Publication date: Sep 27, 2021
The beta-glycine dataset is created with the purpose of validating the electron machine learning potential (eMLP) on crystalline beta glycine. It contains 25,676 configurations with normal mode perturbations for the nuclei and unit cell and electric field perturbations. Energies, forces and Wannier centers are computed using density functional theory (DFT) with the PBE functional and a Plane-Wave basis set in the ab-initio quantum chemistry code QuantumESPRESSO.
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File name | Size | Description |
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beta_glycine_dataset.tar.gz
MD5md5:b71055493a168135aea37e89a17e1b04
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49.1 MiB | An archive containing 25,676 perturbed samples of beta-glycine. Read the README file for more information. |
optimized_geometry.xyz
MD5md5:3b9eb088765d9c81b5b6fdd80d8c2568
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4.8 KiB | The extended xyz file of the optimized geometry and electron pairs of beta-glycine. |
README.txt
MD5md5:f125ad4fbb8d108eb04faf7cbdb82612
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3.4 KiB | Detailed description of the dataset and all the files. |
2021.155 (version v1) [This version] | Sep 27, 2021 | DOI10.24435/materialscloud:jn-44 |