Abstract
Surface-enhanced Raman spectroscopy (SERS) improves the scope and power of Raman spectroscopy by taking advantage of plasmonic nanostructures, which have the potential to enhance Raman signal strength by several orders of magnitude, which can allow for the detection of analyte molecules. The dataset presented provides results of a computational study that used a finite element method (FEM) to model gold nanowires on a silicon dioxide substrate. The survey calculated the surface average of optical surface enhancement due to plasmonic effects across the entire model and studied various geometric parameters regarding the width of the nanowires, spacing between the nanowires, and thickness of the silicon dioxide substrate. From this data, enhancement values were found to have a periodicity due to the thickness of the silicon dioxide. Additionally, strong plasmonic enhancement for smaller distances between nanowires were found, as expected; however, additional surface enhancement at greater gap distances were observed, which were not anticipated, possibly due to resonance with periodic dimensions and the frequency of the light. This data presentation will benefit future SERS studies by probing further into the computational and mathematical material presented previously.
Highlights
Due to advances in nanotechnology engineering and manufacturing in recent years, there has been an increase in improvements to surfaced-enhanced Raman spectroscopy (SERS)
Plasmonic structures on the substrate surface can improve the Raman signal by many orders of magnitude [9,10,11] and can be tuned by taking advantage of specific nanostructure geometries capable of enhancing the electric near-field surrounding the nanostructures
The data presented and discussed in this paper show the results of computational modeling of plasmonic nanostructures
Summary
Due to advances in nanotechnology engineering and manufacturing in recent years, there has been an increase in improvements to surfaced-enhanced Raman spectroscopy (SERS). Plasmonic structures on the substrate surface can improve the Raman signal by many orders of magnitude [9,10,11] and can be tuned by taking advantage of specific nanostructure geometries capable of enhancing the electric near-field surrounding the nanostructures. One example of such nanostructures is a plasmonic nanograting; a structure that assumes a periodic assembly of plasmonic elements with nanoscale dimensions in at least one direction. A FEM was used in this study, and line averages across the surface of a simulated 2D cross-section of a grating and substrate were analyzed to improve the understanding of the electric field properties surrounding the structure
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