Morphological modelling of three-phase microstructures of anode layers using SEM images

Area of Science:

• Materials Science
• Chemical Engineering
• Computational Modeling

Background:

• Accurate modeling of three-phase anode layers in fuel cells is crucial for performance optimization.
• Existing methods may lack the precision to capture complex microstructural morphologies.
• Scanning Electron Microscopy (SEM) provides detailed but complex microstructural data.

Purpose of the Study:

• To develop a general and accurate method for modeling 3D microstructures of three-phase anode layers.
• To validate the proposed modeling approach against experimental SEM data.
• To provide a straightforward modeling technique applicable to fuel cell materials.

Main Methods:

• Characterization of anode layer microstructures using SEM imaging.
• Application of morphological measurements including cross-covariances, granulometry, and linear erosion.
• Development of a generic three-phase material model based on two independent underlying random sets.
• Utilizing plurigaussian models to represent the underlying random sets.

Main Results:

• The plurigaussian models demonstrated good agreement with SEM images across all morphological measurements.
• The generated microstructures closely matched the spatial distribution and shapes of real anode materials.
• The proposed modeling method requires no numerical optimization and is easily generated.

Conclusions:

• Plurigaussian random set models provide a valid and effective approach for simulating 3D microstructures of three-phase anode layers.
• This method offers a simplified yet accurate alternative for fuel cell material design and analysis.
• The technique facilitates the generation of realistic microstructural models directly from experimental data.