Automated quantitative 3D analysis of faceting of particles in tomographic datasets

Characterization of facets of particles is a common problem. In this paper an algorithm is presented which allows automated quantitative 3D analysis of facets of many particles within tomographic datasets. The algorithm is based on the analysis of probability distributions of the orientations of triangle normals of mesh representations. The result consists of lists containing number of detected facets, their size, global orientation and the interplanar angles between facets for each analyzed particle. Characterization of each particle according to any of these facet properties is then possible, e.g. statistics about different crystal shapes or removal of particles that do not show significant faceting. Analyses of a 3D dataset obtained by focused ion beam (FIB) tomography of a sample containing spinel particles are presented.