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.

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.

Green synthesis of propylene oxide directly from propane.

The chemical industry faces the challenge of bringing emissions of climate-damaging CO2 to zero. However, the synthesis of important intermediates, such as olefins or epoxides, is still associated with the release of large amounts of greenhouse gases. This is due to both a high energy input for many process steps and insufficient selectivity of the underlying catalyzed reactions. Surprisingly, we find that in the oxidation of propane at elevated temperature over apparently inert materials such as boron nitride and silicon dioxide not only propylene but also significant amounts of propylene oxide are formed, with unexpectedly small amounts of CO2. Process simulations reveal that the combined synthesis of these two important chemical building blocks is technologically feasible. Our discovery leads the ways towards an environmentally friendly production of propylene oxide and propylene in one step. We demonstrate that complex catalyst development is not necessary for this reaction.

Transition-Metal-Doping of CaO as Catalyst for the OCM Reaction, a Reality Check.

In this study, first-row transition metal-doped calcium oxide materials (Mn, Ni, Cr, Co., and Zn) were synthesized, characterized, and tested for the OCM reaction. Doped carbonate precursors were prepared by a co-precipitation method. The synthesis parameters were optimized to yield materials with a pure calcite phase, which was verified by XRD. EPR measurements on the doped CaO materials indicate a successful substitution of Ca2+ with transition metal ions in the CaO lattice. The materials were tested for their performance in the OCM reaction, where a beneficial effect towards selectivity and activity effect could be observed for Mn, Ni, and Zn-doped samples, where the selectivity of Co- and Cr-doped CaO was strongly reduced. The optimum doping concentration could be identified in the range of 0.04-0.10 atom%, showing the strongest decrease in the apparent activation energy, as well as the maximum increase in selectivity.

The Influence of the Chemical Potential on Defects and Function of Perovskites in Catalysis.

A Sm-deficient Sm0.96MnO3 perovskite was prepared on a gram scale to investigate the influence of the chemical potential of the gas phase on the defect concentration, the oxidation states of the metals and the nature of the oxygen species at the surface. The oxide was treated at 450°C in nitrogen, synthetic air, oxygen, water vapor or CO and investigated for its properties as a catalyst in the oxidative dehydrogenation of propane both before and after treatment. After treatment in water vapor, but especially after treatment with CO, increased selectivity to propene was observed, but only when water vapor was added to the reaction gas. As shown by XRD, SEM, EDX and XRF, the bulk structure of the oxide remained stable under all conditions. In contrast, the surface underwent strong changes. This was shown by AP-XPS and AP-NEXAFS measurements in the presence of the different gas atmospheres at elevated temperatures. The treatment with CO caused a partial reduction of the metals at the surface, leading to changes in the charge of the cations, which was compensated by an increased concentration of oxygen defects. Based on the present experiments, the influence of defects and concentration of electrophilic oxygen species at the catalyst surface on the selectivity in propane oxidation is discussed.

Enhancing the Catalytic Activity of Palladium Nanoparticles via Sandwich-Like Confinement by Thin Titanate Nanosheets.

As atomically thin oxide layers deposited on flat (noble) metal surfaces have been proven to have a significant influence on the electronic structure and thus the catalytic activity of the metal, we sought to mimic this architecture at the bulk scale. This could be achieved by intercalating small positively charged Pd nanoparticles of size 3.8 nm into a nematic liquid crystalline phase of lepidocrocite-type layered titanate. Upon intercalation the galleries collapsed and Pd nanoparticles were captured in a sandwichlike mesoporous architecture showing good accessibility to Pd nanoparticles. On the basis of X-ray photoelectron spectroscopy (XPS) and CO diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS) Pd was found to be in a partially oxidized state, while a reduced Ti species indicated an electronic interaction between nanoparticles and nanosheets. The close contact of titanate sandwiching Pd nanoparticles, moreover, allows for the donation of a lattice oxygen to the noble metal (inverse spillover). Due to the metal-support interactions of this peculiar support, the catalyst exhibited the oxidation of CO with a turnover frequency as high as 0.17 s-1 at a temperature of 100 °C.

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.

Tungsten-niobium oxide bronzes: a bulk and surface structural study.

