Dataset

23-Single-Element-DNPs_RSCDD_2023-Co



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Name 23-Single-Element-DNPs_RSCDD_2023-Co
Extended ID 23-Single-Element-DNPs_RSCDD_2023-Co_AndolinaSaidi__DS_jt0lax9yd15r_0
Description Configurations of Co 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 Co (100.0%)
Number of Data Objects 3,337
Number of Configurations 3,356
Number of Atoms 67,320
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_Co_initial — Initial training configurations of Co from 23-Single-Element-DNPs_RSCDD_2023
23-Single-Element-DNPs_RSCDD_2023_Co_adaptive — Adaptive training configurations of Co from 23-Single-Element-DNPs_RSCDD_2023
Configuration Sets by ID CS_930yaofweori_0
CS_glawo3b09ltw_0
Data Objects
ColabFit ID DS_jt0lax9yd15r_0
Files colabfitspec.json

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