Name: 23-Single-Element-DNPs_RSCDD_2023-Pt Extended ID: 23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0 Description: Configurations of Pt 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: 10.60732/49b97320 Calculated Property Types: atomic_forces cauchy_stress energy Elements: Pt (100.0%) Methods: DFT-PBE Software: VASP Number of Configurations: 2,605 Number of Atoms: 62,053 Publication Link: https://doi.org/10.1039/D3DD00046J Data Source Link: https://github.com/saidigroup/23-Single-Element-DNPs