Data for: Wide-Range Predictions of Hydrogen-Dependent Vacancy Diffusion in Nickel from a near-DFT-Accurate Machine-Learning Potential

Si Zhu, Nobuyoshi Komai, Shihao Zhang, Shigenobu Ogata

This archive provides the reproducibility materials associated with the manuscript “Wide-Range Predictions of Hydrogen-Dependent Vacancy Diffusion in Nickel from a near-DFT-Accurate Machine-Learning Potential.” It contains the numerical data underlying the manuscript figures and diffusion maps, representative EHTI MD/GCMC input files, the trained MTP potential for the Ni–H system, and the corresponding training and validation datasets.