Finite Element Prediction of the Thermal Conductivity of GNP/Al Composites

A 3D multi-scale finite element model was developed to predict the effective thermal conductivity of graphene nanoplatelet (GNP)/Al composites. The factors influencing the effective thermal conductivity of the GNP/Al composites were investigated, including the orientation, shape, aspect ratio, configuration and volume fraction of GNPs. The results show that GNPs shape has a little influence on the thermal conductivity of GNP/Al composites, and composites with elliptic GNPs have the highest thermal conductivity. In addition, with increasing the aspect ratio of GNPs, the thermal conductivity of GNP/Al composites increases and finally tends to be stable. The GNPs configuration strongly influences the thermal conductivity of GNP/Al composites, and the thermal conductivity of the composites with layered GNPs is the highest among the five configurations. The effective thermal conductivity is sensitive to volume fraction of GNPs. Ideally, when the volume fraction of layered GNPs reaches 1.54%, the thermal conductivity of GNP/Al composites is as high as 400 W/m K. The findings of this study could provide a good theoretical basis for designing high thermal conductivity GNP/Al composites.