Dataset

mlearn_Ge_test




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Name mlearn_Ge_test
Extended ID mlearn_Ge_test__Zuo-Chen-Li-Deng-Chen-Behler-Csanyi-Shapeev-Thompson-Wood-Ong__DS_pyrk84w3auvb_0
Description A comprehensive DFT data set was generated for six elements - Li, Mo, Ni, Cu, Si, and Ge. These elements were chosen to span a variety of chemistries (main group metal, transition metal, and semiconductor), crystal structures (bcc, fcc, and diamond) and bonding types (metallic and covalent). This dataset comprises only the Ge configurations
Authors Yunxing Zuo
Chi Chen
Xiangguo Li
Zhi Deng
Yiming Chen
Jörg Behler
Gábor Csányi
Alexander V. Shapeev
Aidan P. Thompson
Mitchell A. Wood
Shyue Ping Ong
DOI 10.60732/1a1e4a52
https://commons.datacite.org/doi.org/10.60732/1a1e4a52
https://doi.datacite.org/dois/10.60732%2F1a1e4a52
https://doi.org/10.60732/1a1e4a52

Cite as: Zuo, Y., Chen, C., Li, X., Deng, Z., Chen, Y., Behler, J., Csányi, G., Shapeev, A. V., Thompson, A. P., Wood, M. A., and Ong, S. P. "mlearn Ge test." ColabFit, 2023. https://doi.org/10.60732/1a1e4a52.
For other citation formats, see the DataCite Fabrica page for this dataset.
Calculated Property Types atomic_forces
cauchy_stress
energy
Elements
Ge (100.0%)
Number of Configurations 25
Number of Atoms 1,568
Publication Link https://doi.org/10.1021/acs.jpca.9b08723
Data Source Link https://github.com/materialsvirtuallab/mlearn
Configuration Sets by Name
Configuration Sets by ID
ColabFit ID DS_pyrk84w3auvb_0
Downloads 7
Files colabfitspec.json

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