Dataset

Si_Al_Ti_Seko_PRB_2019_train


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Species content of dataset


Name :
Si_Al_Ti_Seko_PRB_2019_train
Authors :
Atsuto Seko, Atsushi Togo, Isao Tanaka
Description :
Test sets from Si_Al_Ti_Seko_PRB_2019. This dataset is compiled of 10,000 selected structures from the ICSD, divided into training and test sets. The dataset was generated for the purpose of training a MLIP with introduced high-order linearly independent rotational invariants up to the sixth order based on spherical harmonics. DFT calculations were carried out with VASP using the PBE cross-correlation functional and an energy cutoff of 400 eV.
DOI :
https://doi.org/10.60732/9b58ca47 https://commons.datacite.org/doi.org/10.60732/9b58ca47
Cite As :
Seko, A., Togo, A., and Tanaka, I. "Si Al Ti Seko PRB 2019 train." ColabFit, 2023. https://doi.org/10.60732/9b58ca47.
ColabFit ID :
DS_swqa99vqo249_0
Extended ID :
Si_Al_Ti_Seko_PRB_2019_train__Seko-Togo-Tanaka__DS_swqa99vqo249_0
Date Added :
2023-12-11
License :
CC0-1.0
Downloads :
31
Num. Configurations :
36,152
Num. Atoms :
1,774,526
Calculated Property Types :
atomic_forces cauchy_stress energy
Elements :
Al (35.15%) Si (32.55%) Ti (32.3%)
Methods :
DFT-PBE
Software :
VASP
Publication Link :
https://doi.org/10.1103/PhysRevB.99.214108
Other Links :
https://doi.org/10.1063/5.0129045 https://sekocha.github.io/
Spec File :
colabfitspec.json
Configuration Sets by Name :
Configuration Sets by ID :
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Si_Al_Ti_Seko_PRB_2019_test

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