Data-Centric Heterogeneous Catalysis: Identifying Rules and Materials Genes of Alkane Selective Oxidation.

Artificial intelligence (AI) can accelerate catalyst design by identifying key physicochemical descriptive parameters correlated with the underlying processes triggering, favoring, or hindering the performance. In analogy to genes in biology, these parameters might be called "materials genes" of heterogeneous catalysis. However, widely used AI methods require big data, and only the smallest part of the available data meets the quality requirement for data-efficient AI. Here, we use rigorous experimental procedures, designed to consistently take into account the kinetics of the catalyst active states formation, to measure 55 physicochemical parameters as well as the reactivity of 12 catalysts toward ethane, propane, and n-butane oxidation reactions. These materials are based on vanadium or manganese redox-active elements and present diverse phase compositions, crystallinities, and catalytic behaviors. By applying the sure-independence-screening-and-sparsifying-operator symbolic-regression approach to the consistent data set, we identify nonlinear property-function relationships depending on several key parameters and reflecting the intricate interplay of processes that govern the formation of olefins and oxygenates: local transport, site isolation, surface redox activity, adsorption, and the material dynamical restructuring under reaction conditions. These processes are captured by parameters derived from N2 adsorption, X-ray photoelectron spectroscopy (XPS), and near-ambient-pressure in situ XPS. The data-centric approach indicates the most relevant characterization techniques to be used for catalyst design and provides "rules" on how the catalyst properties may be tuned in order to achieve the desired performance.

Shape-Dependent CO2 Hydrogenation to Methanol over Cu2O Nanocubes Supported on ZnO.

The hydrogenation of CO2 to methanol over Cu/ZnO-based catalysts is highly sensitive to the surface composition and catalyst structure. Thus, its optimization requires a deep understanding of the influence of the pre-catalyst structure on its evolution under realistic reaction conditions, including the formation and stabilization of the most active sites. Here, the role of the pre-catalyst shape (cubic vs spherical) in the activity and selectivity of ZnO-supported Cu nanoparticles was investigated during methanol synthesis. A combination of ex situ, in situ, and operando microscopy, spectroscopy, and diffraction methods revealed drastic changes in the morphology and composition of the shaped pre-catalysts under reaction conditions. In particular, the rounding of the cubes and partial loss of the (100) facets were observed, although such motifs remained in smaller domains. Nonetheless, the initial pre-catalyst structure was found to strongly affect its subsequent transformation in the course of the CO2 hydrogenation reaction and activity/selectivity trends. In particular, the cubic Cu particles displayed an increased activity for methanol production, although at the cost of a slightly reduced selectivity when compared to similarly sized spherical particles. These findings were rationalized with the help of density functional theory calculations.

Achieving Digital Catalysis: Strategies for Data Acquisition, Storage and Use.

Heterogeneous catalysis is an important area of research that generates data as intricate as the phenomenon itself. Complexity is inherently coupled to the function of the catalyst and advance in knowledge can only be achieved if this complexity is adequately captured and accounted for. This requires integration of experiment and theory, high data quality and quality control, close interdisciplinary collaboration, and sharing of data and metadata, which is facilitated by the application of joint data management strategies. This Viewpoint Article first discusses the potential of a digital transition in catalysis research. Then, a summary of the current status in terms of data infrastructure in heterogeneous catalysis is presented, defining the various types of (meta-) data, from catalyst synthesis to functional analysis. Finally, an already implemented working concept for local data acquisition and storage is introduced and the benefits and further development directions for catalysis data use and sharing are discussed.

Materials genes of heterogeneous catalysis from clean experiments and artificial intelligence.

