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Characterization of a photoluminescence-based fiber optic sensor system

dc.contributor.authorYi, Zhangjing, author
dc.contributor.authorLear, Kevin L., advisor
dc.contributor.authorPezeshki, Ali, committee member
dc.contributor.authorMueller, Jennifer L., committee member
dc.description.abstractMeasuring multiple analyte concentrations is essential for a wide range of environmental applications, which are important for the pursuit of public safety and health. Target analytes are often toxic chemical compounds found in groundwater or soil. However, in-situ measurement of such analytes still faces various challenges. Some of these challenges are rapid response for near-real time monitoring, simultaneous measurements of multiple analytes in a complex target environment, and high sensitivity for low analyte concentration without sample pretreatment. This thesis presents a low-cost, robust, multichannel fiber optic photoluminescence (PL)-based sensor system using a time-division multiplexing architecture for multiplex biosensor arrays for in-situ measurements in environmental applications. The system was designed based upon an indirect sensing scheme with a pH or oxygen sensitive dye molecules working as the transducer that is easily adaptable with various enzymes for detecting different analytes. A characterization of the multi-channel fiber optic PL-based sensor system was carried out in this thesis. Experiments were designed with interests in investigating this system's performance with only the transducer thus providing reference figures of merit, such as sensitivity and limit of detection, for further experiments or applications with the addition of various biosensors. A pH sensitive dye, fluoresceinamine (FLA), used as the transducer is immobilized in a poly vinyl alcohol (PVA) matrix for the characterization. The system exhibits a sensitivity of 8.66×10 5 M -1 as the Stern-Volmer constant, K SV , in H + concentration measurement range of 0.002 - 891 μM (pH of 3.05 - 8.69). A mathematical model is introduced to describe the Stern-Volmer equation's non-idealities, which are fluorophore fractional accessibility and the back reflection. Channel-to-channel uniformity is characterized with the modified Stern-Volmer model. Combining the FLA with appropriate enzymatic biosensors, the system is capable of 1,2-dichloroethane (DCA) and ethylene dibromide (EDB) detection. The calculated limit of detection (LOD) of the system can be as low as 0.08 μg/L for DCA and 0.14 μg/L for EDB. The performances of fused fiber coupler and bifurcated fiber assembly were investigated for the application in the fiber optic PL-based sensor systems in this thesis. Complex tradeoffs among back reflection noise, coupling efficiency and split ratio were analyzed with theoretical and experimental data. A series of experiments and simulations were carried out to compare the two types of fiber assemblies in the PL-based sensor systems in terms of excess loss, split ratio, back reflection, and coupling efficiency. A noise source analysis of three existing PL-intensity-based fiber optic enzymatic biosensor systems is provided to reveal the power distribution of different noise components. The three systems are a single channel system with a spectrometer as the detection device, a lab-developed multi-channel system, and a commercial prototype multi-channel system both using a photomultiplier tube (PMT) as the detection device. The thesis discusses the design differences of all three systems and some of the circuit design alteration attempts for performance improvements.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.publisherColorado State University. Libraries
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dc.subjectfiber optic
dc.titleCharacterization of a photoluminescence-based fiber optic sensor system
dcterms.rights.dplaThis Item is protected by copyright and/or related rights ( You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). and Computer Engineering State University of Science (M.S.)


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