Dataset
a-AlOx_JCP_2020
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Name | a-AlOx_JCP_2020 |
---|---|
Extended ID | a-AlOx_JCP_2020__Li-Ando-Watanabe__DS_70btumen3361_0 |
Description | This dataset was used for the training of an MLIP for amorphous alumina (a-AlOx). Two configurations sets correspond to i) the actual training data and ii) additional reference data. Ab initio calculations were performedwith the Vienna Ab initio Simulation Package. The projector augmented wave method was used to treat the atomic core electrons,and the Perdew-Burke-Ernzerhof functional within the generalized gradient approximation was used to describe the electron-electron interactions. The cutoff energy for the plane-wave basis set was set to 550 eV during the ab initio calculation. The obtained reference database includes the DFT energies of 41,203 structures. The supercell size of the AlOx reference structures varied from 24 to 132 atoms. K-point values are given for structures with: Al0, Al12, Al24, Al48 and Al192. |
Authors |
Wenwen Li Yasunobu Ando Satoshi Watanabe |
DOI |
10.60732/96296d27
https://commons.datacite.org/doi.org/10.60732/96296d27 https://doi.datacite.org/dois/10.60732%2F96296d27 https://doi.org/10.60732/96296d27 Cite as: Li, W., Ando, Y., and Watanabe, S. "a-AlOx JCP 2020." ColabFit, 2023. https://doi.org/10.60732/96296d27. For other citation formats, see the DataCite Fabrica page for this dataset. |
Calculated Property Types |
atomic_forces cauchy_stress energy |
Elements |
Al (43.36%) O (56.64%) |
Number of Configurations | 123,586 |
Number of Atoms | 4,541,918 |
Links |
https://doi.org/10.24435/materialscloud:y1-zd https://doi.org/10.1063/5.0026289 |
Configuration Sets by Name |
a-AlOx_training — Structures used for training of neural network potential. a-AlOx_reference — Additional reference DFT calculations that author used for reference. |
Configuration Sets by ID |
CS_b5w6rfo70yuv_0 CS_c2ln65h5napd_0 |
Calculated Properties | |
ColabFit ID | DS_70btumen3361_0 |
Files | colabfitspec.json |
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