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Name a-AlOx_JCP_2020
Extended ID a-AlOx_JCP_2020_LiAndoWatanabe__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

Cite as: Li, W., Ando, Y., and Watanabe, S. "a-AlOx JCP 2020." ColabFit, 2023.
For other citation formats, see the DataCite Fabrica page for this dataset.
Elements Al (43.36%)
O (56.64%)
Number of Data Objects 123,586
Number of Configurations 123,586
Number of Atoms 4,541,918
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
Data Objects Too many to display
ColabFit ID DS_70btumen3361_0
Files colabfitspec.json

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