An accurate numerical prediction for the thermal conductivity of thermal interface materials

Particulate composites are widely utilized in the electronic packaging field. To enhance the thermal dissipation in the packaging component, the interfacial thermal materials (TIMs) are commonly employed between chip and heat sink, which compose of thermal-conductive particulate fillers. The accurate prediction of the thermal conductivity of TIMs benefits the design of their formula. In this paper, we introduce the Al 2 O 3 powder and diamond particles in silicone matrix to improve the thermal conductivity of TIMs. Firstly, the filler-matrix and filler-filler interfacial thermal resistance (ITR) in the Al 2 O 3 -diamond/silicone composites are identified taking advantage of the high-throughput numerical simulation, machine learning algorithm as well as simple experiment measurements. The accuracy determination of the ITRs is further validated by the comparison of thermal conductivity of binary composites between the numerical prediction and experiment measurements. Finally, the thermal conductivities of the TIMs with a series of gradation are numerically predicted, showing good agreement with the measured thermal conductivity of the corresponding experimental samples, presenting the values as high as 5.7 W/mK.