The Centre for Materials and Processes of IMT Nord Europe guest edits a Special Issue of the open access journal “Polymers” (IF: 4.967, Q1) dedicated to ‘’Fiber Reinforced Thermoplastic Composites: Processing / Structure / Performance Inter-relationships‘’. Manuscript submission is open until 31 May 2023.
Message from the Guest Editors:
This Special Issue aims to exhibit cutting-edge research in the field of fiber-reinforced thermoplastic composites. The search for eco-responsible solutions is attracting the interest of end-use industries toward fiber-reinforced thermoplastic composites (FRT). However, numerous challenges are still limiting the development of efficient optimization approaches of FRT composites for structural parts. Such challenges emanate from complexities related to (i) the multiscale structure of reinforcement and (ii) multiphysical phenomena governing the use of thermoplastics within liquid resin transfer processes.
In this context, the development of new interdisciplinary approaches for better understanding processing–structure–performance inter-relationships is encouraged to alleviate challenges related to (i) smart manufacturing, (ii) advanced microstructure characterization, (iii) numerical modeling of physical phenomena or (iv) simulation approaches.
Multidisciplinary articles and review papers are encouraged to cover emerging topics such as artificial intelligence applied to manufacturing, data-driven simulations, multimodal microstructure characterization, hierarchical FRT composites, mechanical metamaterials, etc.
Ass. Prof. Dr. Abderrahmane Ayadi
Prof. Dr. Patricia Krawczak
Prof. Dr Chung-Hae Park
Keywords: high-performance thermoplastic composites; hierarchical fibre-reinforced composites; mechanical metamaterials; ultra-lightweight composites; one-shot short cycle time manufacturing processes; zero-defect manufacturing; low cost manufacturing technologies; non-destructive imagery-based microstructure characterization; numerical modelling and simulation; process-induced flaws prediction; image-based full-scale simulations; artificial intelligence-based manufacturing; data-driven simulations