|About this Abstract
||7th World Congress on Integrated Computational Materials Engineering (ICME 2023)
||Optimizing AgAuCuPdPt High Entropy Alloy Compositions as Efficient Catalysts for CO2 Reduction Reaction
||Chinmay Dahale, Sriram Goverapet Srinivasan, Beena Rai
|On-Site Speaker (Planned)
||Sriram Goverapet Srinivasan
High entropy alloys (HEA) are emerging as superior catalysts for diverse chemical conversions. While their vast compositional and configurational degrees of freedom offer a rich platform for catalyst discovery, elemental segregation could limit the chemical diversity at the surfaces of these alloys. Building upon our recent work (Dahale et al, Mol. Syst. Des. Eng., 2022,7, 878-888), we use a combination of machine learning based adsorption energy prediction and Bayesian optimization to identify AgAuCuPdPt HEA compositions that are both active and selective for CO2 reduction reaction (CORR). We further show that, the reduction in the chemical diversity at the surface due to elemental segregation causes only a marginal change in the activity but a significant enhancement in the selectivity for CORR.