Composition-Designed High Entropy Perovskite Oxides for Oxygen Evolution Catalysis

Abstract

Abstract 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. The vast composition space for HEOs needs considerable efforts to find possible catalysts, which disturbs the further development beyond simple chemical compositions like equimolar ones. In this study, we conducted the fast and efficient design of the perovskite HEOs of La(Cr, Mn, Fe, Co, Ni)O3 with high OER catalytic activity using Bayesian optimization and elucidated the relationship between chemical compositions and OER catalytic activities. The HEOs with optimized compositions exhibited much higher activities than 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 to enhance the catalytic activities and provided the insight that inactive elements (Cr and Mn) in HEOs even promoted the OER activities. These findings suggest the solution of data-based predictions to improve catalytic performances in multi-element transition metal oxides.