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Organic electrochemistry is currently experiencing an era of renaissance, which is closely related to the possibility of carrying out organic transformations under mild conditions, with high selectivity, high yields, and without the use of toxic solvents. Combination of organic electrochemistry with alternative approaches, such as photo-chemistry was found to have great potential due to induced synergy effects. In this work, we propose for the first time utilization of plasmon triggering of enhanced and regio-controlled organic chemical transformation performed in photoelectrochemical regime. The advantages of the proposed route is demonstrated in the model amination reaction with formation of C-N bond between pyrazole and substituted benzene derivatives. Amination was performed in photo-electrochemical mode on the surface of plasmon active Au@Pt electrode with attention focused on the impact of plasmon triggering on the reaction efficiency and regio-selectivity. The ability to enhance the reaction rate significantly and to tune products regio-selectivity is demonstrated. We also performed density functional theory calculations to inquire about the reaction mechanism and potentially explain the plasmon contribution to electrochemical reaction rate and regioselectivity., (© 2024 The Authors. ChemPlusChem published by Wiley-VCH GmbH.)

Enantioselective hydrogenation of olefins by Rh-based chiral catalysts has been extensively studied for more than 50 years. Naively, one would expect that everything about this transformation is known and that selecting a catalyst that induces the desired reactivity or selectivity is a trivial task. Nonetheless, ligand engineering or selection for any new prochiral olefin remains an empirical trial-error exercise. In this study, we investigated whether machine learning techniques could be used to accelerate the identification of the most efficient chiral ligand. For this purpose, we used high throughput experimentation to build a large dataset consisting of results for Rh-catalyzed asymmetric olefin hydrogenation, specially designed for applications in machine learning. We showcased its alignment with existing literature while addressing observed discrepancies. Additionally, a computational framework for the automated and reproducible quantum-chemistry based featurization of catalyst structures was created. Together with less computationally demanding representations, these descriptors were fed into our machine learning pipeline for both out-of-domain and in-domain prediction tasks of selectivity and reactivity. For out-of-domain purposes, our models provided limited efficacy. It was found that even the most expensive descriptors do not impart significant meaning to the model predictions. The in-domain application, while partly successful for predictions of conversion, emphasizes the need for evaluating the cost-benefit ratio of computationally intensive descriptors and for tailored descriptor design. Challenges persist in predicting enantioselectivity, calling for caution in interpreting results from small datasets. Our insights underscore the importance of dataset diversity with broad substrate inclusion and suggest that mechanistic considerations could improve the accuracy of statistical models., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

In the past decade, computational tools have become integral to catalyst design. They continue to offer significant support to experimental organic synthesis and catalysis researchers aiming for optimal reaction outcomes. More recently, data-driven approaches utilizing machine learning have garnered considerable attention for their expansive capabilities. This Perspective provides an overview of diverse initiatives in the realm of computational catalyst design and introduces our automated tools tailored for high-throughput in silico exploration of the chemical space. While valuable insights are gained through methods for high-throughput in silico exploration and analysis of chemical space, their degree of automation and modularity are key. We argue that the integration of data-driven, automated and modular workflows is key to enhancing homogeneous catalyst design on an unprecedented scale, contributing to the advancement of catalysis research., (© 2023 The Authors. ChemPlusChem published by Wiley-VCH GmbH.)

Computational chemistry pipelines typically commence with geometry generation, well-established for organic compounds but presenting a considerable challenge for transition metal complexes. This paper introduces MACE, an automated computational workflow for converting chemist SMILES/MOL representations of the ligands and the metal center to 3D coordinates for all feasible stereochemical configurations for mononuclear octahedral and square planar complexes directly suitable for quantum chemical computations and implementation in high-throughput computational chemistry workflows. The workflow is validated through a structural screening of a data set of transition metal complexes extracted from the Cambridge Structural Database. To further illustrate the power and capabilities of MACE, we present the results of a model DFT study on the hemilability of pincer ligands in Ru, Fe, and Mn complexes, which highlights the utility of the workflow for both focused mechanistic studies and larger-scale high-throughput pipelines.

The premise of most studies on the homogeneous electrocatalytic CO 2 reduction reaction (CO 2 RR) is a good understanding of the reaction mechanisms. Yet, analyzing the reaction intermediates formed at the working electrode is challenging and not always attainable. Here, we present a new, general approach to studying the reaction intermediates applied for CO 2 RR catalyzed by a series of cobalt complexes. The cobalt complexes were based on the TPA-ligands (TPA = tris(2-pyridylmethyl)amine) modified by amino groups in the secondary coordination sphere. By combining the electrochemical experiments, electrochemistry-coupled electrospray ionization mass spectrometry, with density functional theory (DFT) calculations, we identify and spectroscopically characterize the key reaction intermediates in the CO 2 RR and the competing hydrogen-evolution reaction (HER). Additionally, the experiments revealed the rarely reported in situ changes in the secondary coordination sphere of the cobalt complexes by the CO 2 -initiated transformation of the amino substituents to carbamates. This launched an even faster alternative HER pathway. The interplay of three catalytic cycles, as derived from the experiments and supported by the DFT calculations, explains the trends that cobalt complexes exhibit during the CO 2 RR and HER. Additionally, this study demonstrates the need for a molecular perspective in the electrocatalytic activation of small molecules efficiently obtained by the EC-ESI-MS technique.

