Dataset

23-Single-Element-DNPs_RSCDD_2023-Kr



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Name 23-Single-Element-DNPs_RSCDD_2023-Kr
Extended ID 23-Single-Element-DNPs_RSCDD_2023-Kr_AndolinaSaidi__DS_omnl1yy49sdh_0
Description Configurations of Kr 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 Kr (100.0%)
Number of Data Objects 2,875
Number of Configurations 2,975
Number of Atoms 97,920
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_Kr_initial — Initial training configurations of Kr from 23-Single-Element-DNPs_RSCDD_2023
23-Single-Element-DNPs_RSCDD_2023_Kr_adaptive — Adaptive training configurations of Kr from 23-Single-Element-DNPs_RSCDD_2023
Configuration Sets by ID CS_ul6m9ywmc6fr_0
CS_ngfeueamq03b_0
Data Objects
ColabFit ID DS_omnl1yy49sdh_0
Files colabfitspec.json

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