Microstructure-statistics-property relations of anisotropic polydisperse particulate composites using tomography
A Gillman1, K Matouš, S Atkinson
1Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, Indiana 46556, USA.
Summary
This study uses micro-CT to link composite microstructure to thermal conductivity. The method accurately predicts anisotropic thermal properties based on particle shape and distribution.
Area of Science:
- Materials Science
- Computational Mechanics
- Image Analysis
Background:
- Understanding microstructure-property relationships is crucial for designing advanced materials.
- Anisotropic composite materials exhibit direction-dependent properties, requiring sophisticated characterization.
- Existing methods often rely on simplifying assumptions about microstructure symmetry.
Purpose of the Study:
- To develop a systematic method for establishing microstructure-statistics-property relations in anisotropic polydisperse particulate composites.
- To utilize micro-CT data for accurate 3D microstructure characterization.
- To compute the anisotropic thermal-conductivity tensor without assuming statistical isotropy or ellipsoidal symmetry.
Main Methods:
- Employing micro-CT to generate detailed 3D representations of polydisperse microstructures.
- Developing an image processing pipeline for particle identification and modeling with idealized shapes.
- Calculating n-point probability functions directly from micro-CT data to describe morphology.
- Applying the Hashin-Shtrikman variational principle with statistical descriptors to estimate thermal conductivity.
Main Results:
- Successfully generated 3D microstructure data and processed it to extract morphological descriptors.
- Computed anisotropic bounds and self-consistent estimates for the thermal-conductivity tensor.
- Demonstrated the impact of particle morphology (ellipsoidal, spherical) on the anisotropic thermal-conductivity tensor.
- Validated the method's ability to handle non-isotropic and non-ellipsoidal symmetries.
Conclusions:
- The developed micro-CT-based method provides a robust framework for linking microstructure statistics to macroscopic properties of composites.
- This approach enables accurate prediction of anisotropic thermal conductivity by directly analyzing complex, real microstructures.
- The findings highlight the significant influence of particle morphology on the directional thermal transport behavior of composites.
