材料科学
石墨烯
硅
界面热阻
变形(气象学)
热传导
复合材料
热导率
极限抗拉强度
热的
热阻
基质(水族馆)
纳米技术
热力学
光电子学
海洋学
地质学
物理
作者
Chao Li,Jie Wang,Yunhe Sheng,Lina Yang,Yu Su
标识
DOI:10.1016/j.ijheatmasstransfer.2022.123383
摘要
• Analysis of the strain effect on graphene/silicon interfacial thermal resistance. • Tensile strains considered in graphene or in graphene/silicon heterostructures. • Complex states with combined tensile and compressive strains considered. • Interfacial thermal resistance converges with compression under combined strains. • Interfacial thermal resistance increases with in-plane tensile strain in graphene. Evaluating the interfacial thermal resistance is a key step in modeling the heat transport in graphene-based thermal interface materials. However, it is always a challenge to accurately estimate such quantity under residual strains which are inevitably induced during fabrication and application of such materials. In this study, the strain effect on the interfacial thermal resistance between graphene and silicon is systematically investigated through molecular dynamics computation. Tensile strain and compressive strain, parallel and perpendicular to the interfaces, are respectively applied to two forms of heterostructures (i.e., supported graphene on Si substrate and embedded graphene between two Si substrates). The results show that the interfacial thermal resistance gradually increases as the tensile strain in graphene increases in the range of 0 to 0.1, mainly caused by the decrease in the overlap of vibrational density of states between graphene and silicon. However, there is no such monotonic increase in the interfacial thermal resistance with the overall tensile strain applied on both graphene and silicon. In addition, as the compressive strain increases, the interfacial thermal resistances under various residual tensile strains gradually decrease and converge. By analysing the contribution of graphene motion in separate directions, we found out that the out-of-plane motion dominates the interfacial heat conduction.
科研通智能强力驱动
Strongly Powered by AbleSci AI