Tomographic images are often superimposed by so called ring artefacts. Ring artefacts are concentric rings in the images around the center of rotation of the tomographic setup caused e.g. by differences in the individual pixel response of the detector. They complicate the post processing of the data, i.e. the segmentation of individual image information. Hence, for a quantitative analysis of the tomographic images a significant reduction of these artefacts is essential. In this paper, a simple but efficient method to eliminate such artefacts during the reconstruction is proposed.

Nondestructive 3D mapping of crystallographic phases is introduced providing distribution of phase fractions within the bulk (centimeter range) of samples with micrometer-scale resolution. The novel neutron tomography based technique overcomes critical limitations of existing techniques and offers a wide range of potential applications. It is demonstrated for steel samples exhibiting phase transformation after being subjected to tensile and torsional deformation.

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A Geant4-based Python/C++ simulation and coding framework, which has been developed and used in order to aid the R&D efforts for thermal neutron detectors at neutron scattering facilities, is described. Built upon configurable geometry and generator modules, it integrates a general purpose object oriented output file format with meta-data, developed in order to facilitate a faster turn-around time when setting up and analysing simulations. Also discussed are the extensions to Geant4 which have been implemented in order to include the effects of low-energy phenomena such as Bragg diffraction in the polycrystalline support materials of the detector. Finally, an example application of the framework is briefly shown.