Dataset

23-Single-Element-DNPs_RSCDD_2023-Mo



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Name 23-Single-Element-DNPs_RSCDD_2023-Mo
Extended ID 23-Single-Element-DNPs_RSCDD_2023-Mo__Andolina-Saidi__DS_bjkftn0ug9r3_0
Description Configurations of Mo 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/b6ece7fd
https://commons.datacite.org/doi.org/10.60732/b6ece7fd
https://doi.datacite.org/dois/10.60732%2Fb6ece7fd
https://doi.org/10.60732/b6ece7fd

Cite as: Andolina, C. M., and Saidi, W. A. "23-Single-Element-DNPs RSCDD 2023-Mo." ColabFit, 2023. https://doi.org/10.60732/b6ece7fd.
For other citation formats, see the DataCite Fabrica page for this dataset.
Property Types atomic_forces
cauchy_stress
energy
Elements Mo (100.0%)
Number of Property Objects 3,718
Number of Configurations 3,718
Number of Atoms 66,612
Links https://github.com/saidigroup/23-Single-Element-DNPs
https://doi.org/10.1039/D3DD00046J
Configuration Sets by Name 23-Single-Element-DNPs_RSCDD_2023_Mo_initial — Initial training configurations of Mo from 23-Single-Element-DNPs_RSCDD_2023
23-Single-Element-DNPs_RSCDD_2023_Mo_adaptive — Adaptive training configurations of Mo from 23-Single-Element-DNPs_RSCDD_2023
Configuration Sets by ID CS_76hrj9n9pbqa_0
CS_d6380tncn94p_0
Property Objects
ColabFit ID DS_bjkftn0ug9r3_0
Files colabfitspec.json

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