Estimation of 3D Effective Properties from 2D Cross Sections in Porous Electrodes

Nowadays tomographic techniques are used to reconstruct the 3D microstructure of Solid Oxide Fuel Cell (SOFC) electrodes from a sequence of 2D cross sections and to evaluate the effective properties of real samples. However, this approach involves expensive instrumentation and time-consuming procedures. Thus, there is the need of short-cut methods to infer 3D properties from a single 2D cross section for a rapid characterization of the electrode properties.

In this study, the correlation between 2D and 3D properties is studied through the numerical reconstruction of the electrode microstructure by using packing algorithms. 3D effective geometrical properties, such as the mean particle diameter, the pore size, the specific surface area and the three-phase boundary length per unit volume are calculated and correlated to 2D properties evaluated in a cross section, such as the mean diameter of the sectioned particles, the mean chord length, the particle perimeter exposed to the porous phase and the number of three-phase boundary points per unit area, respectively. A strong correlation is found between 2D and 3D properties in a wide range of porosity, particle size and electrode composition. A statistical analysis on the accuracy of the estimated properties as a function of the size of the cross section is also reported.

The results of this study provide practical indications that can be easily applied to Scanning Electron Microscope (SEM) images of real samples for a rapid estimation of the effective properties of the electrodes.