Thorpe, Stephen (2019) Electrochemical Guided Mode Resonance Biosensors. PhD thesis, University of York.
Abstract
Biosensing technology currently uses a single transduction mode, restricting the systems the technology can be applied to and the information that can be gained. Multimodal biosensing combines multiple transduction technologies to probe different properties simultaneously, increasing the range of measurable interactions, the amount of information that can be extracted, and the detection accuracy.
Guided mode resonance sensors are one dimensional periodic grating structures that measure the local refractive index at the grating surface, and have been used extensively for label-free biosensing assays. Electrochemical biosensors measure the activity of chemical reactions through changes in electrical current. Combining refractive index and electrochemical sensing allows for the parallel interrogation of the presence and activity of biomolecules.
A multimodal electrochemical guided mode resonance (EGMR) sensor based on a 1D GMR grating structure with a layer of indium tin oxide is presented. Simulation of the GMR structure was used to inform the EGMR design for the best compromise between electrochemical and optical sensing performance. The fabricated device is characterised optically and electrically. Combined electrochemical and optical sensing measurements were demonstrated in parallel to characterise a redox active molecule.
The electrochemical chirped GMR (ECGMR) was applied to developing a low cost multiplexed label-free biosensor. The chirped GMR sensor converts the spectral response of the GMR to spatial information allowing binding to be measured using a monochromatic source and a camera. A biocompatible antibody electrografting protocol was demonstrated for creating a multiplexed antibody array of sepsis biomarkers using the ECGMR. Parallel label-free detection of CRP, IgG and Escherichia coli was demonstrated.
This work is the first example of a multimodal GMR, and progresses the use of biosensing technology for point-of-care applications.
Metadata
Supervisors: | Johnson, Steven D and Krauss, Thomas F and Thomas, Gavin H |
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Awarding institution: | University of York |
Academic Units: | The University of York > Biology (York) |
Identification Number/EthosID: | uk.bl.ethos.811391 |
Depositing User: | Mr Stephen Thorpe |
Date Deposited: | 13 Aug 2020 16:34 |
Last Modified: | 21 Apr 2022 09:53 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:26224 |
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