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Texture tomography, a versatile framework to study crystalline texture in 3D.
- Source :
-
IUCrJ [IUCrJ] 2024 Sep 01; Vol. 11 (Pt 5), pp. 809-820. Date of Electronic Publication: 2024 Sep 01. - Publication Year :
- 2024
-
Abstract
- Crystallographic texture is a key organization feature of many technical and biological materials. In these materials, especially hierarchically structured ones, the preferential alignment of the nano constituents heavily influences the macroscopic behavior of the material. To study local crystallographic texture with both high spatial and angular resolution, we developed Texture Tomography (TexTOM). This approach allows the user to model the diffraction data of polycrystalline materials using the full reciprocal space of the crystal ensemble and describe the texture in each voxel via an orientation distribution function, hence it provides 3D reconstructions of the local texture by measuring the probabilities of all crystal orientations. The TexTOM approach addresses limitations associated with existing models: it correlates the intensities from several Bragg reflections, thus reducing ambiguities resulting from symmetry. Further, it yields quantitative probability distributions of local real space crystal orientations without further assumptions about the sample structure. Finally, its efficient mathematical formulation enables reconstructions faster than the time scale of the experiment. This manuscript presents the mathematical model, the inversion strategy and its current experimental implementation. We show characterizations of simulated data as well as experimental data obtained from a synthetic, inorganic model sample: the silica-witherite biomorph. TexTOM provides a versatile framework to reconstruct 3D quantitative texture information for polycrystalline samples; it opens the door for unprecedented insights into the nanostructural makeup of natural and technical materials.<br /> (open access.)
Details
- Language :
- English
- ISSN :
- 2052-2525
- Volume :
- 11
- Issue :
- Pt 5
- Database :
- MEDLINE
- Journal :
- IUCrJ
- Publication Type :
- Academic Journal
- Accession number :
- 39046078
- Full Text :
- https://doi.org/10.1107/S2052252524006547