Dataset
V_PRM2019
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Name | V_PRM2019 |
---|---|
Extended ID | V_PRM2019__Byggmästar-Nordlund-Djurabekova__DS_ouwlietscprn_0 |
Description | This dataset was designed to enable machine-learning of V 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/aad06a25
https://commons.datacite.org/doi.org/10.60732/aad06a25 https://doi.datacite.org/dois/10.60732%2Faad06a25 https://doi.org/10.60732/aad06a25 Cite as: Byggmästar, J., Nordlund, K., and Djurabekova, F. "V PRM2019." ColabFit, 2023. https://doi.org/10.60732/aad06a25. For other citation formats, see the DataCite Fabrica page for this dataset. |
Calculated Property Types |
atomic_forces cauchy_stress energy |
Elements |
V (100.0%) |
Number of Configurations | 3,802 |
Number of Atoms | 46,466 |
Links |
https://gitlab.com/acclab/gap-data/-/tree/master https://doi.org/10.1103/PhysRevMaterials.4.093802 |
Configuration Sets by Name | |
Configuration Sets by ID | |
Calculated Properties | |
ColabFit ID | DS_ouwlietscprn_0 |
Files | colabfitspec.json |
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