Prediction of the mechanical characteristics of multi-walled carbon nanotube/epoxy composites using a new form of the rule of mixtures

• Published in: Carbon (New York) Vol. 48; no. 11; pp. 3218 - 3228
• Main Authors: Omidi, Meisam, Rokni D.T., Hossein, Milani, Abbas S., Seethaler, Rudolf J., Arasteh, R.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.09.2010; Elsevier
• Subjects: Carbon; Cross-disciplinary physics: materials science; rheology; Exact sciences and technology; Fullerenes and related materials; diamonds, graphite; Materials science; Mathematical models; Mechanical properties; Modulus of elasticity; Multi wall carbon nanotubes; Physics; Polymer matrix composites; Specific materials; Tensile strength; Waviness; Viscosity; Amines; Experimental data; Shape; Prediction; Mechanical properties; High temperature; Orientation; Carbon; Young modulus; Resistance; Composite materials; Multiwalled nanotube; Efficiency; Models; Resins; Rheological properties
• ISSN: 0008-6223; 1873-3891
• DOI: 10.1016/j.carbon.2010.05.007

Multi-walled carbon nanotubes (MWCNTs) were used in the low-viscosity, thermosetting polyester epoxy/amine resin LY-5052 with high temperature resistance to fabricate MWCNT/epoxy composites. Tensile tests of the specimens were carried out to obtain mechanical properties of MWCNT/epoxy composites for various weight-percents (wt.%) of MWCNTs. Experimental results show that the Young’s modulus and the tensile strength of the composites can be significantly improved by adding a small percentage of MWCNT. A new form of the rule of mixtures, including an exponential shape function, length efficiency parameter, orientation efficiency factor and a waviness parameter, is proposed for a more accurate prediction of the mechanical properties of MWCNT-reinforced epoxy composites, for both low and high wt.% ranges. In order to verify the suitability of the model, the ensuing predictions are compared to the available experimental data in the literature. Results demonstrate a good predictability of the modified form over a wide range of tests.