Computational Study of Graphene–Polypyrrole Composite Electrical Conductivity

Abstract

In this study, the electrical properties of graphene–polypyrrole (graphene-PPy) nanocomposites were thoroughly investigated. A numerical model, based on the Simmons and McCullough equations, in conjunction with the Monte Carlo simulation approach, was developed and used to analyze the effects of the thickness of the PPy, aspect ratio diameter of graphene nanorods, and graphene intrinsic conductivity on the transport of electrons in graphene–PPy–graphene regions. The tunneling resistance is a critical factor determining the transport of electrons in composite devices. The junction capacitance of the composite was predicted. A composite with a large insulation thickness led to a poor electrochemical electrode. The dependence of the electrical conductivity of the composite on the volume fraction of the filler was studied. The results of the developed model are consistent with the percolation theory and measurement results reported in literature. The formulations presented in this study can be used for optimization, prediction, and design of polymer composite electrical properties.

Advances in Monte Carlo Method for Simulating the Electrical Percolation Behavior of Conductive Polymer Composites with a Carbon-Based Filling

“…Additionally, the decrease in the polymer potential barrier and the increase in the graphene aspect ratio had a positive effect on the electrical tunneling behavior, as shown in Figure 6c-f. To study the feasibility of graphene-polypyrene (graphene-PPy) composites in th field of energy storage batteries, Folorunso et al [114] combined Simmons an McCullough equations with Monte Carlo simulations to develop a numerical model f an in-depth study of the electrical properties of graphene-PPy composites. The study le to the following conclusions: tunneling resistance was a key factor in determining the ele tron transport in the composites; the tunneling distance of graphene in the polymer w strongly related to its diameter and the insulating thickness; and an increase in the leng of graphene and a decrease in the insulating thickness led to a decrease in the tunnelin distance, which, in turn, favors the electron transport.…”

Development of Series-Parallel and Neural-Network Based Models for Predicting Electrical Conductivity of Polymer Nanocomposite

“…Therefore, studying the electrical conductivity of polymer nanocomposite electrodes is essential to their performance specifications. The total resistance of polymer nanocomposite can be represented as the sum of the tunneling and intrinsic resistance, as presented in Equation ( 1), [11], [12].…”

A review on synthetic strategies and gas sensing approach for polypyrrole‐based hybrid nanocomposites

“…Their introduction into PPy may lead to electronic interactions, charge transfers, morphological features, and integration of these effects between the constituent of nanocomposites system. The role of fillers in PPy with CNTs [ 43,44 ] shows high electrical conductivity, chemical stability, low mass density, and large surface area, but graphene [ 45,46 ] is preferred over CNTs due to its large sensing area per unit volume and high electron mobility with superior sensitivity at room temperature. [ 47,48 ] PPy and metal oxides (NiO, ZnO, TiO 2 , and CuO) composites have been described with catalytic behavior, high conductivity for use in wastewater treatment, and sensors.…”