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README.md

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----
-configs:
-- config_name: default
-  data_files: "main/*.parquet"
-license: bsd-3-clause
-tags:
-- molecular dynamics
-- mlip
-- interatomic potential
-pretty_name: mlearn Ge train
----
-# Dataset  
-mlearn Ge 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 Ge configurations  
-<br>Additional details stored in dataset columns prepended with "dataset_".  
-### 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  
-228  
-### Number of atoms  
-14072  
-### Elements included  
-Ge  
-### Properties included  
-energy, atomic forces, cauchy stress  
-### 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 Ge train_. ColabFit, 2023. https://doi.org/10.60732/4552d3fd