ABSTRACT: The performance in heterogeneous catalysis is an example of a complex materials function, governed by an intricate interplay of several processes (e.g., the different surface chemical reactions, and the dynamic restructuring of the catalyst material at reaction conditions). Modeling the full catalytic progression via first-principles statistical mechanics is impractical, if not impossible. Instead, we show here how a tailored artificial-intelligence approach can be applied, even to a small number of materials, to model catalysis and determine the key descriptive parameters ("materials genes") reflecting the processes that trigger, facilitate, or hinder catalyst performance. We start from a consistent experimental set of "clean data," containing nine vanadium-based oxidation catalysts. These materials were synthesized, fully characterized, and tested according to standardized protocols. By applying the symbolic-regression SISSO approach, we identify correlations between the few most relevant materials properties and their reactivity. This approach highlights the underlying physicochemical processes, and accelerates catalyst design. IMPACT STATEMENT: Artificial intelligence (AI) accepts that there are relationships or correlations that cannot be expressed in terms of a closed mathematical form or an easy-to-do numerical simulation. For the function of materials, for example, catalysis, AI may well capture the behavior better than the theory of the past. However, currently the flexibility of AI comes together with a lack of interpretability, and AI can only predict aspects that were included in the training. The approach proposed and demonstrated in this IMPACT article is interpretable. It combines detailed experimental data (called "clean data") and symbolic regression for the identification of the key descriptive parameters (called "materials genes") that are correlated with the materials function. The approach demonstrated here for the catalytic oxidation of propane will accelerate the discovery of improved or novel materials while also enhancing physical understanding. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1557/s43577-021-00165-6.

Nanoparticles Supported on Sub-Nanometer Oxide Films: Scaling Model Systems to Bulk Materials.

Ultrathin layers of oxides deposited on atomically flat metal surfaces have been shown to significantly influence the electronic structure of the underlying metal, which in turn alters the catalytic performance. Upscaling of the specifically designed architectures as required for technical utilization of the effect has yet not been achieved. Here, we apply liquid crystalline phases of fluorohectorite nanosheets to fabricate such architectures in bulk. Synthetic sodium fluorohectorite, a layered silicate, when immersed into water spontaneously and repulsively swells to produce nematic suspensions of individual negatively charged nanosheets separated to more than 60 nm, while retaining parallel orientation. Into these galleries oppositely charged palladium nanoparticles were intercalated whereupon the galleries collapse. Individual and separated Pd nanoparticles were thus captured and sandwiched between nanosheets. As suggested by the model systems, the resulting catalyst performed better in the oxidation of carbon monoxide than the same Pd nanoparticles supported on external surfaces of hectorite or on a conventional Al2 O3 support. XPS confirmed a shift of Pd 3d electrons to higher energies upon coverage of Pd nanoparticles with nanosheets to which we attribute the improved catalytic performance. DFT calculations showed increasing positive charge on Pd weakened CO adsorption and this way damped CO poisoning.

Catalytic activity, water formation, and sintering: Methane activation over Co- and Fe-doped MgO nanocrystals.

Microstructure, structure, and compositional homogeneity of metal oxide nanoparticles can change dramatically during catalysis. Considering the different stabilities of cobalt and iron ions in the MgO host lattice [M. Niedermaier et al., J. Phys. Chem. C 123, 25991 (2019)], we employed MgO nanocube powders with or without transition metal admixtures for the oxidative coupling of methane (OCM) reaction to analyze characteristic differences in catalytic activity and sintering behavior. Undoped MgO nanocrystals exhibit the highest C2 selectivity and retain the nanocrystallinity of the starting material after 24 h time on stream. For the Co-Mg-O nanoparticle powder, which exhibits the highest activity and COx selectivity and where OCM-induced coarsening is strongest, we found that the Co2+ ions remain homogeneously distributed over the MgO lattice. Trivalent Fe ions migrate to the surface of Fe-Mg-O nanoparticles where they form a magnesioferrite phase (MgFe2O4) with a characteristic impact on catalytic performance: Fe-Mg-O is initially less selective than MgO despite its lower activity. An increase in C2 selectivity and a decrease in the CO2/CO ratio with time on stream are attributed to the increasing fraction of coarsened particles that become depleted in redox active Fe. Surface water is a by-product of the OCM reaction, favors mass transport across the particle surfaces, and serves as a sintering aid during catalysis. The characteristic changes in size and morphology of MgO, Co-doped, and Fe-doped MgO particles can be consistently explained by activity and C2 selectivity trends. The original morphology of the nanocubes as a starting material for the OCM reaction does not impact the catalytic activity.

