Dataset

Ta_PRM2019



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Name Ta_PRM2019
Extended ID Ta_PRM2019_ByggmastarNordlundDjurabekova__DS_f897om5zgwj4_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
Elements Ta (100.0%)
Number of Data Objects 3,775
Number of Configurations 3,775
Number of Atoms 45,439
Links https://doi.org/10.1103/PhysRevMaterials.4.093802
https://gitlab.com/acclab/gap-data/-/tree/master
Configuration Sets by Name
Configuration Sets by ID
Data Objects
ColabFit ID DS_f897om5zgwj4_0
Files colabfitspec.json

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