2021/06/15 by Jack K. Pedersen, Christian M. Clausen, Pedersen, Jack K. +23 · 1 citation
Engineering · #Advanced Materials Characterization Techniques #Chemical Physics (physics.chem-ph) #FOS: Physical sciences #High Entropy Alloys Studies #High-Temperature Coating Behaviors #Materials Science (cond-mat.mtrl-sci)
paper · pdf · doi:10.48550/arxiv.2106.08212
openalex publication_date 2021/06/15 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Active, selective and stable catalysts are imperative for sustainable energy\nconversion, and engineering materials with such properties are highly desired.\nHigh-entropy alloys (HEAs) offer a vast compositional space for tuning such\nproperties. Too vast, however, to traverse without the proper tools. Here, we\nreport the use of Bayesian optimization on a model based on density functional\ntheory (DFT) to predict the most active compositions for the electrochemical\noxygen reduction reaction (ORR) with the least possible number of sampled\ncompositions for the two HEAs Ag-Ir-Pd-Pt-Ru and Ir-Pd-Pt-Rh-Ru. The discovered\noptima are then scrutinized with DFT and subjected to experimental validation\nwhere optimal catalytic activities are verified for Ag-Pd, Ir-Pt, and Pd-Ru\nbinary systems. This study offers insight into the number of experiments needed\nfor exploring the vast compositional space of multimetallic alloys which has\nbeen determined to be on the order of 50 for ORR on these HEAs.\n