Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/47611
Title: Development of fiber-based supercontinuum light sources for the biosensor and bio-imaging applications
Authors: Tang, Dingyuan.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Microelectronics
Issue Date: 2008
Abstract: The current research project is concerned with the development of the fiber-based supercontinuum light sources. Our approach for the generation of such a light is through the nonlinear optical pulse propagation in the special optical fibers such as the photonic crystal fibers. In the project we have first experimentally investigated the noise-like pulse (NLP) generation in the dispersion-managed fiber laser operating in the anomalous dispersion regime. NLPs with spectral bandwidth of 32.1nm were achieved. Parallel to the experimental studies, we have also theoretically analyzed the physical mechanism of the NLP generation in fiber lasers and firstly pointed out that the NLP emission was caused by the combined effect of soliton collapse and positive cavity feedback in the fiber lasers. Based on our theoretical study on the NLP generation in fiber lasers, we predicted that NLP with superbroad bandwidth could be generated in the conventional fiber lasers without dispersion managed cavity. We then experimentally built up a conventional passively mode-locked fiber laser without dispersion management, and experimentally achieved the high energy NLPs with a superbroad bandwidth of 93nm. In addition, a long cavity dispersion-managed fiber laser was also experimentally studied and NLPs with over 100 nJ pulse energy were also demonstrated. For the long cavity fiber lasers, the stimulated Raman effect becomes important. We therefore theoretically analyzed the role of Raman self-frequency shift effect in the NLP generation over gain effect, and experimentally investigated the difference of NLP generation between the long cavity fiber laser and the short cavity fiber laser, and further obtained NLPs with up to 120 nm bandwidth.
URI: http://hdl.handle.net/10356/47611
Schools: School of Electrical and Electronic Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Research Reports (Staff & Graduate Students)

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