REaL-tIme characterization of ANisotropic Carbon-based tEchnological fibres, films and composites

Research Project, 2023 – 2027

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 highperformance
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.