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.

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.

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.

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.

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.

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.

Computational Approach to Molecular Catalysis by 3d Transition Metals: Challenges and Opportunities.

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.

Accurate and rapid prediction of pKa of transition metal complexes: semiempirical quantum chemistry with a data-augmented approach.

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.

Importance of Methane Chemical Potential for Its Conversion to Methanol on Cu-Exchanged Mordenite.

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 [Cu3 (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.

Importance of Methane Chemical Potential for Its Conversion to Methanol on Cu-exchanged Mordenite.

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.

Revisiting van der Waals Radii: From Comprehensive Structural Analysis to Knowledge-Based Classification of Interatomic Contacts.

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.

Revisiting van der Waals Radii: From Comprehensive Structural Analysis to Knowledge-Based Classification of Interatomic Contacts.

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.

Phosphorescent Iridium(III) Complexes with Acyclic Diaminocarbene Ligands as Chemosensors for Mercury.

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(NH2)(NHC6H4-4-X)}] with an ADC ligand reacts selectively with Hg2+ 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.

The accuracy challenge of the DFT-based molecular assignment of 13C MAS NMR characterization of surface intermediates in zeolite catalysis.

The influence of the model and method choice on the DFT predicted 13C NMR chemical shifts of zeolite surface methoxide species has been systematically analyzed. Twelve 13C 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(CH3)-Al surface methoxide species in ZSM-5 zeolite with well-defined experimental NMR parameters (chemical shift, δ(13C) 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 13C 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 13C chemical shifts of zeolite surface intermediates.

Intrinsic Facet-Dependent Reactivity of Well-Defined BiOBr Nanosheets on Photocatalytic Water Splitting.

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.

Photochromic Free MOF-Based Near-Infrared Optical Switch.

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 [Cu2 C4 O8 ] 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.

Multicolor Organometallic Mechanophores for Polymer Imaging Driven by Exciplex Level Interactions.

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.

Hydrocarbon Synthesis via Photoenzymatic Decarboxylation of Carboxylic Acids.

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.

Catalytic (de)hydrogenation promoted by non-precious metals - Co, Fe and Mn: recent advances in an emerging field.

Catalytic hydrogenation and dehydrogenation reactions form the core of the modern chemical industry. This vast class of reactions is found in any part of chemical synthesis starting from the milligram-scale exploratory organic chemistry to the multi-ton base chemicals production. Noble metal catalysis has long been the key driving force in enabling these transformations with carbonyl substrates and their nitrogen-containing counterparts. This review is aimed at introducing the reader to the remarkable progress made in the last three years in the development of base metal catalysts for hydrogenations and dehydrogenative transformations.

Towards operando computational modeling in heterogeneous catalysis.

An increased synergy between experimental and theoretical investigations in heterogeneous catalysis has become apparent during the last decade. Experimental work has extended from ultra-high vacuum and low temperature towards operando conditions. These developments have motivated the computational community to move from standard descriptive computational models, based on inspection of the potential energy surface at 0 K and low reactant concentrations (0 K/UHV model), to more realistic conditions. The transition from 0 K/UHV to operando models has been backed by significant developments in computer hardware and software over the past few decades. New methodological developments, designed to overcome part of the gap between 0 K/UHV and operando conditions, include (i) global optimization techniques, (ii) ab initio constrained thermodynamics, (iii) biased molecular dynamics, (iv) microkinetic models of reaction networks and (v) machine learning approaches. The importance of the transition is highlighted by discussing how the molecular level picture of catalytic sites and the associated reaction mechanisms changes when the chemical environment, pressure and temperature effects are correctly accounted for in molecular simulations. It is the purpose of this review to discuss each method on an equal footing, and to draw connections between methods, particularly where they may be applied in combination.