Dataset

23-Single-Element-DNPs_RSCDD_2023-Li



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Name 23-Single-Element-DNPs_RSCDD_2023-Li
Extended ID 23-Single-Element-DNPs_RSCDD_2023-Li_AndolinaSaidi__DS_wyo91w20wlgm_0
Description Configurations of Li 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/f5cc2a19
https://commons.datacite.org/doi.org/10.60732/f5cc2a19
https://doi.datacite.org/dois/10.60732%2Ff5cc2a19
https://doi.org/10.60732/f5cc2a19

Cite as: Andolina, C. M., and Saidi, W. A. "23-Single-Element-DNPs RSCDD 2023-Li." ColabFit, 2023. https://doi.org/10.60732/f5cc2a19.
For other citation formats, see the DataCite Fabrica page for this dataset.
Elements Li (100.0%)
Number of Data Objects 2,536
Number of Configurations 2,536
Number of Atoms 93,724
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_Li_initial — Initial training configurations of Li from 23-Single-Element-DNPs_RSCDD_2023
23-Single-Element-DNPs_RSCDD_2023_Li_adaptive — Adaptive training configurations of Li from 23-Single-Element-DNPs_RSCDD_2023
Configuration Sets by ID CS_at0y4eff20n2_0
CS_kz3alvgyhb02_0
Data Objects
ColabFit ID DS_wyo91w20wlgm_0
Files colabfitspec.json

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