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Name 23-Single-Element-DNPs_RSCDD_2023-Zn
Extended ID 23-Single-Element-DNPs_RSCDD_2023-Zn_AndolinaSaidi__DS_xsad0btc0bsn_0
Description Configurations of Zn 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/dfa1e792

Cite as: Andolina, C. M., and Saidi, W. A. "23-Single-Element-DNPs RSCDD 2023-Zn." ColabFit, 2023.
For other citation formats, see the DataCite Fabrica page for this dataset.
Elements Zn (100.0%)
Number of Data Objects 4,052
Number of Configurations 4,052
Number of Atoms 107,039
Configuration Sets by Name 23-Single-Element-DNPs_RSCDD_2023_Zn_initial — Initial training configurations of Zn from 23-Single-Element-DNPs_RSCDD_2023
23-Single-Element-DNPs_RSCDD_2023_Zn_adaptive — Adaptive training configurations of Zn from 23-Single-Element-DNPs_RSCDD_2023
Configuration Sets by ID CS_khmk1r0jgpve_0
Data Objects
ColabFit ID DS_xsad0btc0bsn_0
Files colabfitspec.json

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