On a pluri-Gaussian model for three-phase microstructures, with applications to 3D image data of gas-diffusion electrodes

A pluri-Gaussian model for three-phase microstructures is presented and relationships between model parameters and microstructure characteristics are discussed. In particular, analytical formulas for two-point coverage probability functions in terms of covariance functions of the underlying Gaussian random fields are considered, which allow for an efficient estimation of model parameters. The model is fitted to tomographic image data obtained by FIB-tomography, which represent porous gas-diffusion electrodes consisting of silver and poly-tetrafluorethylene. The considered type of electrode is used as oxygen depolarized cathode for the production of chlorine. In order to fit the microstructure model, the covariance functions of the Gaussian random fields are parameterized, which leads to a stochastic microstructure model with five parameters. It is shown that most microstructure characteristics of tomographic image data are well reproduced by the model despite the low number of model parameters. Finally, limitations of the model with respect to the fit of continuous phase size distributions are discussed. Combining stochastic microstructure modeling with numerical simulation of effective macroscopic properties will allow in future work for a model-based investigation of microstructure-property relationships for the considered gas-diffusion electrodes.