Prediction of Electrical Conductivity of Porous Composites Using a Simplified Monte Carlo 3D Equivalent Electronic Circuit Network Model: LSM-YSZ Case Study

Multiphase electric charge conductors composed of materials with various properties are widely utilized in both research and industrial applications. The composite materials include porous electrodes and other components mainly applied in fuel cell and battery technologies. In this study, a simplified Monte Carlo equivalent electronic circuit (EEC) network model is presented. In comparison to similar models, the present EEC network model allows an accurate prediction of the electrical properties of such materials, thus saving time-consuming exper-imental determination. The distinct feature of this EEC network model is that it requires only experimentally easily obtainable data as the input parameters: phase composition, porosity and bulk electrical conductivity of the individual constituents. During its run, the model generates a large number of artificial cubically shaped specimens based on random distribution of individual phases according to the input composition. Each of the specimens generated was modelled by a corresponding EEC network. The EEC networks were solved using Kirchhoff's laws, resulting in impedance response simulation for the prediction of composite conductivity values. The EEC network model was validated using lanthanum strontium manganite mixed with yttria-stabilized zir-conia. Excellent agreement was obtained between the experimentally determined and the calculated electrical conductivity for sample porosities of 0 to 60 %. Due to its variability, the EEC network model can be suitable for a wide range of practical applications. The presented approach has high potential to save an enormous amount of experimental effort, while maintaining sufficient accuracy, when designing corresponding multiphase electrode structures.

Automated summary

This study presents a simplified Monte Carlo equivalent electronic circuit (EEC) network model that accurately predicts the electrical properties of composite materials, saving time-consuming experimental determination. The model only requires easily obtainable input parameters: phase composition, porosity, and bulk electrical conductivity. By generating artificial specimens and solving the EEC networks using Kirchhoff's laws, impedance response simulation is performed and composite conductivity values are predicted. The model was validated for lanthanum strontium manganite mixed with yttria-stabilized zirconia, showing excellent agreement between experimentally determined and calculated electrical conductivity. Due to its variability, the EEC network model is suitable for a wide range of practical applications. This approach has the potential to save a large amount of experimental effort while maintaining sufficient accuracy in designing multiphase electrode structures.