Electrical Conductivity Modeling of Graphene-based Conductor Materials

Abstract

Graphene-based conductors such as films and fibers aim to transfer graphene's extraordinary properties to the macroscopic scale. They show great potential for large-scale applications, but there is a lack of theoretical models to describe their electrical characteristics. We present a network simulation method to model the electrical conductivity of graphene-based conductors. The method considers all of the relevant microscopic parameters such as graphene flake conductivity, interlayer conductivity, packing density, and flake size. To provide a mathematical framework, we derive an analytical expression, which reproduces the essential features of the network model. We also find good agreement with experimental data. Our results offer production guidelines and enable the systematic optimization of high-performance graphene-based conductor materials. A generalization of the model to any conductor based on two-dimensional materials is straightforward.

Strain Sensing Coatings for Large Composite Structures Based on 2D MXene Nanoparticles

“…The electromechanical mechanism of nanoparticle-based strain sensors is well explained by an analytical approach [34]. Surface topography images also provide in-depth details on how the structure of the nanocoating behaves under a wide range of deformations (0-60%) [32].…”

Anisotropic transport properties of graphene-based conductor materials

“…They characterize the individual microscopic building blocks of the thin film and are closely linked to the macroscopic conductivity tensor. The input parameters can be modeled according to statistical distributions or with uniform effective quantities [23]. Even though the flakes do not form a perfect single layer, this approach has shown to be a good approximation as was shown in comparison with experimental data taken from different films [25].…”

“…Further details are reported in Refs. [23,24]. We modeled our nanographite flakes as randomly shaped polygons with a surface area A and a thickness t flake .…”

“…Also, transfer matrix methods for calculating a dynamical conductivity were reported [22]. Very recently, simulations based on random resistor networks were established to model systems made from 2D building blocks [23][24][25].…”

Electronic Transport in 2D‐Based Printed FETs from a Multiscale Perspective

“…[ 18 ] Very recently, Rizzi et al. [ 19,20 ] have proposed a computationally efficient resistor network model for graphene‐based conductor materials to calculate the overall electrical conductivity. Nonetheless, this and other methods require strong assumptions in the consideration of vertical transport: for example, the overlapping regions are collapsed into single points or external/fitting parameters are needed to model conductance between overlapping nanotubes.…”