Bayesian Optimization of High‐Entropy Alloy Compositions for Electrocatalytic Oxygen Reduction**

Active, selective and stable catalysts are imperative for sustainable energy conversion, engineering materials with such properties highly desired. High-entropy alloys (HEAs) offer a vast compositional space tuning properties. Too vast, however, to traverse without the proper tools. Here, we report use of Bayesian optimization on model based density functional theory (DFT) predict most active compositions electrochemical oxygen reduction reaction (ORR) least possible number sampled two HEAs Ag-Ir-Pd-Pt-Ru Ir-Pd-Pt-Rh-Ru. The discovered optima then scrutinized DFT subjected experimental validation where optimal catalytic activities verified Ag–Pd, Ir–Pt, Pd–Ru binary alloys. This study offers insight into experiments needed optimizing multimetallic which has been determined be order 50 ORR these HEAs.