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dc.contributor.authorCsanyi, Gabor
dc.date.accessioned2022-03-08T16:04:43Z
dc.date.available2022-03-08T16:04:43Z
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/334766
dc.descriptionThis is a machine learning interatomic potential for carbon, using the GAP framework.
dc.formatGAP, QUIP (http:/www.github.com/libAtoms/GAP)
dc.rightsAttribution-NonCommercial 4.0 International (CC BY-NC 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectinteratomic potential
dc.subjectcarbon
dc.subjectmolecular dynamics
dc.subjectmachine learning
dc.titleResearch data supporting "An Accurate and Transferable Machine Learning Potential for Carbon"
dc.typeDataset
dc.publisher.departmentDepartment of Engineering
dc.date.updated2022-03-04T13:53:33Z
dc.identifier.doi10.17863/CAM.82086
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc/4.0/
dcterms.formatzip
dc.contributor.orcidCsanyi, Gabor [0000-0002-8180-2034]
rioxxterms.typeOther
datacite.issupplementedby.doi10.17863/CAM.84096
datacite.issupplementto.urlhttps://www.repository.cam.ac.uk/handle/1810/315375
cam.depositDate2022-03-04
pubs.licence-identifierapollo-deposit-licence-2-1
pubs.licence-display-nameApollo Repository Deposit Licence Agreement
datacite.isderivedfrom.doi10.1063/5.0005084


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Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Except where otherwise noted, this item's licence is described as Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)