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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/235918
- Title
- Fabrication and characterization of nano-particles-enhanced epoxy
- Author(s)
- Faleh, Haydar; Al-Mahaidi, Riadh; Shen, Luming
- Abstract
- Epoxy has been widely used as adhesives in retrofitting structures with carbon fiber reinforced polymer (CFRP). In this study, different weight fractions of multi-walled carbon nanotubes (MWCNTs) and Silicon Carbide nanopowder (SiC) will be dispersed into epoxy to produce toughened adhesives that can effectively improve the CFRP/structure bonding performance. The preliminary experimental results indicate that adding 2 wt.% MWCNTs into Araldite-420 will increase its ultimate strength by 17% and its elastic modulus by 14%. On the other hand, Araldite-420's elastic modulus will increase by nearly 50% when 1.0 wt.% of SiC powder is added. Ultrasonic mixing may increase the elastic modulus of Sikadur-30 but reduce its strength and ductility regardless of the amount of nanoparticles dispersed. No significant effect of nano-particle infusion on the glass transition temperature of the epoxies was found. The mechanism of nanoparticles infusion effects on the mechanical properties of the epoxies is also examined using SEM.
- Publication type
- Journal article
- Research centre
- Swinburne University of Technology. Faculty of Engineering and Industrial Sciences
- Source
- Composites Part B: Engineering, Vol. 43, no. 8 (Dec 2012), pp. 3076-3080
- Publication year
- 2012
- FOR Code(s)
- 09 Engineering
- Keyword(s)
- Carbon fibre reinforced polymers; Epoxy; Mechanical properties; Multi-walled carbon nanotubes; Nanoparticles; Particle-reinforcement; PMCs; Polymer-matrix composites; Silicon Carbide nanopowder
- Publisher
- Elsevier
- ISSN
- 1359-8368
- Publisher URL
- http://dx.doi.org/10.1016/j.compositesb.2012.04.055
- Copyright
- Copyright © 2012 Elsevier Ltd. All rights reserved.
- Research Projects
-
Multi-scale model-based simulation of glass fragmentation under blast loading, Australian Research Council grant number DP0772478
- Peer reviewed
