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The three-dimensional microstructure of polycrystalline materials unravelled by synchrotron light, , , , , , , , and . Actualite Chimique, (October 2011)Three-dimensional grain mapping by x-ray diffraction contrast tomography and the use of Friedel pairs in diffraction data analysis, , , , , , , and . Review of Scientific Instruments, 80 (3): 033905 (2009)X-ray micro-tomography an attractive characterisation technique in materials science, , , , , , , , , and . Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 200 (0): 273 - 286 (2003)Proceedings of the E-MRS 2002 Symposium I on Synchrotron Radiation and Materials Science.New opportunities for 3D materials science of polycrystalline materials at the micrometre lengthscale by combined use of X-ray diffraction and X-ray imaging, , , , , , , , , and 3 other author(s). Materials Science and Engineering: A, 524 (1-2): 69--76 (2009)Special Topic Section: Probing strains and Dislocation Gradients with diffraction.Three dimensional imaging of damage in structural materials using high resolution micro-tomography, , , , , and . Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 238 (1-4): 75--82 (2005)Synchrotron Radiation in Materials Science - Proceedings of the 4th Conference on Synchrotron Radiation in Materials Science.Interaction of Legionella pneumophila with Dictyostelium discoideum, , , , , , , , , and 1 other author(s). Legionella-Proceedings of the 5th International Symposium, (2001)Symmetries in Physics: Group Theory applied to Physical Problems, and . Springer, Berlin, Second edition, (1996)High resolution X-ray tomography of micromechanisms of fatigue crack closure, , , and . Scripta Materialia, 55 (1): 47 - 50 (2006)Viewpoint set no. 41 "3D Characterization and Analysis of Materials" Organized by G. Spanos.Characterization of polycrystalline materials using synchrotron X-ray imaging and diffraction techniques, , , , , , , , and . JOM Journal of the Minerals, Metals and Materials Society, 62 (12): 22--28 (2010)A Neurobiologically-inspired Deep Learning Framework for Autonomous Context Learning., , and . ICTAI, page 97-104. IEEE, (2021)