Fluctuating Storage of the Active Phase in a Mn-Na2 WO4 /SiO2 Catalyst for the Oxidative Coupling of Methane.

Structural dynamics of a Mn-Na2 WO4 /SiO2 catalyst were detected directly under reaction conditions during the oxidative coupling of methane via in situ XRD and operando Raman spectroscopy. A new concept of fluctuating storage and release of an active phase in heterogeneous catalysis is proposed that involves the transient generation of active sodium oxide species via a reversible reaction of Na2 WO4 with Mn7 SiO12 . The process is enabled by phase transitions and melting at the high reaction temperatures that are typically applied.

Atomic-Scale Observation of the Metal-Promoter Interaction in Rh-Based Syngas-Upgrading Catalysts.

The direct conversion of syngas to ethanol, typically using promoted Rh catalysts, is a cornerstone reaction in CO2 utilization and hydrogen storage technologies. A rational catalyst development requires a detailed structural understanding of the activated catalyst and the role of promoters in driving chemoselectivity. Herein, we report a comprehensive atomic-scale study of metal-promoter interactions in silica-supported Rh, Rh-Mn, and Rh-Mn-Fe catalysts by aberration-corrected (AC) TEM. While the catalytic reaction leads to the formation of a Rh carbide phase in the Rh-Mn/SiO2 catalyst, the addition of Fe results in the formation of bimetallic Rh-Fe alloys, which further improves the selectivity and prevents the carbide formation. In all promoted catalysts, Mn is present as an oxide decorating the metal particles. Based on the atomic insight obtained, structural and electronic modifications induced by promoters are revealed and a basis for refined theoretical models is provided.

Stepwise Methane-to-Methanol Conversion on CuO/SBA-15.

The direct partial oxidation of methane to methanol is a challenging scientific and economical objective to expand the application of this abundant fuel gas as a major resource for one-step production of value-added chemicals. Despite substantial efforts to commercialize this synthetic route, to date no heterogeneous catalyst can selectively oxidize methane to methanol by O2 with an economically acceptable conversion. Cu-exchanged zeolites have been recently highlighted as one of the most promising bioinspired catalysts toward the direct production of methanol from methane under mild conditions. In this work, Cu-based catalysts were prepared using mesoporous silica SBA-15 as an alternative support and their activity for this conversion was investigated. The results demonstrate that highly dispersed CuO species on SBA-15 are able to react with methane and subsequently produce methanol with high selectivity (>84 %) through water-assisted extraction. Furthermore, it was confirmed that the main intermediate formed after interaction of the catalyst with methane is a methoxyl species, which can be further converted to methanol or dimethyl ether on extraction with water or methanol, respectively.

Insights into structure and dynamics of (Mn,Fe)Ox-promoted Rh nanoparticles.

The mutual interaction between Rh nanoparticles and manganese/iron oxide promoters in silica-supported Rh catalysts for the hydrogenation of CO to higher alcohols was analyzed by applying a combination of integral techniques including temperature-programmed reduction (TPR), X-ray photoelectron spectroscopy (XPS), X-ray absorption spectroscopy (XAS) and Fourier transform infrared (FTIR) spectroscopy with local analysis by using high angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) in combination with energy dispersive X-ray spectroscopy (EDX). The promoted catalysts show reduced CO adsorption capacity as evidenced through FTIR spectroscopy, which is attributed to a perforated core-shell structure of the Rh nano-particles in accordance with the microstructural analysis from electron microscopy. Iron and manganese occur in low formal oxidation states between 2+ and zero in the reduced catalysts as shown by using TPR and XAS. Infrared spectroscopy measured in diffuse reflectance at reaction temperature and pressure indicates that partial coverage of the Rh particles is maintained at reaction temperature under operation and that the remaining accessible metal adsorption sites might be catalytically less relevant because the hydrogenation of adsorbed carbonyl species at 523 K and 30 bar hydrogen essentially failed. It is concluded that Rh0 is poisoned due to the adsorption of CO under the reaction conditions of CO hydrogenation. The active sites are associated either with a (Mn,Fe)Ox (x < 0.25) phase or species at the interface between Rh and its co-catalyst (Mn,Fe)Ox.

