The use of Surface Enhanced Raman Spectroscopy (SERS) for biomedical applications

Recent advances in nanotechnology and the biotechnology revolution have created an immense opportunity for the use of noble metal nanoparticles as Surface Enhanced Raman Spectroscopy (SERS) substrates for biological sensing and diagnostics. This is because SERS enhances the intensity of the Raman scattered signal from an analyte by orders of 106 or more. This dissertation deals with the different aspects involved in the application of SERS for biosensing. It discusses initial studies performed using traditional chemically reduced silver colloidal nanoparticles for the SERS detection of a myriad of proteins and nucleic acids. It examines ways to circumvent the inherent aggregation problems associated with colloidal nanoparticles that frequently lead to poor data reproducibility. The different methods examined to create robust SERS substrates include the creation of thermally evaporated silver island films on microscope glass slides, using the technique of Nanosphere Lithography (NSL) to create hexagonally close packed periodic particle arrays of silver nanoparticles on glass substrates as well as the use of optically tunable gold nanoshell films on glass substrates. The three different types of SERS surfaces are characterized using UV-Vis absorption spectroscopy, Electron Microscopy (EM), Atomic Force Microscopy (AFM) as well as SERS using the model Raman active molecule trans-1,2-bis(4-pyridyl)ethylene (BPE). Also discussed is ongoing work in the initial stages of the development of a SERS based biosensor using gold nanoshell films for the direct detection of b-amyloid, the causative agent for Alzheimer's disease. Lastly, the use of gold nanoshells as SERS substrates for the intracellular detection of various biomolecules within mouse fibroblast cells in cell culture is discussed. The dissertation puts into perspective how this study can represent the first steps in the development of a robust gold nanoshell based SERS biosensor that can improve the ability to monitor biological processes in real time, thus providing new avenues for designing systems for the early diagnosis of diseases.