Dataset
JARVIS_mlearn
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| Name | JARVIS_mlearn |
|---|---|
| Extended ID | JARVIS_mlearn__Zuo-Chen-Li-Deng-Chen-Behler-Csanyi-Shapeev-Thompson-Wood-Ong__DS_g9sra4y8efji_0 |
| Description | The JARVIS_mlearn dataset is part of the joint automated repository for various integrated simulations (JARVIS) database. This dataset contains configurations from the Organic Materials Database (OMDB): a dataset of 12,500 crystal materials for the purpose of training models for the prediction of properties for complex and lattice-periodic organic crystals with large numbers of atoms per unit cell. Dataset covers 69 space groups, 65 elements; averages 82 atoms per unit cell. This dataset also includes classical force-field inspired descriptors (CFID) for each configuration. JARVIS is a set of tools and collected datasets built to meet current materials design challenges. |
| 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/f3f6ad68
https://commons.datacite.org/doi.org/10.60732/f3f6ad68 https://doi.datacite.org/dois/10.60732%2Ff3f6ad68 https://doi.org/10.60732/f3f6ad68 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. "JARVIS mlearn." ColabFit, 2023. https://doi.org/10.60732/f3f6ad68. For other citation formats, see the DataCite Fabrica page for this dataset. |
| Calculated Property Types |
atomic_forces cauchy_stress energy |
| Elements |
Cu (26.43%)
Ge (13.51%) Li (11.14%) Mo (9.74%) Ni (26.42%) Si (12.75%) |
| Number of Configurations | 1,566 |
| Number of Atoms | 115,742 |
| Publication Link | https://doi.org/10.1021/acs.jpca.9b08723 |
| Data Source Link | https://figshare.com/ndownloader/files/40424156 |
| Other Links |
https://jarvis.nist.gov/ https://github.com/materialsvirtuallab/mlearn |
| Configuration Sets by Name | |
| Configuration Sets by ID | |
| ColabFit ID | DS_g9sra4y8efji_0 |
| Downloads | 7 |
| Files | colabfitspec.json |
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