Dataset

23-Single-Element-DNPs_RSCDD_2023-Re



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Name 23-Single-Element-DNPs_RSCDD_2023-Re
Extended ID 23-Single-Element-DNPs_RSCDD_2023-Re_AndolinaSaidi__DS_gzbvdicu231p_0
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.
Authors Christopher M. Andolina
Wissam A. Saidi
DOI 10.60732/1e0997f8
https://commons.datacite.org/doi.org/10.60732/1e0997f8
https://doi.datacite.org/dois/10.60732%2F1e0997f8
https://doi.org/10.60732/1e0997f8

Cite as: Andolina, C. M., and Saidi, W. A. "23-Single-Element-DNPs RSCDD 2023-Re." ColabFit, 2023. https://doi.org/10.60732/1e0997f8.
For other citation formats, see the DataCite Fabrica page for this dataset.
Elements Re (100.0%)
Number of Data Objects 5,029
Number of Configurations 5,029
Number of Atoms 101,248
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_Re_initial — Initial training configurations of Re from 23-Single-Element-DNPs_RSCDD_2023
23-Single-Element-DNPs_RSCDD_2023_Re_adaptive — Adaptive training configurations of Re from 23-Single-Element-DNPs_RSCDD_2023
Configuration Sets by ID CS_ajtktbd5todo_0
CS_usuopd9lhi9h_0
Data Objects
ColabFit ID DS_gzbvdicu231p_0
Files colabfitspec.json

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