SwissFEL

La plus récente grande installation de recherche du PSI génère de très courtes impulsions de rayons X, ayant les propriétés du laser. Cela permet aux chercheurs de suivre des processus extrêmement rapides tels que l'apparition de nouvelles molécules lors de réactions chimiques, de déterminer la structure détaillée de protéines vitales ou de comprendre la composition exacte de matériaux. Les chercheurs pourront ainsi obtenir des informations auxquelles les méthodes actuelles ne permettent pas d'accéder. Les connaissances acquises élargissent notre compréhension de la nature et débouchent sur des applications pratiques telles que de nouveaux médicaments, des processus plus efficaces dans l'industrie chimique ou de nouveaux matériaux en électronique.

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tensor_tomography

Macroscopic mapping of microscale fibers in freeform injection molded fiber-reinforced composites using X-ray scattering tensor tomography

Prediction of the mechanical properties dictated by the local microfiber orientation is essential for the performance characterization of fiber-reinforced composites. Typically, tomographic imaging methods that provide fine spatial resolution are employed to investigate various materials' local micro- and nano-architecture in a non-destructive manner. However, conventional imaging techniques are limited by a substantial trade-off between the structure size of interest and the accessible field of view (FOV). Researchers from the TOMCAT beamline at Paul Scherrer Institut, Xnovo Technology ApS, and the Technical University of Denmark have demonstrated the potential of X-ray scattering tensor tomography for industrial applications by characterizing the microstructure of a centimeter-sized industrially relevant freeform injection molding fiber-reinforced composite sample. This emerging technique provides unprecedented access to microstructural information over centimeter-sized sample volumes paving the way towards its potential integration as an invaluable tool, for instance, in the fiber-reinforced-composite (FRC) industry. The obtained fiber orientation and anisotropy information over statistically relevant large volumes can be used to predict the mechanical properties of final products, optimize production parameters, and improve fiber injection molding simulation frameworks. The work is published in Composites Part B: Engineering on 15 March 2022.

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