A method is introduced for the automated analysis of reactivity exploration for extended in silico databases of transition-metal catalysts. The proposed workflow is designed to tackle two key challenges for bias-free mechanistic explorations on large databases of catalysts: (1) automated exploration of the chemical space around each catalyst with unique structural and chemical features and (2) automated analysis of the resulting large chemical data sets. To address these challenges, we have extended the application of our previously developed ReNeGate method for bias-free reactivity exploration and implemented an automated analysis procedure to identify the classes of reactivity patterns within specific catalyst groups. Our procedure applied to an extended series of representative Mn(I) pincer complexes revealed correlations between structural and reactive features, pointing to new channels for catalyst transformation under the reaction conditions. Such an automated high-throughput virtual screening of systematically generated hypothetical catalyst data sets opens new opportunities for the design of high-performance catalysts as well as an accelerated method for expert bias-free high-throughput in silico reactivity exploration.

The stoichiometric conversion of methane to methanol by Cu-exchanged zeolites can be brought to highest yields by the presence of extraframework Al and high CH 4 chemical potentials. Combining theory and experiments, the differences in chemical reactivity of monometallic Cu-oxo and bimetallic Cu-Al-oxo nanoclusters stabilized in zeolite mordenite (MOR) are investigated. Cu-L 3 edge X-ray absorption near-edge structure (XANES), infrared (IR), and ultraviolet-visible (UV-vis) spectroscopies, in combination with CH 4 oxidation activity tests, support the presence of two types of active clusters in MOR and allow quantification of the relative proportions of each type in dependence of the Cu concentration. Ab initio molecular dynamics (MD) calculations and thermodynamic analyses indicate that the superior performance of materials enriched in Cu-Al-oxo clusters is related to the activity of two μ-oxo bridges in the cluster. Replacing H 2 O with ethanol in the product extraction step led to the formation of ethyl methyl ether, expanding this way the applicability of these materials for the activation and functionalization of CH 4 . We show that competition between different ion-exchanged metal-oxo structures during the synthesis of Cu-exchanged zeolites determines the formation of active species, and this provides guidelines for the synthesis of highly active materials for CH 4 activation and functionalization.

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.

Exploration of the chemical reaction space of chemical transformations in multicomponent mixtures is one of the main challenges in contemporary computational chemistry. To remove expert bias from mechanistic studies and to discover new chemistries, an automated graph-theoretical methodology is proposed, which puts forward a network formalism of homogeneous catalysis reactions and utilizes a network analysis tool for mechanistic studies. The method can be used for analyzing trajectories with single and multiple catalytic species and can provide unique conformers of catalysts including multinuclear catalyst clusters along with other catalytic mixture components. The presented three-step approach has the integrated ability to handle multicomponent catalytic systems of arbitrary complexity (mixtures of reactants, catalyst precursors, ligands, additives, and solvents). It is not limited to predefined chemical rules, does not require prealignment of reaction mixture components consistent with a reaction coordinate, and is not agnostic to the chemical nature of transformations. Conformer exploration, reactive event identification, and reaction network analysis are the main steps taken for identifying the pathways in catalytic systems given the starting precatalytic reaction mixture as the input. Such a methodology allows us to efficiently explore catalytic systems in realistic conditions for either previously observed or completely unknown reactive events in the context of a network representing different intermediates. Our workflow for the catalytic reaction space exploration exclusively focuses on the identification of thermodynamically feasible conversion channels, representative of the (secondary) catalyst deactivation or inhibition paths, which are usually most difficult to anticipate based solely on expert chemical knowledge. Thus, the expert bias is sought to be removed at all steps, and the chemical intuition is limited to the choice of the thermodynamic constraint imposed by the applicable experimental conditions in terms of threshold energy values for allowed transformations. The capabilities of the proposed methodology have been tested by exploring the reactivity of Mn complexes relevant for catalytic hydrogenation chemistry to verify previously postulated activation mechanisms and unravel unexpected reaction channels relevant to rare deactivation events.

Metal-modified zeolites are versatile catalytic materials with a wide range of industrial applications. Their catalytic behaviour is determined by the nature of externally introduced cationic species, i.e. , its geometry, chemical composition, and location within the zeolite pores. Superior catalyst designs can be unlocked by understanding the confinement effect and spatial limitations of the zeolite framework and its influence on the geometry and location of such cationic active sites. In this study, we employ the genetic algorithm (GA) global optimization method to investigate extraframework aluminum species and their structural variations in different zeolite matrices. We focus on extraframework aluminum (EFAl) as a model system because it greatly influences the product selectivity and catalytic stability in several zeolite catalyzed processes. Specifically, the GA was used to investigate the configurational possibilities of EFAl within the mordenite (MOR) and ZSM-5 frameworks. The x TB semi-empirical method within the GA was employed for an automated sampling of the EFAl-zeolite space. Furthermore, geometry refinement at the density functional theory (DFT) level of theory allowed us to improve the most stable configurations obtained from the GA and elaborate on the limitations of the x TB method. A subsequent ab initio thermodynamics analysis (aiTA) was chosen to predict the most favourable EFAl structure(s) under the catalytically relevant operando conditions.

While Mn-catalyzed (de)hydrogenation of carbonyl derivatives has been well established, the reactivity of Mn hydrides with olefins remains very rare. Herein, we report a Mn(I) pincer complex that effectively promotes site-controlled transposition of olefins. This reactivity is shown to emerge once the N-H functionality within the Mn/NH bifunctional complex is suppressed by alkylation. While detrimental for carbonyl (de)hydrogenation, such masking of the cooperative N-H functionality allows for the highly efficient conversion of a wide range of allylarenes to higher-value 1-propenybenzenes in near-quantitative yield with excellent stereoselectivities. The reactivity toward a single positional isomerization was also retained for long-chain alkenes, resulting in the highly regioselective formation of 2-alkenes, which are less thermodynamically stable compared to other possible isomerization products. The detailed mechanistic analysis of the reaction between the activated Mn catalyst and olefins points to catalysis operating via a metal-alkyl mechanism-one of the three conventional transposition mechanisms previously unknown in Mn complexes., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

