhanced performances of zeolite stabilized nanoclusters in various catalytic processes, and the application of computational modeling approaches for addressing the puzzle of catalyst-reactivity relationships. The article will be concluded with a brief discussion on the perspective for future developments anticipated for this field.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.ChemE/Inorganic Systems Engineerin

ChemSpaX: Exploration of chemical space by automated functionalization of molecular scaffold

Exploration of the local chemical space of molecular scaffolds by post-functionalization (PF) is a promising route to discover novel molecules with desired structure and function. PF with rationally chosen substituents based on known electronic and steric properties is a commonly used experimental and computational strategy in screening, design and optimization of catalytic scaffolds. Automated generation of reasonably accurate geometric representations of post-functionalized molecular scaffolds is highly desirable for data-driven applications. However, automated PF of transition metal (TM) complexes remains challenging. In this work a Python-based workflow, ChemSpaX, that is aimed atautomating the PF of a given molecular scaffold with special emphasis on TM complexes, is introduced. In three representative applications of ChemSpaX by comparing with DFT and DFT-B calculations, we show that the generated structures have a reasonable quality for use in computational screening applications. Furthermore, we show that ChemSpaX generated geometries can be used in machine learning applications to accurately predict DFT computed HOMO–LUMO gaps for transition metal complexes. ChemSpaX is open-source and aims to bolster and democratize the efforts of the scientific community towards data-driven chemical discovery.ChemE/Inorganic Systems Engineerin

Homogeneous hydrogenation of saturated bicarbonate slurry to formates using multiphase catalysis

Formic acid and formate salts are key intermediates along the pathways for CO2utilization and hydrogen storage. Herein we report a highly efficient multiphase catalytic system utilizing a ruthenium PNP pincer catalyst for converting supersaturated bicarbonate solutions and slurries to aqueous formate solutions up to 12 M in molarity. The biphasic catalytic system delivers turnover frequencies up to 73 000 h−1and remains stable for up to 474 000 turnovers once reaction conditions are optimized.ChemE/Inorganic Systems EngineeringChemE/Algemee

Mechanistic investigation of benzene esterification by K₂CO₃/TiO₂: The catalytic role of the multifunctional interface

Potassium carbonate dispersed over a defective TiO2support (K2CO3/TiO2) is an efficient catalyst for benzene esterification with CO2and CH3OH. Density functional theory calculations reveal that this unique catalytic reactivity originates from the cooperation of the Ti3+/K+surface sites. The K2CO3promotor steers the stabilization of surface intermediates thus preventing catalyst deactivation.ChemE/Inorganic Systems EngineeringChemE/Algemee

Performance of homogeneous catalysts viewed in dynamics

Effective assessment of catalytic performance is the foundation for the rational design and development of new catalysts with superior performance. The ubiquitous screening/optimization studies use reaction yields as the sole performance metric in an approach that often neglects the complexity of the catalytic system and intrinsic reactivities of the catalysts. Using an example of hydrogenation catalysis, we examine the transient behavior of catalysts that are often encountered in activation, deactivation and catalytic turnover processes. Each of these processes and the reaction environment in which they take place are gradually shown to determine the real-time catalyst speciation and the resulting kinetics of the overall catalytic reaction. As a result, the catalyst performance becomes a complex and time-dependent metric defined by multiple descriptors apart from the reaction yield. This behaviour is not limited to hydrogenation catalysis and affects various catalytic transformations. In this feature article, we discuss these catalytically relevant descriptors in an attempt to arrive at a comprehensive depiction of catalytic performance. ChemE/Inorganic Systems EngineeringTeam Georgy Filonenk

Model-based evaluation and data requirements for parallel kinetic experimentation and data-driven reaction identification and optimization

Recently there has been growing interest in implementing the high-throughput approach to access the dynamics of chemical processes across different fields. With an ever-increasing amount of data provided by high-throughput experimentation, the development of fully-integrated workflows becomes crucial. These workflows should combine novel experimental tools and interpretation methods to convert the data into valuable information. To design feasible data-driven workflows, it is necessary to estimate the value of information and balance it with the number of experiments and resources required. Basing this kind of workflow on actual physical models appears to be a more feasible strategy as compared to data-extensive empirical statistical methods. Here we show an algorithm that constructs and evaluates kinetic models of different complexity. The algorithm facilitates the evaluation of the experimental data quality and quantityrequirements needed for the reliable discovery of the rates driving the corresponding chemical models. The influence of the quality and quantity of data on the obtained results was indicated by the accuracy of the estimates of the kinetic parameters. We also show that this method can be used to find correct reaction scenarios directly from simulated kinetic data with little to no overfitting. Well-fitting models for theoretical data can then be used as a proxy for optimizing the underlying chemical systems. Taking real physical effects into account, this approach goes beyond: we show that with the kinetic models, one can make a direct, unbiased, quantitative connection between kinetic data and the reaction scenario.ChemE/Inorganic Systems Engineerin

Challenges for the utilization of methane as a chemical feedstock

The abundance of methane has led to a strong interest to use methane as a feedstock in the chemical industry. One of the main challenges is the initial activation of the methane molecule. This has resulted in the development of several different approaches to utilize methane, some more developed than others. In this work the current status of the different approaches is discussed and the main issues for industrial utilization described. A special focus of this work is the status of catalyst development.ChemE/Inorganic Systems EngineeringChemE/Algemee