Dataset
GST_GAP_22_extended
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| Name | GST_GAP_22_extended |
|---|---|
| Extended ID | GST_GAP_22_extended__Zhou-Zhang-Ma-Deringer__DS_efcq7a0h6z5w_0 |
| Description | The extended training dataset for GST_GAP_22, calculated using the PBEsol functional. New configurations, simulated under external electric fields, were labelled with DFT and added to the original reference database GST-GAP-22 contains configurations of phase-change materials on the quasi-binary GeTe-Sb2Te3 (GST) line of chemical compositions. Data was used for training a machine learning interatomic potential to simulate a range of germanium-antimony-tellurium compositions under realistic device conditions. |
| Authors |
Yuxing Zhou Wei Zhang Evan Ma Volker L. Deringer |
| DOI |
10.60732/37c76fa8
https://commons.datacite.org/doi.org/10.60732/37c76fa8 https://doi.datacite.org/dois/10.60732%2F37c76fa8 https://doi.org/10.60732/37c76fa8 Cite as: Zhou, Y., Zhang, W., Ma, E., and Deringer, V. L. "GST GAP 22 extended." ColabFit, 2023. https://doi.org/10.60732/37c76fa8. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
Ge (23.54%) Sb (21.81%) Te (54.65%) |
| Number of Configurations | 2,916 |
| Number of Atoms | 399,247 |
| Links |
https://doi.org/10.5281/zenodo.8208202 https://doi.org/10.1038/s41928-023-01030-x |
| Configuration Sets by Name | (None) |
| Configuration Sets by ID | (None) |
| Calculated Properties | |
| ColabFit ID | DS_efcq7a0h6z5w_0 |
| Files | colabfitspec.json |
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