Through-Thickness Thermal Conductivity Prediction Study on Nanocomposites and Multiscale Composites

Michael Zimmer, Xinyu Fan, Jianwen Bao, Richard Liang, Ben Wang, Chuck Zhang, James Brooks

Florida State University, High-Performance Materials Institute, Tallahassee, USA.
National High Fields Magnetic Laboratory, Tallahassee, USA.

DOI: 10.4236/msa.2012.33021                

Abstract

In this research, a modeling and experimental study was conducted to explore the effects of nanoparticle type (aluminum nanoparticles and carbon nanotubes), filler concentration and interactions between the nanoparticle and reinforcing fibers on through-thickness conductivity of nanoparticle/epoxy nanocomposites and nanoparticle/fiber-reinforced multiscale composites. Multiple, notable micromechanical models were evaluated to predict through-thickness thermal conductivity of both composite systems, and then compared to the experimental results. The results showed that filler volume fraction ranges and thermal conductivity differences of the constituent materials for the thermal conductivity ratio (k_m/k_f or k_f/k_m) used in the models can affect the resulting predictions. Certain models were found to be suitable for varying conditions on the thermal conductivity ratio. Finite element models (FEM) were developed to reveal heat transport mechanisms of the resultant nanocomposites and multiscale composites. The nanocomposite design for finite element analysis (FEA) provided close predictions and performed better than the micromechanical models. On the multiscale composite system, predictions were concluded to be dependent upon the FEM design where the interactions between nanoparticles and fibers are critical to accurately determine the through-thickness thermal conductivity.

Keywords

Thermal Conductivity; Micromechanical Models; Finite Element Models; Nanocomposites; Multiscale Composites; Carbon Nanotubes

Conflicts of Interest

The authors declare no conflicts of interest.

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