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Name 23-DNPs-RSCDD-2023-Mg
Extended ID 23-DNPs-RSCDD-2023-Mg_AndolinaSaidi__DS_i0qwoifqvyoe_0
Description Configurations of Mg 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 Mg (100.0%)
Number of Data Objects 2,938
Number of Configurations 2,938
Number of Atoms 57,353
Configuration Sets by Name 23-DNPs-RSCDD-2023_Mg_initial — Initial training configurations of Mg from 23-DNPs-RSCDD-2023
23-DNPs-RSCDD-2023_Mg_adaptive — Adaptive training configurations of Mg from 23-DNPs-RSCDD-2023
Configuration Sets by ID CS_vyp6d49mxmlo_0
Data Objects
ColabFit ID DS_i0qwoifqvyoe_0
Files colabfitspec.json

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