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Title:Aluminum nitride microelectromechanical infrared detectors with integrated metamaterial absorbers
Author(s):Breen, Michael G
Advisor(s):Gong, Songbin
Department / Program:Electrical & Computer Eng
Discipline:Electrical & Computer Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Infrared detector
MEMS
Metamaterial
AlN
Abstract:This work reports the development of uncooled spectrally selective mid-infrared (IR) detectors based on the seamless integration of metamaterial (MM) structures with microelectromechanical (MEMS) AlN resonators. Historically, uncooled absorbers have been limited in two key metrics: selectivity, the ability to distinguish distinct wavelengths of incident light, and sensitivity, the ability to detect low level amounts of radiation. In recent years, research has been done on improving these metrics using spectrally selective MM absorbers and highly sensitive MEMS detectors. In this thesis, the full hybridization of MM absorbers and MEMS resonators is demonstrated. The complete coverage of the resonator surface with both polarized and unpolarized MM results in high mid-IR absorption >80 % at an optimized spectral wavelength of 9.6 μm with a Full Width at Half Maximum (FWHM) of 1.02 μm without compromising resonator acoustic performance. A novel detector readout has also been implemented to boost sensitivity as well as to linearly convert incident IR power to a DC voltage for optimum integration into focal plane arrays (FPAs). A sensitivity metric called the temperature coefficient of reflection coefficient (TCΓ) is defined which is analogous to the temperature coefficient of resistance (TCR) described for conventional uncooled bolometer IR detectors. TCΓ values of 6% were measured, matching the state of the art TCR values of microbolometers which are typically 3-5%. Future optimization of device structure and fabrication can further increase the TCΓ value, showing promise for surpassing current microbolometer FPAs.
Issue Date:2017-04-28
Type:Thesis
URI:http://hdl.handle.net/2142/98148
Rights Information:Copyright 2017 Michael Breen
Date Available in IDEALS:2017-09-29
Date Deposited:2017-08


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