Dataset
23-Single-Element-DNPs_RSCDD_2023-Ti
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| Name | 23-Single-Element-DNPs_RSCDD_2023-Ti |
|---|---|
| Extended ID | 23-Single-Element-DNPs_RSCDD_2023-Ti__Andolina-Saidi__DS_ofpcyxez6xsc_0 |
| Description | Configurations of Ti 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/f08eba7c
https://commons.datacite.org/doi.org/10.60732/f08eba7c https://doi.datacite.org/dois/10.60732%2Ff08eba7c https://doi.org/10.60732/f08eba7c Cite as: Andolina, C. M., and Saidi, W. A. "23-Single-Element-DNPs RSCDD 2023-Ti." ColabFit, 2023. https://doi.org/10.60732/f08eba7c. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
Ti (100.0%) |
| Number of Configurations | 5,665 |
| Number of Atoms | 153,659 |
| 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_Ti_initial — Initial training configurations of Ti from 23-Single-Element-DNPs_RSCDD_2023 23-Single-Element-DNPs_RSCDD_2023_Ti_adaptive — Adaptive training configurations of Ti from 23-Single-Element-DNPs_RSCDD_2023 |
| Configuration Sets by ID |
CS_7omiqh2lk645_0 CS_cobjd30za0cu_0 |
| Calculated Properties | |
| ColabFit ID | DS_ofpcyxez6xsc_0 |
| Files | colabfitspec.json |
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