Characterization of Carbon Nanostructures Based on Transmission Line Model.
Abstract
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.
Authors
Zhang, JiefuCollections
- Theses [3930]