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dc.contributor.advisorMagnusson, Robert
dc.creatorBuchanan-vega, Joseph Anthony
dc.date.accessioned2024-01-31T18:38:14Z
dc.date.available2024-01-31T18:38:14Z
dc.date.created2023-12
dc.date.issued2023-12-15
dc.date.submittedDecember 2023
dc.identifier.urihttp://hdl.handle.net/10106/31958
dc.description.abstractGuided-mode resonance (GMR) sensors are developed and implemented for multiparametric label-free sensing, transmission sensing, enhanced reflection sensing, and low analyte concentration sensing; these are the topics presented in this work. The complete biosensor – capable of label-free multiparametric data collection – is designed, fabricated, and implemented. Multiparametric data collection has previously been relegated to one variable on the sensor surface and one bulk media variable. We use a lookup table and the novel application of an inversion algorithm to simultaneously determine two variables on the sensor surface and one bulk media variable. Multiparametric data sets are required to monitor multiple variables in one spectral measurement. Interpreting and deconvolving this spectral data can be done in a myriad of ways with varying degrees of success. We explore different coding algorithm concepts to interpret multimode data. GMR sensors primarily use the reflection response of resonant structures. We introduce a replicable method to design GMR-assisted Rayleigh sensors dependent on guided-modes shaping the spectral profile which allows the Rayleigh anomaly to produce a transmittance peak. The Rayleigh sensor designs have transmission peaks that shift by one device period per RIU. Multiple high-performance transmissive devices are presented. Development of high sensitivity reflection GMR sensors is a prevalent concept in the GMR biosensor field. It is found that the addition of a thin silicon layer produces mode confinement in/near the bulk media of a sensor and increases the sensitivity of reflection based GMR sensors. Lastly, we present a sandwich detection method to improve the limit of detection of neuropeptide Y (NPY) molecules that adhere to a GMR sensors functionalized surface. The sandwich detection method yields a 20-fold increase in the limit of detection of NPY molecules: these molecules are significant in the physical and emotional trauma response in the human brain. Through this work we explore guided-mode resonance (GMR) devices implemented for multiparametric sensors, transmission applications, high sensitivity sensors, and low concentration biomolecule detection. Each of these designs and applications are significant when considering the wide range of implementation of GMR sensors.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.subjectGuided-mode resonance
dc.subjectSensors
dc.subjectBiomolecule
dc.subjectSensitivity
dc.subjectRefractive index
dc.subjectBiolayer
dc.subjectGMR
dc.subjectRayleigh
dc.subjectInversion
dc.subjectBackfit
dc.subjectBulk
dc.subjectFilm
dc.subjectResonance
dc.subjectYeast
dc.subjectNeuropeptide Y
dc.subjectNPY
dc.subjectCon A
dc.subjectIndex of refraction
dc.subjectTransmission
dc.subjectReflection
dc.subjectConcanavalin A
dc.subjectThickness
dc.subjectBiosensors
dc.subjectLimit of detection
dc.titleApplications of the Guided-Mode Resonance Sensor in Multiparametric, Transmissive, and Picomolar Regimes
dc.typeThesis
dc.date.updated2024-01-31T18:38:14Z
thesis.degree.departmentElectrical Engineering
thesis.degree.grantorThe University of Texas at Arlington
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy in Electrical Engineering
dc.type.materialtext
dc.creator.orcid0000-0003-3971-3983


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