Quantitative data analysis methods for 3D microstructure characterization of Solid Oxide Cells

The performance of electrochemical ceramic devices such as solid oxide fuel and electrolyser cells depends on the distribution of constituent phases on the micro or nano scale, also known as the microstructure. The microstructure governs key properties such as ion, electron and gas transport through percolating networks and reaction rates at the triple phase boundaries. Quantitative analysis of microstructure is thus important both in research and development of optimal microstructure design and fabrication. Three dimensional microstructure characterization in particular holds great promise for gaining further fundamental understanding of how microstructure affects performance. In this work, methods for automatic 3D characterization of microstructure are studied: from the acquisition of 3D image data by focused ion beam tomography to the extraction of quantitative measures that characterize the microstructure. The methods are exemplied by the analysis of Ni-YSZ and LSC-CGO electrode samples. Automatic methods for preprocessing the raw 3D image data are developed. The preprocessing steps correct for errors introduced by the image acquisition by the focused ion beam serial sectioning. Alignment of the individual image slices is performed by automatic detection of ducial marks. Uneven illumination is corrected by tting hypersurfaces to the spatial intensity variation in the 3D image data. Routine use of quantitative three dimensional analysis of microstructure is generally restricted by the time consuming task of manually delineating structures within each image slice or the quality of manual and automatic segmentation schemes. To solve this, a framework for the automatic segmentation of 3D image data is developed. The technique is based on a level set method and uses numerical approximations to partial differential equations to evolve a 3D surface to capture the phase boundaries. Vector fields derived from the experimentally acquired data are used as the driving forces. The framework performs the segmentation in 3D rather than on a slice by slice basis. It naturally supplies sub-voxel accuracy of segmented surfaces and allows constraints on the surface curvature to enforce a smooth surface in the segmentation. A high accuracy method is developed for calculating two phase boundary surface areas and triple phase boundary length of triple phase systems. The calculations are based on sub-voxel accuracy segmentations of the constituent phases. The method performs a three phase polygonization of the interface boundaries which results in a non-manifold mesh of connected faces. The triple phase boundaries can be extracted from the mesh as connected curve loops without branches. The accuracy of the method is analyzed by calculations on geometrical primitives. A suite of methods is developed for characterizing the shape and connectivity of phase networks. The methods utilize the fast marching method to compute distance maps and optimal paths in the microstructure network. The extracted measurements are suited for the quantitative comparison and evaluation of microstructures. The quantitative measures characterize properties of network path tortuosity, network thickness, transport path width and dead ends.