Dataset

Ta_PRM2019

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Name :

Ta_PRM2019

Extended ID :

Ta_PRM2019__Byggmastar-Nordlund-Djurabekova__DS_40zw467dnc6d_0

ColabFit ID :

DS_40zw467dnc6d_0

Files :

colabfitspec.json

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.

Num. Configurations :

3,773

Num. Atoms :

45,385

Downloads :

Calculated Property Types :

atomic_forces cauchy_stress energy

Elements :

Ta (100.0%)

Methods :

DFT-PBE

Software :

VASP

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 :

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