23-Single-Element-DNPs RSCDD 2023-Re

Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.

Andolina与Saidi于2023年发布的Re元素配置文件，该文件是23个简约、精选的DFT计算属性集合之一，旨在为深度神经网络势（DNPs）的机器学习提供输入。每个元素集合平均包含约4000个结构，每个结构包含27个原子。配置元数据包括可用的材料项目ID，以及用于计算MD轨迹的温度。这些温度对应于熔点（MT）及低于2000K元素的0.25*MT，对于高于2000K的元素，则为MT、0.6*MT及0.25*MT。