The choice of a solvent and the reaction conditions often defines the overall behavior of a homogeneous catalytic system by affecting the preferred reaction mechanism and thus the activity and selectivity of the catalytic process. Here, we explore the role of solvation in the mechanism of ketone reduction using a model representative of a bifunctional Mn-diamine catalyst through density functional theory calculations in a microsolvated environment by considering explicit solvent and fully solvated ab initio molecular dynamics simulations for the key elementary steps. Our computational analysis reveals the possibility of a Meerwein-Ponndorf-Verley (MPV) type mechanism in this system, which does not involve the participation of the N-H moiety and the formation of a transition-metal hydride species in ketone conversion. This path was not previously considered for Mn-based metal-ligand cooperative transfer hydrogenation homogeneous catalysis. The MPV mechanism is strongly facilitated by the solvent molecules present in the reaction environment and can potentially contribute to the catalytic performance of other related catalyst systems. Calculations indicate that, despite proceeding effectively in the second coordination sphere of the transition-metal center, the MPV reaction path retains the enantioselectivity preference induced by the presence of the small chiral N , N '-dimethyl-1,2-cyclohexanediamine ligand within the catalytic Mn(I) complex., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

Automation and microfluidic tools potentially enable efficient, fast, and focused reaction development of complex chemistries, while minimizing resource- and material consumption. The introduction of automation-assisted workflows will contribute to the more sustainable development and scale-up of new and improved catalytic technologies. Herein, the application of automation and microfluidics to the development of a complex asymmetric hydrogenation reaction is described. Screening and optimization experiments were performed using an automated microfluidic platform, which enabled a drastic reduction in the material consumption compared to conventional laboratory practices. A suitable catalytic system was identified from a library of Ru II -diamino precatalysts. In situ precatalyst activation was studied with 1 H/ 31 P nuclear magnetic resonance (NMR), and the reaction was scaled up to multigram quantities in a batch autoclave. These reactions were monitored using an automated liquid-phase sampling system. Ultimately, in less than a week of total experimental time, multigram quantities of the target enantiopure alcohol product were provided by this automation-assisted approach., (© 2022 The Authors. ChemSusChem published by Wiley-VCH GmbH.)

Finding alternative ways to tailor the electronic properties of a catalyst to actively and selectively drive reactions of interest has been a growing research topic in the field of electrochemistry. In this Letter, we investigate the tuning of the surface electronic properties of electrocatalysts via polymer modification. We show that when a nickel oxide water oxidation catalyst is coated with polytetrafluoroethylene, stable Ni-CF x bonds are introduced at the nickel oxide/polymer interface, resulting in shifting of the reaction selectivity away from the oxygen evolution reaction and toward hydrogen peroxide formation. It is shown that the electron-withdrawing character of the surface fluorocarbon molecule leaves a slight positive charge on the water oxidation intermediates at the adjacent active nickel sites, making their bonds weaker. The concept of modifying the surface electronic properties of an electrocatalyst via stable polymer modification offers an additional route to tune multipathway reactions in polymer/electrocatalyst environments, like with ionomer-modified catalysts or with membrane electrode assemblies., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

Homogeneously catalyzed reactions often make use of additives and promotors that affect reactivity patterns and improve catalytic performance. While the role of reaction promotors is often discussed in view of their chemical reactivity, we demonstrate that they can be involved in catalysis indirectly. In particular, we demonstrate that promotors can adjust the thermodynamics of key transformations in homogeneous hydrogenation catalysis and enable reactions that would be unfavorable otherwise. We identified this phenomenon in a set of well-established and new Mn pincer catalysts that suffer from persistent product inhibition in ester hydrogenation. Although alkoxide base additives do not directly participate in inhibitory transformations, they can affect the equilibrium constants of these processes. Experimentally, we confirm that by varying the base promotor concentration one can control catalyst speciation and inflict substantial changes to the standard free energies of the key steps in the catalytic cycle. Despite the fact that the latter are universally assumed to be constant, we demonstrate that reaction thermodynamics and catalyst state are subject to external control. These results suggest that reaction promotors can be viewed as an integral component of the reaction medium, on its own capable of improving the catalytic performance and reshaping the seemingly rigid thermodynamic landscape of the catalytic transformation.

The reactivity theories and characterization studies for metal-containing zeolites are often focused on probing the metal sites. We present a detailed computational study of the reactivity of Zn-modified BEA zeolite towards C-H bond activation of the methane molecule as a model system that highlights the importance of representing the active site as the whole reactive ensemble integrating the extra-framework Zn EF 2+ cations, framework oxygens (O F 2- ), and the confined space of the zeolite pores. We demonstrate that for our model system the relationship between the Lewis acidity, defined by the probe molecule adsorption energy, and the activation energy for methane C-H bond cleavage performs with a determination coefficient R 2 = 0.55. This suggests that the acid properties of the localized extra-framework cations can be used only for a rough assessment of the reactivity of the cations in the metal-containing zeolites. In turn, studying the relationship between the activation energy and pyrrole adsorption energy revealed a correlation, with R 2 = 0.80. This observation was accounted for by the similarity between the local geometries of the pyrrole adsorption complexes and the transition states for methane C-H bond cleavage. The inclusion of a simple descriptor for zeolite local confinement allows transferability of the obtained property-activity relations to other zeolite topologies. Our results demonstrate that the representation of the metal cationic species as a synergistically cooperating active site ensembles allows reliable detection of the relationship between the acid properties and reactivity of the metal cation in zeolite materials.

