Grothausmann, R.; Fiechter, S.; Beare, R.; Lehmann, G.; Kropf, H.; Vinod Kumar, G.S.; Manke, I.; Banhart, J.: Automated quantitative 3D analysis of faceting of particles in tomographic datasets. Ultramicroscopy 122 (2012), p. 65-75
Characterisation of facets of particles is a common problem. In this article an algorithm is pre- sented 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 trian- gle 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 analysed particle. Cha- racterisation of each particle according to any of these facet properties is then possible, e.g. statistics about dierent crystal shapes or removal of particles that do not show signicant faceting. Analyses of a 3D dataset obtained by Focused Ion Beam (FIB) tomography of a sample containing spinel particles are presented.