Plasmon-Mediated Organic Photoelectrochemistry Applied to Amination Reactions.

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.

MACE: Automated Assessment of Stereochemistry of Transition Metal Complexes and Its Applications in Computational Catalysis.

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.

Electrocatalytic CO2 Reduction: Monitoring of Catalytically Active, Downgraded, and Upgraded Cobalt Complexes.

The premise of most studies on the homogeneous electrocatalytic CO2 reduction reaction (CO2RR) 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 CO2RR 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 CO2RR 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 CO2-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 CO2RR 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.

Paving the road towards automated homogeneous catalyst design.

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.

HiREX: High-Throughput Reactivity Exploration for Extended Databases of Transition-Metal Catalysts.

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.

Speciation and Reactivity Control of Cu-Oxo Clusters via Extraframework Al in Mordenite for Methane Oxidation.

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 CH4 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-L3 edge X-ray absorption near-edge structure (XANES), infrared (IR), and ultraviolet-visible (UV-vis) spectroscopies, in combination with CH4 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 H2O 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 CH4. 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 CH4 activation and functionalization.

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.

ReNeGate: A Reaction Network Graph-Theoretical Tool for Automated Mechanistic Studies in Computational Homogeneous Catalysis.

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.

Global optimization of extraframework ensembles in zeolites: structural analysis of extraframework aluminum species in MOR and MFI zeolites.

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 xTB 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 xTB method. A subsequent ab initio thermodynamics analysis (aiTA) was chosen to predict the most favourable EFAl structure(s) under the catalytically relevant operando conditions.

Switching between Hydrogenation and Olefin Transposition Catalysis via Silencing NH Cooperativity in Mn(I) Pincer Complexes.

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.

CO2 Hydrogenation to Methanol over Cd4/TiO2 Catalyst: Insight into Multifunctional Interface.

Supported metal catalysts have shown to be efficient for CO2 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 CO2 hydrogenation to CH3OH over a recently reported catalyst of Cd4/TiO2. Calculations reveal that the metal-oxide interface is the active center for CO2 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 Cd4/TiO2 is the relevant intermediate for the production of CH3OH, and CH2O# formation is the rate-determining step. These findings demonstrate the crucial role of the Cd-TiO2 interface for controlling the CO2 reduction reactivity and CH3OH selectivity.

Solvent-Assisted Ketone Reduction by a Homogeneous Mn Catalyst.

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.

Polymer Modification of Surface Electronic Properties of Electrocatalysts.

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.

Solvent-mediated outer-sphere CO2 electro-reduction mechanism over the Ag111 surface.

The electrocatalytic CO2 reduction reaction (CO2RR) is one of the key technologies of the clean energy economy. Molecular-level understanding of the CO2RR 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 CO2RR 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 CO2 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 CO2 towards the Ag111 electrocatalyst surface. By combining DFT calculations and ab initio molecular dynamics simulations we identify favorable pathways for CO2 reduction directly over the EDL without the need for adsorption to the catalyst surface. The dense EDL promotes homogeneous phase reduction of CO2 via electron transfer from the surface to the electrolyte. Such an outer-sphere mechanism favors the formation of formate as the CO2RR product. The formate can undergo dehydration to CO via a transition state stabilized by solvated alkali cations in the EDL.

Automation and Microfluidics for the Efficient, Fast, and Focused Reaction Development of Asymmetric Hydrogenation Catalysis.

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 RuII -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.

Basic Promotors Impact Thermodynamics and Catalyst Speciation in Homogeneous Carbonyl Hydrogenation.

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.

High Stability of Methanol to Aromatic Conversion over Bimetallic Ca,Ga-Modified ZSM-5.

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.

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 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.

Property-activity relations of multifunctional reactive ensembles in cation-exchanged zeolites: a case study of methane activation on Zn2+-modified zeolite BEA.

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 ZnEF2+ cations, framework oxygens (OF2-), 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 R2 = 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 R2 = 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.

Unraveling the Nature of Extraframework Catalytic Ensembles in Zeolites: Flexibility and Dynamics of the Copper-Oxo Trimers in Mordenite.

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 [Cu3O3]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 [Cu3O3]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 Cu3O unit, similar to that in methane monooxygenase (MMO) enzymes.