Issue 79, 2017, Issue in Progress

A two-step model for the tunneling conductivity of polymer carbon nanotube nanocomposites assuming the conduction of interphase regions

Abstract

This work develops a two-step model for the conductivity of polymer carbon nanotube (CNT) nanocomposites (PCNT) assuming the properties of tunneling and interphase regions. In step 1, CNT and the surrounding interphase are considered as pseudoparticles and a simple model predicts their conductivity. After that, a suitable model calculates the conductivity of nanocomposites containing pseudoparticles, tunneling regions and polymer matrixes in step 2. The waviness of CNT as well as the fractions of CNT and interphase regions in the conductive networks is also considered. The experimental results of several samples and the reasonable roles of all parameters in the conductivity of nanocomposites support the predictions of the two-step model. Thin and long CNTs can cause a high conductivity, but only thick CNTs result in the least conductivity. Also, the thickness and conduction of interphase zones directly control the conductivity of nanocomposites. So, it is important to provide a strong interphase in PCNT to achieve a high conductivity. Moreover, a poor percolation threshold and a short tunneling distance enhance the conductivity of nanocomposites, whereas only a large tunneling distance dominantly reduces the conductivity.

Graphical abstract: A two-step model for the tunneling conductivity of polymer carbon nanotube nanocomposites assuming the conduction of interphase regions

Article information

Article type
Paper
Submitted
25 Jul 2017
Accepted
14 Oct 2017
First published
27 Oct 2017
This article is Open Access
Creative Commons BY license

RSC Adv., 2017,7, 50225-50233

A two-step model for the tunneling conductivity of polymer carbon nanotube nanocomposites assuming the conduction of interphase regions

R. Razavi, Y. Zare and K. Y. Rhee, RSC Adv., 2017, 7, 50225 DOI: 10.1039/C7RA08214B

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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