Research data supporting "An Accurate and Transferable Machine Learning Potential for Carbon"
Citation
Csanyi, G. (2022). Research data supporting "An Accurate and Transferable Machine Learning Potential for Carbon" [Dataset]. https://doi.org/10.17863/CAM.82086
Description
This is a machine learning interatomic potential for carbon, using the GAP framework.
Format
GAP, QUIP (http:/www.github.com/libAtoms/GAP)
Keywords
interatomic potential, carbon, molecular dynamics, machine learning
Relationships
Is supplemented by: https://doi.org/10.17863/CAM.84096
Related research output: https://doi.org/10.1063/5.0005084
Publication Reference: https://doi.org/10.1063/5.0005084https://www.repository.cam.ac.uk/handle/1810/315375
Identifiers
This record's DOI: https://doi.org/10.17863/CAM.82086
Rights
Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Licence URL: https://creativecommons.org/licenses/by-nc/4.0/
Statistics
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IRUS guide.