Dataset

23-Single-Element-DNPs_RSCDD_2023-Sb


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Name 23-Single-Element-DNPs_RSCDD_2023-Sb
Extended ID 23-Single-Element-DNPs_RSCDD_2023-Sb__Andolina-Saidi__DS_z90lfjg88fzo_0
Description Configurations of Sb 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 10.60732/7980ece8
https://commons.datacite.org/doi.org/10.60732/7980ece8
https://doi.datacite.org/dois/10.60732%2F7980ece8
https://doi.org/10.60732/7980ece8

Cite as: Andolina, C. M., and Saidi, W. A. "23-Single-Element-DNPs RSCDD 2023-Sb." ColabFit, 2023. https://doi.org/10.60732/7980ece8.
For other citation formats, see the DataCite Fabrica page for this dataset.
Calculated Property Types atomic_forces
cauchy_stress
energy
Elements Sb (100.0%)
Number of Configurations 5,529
Number of Atoms 122,289
Links https://github.com/saidigroup/23-Single-Element-DNPs
https://doi.org/10.1039/D3DD00046J
Configuration Sets by Name 23-Single-Element-DNPs_RSCDD_2023_Sb_initial — Initial training configurations of Sb from 23-Single-Element-DNPs_RSCDD_2023
23-Single-Element-DNPs_RSCDD_2023_Sb_adaptive — Adaptive training configurations of Sb from 23-Single-Element-DNPs_RSCDD_2023
Configuration Sets by ID CS_hc54smpg9szc_0
CS_phvtq3gu8pz7_0
Calculated Properties
ColabFit ID DS_z90lfjg88fzo_0
Files colabfitspec.json

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