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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