Analytical applications of nanostructured plasmonic crystals

Surface plasmon resonances (SPR) have been exploited through various means for the realization of label-free, surface-sensitive chemical analysis and imaging, all of which rely on the interactions between the local environment and the evanescent electric fields generated by the surface plasmons at the metal-dielectric interface. Plasmonic crystals are a versatile platform for the tunable coupling of light into surface plasmon modes, and soft nanoimprint lithography represents a class of fabrication techniques capable of inexpensive, high fidelity replication of nanoscale features over large areas; these methods are well-matched for surface-enhanced sensing applications whose performance depends strongly on these fabrication characteristics. The work presented in this dissertation focused on the development of new surface-enhanced Raman spectroscopy and surface plasmon resonance imaging modalities based on this nanostructured plasmonic crystal platform. Nanostructured plasmonic crystals were patterned onto the tips of silica optical fibers using a soft embossing method for use as single-fiber SERS optrodes, and enhanced Raman scattering was observed for benzenethiol monolayers adsorbed onto the structured fiber tip as well as for Rhodamine 6G dissolved in aqueous solution. The inherent versatility of this plasmonic platform for SERS-based sensing was demonstrated through the effective Raman enhancements obtained in markedly different refractive index environments. Nanoimprinted plasmonic crystals were also adapted for reflection imaging studies of thin films deposited onto the metal surface. Normalized contrast metrics were developed based on reflection images of polyelectrolyte layer-by-layer assemblies acquired using bandpass filters to restrict the accessible wavelength ranges and quantitatively calibrated to the surface film thickness. As a model system, Aplysia pedal neurons were cultured on the plasmonic crystal surface, and the thicknesses of neuronal processes were quantitated using the calibrations derived for this reflection imaging protocol using common laboratory equipment: a reflection microscope, commercially available bandpass filters, and a digital camera. The imaging-based measurements of neuronal process thickness were verified independently using atomic force microscopy with excellent agreement between the two methods. The applications explored in this dissertation demonstrate the broader utility of nanoimprinted plasmonic crystals for chemical sensing and imaging