Datasets:

colabfit
/

mlearn_Mo_train

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Cite this dataset
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

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Dataset Name

mlearn Mo train

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

Dataset 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

Publication

https://doi.org/10.1021/acs.jpca.9b08723

Original data link

https://github.com/materialsvirtuallab/mlearn/tree/master/data

License

BSD-3-Clause

Number of unique molecular configurations

194

Number of atoms

10087

Elements included

Properties included

energy, atomic forces, cauchy stress

Usage

ds.parquet : Aggregated dataset information.
co/ directory: Configuration rows each include a structure, calculated properties, and metadata.
cs/ directory : Configuration sets are subsets of configurations grouped by some common characteristic. If cs/ does not exist, no configurations sets have been defined for this dataset.
cs_co_map/ directory : The mapping of configurations to configuration sets (if defined).