Date of Award
Spring 2020
Project Type
Thesis
Program or Major
Electrical and Computer Engineering
Degree Name
Master of Science
First Advisor
Edward Song
Second Advisor
John Lacourse
Third Advisor
W. R. Seitz
Abstract
A target receptor is an essential component in developing selective biological and chemical sensors. Among various approaches in receptor implementation, templated polymers are synthetic biochemical receptors that mimic natural molecular recognition. They have the favorable arrangement of polymer structures to be steady in harsh conditions and can also be custom tailored to exhibit target affinity as well as interfacing with transducers. Effective templated polymer synthesis depends on the co-polymerization of functional monomers which will interact with the sensing molecule. This thesis proposes a rational design approach towards the integration of templated polymers with electrochemical sensing. The synthesized single-chain label-free flexible polymers with binding sites show selective affinity toward both electroactive and non-electroactive target molecule.
This thesis proposes a novel approach in electrochemical templated polymer-based sensing platform. The developed platform shows binding-induced changes in the electron transfer kinetics at the templated polymer-attached electrode when the target molecule binds specifically to the receptor. In this work, a stimuli-responsive single-chain copolymer was developed for explicit analyte detection of 4-nitrophenol, a neurotoxin and environmental pollutant, and L-glutamate, a well-known neurochemical. The polymer backbone experiences a conformation change upon template binding and the electrochemical measurement can be used to characterize these changes. This new detection approach can be used for label-free sensing of various non-electroactive chemical species and can potentially lead to the development of a non-enzymatic electrochemical sensors.
Recommended Citation
AHMAD, HABIB MUHAMMAD NAZIR, "TEMPLATED SINGLE-CHAIN POLYMER-BASED ELECTROCHEMICAL SENSING" (2020). Master's Theses and Capstones. 1360.
https://scholars.unh.edu/thesis/1360