Dataset

23-Single-Element-DNPs_RSCDD_2023-Sr



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Name 23-Single-Element-DNPs_RSCDD_2023-Sr
Extended ID 23-Single-Element-DNPs_RSCDD_2023-Sr_AndolinaSaidi__DS_o3itca7mk80r_0
Description Configurations of Sr 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 Sr (100.0%)
Number of Data Objects 3,037
Number of Configurations 3,155
Number of Atoms 49,426
Links https://doi.org/10.1039/D3DD00046J
https://github.com/saidigroup/23-Single-Element-DNPs
Configuration Sets by Name 23-Single-Element-DNPs_RSCDD_2023_Sr_initial — Initial training configurations of Sr from 23-Single-Element-DNPs_RSCDD_2023
23-Single-Element-DNPs_RSCDD_2023_Sr_adaptive — Adaptive training configurations of Sr from 23-Single-Element-DNPs_RSCDD_2023
Configuration Sets by ID CS_rvxwpu4oigbw_0
CS_9ujlbe32sbhw_0
Data Objects
ColabFit ID DS_o3itca7mk80r_0
Files colabfitspec.json

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