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Bioinspired self-healing of advanced composite structures using hollow glass fibres

Open access
Trask, R.S, Williams, G.J, Bond, I.P·2007·Journal of The Royal Society Interface

Abstract

Self-healing is receiving an increasing amount of worldwide interest as a method to autonomously address damage in materials. The incorporation of a self-healing capability within fibre-reinforced polymers has been investigated by a number of workers previously. The use of functional repair components stored inside hollow glass fibres (HGF) is one such bioinspired approach being considered. This paper considers the placement of self-healing HGF plies within both glass fibre/epoxy and carbon fibre/epoxy laminates to mitigate damage occurrence and restore mechanical strength. The study investigates the effect of embedded HGF on the host laminates mechanical properties and also the healing efficiency of the laminates after they were subjected to quasi-static impact damage. The results of flexural testing have shown that a significant fraction of flexural strength can be restored by the self-repairing effect of a healing resin stored within hollow fibres.

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Metadata

Authors
Trask, R. S., Williams, G. J., & Bond, I. P.
Venue
Journal of The Royal Society Interface
Published
2006-12-19
Volume
4
Issue
13
Pages
363-371
ISSN
  • 1742-5662 (ISSN-L)
  • 1742-5689
OpenAlex
W2089704347
Cited by
383
References
0
FWCI
17.33
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Bioinspired self-healing of advanced composite structures using hollow glass fibres. https://app.cochat.ai/papers/10.1098/rsif.2006.0194
The paper
Trask, R. S., Williams, G. J., & Bond, I. P. (2007). Bioinspired self-healing of advanced composite structures using hollow glass fibres. Journal of The Royal Society Interface. https://doi.org/10.1098/rsif.2006.0194

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.