Study on mechanical behaviors and failure mechanism of polyurethane matrix composites inspired by mussel chemistry and arthropod exoskeleton structures under dynamic impact
Source abstract
Abstract
Polyurethane elastomer (PUE), an elastic polymer material of lightweight and unexceptionable mechanical properties, is widely used into the military protective structural materials to resist dynamic impact and absorb energy. However, the mechanical and thermal properties of PUE need to be enhanced due to failure damage caused by the thermal stress softening under high-speed impact. Inspired by the mussel chemistry and the exoskeleton structures of arthropods, catechol and polyethyleneimine were used to functionalize micro carbon fibers (MCFs) to enhance the mechanical and thermal properties of PUE composites. Compared with Pure PUE, the static compression modulus of PUE composite with a filler content of 2.0 wt.% was increased by 99.25%. The dynamic maximum strength and energy absorption were improved by 74.08% and 102.92%, respectively. Besides, the modified MCFs could significantly enhance the viscoelasticity and thermal conductivity characteristics of composites. The enhancement of impact resistance and energy absorption capability of the composites are mainly due to the synergistic effect of tough mussel adhesion proteins and enhancing MCFs. Thereinto, MCFs could provide incredible strength, and plenty of crosslinking networks based on phenol-amine chemistry were served as supporting structures to resist dynamic impact by effective energy dissipation. Therefore, this work can provide a way to prepare PUE composites with excellent thermal and mechanical performance, and it is beneficial to understand the deformation and failure mechanisms of PUE and other soft polymer materials under dynamic impact.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Marine Biology and Environmental Chemistry · Polymer composites and self-healing · Polymer Surface Interaction Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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