Redefining the Stability of Water Oxidation Electrocatalysts: Insights from Materials Databases and Machine Learning

Research on electrochemical water splitting has experienced significant growth in interest in transition metal borides, carbides, pnictides, and chalcogenides, owing to their notable catalytic performance. These materials, collectively called X-ides, are often considered promising electrocatalysts for the oxygen evolution reaction (OER). However, under the strongly oxidizing conditions of the OER, transition metal X-ides often act as precatalysts, undergoing in situ reconstruction to a different, catalytically active phase. Discrepancies exist in the literature, with some studies claiming the absence of such transformations. Building upon previous efforts to elucidate catalytic performance trends in the community, this Perspective discusses a more nuanced approach to X-ide research, emphasizing the need to reassess our understanding of their chemical stability and the significance of the in situ reconstruction process. By discussing the role of experimental and computational databases, we present strategies for predicting X-ide stability and stress the importance of thorough experimental validation. Moreover, we highlight the use of machine learning to extract meaningful insights from these data and urge the community to adopt a standardized, systematic reporting of X-ide performance. Finally, we provide strategic guidelines and directions to advance transition metal X-ide research, ultimately enhancing their future application for a sustainable hydrogen economy.