Data for: Ab initio machine-learning unveils strong anharmonicity in non-Arrhenius self-diffusion of tungsten

The dataset contains all necessary files to reproduce the results presented in the article " Ab initio machine-learning unveils strong anharmonicity in non-Arrhenius self-diffusion of tungsten": DFT input files: INCAR, KPOINTS, POTCAR. All POSCAR files for DFT and thermodynamic integration Moment tensor potential (MTP) file Training dataset for MTP All Hessian Matrix files for thermodynamic integration. For transition state, the stabilized Hessian Matrix is provided. All imaginary mode files for transition state Lattice expansion used in all calculations.

本数据集包含了复现论文《基于从头开始的机器学习揭示钨的非阿伦尼乌斯自扩散中的显著非谐性》中呈现结果所需的所有必要文件：DFT 输入文件：INCAR、KPOINTS、POTCAR。所有 DFT 和热力学积分的 POSCAR 文件，以及矩张量势（MTP）文件。MTP 的训练数据集。所有热力学积分的 Hessian 矩阵文件。对于过渡态，提供了稳定的 Hessian 矩阵。所有过渡态的虚振动模式文件。所有计算中使用的晶格膨胀数据。