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.

The heat of adsorption and sticking probability of phenol were measured on Ni(111) at 150 K and Pt(111) at 90 K using single crystal adsorption calorimetry (SCAC). Phenol adsorbs molecularly on both Ni(111) and Pt(111), with an initial heat adsorption of 200. kJ/mol on Ni(111) and 220 kJ/mol on Pt(111). The integral heat of adsorption at 1/9 ML coverage (−176 kJ/mol for Ni(111) and −175 kJ/mol for Pt(111)) gives a standard enthalpy of formation (ΔH f 0) for C6H5OHad of −272 kJ/mol on Ni(111) and −271 kJ/mol on Pt(111). The measured bonding energies for phenol to Ni(111) and Pt(111) were compared to density functional theory (DFT) calculations from previous literature, showing that DFT functionals that include van der Waals corrections are more accurate, although some calculations on both surfaces, even those with vdW corrections, still grossly underestimated the adsorption energy.

The energetics of the reactions of water with metal oxide surfaces are of tremendous interest for catalysis, electrocatalysis, and geochemistry, yet the energy for the dissociative adsorption of water was only previously measured on one well-defined oxide surface, iron oxide. In the present paper, the enthalpy of the dissociative adsorption of water is measured on NiO(111)-2 × 2 at 300 K using single-crystal adsorption calorimetry. The differential heat of dissociative adsorption decreases with coverage from 170 to 117 kJ/mol in the first 0.25 ML of coverage. Water adsorbs molecularly on top of that, with a heat of ∼92 kJ/mol. Density functional theory (DFT) calculations reproduce the measured energies well (all within 17 kJ/mol) and provide insight into the atomic-level structure of the surfaces studied experimentally. They show that the oxygen-terminated O-octo(2 × 2) structure is the most stable NiO(111)-2 × 2 termination and gives reaction energies with water that are more consistent with the calorimetry results than the metal-terminated surface. They show that water adsorbs dissociatively on this (2 × 2)-O-octo surface to produce a hydroxyl-covered surface with a heat of adsorption of 171 ± 5 kJ/mol in the low-coverage limit (very close to 170 kJ/mol experimentally) and an integral heat that decreases by 14 kJ/mol up to saturation (compared to ∼30 kJ/mol experimentally). Sensitivity of this reaction’s energy to choice of DFT method is tested using a variety of different exchange correlation functionals, including HSE06, and found to be quite weak.

The crystal structure of perovskites can incorporate a wide variety of cations, which makes this class of materials so interesting for studies of links between solid-state chemistry and catalysis. Perovskites are known as typical total combustion catalysts in hydrocarbon oxidation reactions. The fundamental question that we investigate here is whether surface modifications of perovskites can lead to the formation of valuable reaction products in alkane oxidation. We studied the effect of segregated two-dimensional surface nanostructures on selectivity to propene in the oxidative dehydrogenation of propane. Manganese-based perovskites AMnO 3 (A = La, Sm) were prepared by combustion and hydrothermal synthesis. Bulk and surface structures were investigated by X-ray diffraction, temperature-programmed reduction, aberration-corrected scanning transmission electron microscopy (STEM), multiwavelength Raman, and ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) in combination with near-edge X-ray absorption fine structure (NEXAFS) spectroscopy. Surface oxygen species responsible for C−H activation were distinguished by AP-XPS on the basis of a rigorous in situ analysis of the O 1s spectra recorded under a broad range of reaction conditions. Signals at 529.2, 530.1, 530.9, 531.2, and 531.8 eV were attributed to lattice O, defect-affected O, surface O, oxygen in carbonates, and hydroxyl groups, respectively. Operando AP-XPS revealed critical surface features, which occur under catalyst operation. The catalyst performance depends on the synthesis technique and the reaction conditions. In presence of a two-dimensional MnO x surface phase, addition of steam to the feed resulted in an increase in selectivity to the partial oxidation product propene to practically relevant values. The selectivity increase is related to the presence of Mn in a low oxidation state (2+/3+), an increased concentration of hydroxyl groups, and a higher abundance of adsorbed activated oxygen species on the catalyst surface. The surface analysis of a working catalyst highlights the importance of the termination layer of polycrystalline perovskites as a genuine property implemented by catalyst preparation. Such a termination layer controls the chemical properties and reactivity of perovskites. The information provides input for the development of realistic models that can be used by theory to predict functional properties.

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