Platinum-Group Metal (PGM) nanostructures as advantageous alternatives to natural peroxidases have drawn great attention because of their superior catalytic activities, which can effectively enhance performance of enzyme-based in vitro diagnostics. The catalytic activity of metal nanoparticle peroxidase mimics can depend on their size, shape, elemental composition, and surface ligand of PGM nanostructures. Therefore, to develop optimal peroxidase mimics for a few bioanalytical and diagnostic applications, such as enzyme-linked immunosorbent assay (ELISA), it is important to investigate how structural aspects of PGM nanoparticles correlate with the ability of the nanoparticles to serve as functional mimics of protein peroxidase enzymes.
In summary, this dissertation has studied: 1) iridium (Ir), platinum (Pt) and Ir/Pt bimetallic nanowire structures as peroxidase mimics, and the effect of different wires' length on their peroxidase-like activities and certain application of sandwich ELISA for the detection of carcinoembryonic antigen (CEA, a cancer biomarker); 2) ultra-small Ir nanoparticles, with an average size of 1.1 nm, supported by WO2.72 nanowire with high catalytic activity. Those Ir nanoparticles were applied to sandwich ELISA and competitive ELISA for sensitive detection of CEA and aflatoxin B1 (AFB1, a carcinogenic toxin), respectively; 3) the size effect of peroxidase mimics on their catalytic activities and performance in biosensing application, where Pd-Ir core-shell nanoparticles were used as a type of model peroxidase mimics. These studies may significantly stimulate further investigations of PGM nanostructures as peroxidase mimics and other potential applications in in vitro diagnostics.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2023-1029 |
| Date | 01 January 2023 |
| Creators | Gao, Weiwei |
| 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 |
Page generated in 0.0021 seconds