Abstract
The problem of optimizing the topography of metal structures allowing Surface Enhanced Raman Scattering (SERS) sensing is considered. We developed a model, which randomly distributes hemispheroidal particles over a given area of the glass substrate and estimates SERS capabilities of the obtained structures. We applied Power Spectral Density (PSD) analysis to modeled structures and to atomic force microscope images widely used in SERS metal island films and metal dendrites. The comparison of measured and calculated SERS signals from differing characteristics structures with the results of PSD analysis of these structures has shown that this approach allows simple identification and choosing a structure topography, which is capable of providing the maximal enhancement of Raman signal within a given set of structures of the same type placed on the substrate.
Highlights
Surface Enhanced Raman Scattering (SERS) has become a widespread method of highly sensitive structural and compositional analysis of objects related to biology, chemistry, condensed matter physics, etc
In this paper we demonstrate that second order statistics, namely Power Spectral Density (PSD) analysis developed for signal processing, spectra, noise and other random processes [25,26,27,28], and which is in a wide use for surface roughness characterization [29,30,31,32,33,34,35], establishes a direct correlation of SERS abilities of metal structures and their topography
We have modelled a set of structures differing in size and number of randomly distributed hemispheroidal metal nanoparticles placed on glass substrate and evaluated awaited magnitude of Raman signal enhanced by each of the structures
Summary
Surface Enhanced Raman Scattering (SERS) has become a widespread method of highly sensitive structural and compositional analysis of objects related to biology, chemistry, condensed matter physics, etc. Provides higher enhancement [23], and this was demonstrated via deducing distribution of distances between adjacent approximately hemispherical metal islands in SEM images of SERS substrates [24]. In this paper we demonstrate that second order statistics, namely Power Spectral Density (PSD) analysis developed for signal processing, spectra, noise and other random processes [25,26,27,28], and which is in a wide use for surface roughness characterization [29,30,31,32,33,34,35], establishes a direct correlation of SERS abilities of metal structures and their topography. We revealed that the inflection point of the PSD function plotted in a log-log scale relates to a lateral correlation length of the substrate surface and directly correlates with Raman signal enhancement
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