Composition-Designed Multielement Perovskite Oxides for Oxygen Evolution Catalysis

Oxygen evolution reaction (OER) catalysts play an essential role in energy-conversion electrochemical reactions. High-entropy oxides (HEOs) were recently investigated as promising candidates to realize highly active and cost-effective OER catalysts. Since the vast composition space for the HEOs needs considerable efforts to find promising catalysts, the further development beyond simple chemical compositions like equimolar ones has not been achieved yet. In this study, we conducted the fast and efficient design of the perovskite of La(Cr, Mn, Fe, Co, Ni)O3 with high OER catalytic activity using Bayesian optimization and found the relationship between chemical compositions and OER catalytic activities. The multielement perovskites with the optimized compositions exhibited much higher activities than the equimolar LaCr1/5Mn1/5Fe1/5Co1/5Ni1/5O3, which was previously reported as an active catalyst. Bayesian optimization adjusted the concentrations of OER active elements of Fe, Co, and Ni in high contents to enhance the catalytic activities. The optimization also indicates that the OER inactive elements (Cr and Mn) in perovskites even promote the OER activities. These findings suggest the solution of data-based predictions to improve catalytic performances in multielement transition-metal oxides.