Name: 23-Single-Element-DNPs_RSCDD_2023-Sr Extended ID: 23-Single-Element-DNPs_RSCDD_2023-Sr__Andolina-Saidi__DS_o3itca7mk80r_0 Description: Configurations of Sr 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. Authors: Christopher M. Andolina Wissam A. Saidi DOI: 10.60732/69de7b6b Calculated Property Types: atomic_forces cauchy_stress energy Elements: Sr (100.0%) Methods: DFT-PBE Software: VASP Number of Configurations: 3,037 Number of Atoms: 48,387 Publication Link: https://doi.org/10.1039/D3DD00046J Data Source Link: https://github.com/saidigroup/23-Single-Element-DNPs