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Characterization of carbon nanostructures based on transmission line model

In the past two decades carbon nanotubes and graphene have attracted a lot of research attention due to their exceptional electronic properties. The research focus on improving the synthesising techniques will eventually lead to their applications in terahertz wave, millimetre wave and microwave frequencies. In this thesis, a modelling technique based on the transmission line theory is proposed to calculate the 2-port S-parameters of vertically aligned CNT arrays with finite sizes and arbitrary cross sections. The process takes into account all the coupling in the array and gives the analytical solution of S-parameters. The simulation results from the proposed technique are compared with results obtained by effective single conductor model and shows a good matching for small arrays and an increasing difference with the increase of array sizes. From the S-parameters, the fundamental properties of CNT arrays such as input impedance and absorption are obtained and compared with measurement results in microwave frequencies. The dependence of these properties on ambient temperature and host medium are also presented to explore the tunability of CNT arrays. From the Fabry-Perot the wave propagating velocity is also calculated for arrays with different sizes and fitted with a power function. The S-parameters allows the extraction of the complex permittivity, permeability and conductivity of the CNT array. The extracted permittivity and absorption are compared with measurement results. The graphene nanoribbons are simulated in the same manner. The graphene sheet on top of a microstrip gap is simulated using transmission line model at microwave frequencies to show the impact of parasitics and contact resistances. Finally, a graphene based microwave absorber is proposed and modelled under both electric and magnetic bias. The absorber shows good broadband absorption rate and a potential for turning transparent and opaque to microwaves under both electric and magnetic bias.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:667382
Date January 2014
CreatorsZhang, Jiefu
PublisherQueen Mary, University of London
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://qmro.qmul.ac.uk/xmlui/handle/123456789/9102

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