Dataset

23-DNPs-RSCDD-2023-Mg



Download Dataset XYZ file

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
Links https://doi.org/10.1039/D3DD00046J
https://github.com/saidigroup/23-Single-Element-DNPs
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
CS_unfkdtivzd9s_0
Data Objects
ColabFit ID DS_i0qwoifqvyoe_0
Files colabfitspec.json

No uploaded content is transferred in ownership from the original creators to ColabFit. All content is distributed under the license specified by its contributor who has stated that he or she has the authority to share it under the specified license.