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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