Structure-Property Correlations in Model Composite Materials

TL;DR

This paper explores how the microstructure of composite materials influences their physical properties, using Gaussian fields and sphere models to derive bounds and simulate conductivity, providing insights into structure-property relationships.

Contribution

It introduces a new modeling approach for composite microstructures and derives rigorous bounds on properties based on statistical correlation functions.

Findings

Models exhibit low percolation thresholds

Derived bounds on conductivity, diffusivity, and elastic moduli

Simulation results support the bounds' applicability

Abstract

We investigate the effective properties (conductivity, diffusivity and elastic moduli) of model random composite media derived from Gaussian random fields and overlapping hollow spheres. The morphologies generated in the models exhibit low percolation thresholds and give a realistic representation of the complex microstructure observed in many classes of composites. The statistical correlation functions of the models are derived and used to evaluate rigorous bounds on each property. Simulation of the effective conductivity is used to demonstrate the applicability of the bounds. The key morphological features which effect composite properties are discussed.