Benchmarking Computational Alchemy for Carbide, Nitride, and Oxide Catalysts

24 September 2018, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Kohn-Sham density functional theory (DFT)-based searches for hypothetical catalysts are too computationally demanding for wide searches through diverse materials space. Our group has been critically evaluating the performance of an alternative computational method called computational alchemy. An advantage with this method is that it effectively brings no computational cost once a single DFT reference calculation is made. Extending from our 2017 publication in J. Phys. Chem. Lett (DOI: 10.1021/acs.jpclett.7b01974) that tested computational alchemy for transition metal alloys, we now assess the accuracy of computational alchemy schemes on carbides, nitrides, and oxides.

Keywords

computational catalysis
high throughput screening
binding energy descriptors

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