[2Fp01-09] Surface Science(SS2) Chemical Property

[2Fp05] Hydrogen Adsorption on CoCuFeMnNi High Entropy Alloy Surface: A Combined Density Functional Theory and Machine Learning Study

*Allan Abraham Padama¹, Koji Shimizu², Satoshi Watanabe² (1. Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños, 2. Department of Materials Engineering, The University of Tokyo)

We performed density functional theory and machine learning methods to determine the adsorption energy of H atom on CoCuFeMnNi high entropy alloy surface. We found that the CoCuFeMnNi is stable as a face-centered cubic (fcc) solid solution alloy. We calculated, via DFT, the adsorption energies of H atom on the hollow sites of a random subset of the CoCuFeMnNi surfaces. The adsorption of H is influenced by the metal atoms in its nearest neighbor. Cu will tend to reduce the adsorption strength. Meanwhile, Fe and Mn will enhance the adsorption of H. We employed ML algorithm to predict the remaining adsorption energies. We have verified the validity of the algorithm by establishing its accuracy and obtaining good agreement between the DFT calculated and ML predicted values.