Supported metal catalysts have shown to be efficient for CO 2 conversion due to their multifunctionality and high stability. Herein, we have combined density functional theory calculations with microkinetic modeling to investigate the catalytic reaction mechanisms of CO 2 hydrogenation to CH 3 OH over a recently reported catalyst of Cd 4 /TiO 2 . Calculations reveal that the metal-oxide interface is the active center for CO 2 hydrogenation and methanol formation via the formate pathway dominates over the reverse water-gas shift (RWGS) pathway. Microkinetic modeling demonstrated that formate species on the surface of Cd 4 /TiO 2 is the relevant intermediate for the production of CH 3 OH, and CH 2 O # formation is the rate-determining step. These findings demonstrate the crucial role of the Cd-TiO 2 interface for controlling the CO 2 reduction reactivity and CH 3 OH selectivity., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors. ChemCatChem published by Wiley-VCH GmbH.)

The production of valuable aromatics and the rapid catalyst deactivation due to coking are intimately related in the zeolite-catalyzed aromatization reactions. Here, we demonstrate that these two processes can be decoupled by promoting the Ga/HZSM-5 aromatization catalyst with Ca. The resulting bimetallic catalysts combine high selectivity to light aromatics with extended catalyst lifetime in the methanol-to-aromatics process. Evaluation of the catalytic performance combined with detailed catalyst characterization suggests that the added Ca interacts with the Ga-LAS, with a strong effect on the aromatization processes. A genetic algorithm approach complemented by ab initio thermodynamic analysis is used to elucidate the possible structures of bimetallic extraframework species formed under reaction conditions. The promotion effect of minute amounts of Ca is attributed to the stabilization of the intra-zeolite extraframework gallium oxide clusters with moderated dehydrogenation activity., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

The electrocatalytic CO 2 reduction reaction (CO 2 RR) is one of the key technologies of the clean energy economy. Molecular-level understanding of the CO 2 RR process is instrumental for the better design of electrodes operable at low overpotentials with high current density. The catalytic mechanism underlying the turnover and selectivity of the CO 2 RR is modulated by the nature of the electrocatalyst, as well as the electrolyte liquid, and its ionic components that form the electrical double layer (EDL). Herein we demonstrate the critical non-innocent role of the EDL for the activation and conversion of CO 2 at a high cathodic bias for electrocatalytic conversion over a silver surface as a representative low-cost model cathode. By using a multiscale modeling approach we demonstrate that under such conditions a dense EDL is formed, which hinders the diffusion of CO 2 towards the Ag111 electrocatalyst surface. By combining DFT calculations and ab initio molecular dynamics simulations we identify favorable pathways for CO 2 reduction directly over the EDL without the need for adsorption to the catalyst surface. The dense EDL promotes homogeneous phase reduction of CO 2 via electron transfer from the surface to the electrolyte. Such an outer-sphere mechanism favors the formation of formate as the CO 2 RR product. The formate can undergo dehydration to CO via a transition state stabilized by solvated alkali cations in the EDL., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

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 at automating 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., Competing Interests: There are no conflicts of interest to declare., (This journal is © The Royal Society of Chemistry.)

Homogeneous hydrogenation catalysts based on metal complexes provide a diverse and highly tunable tool for the fine chemical industry. To fully unleash their potential, fast and effective methods for the evaluation of catalytic properties are needed. In turn, this requires changes in the experimental approaches to test and evaluate the performance of the catalytic processes. Design of experiment combined with statistical analysis can enable time- and resource-efficient experimentation. In this work, we employ a set of different statistical models to obtain the detailed kinetic description of a highly active homogeneous Mn (I) ketone hydrogenation catalyst as a representative model system. The reaction kinetics were analyzed using a full second order polynomial regression model, two models with eliminated parameters and finally a model which implements "chemical logic". The coefficients obtained are compared with the corresponding high-quality kinetic parameters acquired using conventional kinetic experiments. We demonstrate that various kinetic effects can be well captured using different statistical models, providing important insights into the reaction kinetics and mechanism of a complex catalytic reaction., Competing Interests: The authors declare no conflict of interest., (© 2021 The Authors. ChemCatChem published by Wiley-VCH GmbH.)

Extraframework cations define the chemical versatility of zeolite catalysts. Addressing their structural complexity and dynamic behavior represents one of the main fundamental challenges in the field. Herein, we present a computational approach for the identification and analysis of the accessible pool of intrazeolite extraframework complexes with a Cu/MOR catalyst as an industrially important model system. We employ ab initio molecular dynamics for capturing the ensemble of reactive isomers with the [Cu 3 O 3 ] 2+ stoichiometry confined in the mordenite channels. The high structural diversity of the generated isomers was ensured by concentrating the kinetic energy along the low-curvature directions of the potential energy surface (PES). Geometrically distinct [Cu 3 O 3 ] 2+ complexes were identified via a series of clustering procedures ensuring that one structure of each local minima is retained. The proposed procedure has resulted in a set of previously unknown peroxo-complexes, which are >50 kJ/mol more stable than the recently hypothesized chair-shaped structure. Our analysis demonstrates that the most stable peroxo-containing clusters can be formed under operando conditions from molecular oxygen and the Cu 3 O unit, similar to that in methane monooxygenase (MMO) enzymes.

Potassium carbonate dispersed over a defective TiO2 support (K2CO3/TiO2) is an efficient catalyst for benzene esterification with CO2 and CH3OH. Density functional theory calculations reveal that this unique catalytic reactivity originates from the cooperation of the Ti3+/K+ surface sites. The K2CO3 promotor steers the stabilization of surface intermediates thus preventing catalyst deactivation.

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 %., Competing Interests: The authors declare no conflict of interest., (© 2021 The Authors. ChemCatChem published by Wiley-VCH GmbH.)

