This thesis work aims to develop electrochemical sensors for sub-ppb level detection of inorganic and organic pollutants in drinking water with environmentally benign materials and processes. While traditional laboratory-based methods such as mass spectroscopy, and chromatography have been used to analyze the concentration of contaminants in drinking water, miniaturized electrochemical sensors offer a compelling alternative to those methods, enabling rapid on-site cost-effective detection of low concentrations of pollutants. In this research, a set of three-electrode sensors was designed and fabricated on a flexible substrate using a screen-printing technique. Additionally, an in-situ electrochlorination process was implemented to create the reference electrode. These sensors were utilized to precisely detect lead ions and perfluorooctane sulfonate (PFOS) in drinking water. The first set of sensors was fabricated to measure the concentration of lead ions, a toxic inorganic pollutant, in potable water. The novelty of the proposed research lies in using non-toxic, biodegradable sodium alginate grafted with 2- acrylamido-2-methyl propane sulfonic acid (AMPS) and conductive fillers for trace-level lead ion detection in water. The principle of square wave anodic square wave stripping voltammetry (SWASV) was used to determine the trace level lead ion concentration. Employing a similar approach with a different material, a PFOS sensor was developed. Utilizing chitosan, one of the sustainable and biodegradable biopolymers found in crustacean shells, rapid parts-per-trillion (ppt) level PFOS detection by electrochemical impedance spectroscopy (EIS) was demonstrated. The proposed sensors made low-cost electrochemical detection of contaminants such as lead ions and PFOS possible with eco-friendly materials and processes.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2023-1068 |
| Date | 01 January 2023 |
| Creators | Borjian, Pouya |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Thesis and Dissertation 2023-2024 |
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