Institute for Materials Science and Max Bergman Center of Biomaterials, TU Dresden, 01062 Dresden, Germany.
Nanoscale. 2014 Mar 21;6(6):3344-52. doi: 10.1039/c3nr06388g. Epub 2014 Feb 12.
We developed a multiscale approach to explore the effective thermal conductivity of polycrystalline graphene sheets. By performing equilibrium molecular dynamics (EMD) simulations, the grain size effect on the thermal conductivity of ultra-fine grained polycrystalline graphene sheets is investigated. Our results reveal that the ultra-fine grained graphene structures have thermal conductivity one order of magnitude smaller than that of pristine graphene. Based on the information provided by the EMD simulations, we constructed finite element models of polycrystalline graphene sheets to probe the thermal conductivity of samples with larger grain sizes. Using the developed multiscale approach, we also investigated the effects of grain size distribution and thermal conductivity of grains on the effective thermal conductivity of polycrystalline graphene. The proposed multiscale approach on the basis of molecular dynamics and finite element methods could be used to evaluate the effective thermal conductivity of polycrystalline graphene and other 2D structures.
我们开发了一种多尺度方法来探索多晶石墨烯片的有效热导率。通过进行平衡分子动力学(EMD)模拟,研究了晶粒尺寸对超细微晶多晶石墨烯片热导率的影响。我们的结果表明,超细晶粒石墨烯结构的热导率比原始石墨烯低一个数量级。基于 EMD 模拟提供的信息,我们构建了多晶石墨烯片的有限元模型,以研究更大晶粒尺寸样品的热导率。利用所开发的多尺度方法,我们还研究了晶粒尺寸分布和晶粒热导率对多晶石墨烯有效热导率的影响。基于分子动力学和有限元方法的提出的多尺度方法可用于评估多晶石墨烯和其他 2D 结构的有效热导率。