Date of Award
Doctor of Philosophy
Nobel metal nanoparticles (NPs) exhibit an optical-plasmonic response when perturbed by incident radiation. Gold (Au) is particularly useful as it has a strong surface enhanced Raman scattering (SERS) response and is chemically stable and suitable for biological applications. Often, magnetic properties are also desired, and iron-oxide NPs are utilized for the sake of magnetic separation or delivery and these types of materials are often used with inert plasmonic shells to obtain the desired optical and magnetic features. This provides much more flexibility when designing a detection scheme. Functionalizing these NPs with Raman reporter molecules allows for use in imaging and detection in biological systems, when ultra-sensitive measurements are required, thus, understanding the plasmonic properties of solid and core-shell NPs is of great interest for the sake of designing better detection schemes. Computational investigation has aided this field tremendously as Mie theory, as well as the discrete dipole approximation (DDA), can simulate NP systems to provide expected SERS response for a given design prior to chemical synthesis. This work seeks to provide perspective on how core-shell NPs respond to incident radiation, particularly the E-field, and will provide optical data to show expected SERS response. Assembling solid Au NPs into a large vesicle assembly will consider the possibility of 3D NP structures producing an enhanced SERS effect to allow for increases SERS detection. Smaller assemblies will investigate the source of this SERS enhancement and will seek to determine how the alignment of Au NPs affects the optical-plasmonic response. Together, this predominantly computational investigation will shed light on important characteristics and features of NP systems that can be exploited for experimental application.
Dissertation or thesis originally submitted to ProQuest
Barr, James Wade, "Computational Investigation of Plasmonic Properties of Metal Nanoparticle Assemblies" (2020). Electronic Theses and Dissertations. 2446.