Project description
Innovative X-ray imaging for materials science
A diverse consortium of experts from academia, industry and specialised X-ray instrumentation will drive innovation in materials science and manufacturing. This collaboration will enable the development of new materials and manufacturing processes informed by cutting-edge scientific research while also ensuring that the innovations are practical and applicable in industry. By working closely with industry partners, the EU-funded RELIANCE project will identify the most pressing challenges facing the manufacturing sector and develop solutions that address these challenges. The academic and X-ray instrumentation experts will bring their scientific expertise and technical knowledge to the project. RELIANCE’s methods have the potential to revolutionise Industry 4.0 solutions by providing decentralised decision-making based on current, observed structural properties.
Objective
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.
Fields of science
- natural sciencescomputer and information sciencesdata science
- engineering and technologymechanical engineeringmanufacturing engineering
- engineering and technologymaterials engineeringcomposites
- natural scienceschemical sciencespolymer sciences
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-DN - HORIZON TMA MSCA Doctoral NetworksCoordinator
2800 Kongens Lyngby
Denmark
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Participants (4)
2311 EZ Leiden
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412 96 GOTEBORG
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33700 Merignac
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601 90 Brno Stred
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Partners (11)
5232 Villigen Psi
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3526 KV Utrecht
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6824 BM Arnhem
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38360 Sassenage
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
5500 Middelfart
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504 64 BORAS
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1098 XG Amsterdam
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
405 31 Goteborg
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CW9 6GG NORTHWICH
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1015 Lausanne
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M13 9PL Manchester
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