Advancement of the Power-Law Model and Its Percolation Exponent for the Electrical Conductivity of a Graphene-Containing System as a Component in the Biosensing of Breast Cancer

Abstract

The power-law model for composite conductivity is expanded for graphene-based samples using the effects of interphase, tunnels and net on the effective filler fraction, percolation start and “b” exponent. In fact, filler dimensions, interphase thickness, tunneling distance and net dimension/density express the effective filler fraction, percolation start and “b” exponent. The developed equations are assessed by experimented values from previous works. Additionally, the effects of all parameters on “b” exponent and conductivity are analyzed. The experimented quantities of percolation start and conductivity confirm the predictability of the expressed equations. Thick interphase, large tunneling distance, high aspect ratio and big nets as well as skinny and large graphene nano-sheets produce a low “b” and a high conductivity, because they improve the conduction efficiency of graphene nets in the system. Graphene-filled nanocomposites can be applied in the biosensing of breast cancer cells and thus the developed model can help optimize the performance of biosensors.

Incorporating Microbial Pilin-Based Nanowires into a Water-Stable Electronic Polymer Composite

“…As previously observed with e-PN/PVA composites [20], the conductivity of the e-PN/PVB composites increased with increasing weight percent e-PN (Fig. 2a-d), following classical percolation theory [26]:…”

Effect of microcarbon particle size and dispersion on the electrical conductivity of LLDPE-carbon composite

“…These particles exist within the polymer matrix, creating an interphase region where the filler acts as the nucleus of crystal structures formed during the solidification process. Zare et al (2022) suggest that the electrical conductivity of conductive composite samples can be improved with a thick interphase region. When this area is linked to the tunneling area, it can increase the density and proportionally enhance electron flow within the composite.…”

“…The electrical conductivity of conductive composites can be calculated with predictability, whereby 𝜎𝜎 0 can be obtained through sample tests once the percolation threshold is achieved. Zare et al (2022) suggest that this equation represents only a few factors that influence electrical conductivity, to be specific the filler composition and the initial percolation threshold. In polymer-micro carbon composites, the filler particle size proportion can be predicted, but for nano-sized filler particles, Zare et al (2022) introduced the influence of interphase and tunneling (conductive channels) area.…”

“…Zare et al (2022) suggest that this equation represents only a few factors that influence electrical conductivity, to be specific the filler composition and the initial percolation threshold. In polymer-micro carbon composites, the filler particle size proportion can be predicted, but for nano-sized filler particles, Zare et al (2022) introduced the influence of interphase and tunneling (conductive channels) area. Both areas have the potential to change the electrical conductivity patterns of conductive composite samples.…”

“…CB materials are particularly affected by the porosity of the CB material, as noted by Ren et al (2014). Density affects electrical conductivity in composites via improved filler dispersion in the interphase area and tunneling (Zare et al, 2022), contrasting Marinho et al (2012) findings that density is influenced by compaction pressure in bulk carbon materials. The alignment of density improvement is more acceptable due to variations in filler structure, such as CB materials, compared to variations in compaction pressure or process pressure.…”