Descrizione del progetto
Imaging a raggi X innovativo per la scienza dei materiali
Un consorzio eterogeneo di esperti provenienti dal mondo accademico, dell’industria e della strumentazione a raggi X specializzata trainerà l’innovazione nella scienza dei materiali e nella produzione. Questa collaborazione consentirà lo sviluppo di nuovi materiali e processi di produzione basati su ricerche scientifiche all’avanguardia, garantendo al contempo che le innovazioni siano pratiche e applicabili nell’industria. Lavorando a stretto contatto con i partner dell’industria, il progetto RELIANCE, finanziato dall’UE, identificherà le sfide più urgenti che il settore manifatturiero deve affrontare e svilupperà soluzioni ad hoc. Gli esperti accademici e di strumentazione a raggi X apporteranno al progetto la loro esperienza scientifica e le loro conoscenze tecniche. I metodi di RELIANCE hanno il potenziale per rivoluzionare le soluzioni dell’Industria 4.0 fornendo un processo decisionale decentralizzato basato sulle proprietà strutturali attuali e osservate.
Obiettivo
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.
Campo scientifico
- 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
Programma(i)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Meccanismo di finanziamento
HORIZON-TMA-MSCA-DN - HORIZON TMA MSCA Doctoral NetworksCoordinatore
2800 Kongens Lyngby
Danimarca