Constructing Zirconia Fiber Bridging via Electrospinning to Improve Pre‐Impact and Post‐Impact Flexural Strength of Carbon Fiber Reinforced Polymer
Source abstract
Abstract
ABSTRACT Carbon fiber reinforced polymer (CFRP) composite has undoubtedly revolutionized advanced engineering applications due to its lightweight and high strength. In this study, self‐made zirconia fiber (ZF) via electrospinning was introduced into the interlayer of laminated CFRP composites to construct the fiber bridging to prevent crack generation and propagation, which could improve weak regions of resin‐rich region (RRR) and interfacial transition region (ITR). Low‐velocity impact results showed ZF‐implanted CFRP composites exhibited better impact resistance than unreinforced CFRP composites. Three‐point bending testing results demonstrate that the flexural strength of CFRP composites with 0.25 wt.% ZF before and after impact yielded the greatest 26.3% and 133.4% increments respectively compared with unreinforced ones, and the former had 55% and 121.5% higher energy absorption than that of the control group in pre impact and post‐impact damaged energy absorption respectively. XRM‐CT and SEM scanning results indicated the trace of fiber bridging of ZF on the damaged surface and its effects on shifting delamination failure of unreinforced CFRP composite to shear failure of ZF‐implanted CFRP composites. Overall, introducing ZF into the interlayer might be an easy and effective method for manufacturing high‐performance CFRP composites in industries.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Electrospun Nanofibers in Biomedical Applications · Fiber-reinforced polymer composites · Mechanical Behavior of Composites
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Shock and Vibration of Engineering Materials and Structures Key Lab of Sichuan Province, School of Materials and Chemistry Southwest University of Science and Technology Mianyang China
Institute of Automation Chinese Academy of Sciences Beijing China
School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China
Department of Plasticity Lomonosov Moscow State University Moscow Russia
School of Aerospace Engineering Tsinghua University Beijing China
School of Mechanical Engineering University of Western Australia Perth Australia
Funding
Natural Science Foundation of Sichuan Province
References (47)
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