Introduction

Carbon nanotubes (CNT) are one of the most exciting research areas in modern science. They are the stiffest and strongest fibers known with the remarkable mechanical, electrical and thermal properties. CNTs are used in many cases as an alternative to carbon black to increase the conductivity of low cost non-conducting polymers. Improving the electrical conductivity of polymers is important for a variety of applications. For example, in aerospace components in order to achieve electrostatic discharge and electromagnetic-radio frequency interference protection, improved conductivity is required. Applications such as computer housing or some automotive parts like fuel lines also require some degree of static electrical dissipation which can help to dissipate any dangerous charge which may build up.

Goals

Understanding the behaviour of these materials in flow fields is required. Because during processing, complex flow fields occur inside the material and this flow fields affect the product properties such as electrical and thermal conductivity. It was shown that at higher shear rates, nanotubes are favoured to align in the flow direction and at moderate shear rates they are able to create agglomerates which then induce electrical conductivity increase.

Aim of this work is to reproduce observed nanotube suspension behaviour, such as the formation and dispersion of agglomerates in shear flow. Then predict the evolution of the electrical conductivity. These simulations will give us an insight about the structural development during the production process. This way, we will be able to predict the properties of the final product. Particle level simulations were used to create realistic suspension behaviour. We will explore how the structure and electrical conductivity of the composites are influenced by variables such as nanotube shape, aspect ratio, flow field history and nanotube interactions. Generated microstructures were used to compute the effective electrical conductivities. A resistor network algorithm which considers tunnelling length and contact resistance was used for this purpose.

Recent simulations showed the effect of shear flow on the microstructure and conductivity. In these simulations, nanotubes agglomerate at lower shear rates and deagglomerate at higher shear rates. Alignment in the flow direction was also observed for the high shear rates. It was also seen that increasing shear rate results in a decrease in conductivity and above a critical shear rate, the system cannot percolate anymore to create a conductive network.

Wissenschftliche Kontakte und Kooperationen

• Prof. Dr. Daniel J. Klingenberg, Department of Chemical and Biological Engineering, Univ. of Wisconsin, Madison, 1415, Engineering Drive, WI 53706, USA. 
• Dr. Emilio J. Tozzi, Department of Chemical Engineering and Materials Science, University of California, Davis, CA 95616, USA.