Towards Experimental Handbooks in Catalysis

The “Seven Pillars” of oxidation catalysis proposed by Robert K. Grasselli represent an early example of phenomenological descriptors in the field of heterogeneous catalysis. Major advances in the theoretical description of catalytic reactions have been achieved in recent years and new catalysts are predicted today by using computational methods. To tackle the immense complexity of high-performance systems in reactions where selectivity is a major issue, analysis of scientific data by artificial intelligence and data science provides new opportunities for achieving improved understanding. Modern data analytics require data of highest quality and sufficient diversity. Existing data, however, frequently do not comply with these constraints. Therefore, new concepts of data generation and management are needed. Herein we present a basic approach in defining best practice procedures of measuring consistent data sets in heterogeneous catalysis using “handbooks”. Selective oxidation of short-chain alkanes over mixed metal oxide catalysts was selected as an example.DFG, 390540038, EXC 2008: Unifying Systems in Catalysis "UniSysCat

Materials Genes of Heterogeneous Catalysis from Clean Experiments and Artificial Intelligence

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 re-structuring of the catalyst material at reaction conditions. Modelling 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.<br /

Materials genes of heterogeneous catalysis from clean experiments and artificial intelligence

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 re-structuring of the catalyst material at reaction conditions. Modelling 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

Promoted Ceria: A Structural, Catalytic, and Computational Study

The role of trivalent (La, Sm, Gd, and Y) and tetravalent (Hf, Zr, and Ti) dopants in the catalytic, structural, and electronic properties of ceria was investigated. Promoted ceria catalysts were synthesized by coprecipitation with ammonia and tested in HCl and CO oxidation. Ceria catalysts exhibit a medium high reactivity and excellent stability in HCl oxidation. The intrinsic reactivity of ceria in HCl oxidation can be improved by a factor of 2 when doping with Hf and Zr in appropriate quantities, whereas trivalent dopants are detrimental. Although both oxidation reactions rely on the existence of oxygen vacancies, the order of reactivity in HCl and CO oxidation is not completely parallel. The effects of promoters on the electronic conductivity and the vacancy formation energy were studied by contactless conductivity experiments using the microwave cavity perturbation technique and by density functional theory calculations. Furthermore, transport properties were also assessed on the basis of theoretical calculations. The order of oxygen vacancy formation energy follows well the order of conductivity (polaron mobility) (trivalent > tetravalent > undoped) observed under inert and oxidizing conditions. This implies that none of these properties correlates with the reactivity. On the other hand, reducing conditions strongly enhanced the conductivity of Hf- and Zr-doped ceria. In HCl oxidation, only the balanced reduction of both Cl and O vacancy formation energies allows for an enhanced reactivity. Promoters give rise to lattice contraction–expansion modifying vacancy formation energies, adsorption properties, and surface coverages

The electronic structure of iridium and its oxides

Iridium-based materials are among the most active and stable electrocatalysts for the oxygen evolution reaction. Amorphous iridium oxide structures are found to be more active than their crystalline counterparts. Herein, we combine synchrotron-based Xray photoemission and absorption spectroscopies with theoretical calculations to investigate the electronic structure of Ir metal, rutile-type IrO2, and an amorphous IrOx. Theory and experiment show that while the Ir 4f line shape of Ir metal is well described by a simple Doniach–Šunji´c function, the peculiar line shape of rutile-type IrO2 requires the addition of a shake-up satellite 1 eV above the main line. In the catalytically more active amorphous IrOx, we find that additional intensity appears in the Ir 4f spectrum at higher binding energy when compared with rutile-type IrO2 along with a pre-edge feature in the OK-edge. We identify these additional features as electronic defects in the anionic and cationic frameworks, namely formally OI and IrIII, which may explain the increased activity of amorphous IrOx electrocatalysts. We corroborate our findings by in situ X-ray diffraction as well as in situ X-ray photoemission and absorption spectroscopies