Heterogeneous derivatives of catalysts discovered by Ziegler and Natta are important for the industrial production of polyolefin plastics. However, the interaction between precatalysts, alkylaluminum activators, and oxide supports to form catalytically active materials is poorly understood. This is in contrast to homogeneous or model heterogeneous catalysts that contain resolved molecular structures that relate to activity and selectivity in polymerization reactions. This study describes the reactivity of triisobutylaluminum with high surface area aluminum oxide and a zirconocene precatalyst. Triisobutylaluminum reacts with the zirconocene precatalyst to form hydrides and passivates -OH sites on the alumina surface. The combination of passivated alumina and zirconium hydrides formed in this mixture generates ion pairs that polymerize ethylene., Competing Interests: The authors declare no competing financial interest., (© 2021 The Authors. Published by American Chemical Society.)

The difference in symbiotic specificity between peas of Afghanistan and European phenotypes was investigated using molecular modeling. Considering segregating amino acid polymorphism, we examined interactions of pea LykX-Sym10 receptor heterodimers with four forms of Nodulation factor (NF) that varied in natural decorations (acetylation and length of the glucosamine chain). First, we showed the stability of the LykX-Sym10 dimer during molecular dynamics (MD) in solvent and in the presence of a membrane. Then, four NFs were separately docked to one European and two Afghanistan dimers, and the results of these interactions were in line with corresponding pea symbiotic phenotypes. The European variant of the LykX-Sym10 dimer effectively interacts with both acetylated and non-acetylated forms of NF, while the Afghanistan variants successfully interact with the acetylated form only. We additionally demonstrated that the length of the NF glucosamine chain contributes to controlling the effectiveness of the symbiotic interaction. The obtained results support a recent hypothesis that the LykX gene is a suitable candidate for the unidentified Sym2 allele, the determinant of pea specificity toward Rhizobium leguminosarum bv. viciae strains producing NFs with or without an acetylation decoration. The developed modeling methodology demonstrated its power in multiple searches for genetic determinants, when experimental detection of such determinants has proven extremely difficult., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Solovev, Igolkina, Kuliaev, Sulima, Zhukov, Porozov, Pidko and Andronov.)

The enhancing effect of extraframework Al (EFAl) species on the acidity of bridging hydroxyl groups in a steam-calcined faujasite zeolite (ultrastabilized Y, USY) was investigated by in situ monitoring the H/D exchange reaction between benzene and deuterated zeolites by 1 H MAS NMR spectroscopy. This exchange reaction involves Brønsted acid sites (BAS) located in sodalite cages and supercages. In a reference faujasite zeolite free from EFAl, both populations of BAS are equally and relatively slowly reactive toward C 6 H 6 . In USY, in stark contrast, the H/D exchange of sodalite hydroxyl groups is significantly faster than that of hydroxyl groups located in the faujasite supercages, even though benzene has only access to the supercages. This evidences selective enhancement of BAS near Lewis acidic EFAl species, which according to the NMR findings are located in the faujasite sodalite cages., Competing Interests: The authors declare no competing financial interest., (© 2021 The Authors. Published by American Chemical Society.)

Alkoxycarbonylations are important and versatile reactions that result in the formation of a new C-C bond. Herein, we report on a new and halide-free alkoxycarbonylation reaction that does not require the application of an external carbon monoxide atmosphere. Instead, manganese carbonyl complexes and organo(alkoxy)borate salts react to form an ester product containing the target C-C bond. The required organo(alkoxy)borate salts are conveniently generated from the stoichiometric reaction of an organoborane and an alkoxide salt and can be telescoped without purification. The protocol leads to the formation of both aromatic and aliphatic esters and gives complete control over the ester's substitution (e.g., OMe, O t Bu, OPh). A reaction mechanism was proposed on the basis of stoichiometric reactivity studies, spectroscopy, and DFT calculations. The new chemistry is particularly relevant for the field of Mn(I) catalysis and clearly points to a potential pathway toward irreversible catalyst deactivation., Competing Interests: The authors declare no competing financial interest., (© 2021 The Authors. Published by American Chemical Society.)

According to the ISO 14687-2:2019 standard, the water content of H 2 fuel for transportation and stationary applications should not exceed 5 ppm (molar). To achieve this water content, zeolites can be used as a selective adsorbent for water. In this work, a computational screening study is carried out for the first time to identify potential zeolite frameworks for the drying of high-pressure H 2 gas using Monte Carlo (MC) simulations. We show that the Si/Al ratio and adsorption selectivity have a negative correlation. 218 zeolites available in the database of the International Zeolite Association are considered in the screening. We computed the adsorption selectivity of each zeolite for water from the high-pressure H 2 gas having water content relevant to vehicular applications and near saturation. It is shown that due to the formation of water clusters, the water content in the H 2 gas has a significant effect on the selectivity of zeolites with a helium void fraction larger than 0.1. Under each operating condition, five most promising zeolites are identified based on the adsorption selectivity, the pore limiting diameter, and the volume of H 2 gas that can be dried by 1 dm 3 of zeolite. It is shown that at 12.3 ppm (molar) water content, structures with helium void fractions smaller than 0.07 are preferred. The structures identified for 478 ppm (molar) water content have helium void fractions larger than 0.26. The proposed zeolites can be used to dry 400-8000 times their own volume of H 2 gas depending on the operating conditions. Our findings strongly indicate that zeolites are potential candidates for the drying of high-pressure H 2 gas.