A unified view on heterogeneous and homogeneous catalysts through a combination of spectroscopy and quantum chemistry.

Identifying catalytically active structures or intermediates in homogeneous and heterogeneous catalysis is a formidable challenge. However, obtaining experimentally verified insight into the active species in heterogeneous catalysis is a tremendously challenging problem. Many highly advanced spectroscopic and microscopic methods have been developed to probe surfaces. In this discussion we employ a combination of spectroscopic methods to study two closely related systems from the heterogeneous (the silica-supported vanadium oxide VOx/SBA-15) and homogeneous (the complex K[VO(O2)Hheida]) domains. Spectroscopic measurements were conducted strictly in parallel for both systems and consisted of oxygen K-edge and vanadium L-edge X-ray absorption measurements in conjunction with resonance Raman spectroscopy. It is shown that the full information content of the spectra can be developed through advanced quantum chemical calculations that directly address the sought after structure-spectra relationships. To this end we employ the recently developed restricted open shell configuration interaction theory together with the time-dependent theory of electronic spectroscopy to calculate XAS and rR spectra respectively. The results of the study demonstrate that: (a) a combination of several spectroscopic techniques is of paramount importance in identifying signature structural motifs and (b) quantum chemistry is an extremely powerful guide in cross connecting theory and experiment as well as the homogeneous and heterogeneous catalysis fields. It is emphasized that the calculation of spectroscopic observables provides an excellent way for the critical experimental validation of theoretical results.

Hydrothermal synthesis of bi-functional nanostructured manganese tungstate catalysts for selective oxidation.

The mechanism of C-H activation in selective oxidation reactions of short-chain alkane molecules over transition metal oxides is critically affected by the balance of acid-base and redox sites at the surface of the catalyst. Using the example of manganese tungstate we discuss how the relative abundance of these sites can be controlled via synthetic techniques. Phase-pure catalysts composed of the thermodynamic stable monoclinic MnWO4 phase have been prepared using hydrothermal synthesis. Variation of the initial pH value resulted in rod-shaped nano-crystalline MnWO4 catalysts composed of particles with varying aspect ratio. The synthesis products have been analysed using transmission electron microscopy, X-ray diffraction, infrared, and photoelectron spectroscopy. In situ Raman spectroscopy was used to investigate the dissolution-re-crystallization processes occurring under hydrothermal conditions. Ethanol oxidation was applied to probe the surface functionalities in terms of acid-base and redox properties. Changes in the aspect ratio of the primary catalyst particles are reflected in the product distribution induced by altering the fraction of acid-base and redox sites exposed at the surface of the catalysts in agreement with the proposed mechanism of particle growth by re-crystallization during ageing under hydrothermal conditions.

Selective Alkane Oxidation by Manganese Oxide: Site Isolation of MnOx Chains at the Surface of MnWO4 Nanorods.

The electronic and structural properties of vanadium-containing phases govern the formation of isolated active sites at the surface of these catalysts for selective alkane oxidation. This concept is not restricted to vanadium oxide. The deliberate use of hydrothermal techniques can turn the typical combustion catalyst manganese oxide into a selective catalyst for oxidative propane dehydrogenation. Nanostructured, crystalline MnWO4 serves as the support that stabilizes a defect-rich MnOx surface phase. Oxygen defects can be reversibly replenished and depleted at the reaction temperature. Terminating MnOx zigzag chains on the (010) crystal planes are suspected to bear structurally site-isolated oxygen defects that account for the unexpectedly good performance of the catalyst in propane activation.

The impact of steam on the electronic structure of the selective propane oxidation catalyst MoVTeNb oxide (orthorhombic M1 phase).

