Dataset
mlearn_Mo_train
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| Name | mlearn_Mo_train |
|---|---|
| Extended ID | mlearn_Mo_train__Zuo-Chen-Li-Deng-Chen-Behler-Csanyi-Shapeev-Thompson-Wood-Ong__DS_ytoet4uyc32k_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 Mo 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 |
10.60732/3827e5e1
https://commons.datacite.org/doi.org/10.60732/3827e5e1 https://doi.datacite.org/dois/10.60732%2F3827e5e1 https://doi.org/10.60732/3827e5e1 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 Mo train." ColabFit, 2023. https://doi.org/10.60732/3827e5e1. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
Mo (100.0%)
|
| Number of Configurations | 194 |
| Number of Atoms | 10,087 |
| Publication Link | https://doi.org/10.1021/acs.jpca.9b08723 |
| Data Source Link | https://github.com/materialsvirtuallab/mlearn/tree/master/data |
| Configuration Sets by Name | |
| Configuration Sets by ID | |
| ColabFit ID | DS_ytoet4uyc32k_0 |
| Downloads | 12 |
| Files | colabfitspec.json |
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