Superior nano-mechanical properties of reduced graphene oxide reinforced polyurethane composites. Issue 22 (9th February 2015)

• Record Type: Journal Article
• Authors: Gupta, Tejendra K.; Singh, Bhanu P.; Tripathi, Ravi Kant; Dhakate, Sanjay R.; Singh, Vidya N.; Panwar, O. S.; Mathur, Rakesh B.
• Is Part Of: RSC advances. Volume 5:Issue 22(2015)
• Page Start: 16921
• Page End: 16930
• Publication Date: 2015-02-09
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/c4ra14223c
• Languages: English
• ISSNs: 2046-2069

Abstract

Abstract : RGO reinforced polymer composites with significantly enhanced nanomechanical properties useful for automobile, wind mill blade industries and also in hard and scratch-less coatings on automotive vehicles have been synthesized. Abstract : Polyurethane (PU) based composites were prepared by solvent casting techniques using different wt% (0–5 wt%) of reduced graphene oxide (RGO) as reinforcement. A nanoindentation study has been carried out on these composite sheets in order to investigate their nano-mechanical properties. Incorporation of different wt% RGO into the PU matrix led to a significant increase in the hardness and elastic modulus of the composites. The maximum nanoindentation hardness of 140 MPa for 5.0 wt% RGO loading was observed as compared to 58.5 MPa for pure PU (an overall improvement of 139%). The nanoindentation elastic modulus for the 5.0 wt% RGO loaded sample was 881.7 MPa as compared to 385.7 MPa for pure PU (an overall improvement of 129%). The enhancement in the nano-mechanical properties was correlated with spectroscopic and microscopic investigations using Raman spectroscopy, scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Due to their excellent nano-mechanical properties, these composites find usefulness in structural applications such as the automobile and wind mill blade industries. These composites can also be used in hard and scratch-less coatings on automotive vehicles. The experimental results were in good agreement with theoretical predictions.