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README.md
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---
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configs:
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- config_name: default
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data_files: "main/*.parquet"
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license: bsd-3-clause
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tags:
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- molecular dynamics
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- mlip
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- interatomic potential
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pretty_name: mlearn Ge test
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---
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### Cite this dataset
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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
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### View on the ColabFit Exchange
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https://materials.colabfit.org/id/DS_pyrk84w3auvb_0
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# Dataset Name
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mlearn Ge test
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### Description
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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
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<br>Additional details stored in dataset columns prepended with "dataset_".
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### Dataset authors
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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
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### Publication
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https://doi.org/10.1021/acs.jpca.9b08723
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### Original data link
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https://github.com/materialsvirtuallab/mlearn
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### License
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BSD-3-Clause
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### Number of unique molecular configurations
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25
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### Number of atoms
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1568
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### Elements included
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Ge
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### Properties included
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energy, atomic forces, cauchy stress
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