Catalyst design with machine learning

Hongliang Xin ()
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Hongliang Xin: Virginia Polytechnic Institute and State University

Nature Energy, 2022, vol. 7, issue 9, 790-791

Abstract: Development of oxygen reduction catalysts is of key importance to a range of energy technologies; however, the process has long relied on slow trial-and-error approaches. Now, accelerated discovery of perovskite oxides for use as air electrodes in solid-oxide fuel cells is achieved with machine learning.

Date: 2022
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DOI: 10.1038/s41560-022-01112-8

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