journal article·2013-09

Electrical and mechanical properties of PMMA/reduced graphene oxide nanocomposites prepared via in situ polymerization

Sandeep Nath Tripathi, Parveen Saini, Deeksha Gupta, Veena Choudhary

Journal of Materials Science· Volume 48· Issue 18
Publisher page

Abstract

We report the effect of filler incorporation techniques on the electrical and mechanical properties of reduced graphene oxide (RGO)-filled poly(methyl methacrylate) (PMMA) nanocomposites. Composites were prepared by three different techniques, viz. in situ polymerisation of MMA monomer in presence of RGO, bulk polymerization of MMA in presence of PMMA beads/RGO and by in situ polymerization of MMA in presence of RGO followed by sheet casting. In particular, the effect of incorporation of varying amounts (i.e. ranging from 0.1 to 2 % w/w) of RGO on the electrical, thermal, morphological and mechanical properties of PMMA was investigated. The electrical conductivity was found to be critically dependent on the amount of RGO as well as on the method of its incorporation. The electrical conductivity of 2 wt% RGO-loaded PMMA composite was increased by factor of 107, when composites were prepared by in situ polymerization of MMA in the presence of RGO and PMMA beads, whereas, 108 times increase in conductivity was observed at the same RGO content when composites were prepared by casting method. FTIR and Raman spectra suggested the presence of chemical interactions between RGO and PMMA matrix, whereas XRD patterns, SEM and HRTEM studies show that among three methods, the sheet-casting method gives better exfoliation and dispersion of RGO sheets within PMMA matrix. The superior thermal, mechanical and electrical properties of composites prepared by sheet-casting method provided a facile and logical route towards ultimate target of utilizing maximum fraction of intrinsic properties of graphene sheets.
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Research context

OpenAlex topics: Graphene research and applications · Graphene and Nanomaterials Applications · Polymer Nanocomposite Synthesis and Irradiation

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

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