Design and Enhancement of Fiber Optic Evanescent Wave LSPR-Based Biosensor Fabricated via Self-Assembled Silver Nanoparticles for Salivary Cortisol Detection

Loading...
Thumbnail Image

Date

2024-09-05

Advisor

Nieva, Patricia

Journal Title

Journal ISSN

Volume Title

Publisher

University of Waterloo

Abstract

There are currently no point-of-care means accessible for non-invasive, real-time monitoring of cortisol levels. All available home test kits for cortisol testing require the patients to send out their samples to laboratories after collection and wait days or weeks in some instances to receive their results. Cortisol is an important stress biomarker that is at the core of many mental and physical disorders, and early detection of abnormal cortisol levels is crucial for their prevention. This work aims to fabricate a highly accessible, inexpensive, sensitive, and non-invasive point-of-care salivary cortisol sensor, utilizing a fiber optic evanescent wave sensor (FOEW) enhanced by the effect of localized surface plasmon resonance (LSPR). The development of this sensor presents an advanced analysis on the parameters affecting the performance of FOEW LSPR sensors fabricated via self-assembly of silver spherical nanoparticles. The analysis is based on a combination of numerical and analytical models validated with experiments. A numerical model is first used to solve Mie’s theory to study the absorption of light interacting with nanoparticles due to LSPR using ANSYS LUMERICAL. Nanoparticles ranging from 10 to 100 nm diameter were considered due to their LSPR properties at this range. Simulations show that silver spherical nanoparticles with 30 nm diameter exhibit the highest absorption efficiency, and that the magnitude of absorption correlates positively with the number of nanoparticles. An analytical model is then used to describe the adsorption kinetics and formation of a nanoparticle monolayer on the longitudinal surface of the fiber’s core based on diffusion transport process. The analytical adsorption model suggested that smaller nanoparticles result in higher final surface density. The performance of the FOEW LSPR sensor signal was modeled utilizing smaller nanoparticle sizes (10 nm, 20 nm, and 30 nm) using COMSOL MULTIPHYSICS. Results show that 30 nm-based FOEW LSPR have the highest absorption signal and refractive index sensitivity. The electromagnetic field decay length was modeled in ANSYS LUMERICAL as well, and the results showed that 30 nm nanoparticles have electromagnetic field decay length that engulfs the conjugated ligand and analyte, which is optimum for cortisol biosensing. The sensor response was also modeled by integrating the ligand-analyte interaction model with the FOEW LSPR sensor model. The modeling results agree with experiments performed on FOEW LSPR sensors fabricated using 30 nm diameter nanoparticles, which show enhanced LSPR signal and refractive index sensitivity compared to results obtained using 20 nm, and 10 nm diameter nanoparticles. Characterizations performed on the prepared fiber sensors using Atomic Force Microscopy (AFM) and Scanning Electron Microscopy (SEM) show significantly higher nanoparticle coverage for sensors fabricated using smaller nanoparticles, which validated the modeling results. A working cortisol biosensor was fabricated using the 30 nm based FOEW LSPR sensor by functionalizing the nanoparticles surface with Cysteamine Hydrochloride, allowing for the bioconjugation of anti-cortisol IgG antibodies. This sensor was reproducible with a sensitivity of 0.0128 nm/nM, a limit of detection of 0.1125 pM and a limit of quantification of 0.3712 pM, covering the range cortisol found in saliva. The findings reported in this Thesis therefore present a promising technology for the fabrication of highly sensitive and cost-effective point-of-care cortisol monitoring devices. Which can be widely accessible and can help with the early detection of abnormal cortisol levels, allowing for the prevention of many mental and physical disorders.

Description

Keywords

LC Keywords

Citation