This thesis describes the fabrication and characterization of GaN homojunction visible-blind ultraviolet (UV) p-i-n avalanche photodiodes (APDs) grown by metalorganic chemical vapor deposition (MOCVD) on free-standing bulk GaN substrates. The objective of this research is to develop GaN UV p-i-n APDs with high linear-mode avalanche gains and the Geiger-mode operation for single photon detection. Low noise, high responsivity, and high detectivity are also required for fabricated APDs used as photodiodes in the photovoltaic mode (zero bias) and the photoconductive mode (low reverse bias).
High material defect density and immature fabrication technology have hampered the development of III-nitride APDs in the past. In this thesis, sidewall leakage reduction methods have been developed to achieve significant improvement in dark current density, noise performance, and photo detection performance. A record linear-mode avalanche gain > 10⁵ for GaN APDs was demonstrated at λ = 360 nm. The first Geiger-mode deep UV (DUV) APD using front-illuminated homojunction p-i-n diode structure on a free-standing bulk GaN substrate was also measured with single photo detection efficiency (SPDE) of 1.0 % and dark count probability (DCP) of 0.03 at 265 nm.
The performance of fabricated homojunction GaN p-i-n photodiodes was also evaluated in the photoconductive mode as well as the photovoltaic mode. For an 80-µm-diameter device biased at - 20 V (in the photoconductive mode) the dark current density is lower than 40 pA/cm² which is the lowest value achieved for any III-nitride photodiode so far. Its responsivity is 0.140 A/W at 360 nm with an ultraviolet-visible rejection ratio of 8×10³. The room-temperature noise equivalent power is 4.27×10 ⁻¹⁷ W-Hz-[superscript 0.5] and the detectivity D* is 1.66×10¹⁴ cm-Hz[superscript 0.5]-W ⁻¹ at - 20 V. The minimum detectable optical power is as low as 100 fW. They are among the best values reported for reverse-biased GaN p-i-n photodiodes to date.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/29604 |
| Date | 20 May 2009 |
| Creators | Zhang, Yun |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Thesis |
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