Automated Adsorption Workflow for Semiconductor Surfaces and the Application to Zinc Telluride.

J Chem Inf Model

Department of Materials Science and Engineering, University of California, Berkeley, California 94720, United States.

Published: August 2021

Surface adsorption is a crucial step in numerous processes, including heterogeneous catalysis, where the adsorption of key species is often used as a descriptor of efficiency. We present here an automated adsorption workflow for semiconductors which employs density functional theory calculations to generate adsorption data in a high-throughput manner. Starting from a bulk structure, the workflow performs an exhaustive surface search, followed by an adsorption structure construction step, which generates a minimal energy landscape to determine the optimal adsorbate-surface distance. An extensive set of energy-based, charge-based, geometric, and electronic descriptors tailored toward catalysis research are computed and saved to a personal user database. The application of the workflow to zinc telluride, a promising CO reduction photocatalyst, is presented as a case study to illustrate the capabilities of this method and its potential as a material discovery tool.

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http://dx.doi.org/10.1021/acs.jcim.1c00340DOI Listing

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