configs:
- config_name: default
data_files: main/*.parquet
license: gpl-3.0
tags:
- molecular dynamics
- mlip
- interatomic potential
pretty_name: 23-Single-Element-DNPs RSCDD 2023-Re
Dataset
23-Single-Element-DNPs RSCDD 2023-Re
Description
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.
Additional details stored in dataset columns prepended with "dataset_".
Dataset authors
Christopher M. Andolina, Wissam A. Saidi
Publication
https://doi.org/10.1039/D3DD00046J
Original data link
https://github.com/saidigroup/23-Single-Element-DNPs
License
gpl-3.0
Number of unique molecular configurations
5029
Number of atoms
101248
Elements included
Re
Properties included
energy, atomic forces, cauchy stress
Cite this dataset
Andolina, C. M., and Saidi, W. A. 23-Single-Element-DNPs RSCDD 2023-Re. ColabFit, 2023. https://doi.org/10.60732/1e0997f8