Effect of specific surface area on the rheological properties of graphene nanoplatelet/poly(ethylene oxide) composites

Author:

Haridas Haritha1ORCID,Kontopoulou Marianna1ORCID

Affiliation:

1. Department of Chemical Engineering, Graphene Integrated Functional Technologies, Dupuis Hall, Queen’s University , 19 Division Street, Kingston, ON K7L 3N6, Canada

Abstract

The rheological properties of poly(ethylene oxide) containing graphene nanoplatelets (GNPs) having different specific surface areas (SSAs) are studied using steady shear and small amplitude oscillatory shear experiments. A series of GNPs having SSAs ranging from 175 ± 5 to 430 ± 13 m2/g was prepared using a thermomechanical exfoliation process. The complex viscosity, moduli, and yield stress of the composites increase with SSA, whereas electrical and rheological percolation threshold concentrations decrease, suggesting that higher SSAs promote filler network formation. Modeling of small amplitude oscillatory shear data using a two-phase model confirms that hydrodynamic effects dominate at low concentrations below 8 wt. %, where the particles are noninteracting. At higher concentrations, the response is dominated by filler-phase contributions. We demonstrate that the two-phase model parameters can be used to track the exfoliation of graphite into GNPs. Fitting of rheological percolation curves using Utracki and Lyngaae–Jørgensen models at low concentrations (noninteracting regime) resulted in aspect ratios between 19 and 76. At high concentrations (interacting particles), the aspect ratios determined by the Krieger–Daugherty model ranged between 5 and 24 due to aggregation. The highest aspect ratios (defined as the ratio of major dimension to minor dimension) were associated with GNPs that had the highest SSA of 430 m2/g. Strain sweeps revealed that the critical strain for the onset of nonlinear viscoelasticity scaled with SSA above the percolation threshold. The scaling relationships of the critical strain and storage modulus with volume fraction were used to infer the fractal dimensions of filler networks.

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Society of Rheology

Subject

Mechanical Engineering,Mechanics of Materials,Condensed Matter Physics,General Materials Science

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