The selective propane oxidation catalyst MoVTeNb oxide M1 was investigated by microwave conductivity, synchrotron X-ray photoelectron, soft X-ray absorption and resonant photoelectron spectroscopy under reaction conditions to identify the influence of steam on the electronic bulk and surface properties. Steam significantly increases both the conversion of propane and the selectivity to the target product acrylic acid. The increased catalytic performance comes along with a decreased conductivity, a modification of the surface chemical and electronic structure with an enrichment of covalently bonded V(5+) species to the extent of Mo(6+), a decreased work function and hence polarity of the surface and a modified valence band structure. The higher degree of covalency in metal oxide bonds affects the mobility of the free charge carriers, and hence explains the decrease of the conductivity with steam. Furthermore we could prove that a subsurface space charge region depleted in electrons and thus an upward bending of the electronic band structure are induced by the reaction mixture, which is however not dependent on the steam content.

The electronic factor in alkane oxidation catalysis.

This article addresses the fundamental question of whether concepts from semiconductor physics can be applied to describe the working mode of heterogeneous oxidation catalysts and whether they can be even used to discriminate between selective and unselective reaction pathways. Near-ambient-pressure X-ray photoelectron spectroscopy was applied to the oxidation of n-butane to maleic anhydride on the highly selective catalyst vanadyl pyrophosphate and the moderately selective MoVTeNbO(x) M1 phase. The catalysts were found to act like semiconducting gas sensors with a dynamic charge transfer between the bulk and the surface, as indicated by the gas-phase-dependent response of the work function, electron affinity, and the surface potential barrier. In contrast, only a minor influence of the gas phase on the semiconducting properties and hence no dynamic surface potential barrier was monitored for the total oxidation catalyst V2O5. The surface potential barrier is hence suggested as descriptor for selective catalysts.

Direct imaging of octahedral distortion in a complex molybdenum vanadium mixed oxide.

Complex Mo,V-based mixed oxides that crystallize in the orthorhombic M1-type structure are promising candidates for the selective oxidation of small alkanes. The oxygen sublattice of such a complex oxide has been studied by annular bright field scanning transmission electron microscopy. The recorded micrographs directly display the local distortion in the metal oxygen octahedra. From the degree of distortion we are able to draw conclusions on the distribution of oxidation states in the cation columns at different sites. The results are supported by X-ray diffraction and electron paramagnetic resonance measurements that provide integral details about the crystal structure and spin coupling, respectively.

Sites for methane activation on lithium-doped magnesium oxide surfaces.

Density functional calculations yield energy barriers for H abstraction by oxygen radical sites in Li-doped MgO that are much smaller (12±6 kJ mol(-1)) than the barriers inferred from different experimental studies (80-160 kJ mol(-1)). This raises further doubts that the Li(+)O(˙-) site is the active site as postulated by Lunsford. From temperature-programmed oxidative coupling reactions of methane (OCM), we conclude that the same sites are responsible for the activation of CH4 on both Li-doped MgO and pure MgO catalysts. For a MgO catalyst prepared by sol-gel synthesis, the activity proved to be very different in the initial phase of the OCM reaction and in the steady state. This was accompanied by substantial morphological changes and restructuring of the terminations as transmission electron microscopy revealed. Further calculations on cluster models showed that CH4 binds heterolytically on Mg(2+)O(2-) sites at steps and corners, and that the homolytic release of methyl radicals into the gas phase will happen only in the presence of O2.

Carbon dynamics on the molybdenum carbide surface during catalytic propane dehydrogenation.

The effect of the gas-phase chemical potential on surface chemistry and reactivity of molybdenum carbide has been investigated in catalytic reactions of propane in oxidizing and reducing reactant mixtures by adding H2, O2, H2O, and CO2 to a C3H8/N2 feed. The balance between surface oxidation state, phase stability, carbon deposition, and the complex reaction network involving dehydrogenation reactions, hydrogenolysis, metathesis, water-gas shift reaction, hydrogenation, and steam reforming is discussed. Raman spectroscopy and a surface-sensitive study by means of in situ X-ray photoelectron spectroscopy evidence that the dynamic formation of surface carbon species under a reducing atmosphere strongly shifts the product spectrum to the C3-alkene at the expense of hydrogenolysis products. A similar response of selectivity, which is accompanied by a boost of activity, is observed by tuning the oxidation state of Mo in the presence of mild oxidants, such as H2O and CO2, in the feed as well as by V doping. The results obtained allow us to draw a picture of the active catalyst surface and to propose a structure-activity correlation as a map for catalyst optimization.