In this study, a qualitative equivalence between the electrical percolation threshold and the effective thermal conductivity of composites filled with cylindrical nanofillers has been recognized. The two properties are qualitatively compared on a wide range of aspect ratios, from thin nanoplatelets to long nanotubes. Statistical continuum theory of strong-contrast is utilized to estimate the thermal conductivity of this type of heterogeneous medium, while the percolation threshold is simultaneously evaluated using the Monte Carlo simulations. Statistical two-point probability distribution functions are used as microstructure descriptors for implementing the statistical continuum approach. Monte Carlo simulations are carried out for calculating the two-point correlation functions of computer generated microstructures. Finally, the similarities between the effective conductivity properties and percolation threshold are discussed.
Issue Section:
Bridging Microstructure, Properties, and Processing of Polymer-Based Advanced Materials
Keywords:
carbon nanotubes,
electrical conductivity,
filled polymers,
Monte Carlo methods,
nanocomposites,
percolation,
statistical distributions,
thermal conductivity,
electrical percolation threshold,
thermal conductivity,
Monte Carlo simulation/integration,
strong-contrast homogenization technique,
two-point/three-point correlation functions
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.Copyright © 2012
by American Society of Mechanical Engineers
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