Microstructure-statistics-property relations of anisotropic polydisperse particulate composites using tomography

摘要

In this paper, a systematic method is presented for developing microstructure-statistics-property relations ofnanisotropic polydisperse particulate composites using microcomputer tomography (micro-CT). Micro-CT is usednto obtain a detailed three-dimensional representation of polydisperse microstructures, and an image processingnpipeline is developed for identifying particles. In this work, particles are modeled as idealized shapes in ordernto guide the image processing steps and to provide a description of the discrete micro-CT data set in continuousnEuclidean space. n-point probability functions used to describe the morphology of mixtures are calculated directlynfrom real microstructures. The statistical descriptors are employed in the Hashin-Shtrikman variational principlento compute overall anisotropic bounds and self-consistent estimates of the thermal-conductivity tensor.We makenno assumptions of statistical isotropy nor ellipsoidal symmetry, and the statistical description is obtained directlynfrom micro-CT data. Various mixtures consisting of polydisperse ellipsoidal and spherical particles are preparednand studied to show how the morphology impacts the overall anisotropic thermal-conductivity tensor.