journal article·2013-11

Graphene oxide and base-washed graphene oxide as reinforcements in PMMA nanocomposites

Cristina Vallés, Ian A. Kinloch, Robert J. Young, Neil R. Wilson, Jonathan P. Rourke

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Abstract

Graphene oxide (GO) prepared using the Hummers' method is known to be composed of functionalized graphene sheets decorated by strongly-bound oxidative debris that can be removed by a simple base wash. The use of as-made GO and base-washed GO as reinforcing fillers in poly(methyl methacrylate) (PMMA) nanocomposites has been compared through dynamic mechanical thermal analysis and tensile testing. Nanocomposites with loadings from 0.5 to 10wt.% were produced by melt mixing using a twin screw extruder. Large shifts in the values of Tg for the nanocomposites with respect to PMMA suggest the presence of interactions between the GO and polymer. Thermogravimetric analysis also revealed a significant increase in the decomposition temperatures upon the addition of the GO. Optimal loadings of 1wt.% were found for both fillers, up to which substantial mechanical reinforcement was observed. Comparison with previous nanotube systems, suggests that there was a good dispersion of both fillers below 1wt.%, with aggregation and a deterioration of the mechanical properties occurring at higher loadings. Stress-induced shifts of the Raman D band in the GO revealed the existence of stress-transfer from the PMMA matrix to the fillers during deformation. Overall the as-made GO gave nanocomposites with better properties than those reinforced with based-washed material. Hence, it appears that the presence of the oxidative debris in GO, which acts as a compatibilising surfactant, is beneficial in producing nanocomposites with both a good dispersion and a strong interface between GO and a polymer matrix. © 2013 Elsevier Ltd.
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Research context

OpenAlex topics: Graphene research and applications · Graphene and Nanomaterials Applications · Polymer Nanocomposites and Properties

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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