Measurement of the water absorption on hybrid carbon fibre prepreg waste composite and its impact on flexural performance

Carbon fibre (CF) prepreg, essential to composites and aircraft, generates waste known as carbon fibre prepreg waste (CFW) due to its limited lifespan. This study investigates recycling CFW through hybridization, milling it into powder and mixing it with epoxy resin and alumina to form hybrid compos...

Full description

Bibliographic Details
Published in:Functional Composites and Structures
Main Author: Ahmad Shukri A.A.; Nosbi N.; Omar M.F.; Md Saleh S.S.; Othman M.B.H.; Najib N.M.; Wan Ali W.F.F.
Format: Article
Language:English
Published: Institute of Physics 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202803971&doi=10.1088%2f2631-6331%2fad6e51&partnerID=40&md5=cf04c0020bf85ae7476f644e92ae87fc
Description
Summary:Carbon fibre (CF) prepreg, essential to composites and aircraft, generates waste known as carbon fibre prepreg waste (CFW) due to its limited lifespan. This study investigates recycling CFW through hybridization, milling it into powder and mixing it with epoxy resin and alumina to form hybrid composites. Using Minitab software, optimal compositions were determined from 13 and 20 experimental designs for CFW-EP and CFW-EP-AL, respectively. Results identified 2.5 wt% CFW and 97.5 wt% epoxy resin as optimal for CFW-EP, and 2.5 wt% CFW, 2.5 wt% alumina, and 95 wt% epoxy resin as optimal for CFW-EP-AL. Samples of epoxy resin polymer (EP), carbon prepreg waste reinforced composite (CFW-EP), and carbon prepreg waste reinforced with alumina composite (CFW-EP-AL) were fabricated and tested for moisture absorption and flexural strength, revealing noticeable deterioration over time. These findings highlight the importance of compositional analysis in developing sustainable materials with optimal flexural strength for various applications. © 2024 The Korean Society for Composite Materials and IOP Publishing Limited. All rights, including for text and data mining, AI training, and similar technologies, are reserved.
ISSN:26316331
DOI:10.1088/2631-6331/ad6e51