Highly Conductive Multifunctional Graphene Polycarbonate Nanocomposites

TLDR

Inherent conductivity, high aspect ratio, and nanostructure‑directed assembly of graphene with PC nanospheres drive the excellent electrical properties of the nanocomposites. Graphene nanosheet–bisphenol A polycarbonate nanocomposites were prepared by emulsion mixing and solution blending followed by compression molding, yielding percolation thresholds of ~0.14 and ~0.38 vol % respectively, and a stacked‑disk model was used to analyze SANS data to determine particle size, layer count, and spacing. The 2.2 vol % composites achieved conductivities of 0.512 S/cm (emulsion) and 0.226 S/cm (solution), displayed frequency‑independent behavior at 1.1 and 2.2 vol %, and exhibited higher dynamic tensile moduli and lower glass‑transition temperatures with increasing graphene, while TEM and SANS confirmed well‑dispersed graphene and connectivity in conductive samples.

Abstract

Graphene nanosheet−bisphenol A polycarbonate nanocomposites (0.027−2.2 vol %) prepared by both emulsion mixing and solution blending methods, followed by compression molding at 287 °C, exhibited dc electrical percolation threshold of ∼0.14 and ∼0.38 vol %, respectively. The conductivities of 2.2 vol % graphene nanocomposites were 0.512 and 0.226 S/cm for emulsion and solution mixing. The 1.1 and 2.2 vol % graphene nanocomposites exhibited frequency-independent behavior. Inherent conductivity, extremely high aspect ratio, and nanostructure directed assembly of the graphene using PC nanospheres are the main factors for excellent electrical properties of the nanocomposites. Dynamic tensile moduli of nanocomposites increased with increasing graphene in the nanocomposite. The glass transition temperatures were decreased with increasing graphene for the emulsion series. High-resolution electron microscopy (HR-TEM) and small-angle neutron scattering (SANS) showed isolated graphene with no connectivity path for insulating nanocomposites and connected nanoparticles for the conductive nanocomposites. A stacked disk model was used to obtain the average particle radius, average number of graphene layers per stack, and stack spacing by simulation of the experimental SANS data. Morphology studies indicated the presence of well-dispersed graphene and small graphene stacking with infusion of polycarbonate within the stacks.