Configurations of Al 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-Al
Extended ID: 23-Single-Element-DNPs_RSCDD_2023-Al__Andolina-Saidi__DS_8y775we7um7w_0
Description: Configurations of Al 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/ef6f5966
Calculated Property Types:
atomic_forces
cauchy_stress
energy
Elements:
Al (100.0%)
Methods:
DFT-PBE
Software:
VASP
Number of Configurations: 2,537
Number of Atoms: 86,924
Publication Link: https://doi.org/10.1039/D3DD00046J
Data Source Link: https://github.com/saidigroup/23-Single-Element-DNPs
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