A novel analytic model for prediction of the anisotropic thermal conductivity in polymer composites containing aligned 1D nanofillers

The distribution of thermally conductive fillers significantly affects the thermal conductivity (TC) of polymer composites; however, the description of their relationship and accurate prediction remain quite challenging. In this paper, a novel analytical model is first derived for the calculation of the anisotropic TC in polymer com-posites containing aligned one-dimensional nanofillers (ODNs). The TC of an ODN considering the boundary resistance is obtained via effective medium approximation (EMA), while the TC of composites is derived via the unit cell method. A parameter f that is only related to the distances between the ODNs is introduced, and the proposed model can well describe the impact of the distances between the aligned ODNs on the TC of the composites. To validate the model, finite element method (FEM) simulations are conducted. It is found that the results calculated by the proposed model match well with experimental data and the results of FEM simulations. The influences of the key parameters of the proposed model on the TC of composites are discussed, and the proposed model is also compared with other theoretical models, including the Nan's model, the parallel model, and the series model. This work provides a simple but effective way for predicting and understanding the thermal conductivity of composites containing aligned 1D nanofillers using computational approaches.

Automated summary

This paper presents a novel analytical model for accurately calculating the anisotropic thermal conductivity of polymer composites containing aligned one-dimensional nanofillers. The model considers the boundary resistance and introduces a parameter f related to the distances between the nanofillers, effectively capturing their impact on the thermal conductivity. Finite element method simulations validate the model, and comparisons with other theoretical models are made. The proposed model provides a simple yet effective computational approach for predicting and understanding the thermal conductivity of composites with aligned 1D nanofillers.