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Name 23-Single-Element-DNPs_RSCDD_2023-Al
Extended ID 23-Single-Element-DNPs_RSCDD_2023-Al_AndolinaSaidi__DS_8y775we7um7w_0
Description Configurations of Al 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
DOI 10.60732/ef6f5966

Cite as: Andolina, C. M., and Saidi, W. A. "23-Single-Element-DNPs RSCDD 2023-Al." ColabFit, 2023.
For other citation formats, see the DataCite Fabrica page for this dataset.
Elements Al (100.0%)
Number of Data Objects 2,572
Number of Configurations 2,572
Number of Atoms 88,139
Configuration Sets by Name 23-Single-Element-DNPs_RSCDD_2023_Al_initial — Initial training configurations of Al from 23-Single-Element-DNPs_RSCDD_2023
23-Single-Element-DNPs_RSCDD_2023_Al_adaptive — Adaptive training configurations of Al from 23-Single-Element-DNPs_RSCDD_2023
Configuration Sets by ID CS_x8imjtsl5lh6_0
Data Objects
ColabFit ID DS_8y775we7um7w_0
Files colabfitspec.json

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