• 文献标题:   Optimizing isotope substitution in graphene for thermal conductivity minimization by genetic algorithm driven molecular simulations
  • 文献类型:   Article
  • 作  者:   DAVIES M, GANAPATHYSUBRAMANIAN B, BALASUBRAMANIAN G
  • 作者关键词:  
  • 出版物名称:   APPLIED PHYSICS LETTERS
  • ISSN:   0003-6951 EI 1077-3118
  • 通讯作者地址:   Iowa State Univ
  • 被引频次:   2
  • DOI:   10.1063/1.4979315
  • 出版年:   2017

▎ 摘  要

We 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. Published by AIP Publishing.