Optimizing isotope substitution in graphene for thermal conductivity minimization by genetic algorithm driven molecular simulationsApplied Physics Letters
Publication VersionPublished Version
AbstractWe present results from a computational framework integrating genetic algorithm and molecular dynamics simulations to systematically design isotope engineered graphene structures for reduced thermal conductivity. In addition to the effect of mass disorder, our results reveal the importance of atomic distribution on thermal conductivity for the same isotopic concentration. Distinct groups of isotope-substituted graphene sheets are identified based on the atomic composition and distribution. Our results show that in structures with equiatomic compositions, the enhanced scattering by lattice vibrations results in lower thermal conductivities due to the absence of isotopic clusters.
Copyright OwnerAmerican Institute of Physics
Citation InformationMichael Davies, Baskar Ganapathysubramanian and Ganesh Balasubramanian. "Optimizing isotope substitution in graphene for thermal conductivity minimization by genetic algorithm driven molecular simulations" Applied Physics Letters Vol. 110 Iss. 13 (2017) p. 133107
Available at: http://works.bepress.com/baskar-ganapathysubramanian/15/