Statistical characterization and simulation of graphene-loaded polypyrrole composite electrical conductivity

In this study, an effective method has been described and adopted to quantify the diameter and length of graphene nanofiller. The experimentally measured graphene parameters were modelled by using the Weibull distribution. The fitted graphene nanofiller length and diameter were used to predict the electrical conductivity of the graphene-loaded polypyrrole. The reliability of the dispersion of the filler in the matrix is, aided by the adequate distribution of the filler. An analytical model was developed to study the conductivity of the polypyrrole-graphene (PPy-Gr) composite. In the model, the interfacial effect of the composite constituents was considered and the electrical conductivity of the composite was determined by the simple-sum method. The percolation threshold and the electrical conductivity dependencies of the composites were evaluated by concurrently varying the potential barrier, filler electrical conductivity and the interfacial thickness and the matrix conductivity. The current model produced results, which are in good agreement with experimental measurements of different polymer-composites. It is envisaged that the method employed in this study, can be extended to other polymer-filler mixture as a predictive, optimization and design tool, for polymer composites of any type. (C) 2020 The Author(s). Published by Elsevier B.V.