In this study, a three-dimensional continuum percolation model was developed based on a Monte Carlo simulation approach to investigate the percolation behavior of an electrically insulating matrix reinforced with conductive nano-platelet fillers. The conductivity behavior of composites rendered conductive by randomly dispersed conductive platelets was modeled by developing a three-dimensional finite element resistor network. Parameters related to the percolation threshold and a power-low describing the conductivity behavior were determined. The piezoresistivity behavior of conductive composites was studied employing a reoriented resistor network emulating a conductive composite subjected to mechanical strain. The effects of the governing parameters, i.e., electron tunneling distance, conductive particle aspect ratio and size effects on conductivity behavior were examined.

No abstract

In this study, a numerical modeling approach was used to investigate the current-voltage behavior of conductive nanoplatelet-based nanocomposites. A three-dimensional continuum Monte Carlo model was employed to randomly disperse the nanoplatelets in a cubic representative volume element. A nonlinear finite element-based model was developed to evaluate the electrical behavior of the nanocomposite for different levels of the applied electric field. Also, the effect of filler loading on nonlinear conductivity behavior of nanocomposites was investigated. The validity of the developed model was verified through qualitative comparison of the simulation results with results obtained from experimental works.

The effect of the temperature on the electrical resistivity of polymer nanocomposites with carbon nanotube (CNT) and graphene nanoplatelets (GNP) fillers was investigated. A three-dimensional (3D) continuum Monte Carlo (MC) model was developed to first form percolation networks. A 3D resistor network was subsequently created to evaluate the nanocomposite electrical properties. The effect of temperature on the electrical resistivity of nanocomposites was thus investigated. Other aspects such as polymer tunneling and filler resistivities were considered as well. The presented comprehensive modeling approach is aimed at providing a better understanding of the electrical resistivity behavior of polymer nanocomposites in conjunction with experimental works.

In this study the effect of the temperature on the electrical conductivity of nanocomposites with carbon nanotube (CNT) fillers was investigated. A three-dimensional continuum Monte Carlo model was developed and employed first to form a CNT percolation network. CNT fillers were randomly generated and dispersed in a cubic representative volume element. Periodic boundary conditions were applied in this model to minimize size effects while decreasing computational cost. CNT fibers that connected electrically to each other through electron hopping were recognized and grouped as clusters. In addition to tunneling resistance, the effect of intrinsic CNT resistivity was considered. A three-dimensional resistor network was subsequently developed to evaluate nanocomposite electrical properties. Modeling employing the finite element method was conducted to evaluate the electrical conductivity of the percolation network. Considering the determining role of tunneling resistance on electrical conductivity of CNT based nanocomposites, as well as results obtained from experimental studies, temperature was expected to play an important role in nanocomposite electrical properties. The effect of temperature on electrical conductivity of CNT nanocomposites was thus investigated through employing the developed Monte Carlo and finite element models. Other aspects, including the electrical behavior of the polymer, tunneling resistivity and the intrinsic resistivity of CNT were considered in this study as well. The comprehensiveness of the developed modeling approach enables an evaluation of results in conjunction with experimental data in future works.