Rapid and accurate prediction of reactivity descriptors of transition metal (TM) complexes is a major challenge for contemporary quantum chemistry. The recently-developed GFN2-xTB method based on the density functional tight-binding theory (DFT-B) is suitable for high-throughput calculation of geometries and thermochemistry for TM complexes albeit with moderate accuracy. Herein we present a data-augmented approach to improve substantially the accuracy of the GFN2-xTB method for the prediction of thermochemical properties using pKa values of TM hydrides as a representative model example. We constructed a comprehensive database for ca. 200 TM hydride complexes featuring the experimentally measured pKa values as well as the GFN2-xTB-optimized geometries and various computed electronic and energetic descriptors. The GFN2-xTB results were further refined and validated by DFT calculations with the hybrid PBE0 functional. Our results show that although the GFN2-xTB performs well in most cases, it fails to adequately describe TM complexes featuring multicarbonyl and multihydride ligand environments. The dataset was analyzed with the ordinary least squares (OLS) fitting and was used to construct an automated machine learning (AutoML) approach for the rapid estimation of pKa of TM hydride complexes. The results obtained show a high predictive power of the very fast AutoML model (RMSE ∼ 2.7) comparable to that of the much slower DFT calculations (RMSE ∼ 3). The presented data-augmented quantum chemistry-based approach is promising for high-throughput computational screening workflows of homogeneous TM-based catalysts.

Any catalyst should be efficient and stable to be implemented in practice. This requirement is particularly valid for manganese hydrogenation catalysts. While representing a more sustainable alternative to conventional noble metal-based systems, manganese hydrogenation catalysts are prone to degrade under catalytic conditions once operation temperatures are high. Herein, we report a highly efficient Mn(I)-CNP pre-catalyst which gives rise to the excellent productivity (TOF° up to 41 000 h -1 ) and stability (TON up to 200 000) in hydrogenation catalysis. This system enables near-quantitative hydrogenation of ketones, imines, aldehydes and formate esters at the catalyst loadings as low as 5-200 p.p.m. Our analysis points to the crucial role of the catalyst activation step for the catalytic performance and stability of the system. While conventional activation employing alkoxide bases can ultimately provide catalytically competent species under hydrogen atmosphere, activation of Mn(I) pre-catalyst with hydride donor promoters, e.g. KHBEt 3 , dramatically improves catalytic performance of the system and eliminates induction times associated with slow catalyst activation.

The reaction medium and conditions are the key parameters defining the efficiency and performance of a homogeneous catalyst. In the state-of-the-art molecular descriptions of catalytic systems by density functional theory (DFT) calculations, the reaction medium is commonly reduced to an infinitely diluted ideal solution model. In this work, we carry out a detailed operando computational modeling analysis of the condition dependencies and nonideal solution effects on the mechanism and kinetics of a model ester hydrogenation reaction by a homogeneous Mn(I)-P,N catalyst. By combining DFT calculations, COSMO-RS solvent model, and the microkinetic modeling approach, the kinetic behavior of the multicomponent homogeneous catalyst system under realistic reaction conditions was investigated in detail. The effects of the reaction medium and its dynamic evolution in the course of the reaction were analyzed by comparing the results obtained for the model methyl acetate hydrogenation reaction in a THF solution and under solvent-free neat reaction conditions. The dynamic representations of the reaction medium give rise to strongly nonlinear effects in the kinetic models. The nonideal representation of the reaction medium results in pronounced condition dependencies of the computed energetics of the elementary reaction steps and the computed kinetic profiles but affects only slightly such experimentally accessible kinetic descriptors as the apparent activation energy and the degree of rate control., Competing Interests: The authors declare no competing financial interest., (© 2020 American Chemical Society.)

The influence of the model and method choice on the DFT predicted 13 C NMR chemical shifts of zeolite surface methoxide species has been systematically analyzed. Twelve 13 C NMR chemical shift calculation protocols on full periodic and hybrid periodic-cluster DFT calculations with varied structural relaxation procedures are examined. The primary assessment of the accuracy of the computational protocols has been carried out for the Si-O(CH 3 )-Al surface methoxide species in ZSM-5 zeolite with well-defined experimental NMR parameters (chemical shift, δ( 13 C) value) as a reference. Different configurations of these surface intermediates and their location inside the ZSM-5 pores are considered explicitly. The predicted δ value deviates by up to ±0.8 ppm from the experimental value of 59 ppm due to the varied confinement of the methoxide species at different zeolite sites (model accuracy). The choice of the exchange-correlation functional (method accuracy) introduces ±1.5 ppm uncertainty in the computed chemical shifts. The accuracy of the predicted 13 C NMR chemical shifts for the computational assignment of spectral characteristics of zeolite intermediates has been further analyzed by considering the potential intermediate species formed upon methane activation by Cu/ZSM-5 zeolite. The presence of Cu species in the vicinity of surface methoxide increases the prediction uncertainty to ±2.5 ppm. The full geometry relaxation of the local environment of an active site at an appropriate level of theory is critical to ensure a good agreement between the experimental and computed NMR data. Chemical shifts (δ) calculated via full geometry relaxation of a cluster model of a relevant portion of the zeolite lattice site are in the best agreement with the experimental values. Our analysis indicates that the full geometry optimization of a cluster model at the PBE0-D3/6-311G(d,p) level of theory followed by GIAO/PBE0-D3/aug-cc-pVDZ calculations is the most suitable approach for the calculation of 13 C chemical shifts of zeolite surface intermediates.

We demonstrate herein an all-optical switch based on stimuli-responsive and photochromic-free metal-organic framework (HKUST-1). Ultrafast near-infrared laser pulses stimulate a reversible 0.4 eV blue shift of the absorption band with up to 200 s -1 rate due to dehydration and concomitant shrinking of the structure-forming [Cu 2 C 4 O 8 ] cages of HKUST-1. Such light-induced switching enables the remote modulation of intensities of photoluminescence of single crystals of HKUST-1 as well visible radiation passing through the crystal by 2 order of magnitude. This opens up the possibility of utilyzing stimuli-responsive MOFs for all-optical data processing devices., (© 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

In this study, we construct a 193 nm ultraviolet laser dissociation high-resolution mass spectrometry (HRMS) platform to produce Pt + cations with high efficiency, which is in situ applied for monitoring the "Pt + + alkanes" reactions (where alkanes include methane, ethane, and propane). The conversion intermediates and products could be accurately determined by an orbitrap detector with high resolution (up to 150 000). Importantly, methane conversion by Pt + cations yields [Pt + ethane] + and [Pt + ethylene] + as the sole products formed via the cross-coupling reaction of the Pt-CH 2 intermediate with gaseous methane. However, the Pt + cations promote only the nonoxidative dehydrogenation of ethane and propane to give the corresponding [Pt + alkenes] + and [Pt + alkynes] + . The details of the reaction mechanism are corroborated by density functional theory (DFT) calculations. These results highlight the power of HRMS with the laser dissociation of metal clusters in the generation and reaction characterization of metal ions.

