Optimization of High-Entropy Alloy Catalyst for Ammonia Decomposition and Ammonia Synthesis

The successful synthesis of high-entropy alloy (HEA) nanoparticles, a long-sought goal in materials science, opens new frontier science with applications across catalysis, structural alloys, and energetic materials. Recently, Co25Mo45Fe10Ni10Cu10 HEA made earth-abundant elements was shown to have high catalytic activity for ammonia decomposition, which rivals that state-of-the-art, but prohibitively expensive, ruthenium catalysts. Using computational approach based on first-principles calculations conjunction data analytics machine learning, we build model rapidly compute the adsorption energy H, N, NHx (x = 1, 2, 3) species CoMoFeNiCu surfaces varied compositions atomic arrangements. We show 25/45 Co/Mo ratio identified experimentally as most active composition decomposition increases likelihood surface adsorbs nitrogen equivalently while at same time interacting moderately strongly intermediates. Our study underscores importance modeling learning identify optimize alloys their near-infinite design space.