colabfit/Mo_PRM2019
收藏Hugging Face2025-04-01 更新2025-04-12 收录
下载链接：
https://hf-mirror.com/datasets/colabfit/Mo_PRM2019
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资源简介：
Mo PRM2019数据集是为了使机器学习能够对钼（Mo）的弹性、热学、缺陷性质，以及表面能、熔点和液相结构进行学习而设计的。该数据集是在J. Byggmästar等人的研究基础上构建的，对原始配置进行了重新缩放，并添加了gamma表面配置。数据集包含了3785个独特的分子配置，共45667个原子，涵盖了能量、原子力、柯西应力等属性。
The Mo PRM2019 dataset is designed to enable machine learning for the elastic, thermal, and defect properties of molybdenum (Mo), as well as surface energetics, melting point, and the structure of the liquid phase. The dataset is constructed based on the work of J. Byggmästar et al., with rescaling of the original configurations and the addition of gamma surface configurations. It includes 3785 unique molecular configurations, totaling 45667 atoms, and covers properties such as energy, atomic forces, and Cauchy stress.
提供机构：
colabfit
