Processing Temperature Effect on Failure Behavior of Unidirectional Thermoplastic Polymer-fiber-reinforced Polymers (PFRPs)

Abstract

This study aimed to investigate the influence of processing temperature on the mechanical and morphological properties of unidirectional (UD) thermoplastic polymer-fiber-reinforced polymers (PFRPs). These composites are known for their high recyclability and sustainability. The research focused on UD UHMWPE-polymer-fiber-reinforced HDPE composites as a specific example. To achieve this objective, UD thermoplastic PFRPs were produced through filament winding and hot-pressing techniques, employing five distinct processing temperatures within the range spanning from the melting onset temperature of the polymer matrix to the melting peak temperature of the reinforcing polymer fiber. By conducting the uni-axial tensile tests on the UD UHMWPE-polymer-fiberreinforced HDPE composites fabricated at different processing temperatures, it was shown that the optimal longitudinal tensile properties of the composites, comparable with glassfiber- reinforced thermoset or thermoplastic polymers (GFRPs or GFRTPs), can be achieved when the processing temperature does not significantly exceed the melting onset temperature of the reinforcing polymer fiber. However, when the processing temperature exceeds this threshold, the mechanical properties of the composites are significantly reduced, as evidenced by the transition in the failure morphology from the presence of significant splitting cracks to the occurrence of plastic necking due to the complete melting of the reinforcing polymer fibers in a composite. Particularly, the ductile behavior of the optimal thermoplastic PFRPs investigated in this study is superior than that of carbon-fiberreinforced thermoset or thermoplastic polymers (CFRPs or CFRTPs) and even GFRPs and GFRTPs. This study not only provides valuable insights into the proper fabrication of highperformance thermoplastic PFRPs but also offers useful experimental data that can aid in the validation and development of computational models, particularly those related to processing modeling.