No abstract

Coordination or local environments (e.g., tetrahedra and octahedra) are powerful descriptors of the crystalline structure of materials. These structural descriptors are essential to the understanding of crystal chemistry and the design of new materials. However, extensive statistics on the occurrence of local environment are not available even on common chemistries such as oxides. Here, we present the first large-scale statistical analysis of the coordination environments of cations in oxides using a large set of experimentally observed compounds (about 8000). Using a newly developed method, we provide the distribution of local environment for each cation in oxides. We discuss our results highlighting previously known trends and unexpected coordination environments, as well as compounds presenting very rare coordinations. Our work complements the know-how of the solid state chemist with a statistically sound analysis and paves the way for further data mining efforts linking, for instance, coordination environments to materials properties.

Mixed oxides composed of the four metals Mo, V, Te, and Nb are known to be efficient catalysts in selective oxidation of lower alkanes. The outstanding catalytic performance of such mixed oxides is attributed to the presence of the so-called M1 crystal phase that contains all four elements in the metal positions of the structure. In the present work, an M1 phase composed only of Mo and V has been prepared by hydrothermal synthesis. High crystallinity was achieved by applying a synthesis temperature of 200 °C. The phase-pure mixed MoV oxide was studied as catalyst in the oxidation of propane. In contrast to previous reports, the desirable oxidation product acrylic acid is formed over the Te-free M1 structure in significant amounts, implying that Te is not necessarily required as a component of the active ensemble responsible for selective oxygen insertion. The MoV M1 oxide is, however, less selective compared to that of the M1 structure composed of the four metals Mo, V, Te, and Nb. The reason has been determined by applying a combination of synchrotron-based single crystal structure analysis and near-ambient-pressure X-ray photoelectron spectroscopy. Determination of the crystal structure of MoV M1 oxide reveals partial occupation of sites in the hexagonal channels of the M1 structure by V, which are occupied by Te in MoVTeNb M1 oxide. Hydrolysis of the M-O bonds (M = V, Te) under reaction conditions leads to migration of the metal in the hexagonal channels to the surface. Accumulation of more than 50 at % V on the surface of the MoV M1 oxide most likely causes postcombustion of formed acrylic acid, whereas enrichment of Te at the surface of MoVTeNb M1 oxide results in dilution of surface V5+ species and, consequently, high selectivity

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.