A Monte Carlo Approach for Simulating Electrical Conductivity in Highly Porous Ceramic Composites: Impact of Internal...

Area of Science:

• Materials Science
• Computational Modeling

Background:

• Porous ceramic composites are vital in various applications due to their unique properties.
• Analyzing composite structure and properties is crucial but often experimentally challenging.
• Mathematical modeling offers an efficient alternative to experimental analysis.

Purpose of the Study:

• To develop and validate a Monte Carlo 3D equivalent electronic circuit network model for analyzing highly porous composites.
• To enhance the model to account for void phase coalescence in materials with ≥55% porosity.
• To enable rapid and cost-effective estimation of internal material structure and properties.

Main Methods:

• Utilized a Monte Carlo 3D equivalent electronic circuit network model.
• Incorporated an additional parameter for void phase coalescence.
• Focused on materials with porosity of 55% and higher, using solid oxide cell electrodes as a model.
• Validated the model against experimental conductivity data.

Main Results:

• The enhanced model accurately simulates electrical conductivity for experimental samples up to 75% porosity.
• The model successfully predicts properties of highly porous composites, deviating from lower porosity behaviors.
• Enabled estimation of internal material structure using basic input parameters and experimental conductivity.

Conclusions:

• The developed Monte Carlo model provides a rapid, cost-effective method for studying porous composite microstructures.
• This approach enhances predictive capabilities for optimizing composite material performance.
• The model is particularly effective for materials with high void fractions, advancing their technological applications.