Master of Science in Electrical Engineering (MSEE)
Electrical and Computer Engineering
Over the past few decades, there have been tremendous innovations in electronics and photonics. The development of these ultra-fast growing technologies mostly relies on fundamental understanding of novel materials with unique properties as well as new designs of device architectures with more diverse and better functionalities. In this regard, the promising approach for next-generation nanoscale electronics and photonics is to exploit the extraordinary characteristics of novel nanomaterials. There has been an explosion of interest in graphene for photonic applications as it provides a degree of freedom to manipulate electromagnetic waves. In this thesis, to tailor the broadband blackbody radiation, new aperiodic multilayer structures composed of multiple layers of graphene and hexagonal boron nitride (hBN) are proposed as selective, tunable and switchable thermal emitters. To obtain the layer thicknesses of these aperiodic multilayer structures for maximum emittance/absorptance, a hybrid optimization algorithm coupled to a transfer matrix code is employed. The device simulation indicates that perfect absorption efficiency of unity can be achieved at very narrow frequency bands in the infrared under normal incidence. It has been shown that the chemical potential in graphene enables a promising way to design electrically controllable absorption/emission, resulting in selective, tunable and switchable thermal emitters at infrared frequencies. By simulating different aperiodic thermal emitters with different numbers of graphene layers, the effect of the number of graphene layers on selectivity, tunability, and switchability of thermal emittance is investigated. This study may contribute towards the realization of wavelength selective detectors with switchable intensity for sensing applications.
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Sharifi, Safura, "Aperiodic Multilayer Graphene Based Tunable and Switchable Thermal Emitter at Mid-infrared Frequencies" (2017). LSU Master's Theses. 4416.
Available for download on Saturday, February 23, 2019