A Numerical Investigation Of The Thermal Property Of Particle Filled Polymer Matrix Composite

Particle filled polymer matrix composites have been in-depth studied and widely used due to the superior physical properties combined with polymer matrix and filled particles. Thermal conductivity of composites depend on the thermal property of the matrix and fillers, as well as the filler volume fraction, particle shape, particle size, size distribution and the filler spatial distribution, the bonding degree and other factors. Theoretical study has been met great difficulty, because the complexity of the system. This article with the finite element numerical simulation method was used to study the relationship between thermal properties and microstructure, and especially provided a feasible solution for particle distribution modeling problem. Main research contents are as follows:2D model was investigated first. A Representative Volume Element (RVE) model was developed to investigate the relation between thermal property and microstructure of the particle filled composite. The model was based on two novel algorithms, and was constructed with the same particle spatial distribution structure of the real heterogeneous composite by the introduction of two parameters i.e. the ratio and the radius of particle-poor region, which both were estimated from SEM micrographs. It has been found that the simulation results are accurate in the large scale of filler content. The system with non-uniform particle spatial distribution shows higher thermal conductivity than that with random or uniform particle spatial distribution.The effect of the particle spatial distribution on the thermal conductivity of composites and the essential condition of the formation of the effective thermal conductive pathways were investigated. In order to solve the modeling problem of the representative volume element (RVE) with any volume fraction and specified spatial configuration, the strategy to describe the objective spatial distribution configuration by the spatial distribution potential-energy function was employed, and a Monte Carlo controllable spatial distribution algorithm was designed, which can effectively create the RVE containing cluster and network configurations with any volume fraction.The simulated results show that, at the same volume fraction, the network configuration is easier to form the thermal conductive pathways and feature higher thermal conductivity than the cluster one; the volume fraction play a key role in the formation of the effective thermal conductive pathways, which can occur only when the volume fraction is larger than 20% and the distance between the particles is short to some extent; upon the increasing distance between the particles, the thermal conduction decrease in an exponent form. Therefore, a given amount of volume fraction and relative effective distribution of particles become two essential conditions of the formation of the effective thermal conductive pathways.