Dataset
23-Single-Element-DNPs_RSCDD_2023-Pt
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| Name | 23-Single-Element-DNPs_RSCDD_2023-Pt |
|---|---|
| Extended ID | 23-Single-Element-DNPs_RSCDD_2023-Pt__Andolina-Saidi__DS_0zgz34a90a6i_0 |
| Description | Configurations of Pt 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 |
10.60732/49b97320
https://commons.datacite.org/doi.org/10.60732/49b97320 https://doi.datacite.org/dois/10.60732%2F49b97320 https://doi.org/10.60732/49b97320 Cite as: Andolina, C. M., and Saidi, W. A. "23-Single-Element-DNPs RSCDD 2023-Pt." ColabFit, 2023. https://doi.org/10.60732/49b97320. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
Pt (100.0%)
|
| Number of Configurations | 2,605 |
| Number of Atoms | 62,053 |
| 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_0zgz34a90a6i_0 |
| Downloads | 10 |
| Files | colabfitspec.json |
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