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

作者：Si Zhu, Nobuyoshi Komai, Shihao Zhang, Shigenobu Ogata · 发表于：Mendeley Data · 年份：2026 · DOI：10.17632/r4pw8vv4z2.1 · 研究领域：Materials science、Thermodynamics、Metallurgy

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.