XRCT characterisation of Ti particles inside porous Al2O3

Computed X-ray tomography was used to characterise distribution and sphericity of Ti granules within highly porous (> 35%) Al2O3 powder compacts, as they are key parameters for a successful infiltration by Fe-based alloys. Setting of reconstruction constraints, image editing as well as data processing are the most challenging parts of computed X-ray tomography and principal sources of errors that bias the generated data. Thus, corrective measures have to be applied and the reliability of generated data has to be proved with respect to statistical, stereological and volumetric aspects. Combining an adapted Interface Particle Treatment Algorithm with the Marching Cube Method, Equilibrium Random State Model, cluster splitting and conventional laser diffraction measurements a significant improvement of the three-dimensional reconstructed data was achieved. This study points out the need of the applied algorithms for the proof and improvement of generated data by computed X-ray tomography and gives a short survey of methods that can be applied.