Dataset
23-Single-Element-DNPs_RSCDD_2023-Ag
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| Name | 23-Single-Element-DNPs_RSCDD_2023-Ag |
|---|---|
| Extended ID | 23-Single-Element-DNPs_RSCDD_2023-Ag__Andolina-Saidi__DS_q4h7q8q0fnve_0 |
| Description | Configurations of Ag 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 |
10.60732/7cf58a2f
https://commons.datacite.org/doi.org/10.60732/7cf58a2f https://doi.datacite.org/dois/10.60732%2F7cf58a2f https://doi.org/10.60732/7cf58a2f Cite as: Andolina, C. M., and Saidi, W. A. "23-Single-Element-DNPs RSCDD 2023-Ag." ColabFit, 2023. https://doi.org/10.60732/7cf58a2f. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
Ag (100.0%)
|
| Number of Configurations | 3,654 |
| Number of Atoms | 99,918 |
| Publication Link | https://doi.org/10.1039/D3DD00046J |
| Data Source Link | https://github.com/saidigroup/23-Single-Element-DNPs |
| Configuration Sets by Name | |
| Configuration Sets by ID | |
| ColabFit ID | DS_q4h7q8q0fnve_0 |
| Downloads | 55 |
| Files | colabfitspec.json |
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