Graphene-Based Nanocomposites with Tailored Electrical, Electromagnetic, and Electromechanical Properties

Authored by: M. S. Sarto , G. De Bellis , A. Tamburrano , A. G. D’Aloia , F. Marra

Graphene Science Handbook

Print publication date:  April  2016
Online publication date:  April  2016

Print ISBN: 9781466591318
eBook ISBN: 9781466591325
Adobe ISBN:

10.1201/b19642-35

 Download Chapter

 

Abstract

Graphene nanoplatelets (GNPs) are tiny stacks of graphene layers with thicknesses ranging from 1 to several nanometers and lateral size from hundreds of nanometers to several micrometers. Depending on the fabrication route, GNPs can be produced starting from different precursors, such as graphene oxide (GO) or graphite intercalation compounds (GICs): both routes are compatible with mass production. Polymeric nanocomposites are drawing ever-growing attention thanks to their light weight and the possibility to dramatically increase the matrix properties using very low filler loadings. The main challenge in the practical application of GNP and GNP-based nanocomposites consists of tailoring their functional properties through the control of the synthesis process, using a suitable modeling tool that allows correlating the micro/nanostructure of the material to its functional properties at macroscale. This chapter focuses on the development of GNPs and GNP-based polymer composites with tailored electrical, electromagnetic, and electromechanical properties for applications such as shielding or radar-absorbing materials (RAMs), or piezoresistive strain sensors. We demonstrate the proper control of the morphological characteristics of GNPs and the final functional properties of the nanocomposite (namely, the effective complex permittivity, shielding effectiveness or reflection coefficient, the piezoresistive response) through the proper setting of the synthesis route and of the type of polymeric matrix used. Different parameters are investigated, such as the precursor expansion time and temperature, the exfoliated graphite sonication cycle, the type of solvent used, and the suspension temperature during sonication. A novel simulation model is developed to predict the effective electromagnetic properties of GNP nanocomposites. The presented model is validated by comparison with experimental data, and represents a useful tool for the design by simulation of RAMs.

 Cite
Search for more...
Back to top

Use of cookies on this website

We are using cookies to provide statistics that help us give you the best experience of our site. You can find out more in our Privacy Policy. By continuing to use the site you are agreeing to our use of cookies.