Machine learning-aided unraveling of the importance of structural features for the electrocatalytic oxygen evolution reaction on multimetal oxides based on their A-site metal configurations

Abstract

There is a need for comprehensive descriptors to develop prominent electrocatalysts for use in the oxygen evolution reaction (OER) for water splitting. Through machine learning analysis of the data obtained from multimetal oxides that contain A-site alkaline-/rare-earth and B-site transition metals, this study revealed that the OER activities depend on the A-site-related structures.