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Research data for “A machine-learned interatomic potential for silica and its relation to empirical models”
This dataset supports the paper "A machine-learned interatomic potential for silica and its relation to empirical models". The paper is online here: The following files are provided: xyz-file containing all structures in the training database including forces and
File Size150.1 MB
Data TypeDataset
Published2022
Licensecc-by-4.0
Total Views2,813
Total Downloads1,066
This dataset supports the paper "A machine-learned interatomic potential for silica and its relation to empirical models". The paper is online here:
The following files are provided:
- xyz-file containing all structures in the training database including forces and energies
- GAP file containing the corresponding parameters, which can be used for example for Lammps MD simulations
- Amorphous structure files for silica created by different interatomic potentials.
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Files are hosted on the source repository. Click download to access the full dataset.
Erhard, Linus C. (2022). Research data for “A machine-learned interatomic potential for silica and its relation to empirical models”. https://doi.org/10.5281/zenodo.6353684