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dc.contributor.authorAmer, Maher S.
dc.contributor.authorMohammed, Mohammed K.
dc.contributor.authorAl Mafrage, Ali M.
dc.date.accessioned2020-06-03T12:18:28Z
dc.date.available2020-06-03T12:18:28Z
dc.date.issued2020-05-26
dc.date.submitted2019-10-11
dc.identifier.citationAmer, M. S., Mohammed, M. K., & Al Mafrage, A. M. (2020). Graphene to graphite; a layer by layer experimental measurements and density function theory calculations of electric conductivity. Philosophical Magazine, 1–12. doi:10.1080/14786435.2020.1766710
dc.identifier.issn1478-6435
dc.identifier.issn1478-6443
dc.identifier.doi10.1080/14786435.2020.1766710
dc.identifier.urihttp://hdl.handle.net/10754/662993
dc.description.abstractWe measured the electric conductivity of large (25 × 50 mm) graphene films as a function of number of layers in the range of 1–20 layers. We also calculated the energy gap for such samples using density function theory. Our results showed a conductivity slightly above that of ITO for monolayer graphene and an exponential decrease as the number of graphene layers increased. Both experimental and simulation results showed a convergence of graphene into graphite at as little as 18–20 layers.
dc.description.sponsorshipThe research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST). For computer time, this research used the resources of the Supercomputing Laboratory at KAUST.
dc.publisherInforma UK Limited
dc.relation.urlhttps://www.tandfonline.com/doi/full/10.1080/14786435.2020.1766710
dc.rightsArchived with thanks to Philosophical Magazine
dc.titleGraphene to graphite; a layer by layer experimental measurements and density function theory calculations of electric conductivity
dc.typeArticle
dc.contributor.departmentKing Abdullah University of Science and Technology (KAUST), Physical Science and Engineering Division (PSE), Thuwal, Saudi Arabia
dc.identifier.journalPhilosophical Magazine
dc.rights.embargodate2021-05-26
dc.eprint.versionPost-print
dc.contributor.institutionDepartment of Mechanical and Materials Engineering, Wright State University, Dayton, OH, USA
dc.identifier.pages1-12
kaust.personAmer, Maher S.
dc.date.accepted2020-05-01
kaust.acknowledged.supportUnitSupercomputing Laboratory at KAUST
dc.date.published-online2020-05-26
dc.date.published-print2020-10-01


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