Tomographic Techniques for Multiscale Imaging and Material Characterization


18 Sept.			11:30 - 13:00

ROOM 6

CHARACTERIZATION & METROLOGY
TT.VI - Technical Parallel Track Sessions
Tomographic Techniques for Multiscale Imaging and Material Characterization
Session organized by Sapienza University of Rome Chair: Eugenio CARMINATI, Sapienza University of Rome
Tomographic techniques have become indispensable tools for non-destructive, high-resolution imaging across a wide range of scientific and engineering fields. This session will explore recent advances in tomographic methods, ranging from X-ray Computed Tomography and Electron Tomography to advanced Optical and Synchrotron-based approaches that enable multiscale visualization of structural, morphological, and functional properties in both biological and material systems. Particular emphasis will be placed on developments that push the boundaries of spatial resolution, contrast mechanisms, data reconstruction, and multimodal integration. Contributions addressing applications in materials science, life sciences and energy-related technologies are especially welcome. This session aims to foster cross-disciplinary dialogue and highlight how tomographic imaging is shaping our understanding of complex systems from the nanoscale to the macroscale.
The symposium is part of YougInnovation (FE.II)
TT.VI.H.1 FE.II.12.1	Introductive Keynote Matteo FERRONI University of Brescia and CNR-INSMN Electron tomography techniques and perspectives in materials characterization
TT.VI.H.2 FE.II.12.2	Martina BERNABALE Sapienza University of Rome Application of X-ray microscopy and correlative techniques in the study of ancient metallurgy and corrosion processes
TT.VI.H.3 FE.II.12.3	Flavio COGNIGNI ZEISS Italia Title in definition
TT.VI.H.4 FE.II.12.4	Maria Caterina CROCCO University of Calabria Multiscale study of optical fibers using X-ray computed tomography
TT.VI.H.5 FE.II.12.5	Angelica ACCORINTI - CV Sapienza University of Rome AI-Driven Workflows for Enhanced Processing and Analysis of Complex X-ray Microscopy Datasets