A power model to predict the electrical conductivity of CNT reinforced nanocomposites by considering interphase, networks and tunneling condition

Abstract

This study develops a power-law model for characterizing the conductivity of polymer carbon nanotube (CNT) nanocomposite by defining the “b” exponent as a function of main parameters such as filler dimensions, filler waviness, interphase thickness, network fraction, tunneling distance, and polymer-filler interfacial energy. Both “b” and conductivity are calculated, and the effects of these parameters on the conductivity are determined. The model accurately predicts the experimentally measured conductivity of the samples. The highest filler conductivity and the lowest “b” exponent cause the maximum conductivity. Some parameters, such as tunneling distance, filler concentration, filler radius, interphase thickness, and waviness, directly affects the “b” exponent, while other parameters, such as the fraction of percolated CNT, interfacial energy, and filler length, demonstrate an inverse relationship with “b.” In addition, short tunneling distance, high filler fraction, thin and large nanotubes, thick interphase, poor waviness, high network fraction, and high interfacial energy produce a high conductivity.