Dataset

23_DNPs_RSCDD_2023_Au


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Name 23_DNPs_RSCDD_2023_Au
Extended ID 23-DNPs-RSCDD-2023-Au_AndolinaSaidi__DS_z9wexfuzcghd_0
Description Configurations of Au 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 Au (100.0%)
Number of Data Objects 3,586
Number of Configurations 3,586
Number of Atoms 89,038
Links https://doi.org/10.1039/D3DD00046J
https://github.com/saidigroup/23-Single-Element-DNPs
Configuration Sets by Name 23-DNPs-RSCDD-2023_Au_initial — Initial training configurations of Au from 23-DNPs-RSCDD-2023
23-DNPs-RSCDD-2023_Au_adaptive — Adaptive training configurations of Au from 23-DNPs-RSCDD-2023
Configuration Sets by ID CS_yl6oyd3tyh4x_0
CS_7xqapozo6zid_0
Data Objects
ColabFit ID DS_z9wexfuzcghd_0
Files colabfitspec.json

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