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Name 23-Single-Element-DNPs_RSCDD_2023-Pb
Extended ID 23-Single-Element-DNPs_RSCDD_2023-Pb_AndolinaSaidi__DS_k065jfggbq43_0
Description Configurations of Pb 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/bddd3245

Cite as: Andolina, C. M., and Saidi, W. A. "23-Single-Element-DNPs RSCDD 2023-Pb." ColabFit, 2023.
For other citation formats, see the DataCite Fabrica page for this dataset.
Elements Pb (100.0%)
Number of Data Objects 5,350
Number of Configurations 5,350
Number of Atoms 119,252
Configuration Sets by Name 23-Single-Element-DNPs_RSCDD_2023_Pb_initial — Initial training configurations of Pb from 23-Single-Element-DNPs_RSCDD_2023
23-Single-Element-DNPs_RSCDD_2023_Pb_adaptive — Adaptive training configurations of Pb from 23-Single-Element-DNPs_RSCDD_2023
Configuration Sets by ID CS_90z96dixchiq_0
Data Objects
ColabFit ID DS_k065jfggbq43_0
Files colabfitspec.json

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