Efficient three-phase reconstruction of heterogeneous material from 2D cross-sections via phase-recovery algorithm

Area of Science:

• Materials Science
• Computational Modeling
• Microstructure Analysis

Background:

• Digital reconstruction of heterogeneous media is crucial for computational analysis.
• Limited statistical information from imaging techniques presents a challenge.

Purpose of the Study:

• To present a novel 3D reconstruction approach for three-phase microstructures.
• To reconstruct complex materials from 2D cross-sectional statistical information.

Main Methods:

• A three-step method involving extraction of 2D two-point correlation functions (TPCFs).
• Approximation of 3D TPCFs within a representative volume element (RVE).
• Realization of the 3D microstructure using a modified phase-recovery algorithm.

Main Results:

• The method successfully reconstructs three-phase microstructures, demonstrated for SOFC anode.
• Qualitative comparison validates the computational cross-sections against experimental ones.
• Key microstructural properties, including tortuosity, percolation, and three-phase boundary length (TPBL), are conserved.

Conclusions:

• The developed method offers a robust approach for 3D microstructure reconstruction.
• It is applicable to various complex three-phase heterogeneous materials.
• The technique effectively preserves critical material properties essential for performance analysis.