Authors: Mads K. Plenge, Jack K. Pedersen, Vladislav A. Mints, Matthias Arenz, Jan Rossmeisl
Published: 2022-11-25
Source: Full article
AbstractThe search for better and cheaper electrocatalysts is vital in the global transition to renewable energy resources. High‐entropy alloys (HEAs) provide a near‐infinite number of different alloys with approximately continuous properties such as catalytic activity. In this work, the catalytic activity for the electrochemical oxygen reduction reaction as a function of molar composition of Ag‐Ir‐Pd‐Pt‐Ru HEA is treated as a landscape wherein it is shown that the maxima are connected through ridges. By following the ridges, it is possible to navigate between the maxima using a modified nudged elastic band (NEB) model integrated in a machine learning NEB algorithm. These results provide a new understanding of the composition space being similar to an evolutionary landscape. This provides a possible new search and design strategy for new catalysts in which the composition of known catalysts can be optimized by following ridges rather than exploring the whole alloy composition space.