Dataset

23-DNPs-RSCDD-2023-Nb


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Name 23-DNPs-RSCDD-2023-Nb
Extended ID 23-DNPs-RSCDD-2023-Nb_AndolinaSaidi__DS_ks6kg4p4dc7r_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
Elements Nb (100.0%)
Number of Data Objects 3,114
Number of Configurations 3,114
Number of Atoms 54,086
Links https://doi.org/10.1039/D3DD00046J
https://github.com/saidigroup/23-Single-Element-DNPs
Configuration Sets by Name 23-DNPs-RSCDD-2023_Nb_initial — Initial training configurations of Nb from 23-DNPs-RSCDD-2023
23-DNPs-RSCDD-2023_Nb_adaptive — Adaptive training configurations of Nb from 23-DNPs-RSCDD-2023
Configuration Sets by ID CS_nbe5orby705b_0
CS_okqgvekffbcu_0
Data Objects
ColabFit ID DS_ks6kg4p4dc7r_0
Files colabfitspec.json

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