Materials from the WO3-Nb2O5 system, presenting bronze-type crystal structures, display outstanding functional properties for several applications as thermoelectric materials, lithium-ion battery electrodes, or catalysts. In this work, a series of W-Nb-O oxide bronzes have been synthesized by the hydrothermal method (with Nb/(W + Nb) ratios in the range of 0-1). A combination of bulk and surface characterisation techniques has been applied to get further insights into: (i) the effect of thermal treatments on as-prepared materials and (ii) the surface chemical nature of W-Nb-O oxide bronzes. Thermal treatments promote the following structural changes: (i) loss of emerging long-range order and (ii) the elimination of NH4+ and H2O species from the structural channels of the as-synthesized materials. It has been observed that W-Nb-O bronzes with Nb at% of ca. 50% are able to retain a long-range order after heat-treatments, which is attributed to the presence of a Cs0.5[W2.5Nb2.5O14]-type structure. Increasing amounts of Nb5+ in the materials (i) promote a phase transition to pseudocrystalline phases ordered along the c-axis; (ii) stabilize surface W5+ species (elucidated by XPS); and (iii) increase the proportion of surface Lewis acid sites (as determined by the FTIR of adsorbed CO). Results suggest that pseudocrystalline oxides (with a Nb at% ≥ 50%) are closely related to NbO7 pentagonal bipyramid-containing structures. The stabilisation of Lewis acid sites on these pseudocrystalline materials leads to a higher yield of heavy compounds, at the expense of acrolein formation, in the gas-phase dehydration of glycerol.

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.

Site specific and localized structural displacements in open structured multimetallic oxides.

The structures of solids can locally differ from the macroscopic picture obtained by structural averaging techniques. This difference significantly influences the performance of any functional material. Measurements of these local structures are challenging. Thus, the description of defects is often disregarded. However, in order to understand the functionality, such irregularities have to be investigated. Here, we present a high resolution scanning transmission electron microscopic (STEM) study revealing local structural irregularities in open structured oxides using catalytically active orthorhombic (Mo,V,Te,Nb)Ox as a complex example. Detailed analysis of annular dark field- and annular bright field-STEM images reveal site specific local structural displacements of individual framework and channel sites in the picometer range. These experimental observables can be considered as an important structural addendum for theoretical modelling and should be implemented into the existing data in order to quantify site specific potential energies and stresses. This information can further be used to describe the impact of the structure on the catalytic performance in greater detail.

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.

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.

How to control selectivity in alkane oxidation?

The well-defined particle morphology of crystalline MnWO4 catalysts investigated in the present study facilitates obtaining insight into the origin of selectivity limitations in alkane oxidation. Hydrothermal synthesis at variable pH values granted access to a series of phase-pure MnWO4 catalysts with particles ranging from cube-like (aspect ratio 1.5) to rod- or needle-like (aspect ratio 6.8) shapes. Kinetic studies reveal a strong dependence of the propane consumption rate on the particle shape. The true origin of the structure sensitivity was unraveled by comprehensive bulk and surface analysis using nitrogen adsorption, XRD, SEM, ADF-STEM, STEM-EELS, XPS, multi-laser excitation Raman and DRIFT/operando FTIR spectroscopies, temperature-programmed oxidation (TPO), in situ NEXAFS, and DFT calculations. The active phase is composed of a thin manganese oxy-hydroxide layer formed on the surface of crystalline MnWO4. The differences in catalytic performance within the series clearly illustrate that the structural motif as the most popular descriptor in oxidation catalysis is not essential, since all MnWO4 catalysts in the series under study exhibit the same bulk crystal structure and bulk chemical composition and are phase pure and homogenous. The variable particle shape serves as a proxy that reflects the formation of varying abundance of redox active Mn2+/Mn3+ surface sites, which correlates with catalytic activity. Operando FTIR spectroscopy directly confirms the formation of Mn-OH surface species by abstraction of hydrogen atoms from the propane molecule on nucleophilic oxygen atoms and suggests that active site regeneration occurs via oxidative dehydrogenation of Mn-OH species indicating a single-site nature of the active sites that does not allow four-electron reduction of molecular oxygen. Instead, intermediates are created that cause side reactions and lower the selectivity. The findings highlight fundamental design criteria that may be applied to advance the development of new alkane oxidation catalysts with improved selectivity.

Comparative study of the strongest solid Lewis acids known: ACF and HS-AlF3.

Aluminium chlorofluoride (ACF) and high-surface aluminium fluoride (HS-AlF3) were analyzed by a set of characterization methods to assess their acidic properties: NH3-TPD, CO adsorption followed by DRIFTS, CD3CN-PAS-FTIR and MAS NMR spectroscopy after 15N-pyridine adsorption. Both catalysts contain very strong and medium-strong Lewis acid sites as confirmed by CO adsorption, in which small differences arise from the morphological properties of each catalyst, with ACF being microporous and HS-AlF3 mesoporous. Shifts of the CO vibration band of up to 77 cm-1 were observed, which account for very strong Lewis acid sites. In addition, very strong Lewis acid sites could be identified by CD3CN-PAS for both catalysts, exhibiting a shift of 95 cm-1 from free nitrile, the highest ever reported for a solid Lewis acid.