Dataset
a-AlOx_JCP_2020
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Name | a-AlOx_JCP_2020 |
---|---|
Extended ID | a-AlOx_JCP_2020_LiAndoWatanabe__DS_17w6wkt656q2_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 projectoraugmented 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 |
Elements |
Al (43.36%) O (56.64%) |
Number of Data Objects | 123,571 |
Number of Configurations | 123,574 |
Number of Atoms | 4,541,698 |
Links |
https://doi.org/10.1063/5.0026289 https://doi.org/10.24435/materialscloud:y1-zd |
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_z12elz6o2a7o_0 CS_o3us0p8izy74_0 |
Data Objects | Too many to display |
ColabFit ID | DS_17w6wkt656q2_0 |
Files | colabfitspec.json |
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