Abstract
Motivated by the need for inexpensive, simple, and portable devices for aqueous chemical analysis, we developed a nanoplasmonic colorimetric sensor capable of direct detection of wide range of chemicals. This novel sensor exploits the plasmonic resonance of metallic nanostructures with natural light to transduce changes in the chemical environment to changes in color, thus offering a simple route for real-time, in-situ, and low-cost analysis of aqueous chemical species. Due to its environmental and medical relevance, we chose aqueous ammonia to analyze and determine the efficacy and limit of detection of this sensing platform. For the metallic nanostructures we selected aluminium for its well stablished high reactivity with ammonia. However, the nanoparticle's metal can be chosen based on its reactivity with any given target analyte, therefore creating a tailorable sensor. The work here sets the foundations for a comprehensive analysis which aims to establish how various nanoparticle materials can be used to make a selective biosensor for chemical analysis in aqueous matrices such as environmental water samples, urine, blood serum, and saliva. In this thesis, we discuss the physics behind the sensors structural color, and the analytical techniques developed for ammonia quantification from aqueous solutions.
Notes
If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu
Graduation Date
2021
Semester
Summer
Advisor
Chanda, Debashis
Degree
Master of Science (M.S.)
College
College of Graduate Studies
Department
Nanoscience Technology Center
Degree Program
Nanotechnology
Format
application/pdf
Identifier
CFE0009099; DP0026432
URL
https://purls.library.ucf.edu/go/DP0026432
Language
English
Release Date
February 2023
Length of Campus-only Access
1 year
Access Status
Masters Thesis (Open Access)
STARS Citation
Caribe, Zuriel, "Nanoplasmonic Colorimetric Sensors for Detection of Ammonia From Water and Urine" (2021). Electronic Theses and Dissertations, 2020-2023. 1128.
https://stars.library.ucf.edu/etd2020/1128