Research data supporting "An Accurate and Transferable Machine Learning Potential for Carbon"

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GAP_20_U_s0.1.zip (application/zip, 41Mb)

Authors

  Csanyi, Gabor

Publication Date

2022-03-08

Type

Dataset

Metadata

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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/

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