Energy Maps of Complex Catalyst Surfaces

• Published in: ACS catalysis Vol. 14; no. 16; pp. 12581 - 12591
• Main Authors: Tarasov, Andrey V., Wrabetz, Sabine, Kröhnert, Jutta, Rosowski, Frank, Schlögl, Robert, Trunschke, Annette
• Format: Journal Article
• Language: English
• Published: American Chemical Society 16.08.2024
• Subjects: microcalorimetry; adsorption sites; propene adsorption; alkane oxidation; propane adsorption
• ISSN: 2155-5435; 2155-5435
• DOI: 10.1021/acscatal.4c01308

Chemical reactions that are crucial for energy conversion require catalysts with intricate functional interfaces characterized by high structural and compositional complexity. Computational catalysis offers predictive insights through the simulation of surface structures and elementary processes, but reliable experimental benchmarks are essential for validation. In this study, we provide such experimental data by determining the energetic distribution of adsorption sites of short-chain alkanes (ethane, propane, n-butane) and alkenes (ethene, propene, 1-butene) on the surface of the polycrystalline oxides V2O5, MnWO4, SmMnO3, and MoVO x , and on the benchmark catalyst vanadyl pyrophosphate (VO)2P2O7 (VPP) using microcalorimetry. From the measurement of the heat of adsorption as a function of the degree of coverage, energy distribution spectra were derived, which represent a quantitative energetic fingerprint of the functional interface. Using the adsorption data, turnover frequencies were determined for the oxidation of propane, which served as a complex probe reaction. The integral heat of adsorption of the reactant propane normalized to the number of adsorption sites was thus determined as a descriptor for activity. Correlation diagrams of propane and propene adsorption allow to predict the selectivity. The maximum turnover frequency of the formation of valuable oxygenates is found at moderate adsorption strength of the intermediate propene. The presented method provides a reference data set for systems where detailed atomistic information about the structure of active sites is difficult to obtain due to their inherent complexity.