Dataset
Ta_PRM2019
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| Name | Ta_PRM2019 |
|---|---|
| Extended ID | Ta_PRM2019__Byggmastar-Nordlund-Djurabekova__DS_40zw467dnc6d_0 |
| Description | This dataset was designed to enable machine-learning of Ta elastic, thermal, and defect properties, as well as surface energetics, melting, and the structure of the liquid phase. The dataset was constructed by starting with the dataset from J. Byggmästar et al., Phys. Rev. B 100, 144105 (2019), then rescaling all of the configurations to the correct lattice spacing and adding in gamma surface configurations. |
| Authors |
Jesper Byggmästar Kai Nordlund Flyura Djurabekova |
| DOI |
10.60732/43837a12
https://commons.datacite.org/doi.org/10.60732/43837a12 https://doi.datacite.org/dois/10.60732%2F43837a12 https://doi.org/10.60732/43837a12 Cite as: Byggmästar, J., Nordlund, K., and Djurabekova, F. "Ta PRM2019." ColabFit, 2023. https://doi.org/10.60732/43837a12. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
Ta (100.0%)
|
| Number of Configurations | 3,773 |
| Number of Atoms | 45,385 |
| Publication Link | https://doi.org/10.1103/PhysRevMaterials.4.093802 |
| Data Source Link | https://gitlab.com/acclab/gap-data/-/tree/master |
| Configuration Sets by Name | |
| Configuration Sets by ID | |
| ColabFit ID | DS_40zw467dnc6d_0 |
| Downloads | 15 |
| Files | colabfitspec.json |
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