Lead-free inorganic halide perovskites have triggered appealing interests in various energy-related applications including solar cells and photocatalysis. However, why perovskite-structured materials exhibit excellent photoelectric properties and how the unique crystalline structures affect the charge behaviors are still not well elucidated but essentially desired. Herein, taking inorganic halide perovskite Cs 3 Bi 2 Br 9 as a prototype, the significant derivation process of silver atoms incorporation to induce the structural transformation from Cs 3 Bi 2 Br 9 to Cs 2 AgBiBr 6 , which brings about dramatic differences in photoelectric properties is unraveled. It is demonstrated that the silver incorporation results in the co-operated orbitals hybridization, which makes the electronic distributions in conduction and valence bands of Cs 2 AgBiBr 6 more dispersible, eliminating the strong localization of electron-hole pairs. As consequences of the electronic structures derivation, exhilarating changes in photoelectric properties like band structure, exciton binding energy, and charge carrier dynamics are verified experimentally and theoretically. Using photocatalytic hydrogen evolution activity under visible light as a typical evaluation, such crystalline structure transformation contributes to a more than 100-fold enhancement in photocatalytic performances compared with pristine Cs 3 Bi 2 Br 9 , verifying the significant effect of structural derivations on the exhibited performances. The findings will provide evidences for understanding the origin of photoelectric properties for perovskites semiconductors in solar energy conversion., (© 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Invited for the cover of this issue is the collaborative team of researchers from TU Munich, PNNL and TU Delft. Read the full text of the article at 10.1002/chem.202000772., (© 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Copper-oxo clusters exchanged in zeolite mordenite are active in the stoichiometric conversion of methane to methanol at low temperatures. Here, we show an unprecedented methanol yield per Cu of 0.6, with a 90-95 % selectivity, on a MOR solely containing [Cu 3 (μ-O) 3 ] 2+ active sites. DFT calculations, spectroscopic characterization and kinetic analysis show that increasing the chemical potential of methane enables the utilization of two μ-oxo bridge oxygen out of the three available in the tricopper-oxo cluster structure. Methanol and methoxy groups are stabilized in parallel, leading to methanol desorption in the presence of water., (© 2020 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.)

Surface atomic arrangement and coordination of photocatalysts highly exposed to different crystal facets significantly affect the photoreactivity. However, controversies on the true photoreactivity of a specific facet in heterogeneous photocatalysis still exits. Herein, we exemplified well-defined BiOBr nanosheets dominating with respective facets, (001) and (010), to track the reactivity of crystal facets for photocatalytic water splitting. The real photoreactivity of BiOBr-(001) were evidenced to be significantly higher than BiOBr-(010) for both hydrogen production and oxygen evolution reactions. Further in situ photochemical probing studies verified the distinct reactivity is not only owing to the highly exposed facets, but dominated by the co-exposing facets, leading to an efficient spatial separation of photogenerated charges and further making the oxidation and reduction reactions separately occur with different reaction rates, which ordains the fate of the true photoreactivity., (© 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The front cover artwork is provided by the TheoMAT group of ITMO University (Russia) and the Inorganic Systems Engineering Group of Delft University of Technology (The Netherlands). The image illustrates how one can find the most probable interatomic distance and determine the van der Waals parameters for interatomic interaction from extended and diverse structural datasets. The new approach for background elimination and analysis of extended bulk structural datasets is reported in our paper. Read the full text of the Article at 10.1002/cphc.201901083., (© 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Weak noncovalent interactions are responsible for structure and properties of almost all supramolecular systems, such as nucleic acids, enzymes, and pharmaceutical crystals. However, the analysis of their significance and structural role is not straightforward and commonly requires model studies. Herein, we describe an efficient and universal approach for the analysis of noncovalent interactions and determination of van der Waals radii using the line-of-sight (LoS) concept. The LoS allows to unambiguously identify and classify the "direct" interatomic contacts in complex molecular systems. This approach not only provides an improved theoretical base to molecular "sizes" but also enables the quantitative analysis of specificity, anisotropy, and steric effects of intermolecular interactions., (© 2020 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.)

A new application for bis(cyclometalated) iridium(III) species containing ancillary acyclic diaminocarbene ligands, viz. for sensing of mercury(II) ions, is disclosed. A family of bis(cyclometalated) iridium(III) species supported by both parent isocyanide and acyclic diaminocarbene ligands was prepared, and their electrochemical and photophysical properties were evaluated, revealing efficient blue-green phosphorescence in solution with quantum yields of up to 55%. We uncovered that the photophysical properties of these complexes are dramatically altered by the presence of metal ions and that the complex [Ir(ppy) 2 (CN){C(NH 2 )(NHC 6 H 4 -4-X)}] with an ADC ligand reacts selectively with Hg 2+ ions, enabling its use for sensing of mercury(II) ions in solution. The limit of detection was as low as 2.63 × 10 -7 M, and additional mechanistic studies indicated the formation of an unusual dinuclear iridium(III) cyclometalated intermediate, bridged by a mercury dicyano fragment as a driving force of mercury sensing.

