Dataset
Si_Al_Ti_Seko_PRB_2019_train
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| Name | Si_Al_Ti_Seko_PRB_2019_train |
|---|---|
| Extended ID | Si_Al_Ti_Seko_PRB_2019_train__Seko-Togo-Tanaka__DS_swqa99vqo249_0 |
| 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. |
| Authors |
Atsuto Seko Atsushi Togo Isao Tanaka |
| DOI |
10.60732/9b58ca47
https://commons.datacite.org/doi.org/10.60732/9b58ca47 https://doi.datacite.org/dois/10.60732%2F9b58ca47 https://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. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
Al (35.16%) Si (32.54%) Ti (32.3%) |
| Number of Configurations | 36,155 |
| Number of Atoms | 1,774,664 |
| Links |
https://doi.org/10.1103/PhysRevB.99.214108 https://doi.org/10.1063/5.0129045 https://sekocha.github.io/ |
| Configuration Sets by Name |
Si_Al_Ti_Seko_PRB_2019_train_aluminum — Configurations of aluminum from Si_Al_Ti_Seko_PRB_2019_train Si_Al_Ti_Seko_PRB_2019_train_silicon — Configurations of silicon from Si_Al_Ti_Seko_PRB_2019_train Si_Al_Ti_Seko_PRB_2019_train_titanium — Configurations of titanium from Si_Al_Ti_Seko_PRB_2019_train |
| Configuration Sets by ID |
CS_45m7wyecqipw_0 CS_nuqh1t6t9hbg_0 CS_ovzhgd3n9orq_0 |
| Calculated Properties | |
| ColabFit ID | DS_swqa99vqo249_0 |
| Files | colabfitspec.json |
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