Mo PRM2019

This dataset was designed to enable machine learning of Mo elastic, thermal, and defect properties, as well as surface energetics, melting, and the structure of the liquid phase. The dataset was constructed by starting with the dataset from J. Byggmästar et al., Phys. Rev. B 100, 144105 (2019), then rescaling all of the configurations to the correct lattice spacing and adding in gamma surface configurations.

本数据集旨在赋能机器学习对莫氏弹性、热力学及缺陷特性的掌握，亦涵盖表面能学、熔化现象以及液相结构的解析。该数据集的构建，起始于J. Byggmästar等人的数据集，发表于《物理评论B》第100卷，144105号（2019年），随后对全部配置进行尺度重整，至适宜的晶格间距，并增补了伽马表面配置。