Description du projet
Imagerie à rayons X innovante pour la science des matériaux
Un consortium diversifié composé d’experts issus du monde universitaire, de l’industrie et de l’instrumentation spécialisée dans les rayons X stimulera l’innovation dans le domaine de la science et de la fabrication des matériaux. Cette collaboration permettra de développer de nouveaux matériaux et procédés de fabrication sur la base d’une recherche scientifique de pointe, tout en veillant à ce que les innovations soient pratiques et applicables dans l’industrie. En travaillant étroitement avec des partenaires industriels, le projet RELIANCE, financé par l’UE, identifiera les défis les plus urgents auxquels le secteur manufacturier est confronté, et développera des solutions pour les relever. Les experts universitaires en instrumentation à rayons X apporteront leurs compétences scientifiques et leurs connaissances techniques au projet. Les méthodes de RELIANCE pourraient révolutionner les solutions de l’industrie 4.0 en fournissant une prise de décision décentralisée basée sur les propriétés structurelles actuelles et observées.
Objectif
RELIANCE will develop and implement depth-resolved multimodal X-ray imaging and scattering tools that will enable the automated real-time characterization at the nano-scale of the structure and morphology of materials, devices and their manufacturing processes, reliably and with precision. Providing training in the use of these tools, as well as training in open-access science and development of transferable skills for all ESR fellows is one of the key objectives of RELIANCE.
The methodologies developed by RELIANCE will be implemented for optimizing and controlling the processing of high-performance polymeric materials and composites, i.e. solution-spinning of aramid fibres, compaction-heat stretching of polyethylene film, and pultrusion of composites. RELIANCE will significantly improve quality control of a wide range of technological materials used in composite materials. Through integration of real-time data analysis and process parameters by application of machine learning, the methods will lend themselves to Industry 4.0 solutions relying on cyber physical systems for decentralized decisions based on actual, current structural properties observed during processing.
The real-time access to nanostructure in the diverse applications is provided by specialized X-ray instrumentation. A shared methodology for data reconstruction and machine-learning assisted analysis exploiting prior knowledge and modelling of structural anisotropy, is applied to enable the data reduction speed required to match industrial processing.
RELIANCE brings together a consortium of leading international experts in X-ray scattering, imaging and automatized analysis of scattering data, 3D reconstruction algorithms and automatized analysis of imaging data and Materials Applications, with industrial leaders in manufacturing and application of high-performance polymer materials, and in highly specialized X-ray instrumentation and scientific data acquisition and analysis.
Champ scientifique
- engineering and technologymechanical engineeringmanufacturing engineering
- engineering and technologymaterials engineeringcomposites
- natural scienceschemical sciencespolymer sciences
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencescomputer and information sciencesdata sciencedata processing
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Régime de financement
HORIZON-TMA-MSCA-DN - HORIZON TMA MSCA Doctoral NetworksCoordinateur
2800 Kongens Lyngby
Danemark