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Dilute Nitride Based Vertical Cavity Enhanced Photodetector

Bin Nordin, Mohammad Syahmi (2018) Dilute Nitride Based Vertical Cavity Enhanced Photodetector. PhD thesis, University of Essex.

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Abstract

The research reported in this thesis is aimed at developing and demonstrating the performance of a p-i-n / vertical cavity enhanced (VCE) photodetector structure with different material compositions of dilute nitride. The tunable selectivity is taken into account during the development in order for the VCE photodetector to be able to perform as a tunable receiver. In the first part, the performance of p-i-n photodetectors with 10 and 20 quantum wells are presented. The 20 quantum well photodetector exhibits the highest ever reported quantum efficiency of 80% at -5V bias for applications at 1.0µm wavelength. However, variation in the absorption’s thickness equates to a trade-off between speed, bandwidth, noise-equivalent-power, and detectivity. A GaInNAs/GaAs VCE photodetector with an internal gain of 1.55 for room temperature operation at 1.3µm wavelength is next demonstrated. This is the first internal gain ever reported using a GaInNAs VCE photodetector with a 1.7nm FWHM and an overall quantum efficiency of 67%. The proposed VCE photodetector of GaInNAs/GaNAs showed impressive multiplication at a low reverse bias of 0.5V. The internal gain is detected to be 2.45 at -2V bias with a responsivity of 1.63A/W for room temperature operation. The responsivity and gain of the sample can be enhanced by increasing small range of temperature but then suffered from temperature-induced broadening of the full width half maximum (FWHM). Finally, an avalanche VCE photodetector is proposed, where the preliminary outcome shows the current oscillation behaviour under illumination at room temperature operation. The sample produces very low responsivity of 2.15mA/W due to growth problems with the charge layer which affect the electric field in the multiplication region.

Item Type: Thesis (PhD)
Subjects: Q Science > QC Physics
T Technology > T Technology (General)
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Mohammad Bin Nordin
Date Deposited: 20 Mar 2018 09:45
Last Modified: 11 Jul 2018 09:43
URI: http://repository.essex.ac.uk/id/eprint/21722

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