Dresden 2020 – wissenschaftliches Programm

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O: Fachverband Oberflächenphysik

O 42: Focus Session: Innovation in Machine learning PRocEsses for Surface Science (IMPRESS)

O 42.3: Vortrag

Dienstag, 17. März 2020, 11:30–11:45, TRE Phy

The search of new catalysts for an OCM reaction based on CO2 adsorption properties using data mining technique — •Aliaksei Mazheika1, Frank Rosowski1,2, and Ralph Kraehnert11BasCat, Technische Universitaet Berlin, Berlin, DE — 2BASF SE, Ludwigshafen, DE

The interest in oxidative coupling of methane (OCM) reaction is caused by the fact that this is a relatively simple way for conversion of C1 hydrocarbons (methane) to C2 products (ethane, ethylene). Despite quite many years spent for the search of an efficient catalyst, still the catalyst which would be commercially viable has not been found. Recently Kraehnert et al. have shown that formation of surface carbonates and their decomposition energies play significant role in catalytic performance of materials in OCM reaction [1]. In this study we find the correlation between CO2 adsorption energies on oxide surfaces and formation energies of carbonates. The adsorption energies of carbon dioxide are predicted based on properties of bulk materials, free gas-phase atoms and relaxed surfaces of oxides as proposed by Mazheika et al. [2]. This observation allows us to reformulate experimentally observed volcano plots as the dependence of C2-yield on CO2 adsorption energies. Based on this observation we use a data mining technique subgroup discovery [3] and identify a subgroup of materials with high catalytic activity, and find a way for the search of new materials.

[1] R. Schmack et al., Nat. Comm. 10, 441 (2019).

[2] A. Mazheika et al., manuscript in preparation.

[3] M. Boley et al., Data Min. Knowl. Disc. 31, 1391 (2017).

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