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 CO 2 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., Competing Interests: The authors declare no conflict of interest., (© 2019 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.)

Catalytic reductions of carbonyl-containing compounds are highly important for the safe, sustainable, and economical production of alcohols. Herein, we report on the efficient transfer hydrogenation of ketones catalyzed by a highly potent Mn(I)-NHC complex. Mn-NHC 1 is practical at metal concentrations as low as 75 ppm, thus approaching loadings more conventionally reserved for noble metal based systems. With these low Mn concentrations, catalyst deactivation is found to be highly temperature dependent and becomes especially prominent at increased reaction temperature. Ultimately, understanding of deactivation pathways could help close the activity/stability-gap with Ru and Ir catalysts towards the practical implementation of sustainable earth-abundant Mn-complexes., Competing Interests: The authors declare no conflict of interest., (©2019 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.)

Photoluminescent compounds can undergo various structural changes upon interaction with light. When these changes manifest themselves in the excited state, the resulting emitters can obtain a sensory function. In this work, we designed coordination compounds that can vary their emission color in response to thermal and mechanical stimuli. When embedded in a polymer matrix, Cu-NHC sensors act as mechanophores, and their color-based response can readily describe mechanical stress and phase transition phenomena. A strong practical advantage of new mechanophores over previous generations of organometallic stress sensors stems from their reliance on emission color variations that are easy to detect. In a broad context, our work implies that emission color variations that we often view as thermally governed can also be triggered mechanically and used to generate sensory information.

Computational chemistry provides a versatile toolbox for studying mechanistic details of catalytic reactions and holds promise to deliver practical strategies to enable the rational in silico catalyst design. The versatile reactivity and nontrivial electronic structure effects, common for systems based on 3d transition metals, introduce additional complexity that may represent a particular challenge to the standard computational strategies. In this review, we discuss the challenges and capabilities of modern electronic structure methods for studying the reaction mechanisms promoted by 3d transition metal molecular catalysts. Particular focus will be placed on the ways of addressing the multiconfigurational problem in electronic structure calculations and the role of expert bias in the practical utilization of the available methods. The development of density functionals designed to address transition metals is also discussed. Special emphasis is placed on the methods that account for solvation effects and the multicomponent nature of practical catalytic systems. This is followed by an overview of recent computational studies addressing the mechanistic complexity of catalytic processes by molecular catalysts based on 3d metals. Cases that involve noninnocent ligands, multicomponent reaction systems, metal-ligand and metal-metal cooperativity, as well as modeling complex catalytic systems such as metal-organic frameworks are presented. Conventionally, computational studies on catalytic mechanisms are heavily dependent on the chemical intuition and expert input of the researcher. Recent developments in advanced automated methods for reaction path analysis hold promise for eliminating such human-bias from computational catalysis studies. A brief overview of these approaches is presented in the final section of the review. The paper is closed with general concluding remarks.

A recently discovered photodecarboxylase from Chlorella variabilis NC64A ( CvFAP) bears the promise for the efficient and selective synthesis of hydrocarbons from carboxylic acids. CvFAP, however, exhibits a clear preference for long-chain fatty acids thereby limiting its broad applicability. In this contribution, we demonstrate that the decoy molecule approach enables conversion of a broad range of carboxylic acids by filling up the vacant substrate access channel of the photodecarboxylase. These results not only demonstrate a practical application of a unique, photoactivated enzyme but also pave the way to selective production of short-chain alkanes from waste carboxylic acids under mild reaction conditions.

Quantum chemistry-based codes and methods provide valuable computational tools to estimate reaction energetics and elucidate reaction mechanisms. Electronic structure methods allow directly studying the chemical transformations in molecular systems involving breaking and making of chemical bonds and the associated changes in the electronic structure. The link between the electronic structure and chemical bonding can be provided through the crystal orbital Hamilton population (COHP) analysis that allows quantifying the bond strength by computing Hamilton-weighted populations of localized atomic orbitals. Another important parameter reflecting the nature and strength of a chemical bond is the bond order that can be assessed by the density derived electrostatic and chemical (DDEC6) method which relies on an electron and spin density-partitioning scheme. Herein, we describe a linear correlation that can be established between the DDEC6-derived bond orders and the bond strengths computed with the COHP formalism. We demonstrate that within defined boundaries, the COHP-derived bond strengths can be consistently compared among each other and linked to the DDEC6-derived bond orders independent of the used model. The validity of these correlations and the effective model independence of the electronic descriptors are demonstrated for a variety of gas-phase chemical systems, featuring different types of chemical bonds. Furthermore, the applicability of the derived correlations to the description of complex reaction paths in periodic systems is demonstrated by considering the zeolite-catalyzed Diels-Alder cycloaddition reaction between 2,5-dimethylfuran and ethylene., Competing Interests: The authors declare no competing financial interest.

Ag is a promising catalyst for the production of carbon monoxide (CO) via the electrochemical reduction of carbon dioxide (CO 2 ER). Herein, we study the role of the formate (HCOO - ) intermediate *OCHO, aiming to resolve the discrepancy between the theoretical understanding and experimental performance of Ag. We show that the first coupled proton-electron transfer (CPET) step in the CO pathway competes with the Volmer step for formation of *H, whereas this Volmer step is a prerequisite for the formation of *OCHO. We show that *OCHO should form readily on the Ag surface owing to solvation and favorable binding strength. In situ surface-enhanced Raman spectroscopy (SERS) experiments give preliminary evidence of the presence of O-bound bidentate species on polycrystalline Ag during CO 2 ER which we attribute to *OCHO. Lateral adsorbate interactions in the presence of *OCHO have a significant influence on the surface coverage of *H, resulting in the inhibition of HCOO - and H 2 production and a higher selectivity towards CO., (© 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.)