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Name 23-Single-Element-DNPs_RSCDD_2023-Nb
Extended ID 23-Single-Element-DNPs_RSCDD_2023-Nb_AndolinaSaidi__DS_zbxayq0diq6l_0
Description Configurations of Nb 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 10.60732/2146db76

Cite as: Andolina, C. M., and Saidi, W. A. "23-Single-Element-DNPs RSCDD 2023-Nb." ColabFit, 2023.
For other citation formats, see the DataCite Fabrica page for this dataset.
Elements Nb (100.0%)
Number of Data Objects 3,246
Number of Configurations 3,246
Number of Atoms 56,191
Configuration Sets by Name 23-Single-Element-DNPs_RSCDD_2023_Nb_initial — Initial training configurations of Nb from 23-Single-Element-DNPs_RSCDD_2023
23-Single-Element-DNPs_RSCDD_2023_Nb_adaptive — Adaptive training configurations of Nb from 23-Single-Element-DNPs_RSCDD_2023
Configuration Sets by ID CS_ow5rv5qea9wb_0
Data Objects
ColabFit ID DS_zbxayq0diq6l_0
Files colabfitspec.json

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