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.
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
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