Design and performance simulation of a highly sensitive nano-biosensor based on a realistic array of plasmonic synthesized nanostructures

Abstract

In this study, simulation, analysis, and synthesis of silver plasmonic nanostructures were investigated for use in biomolecule detection. At first, silver nanoparticles (SNPs) were synthesized by a chemical reduction method using polyethylenimine as both a reducing and a stabilizing agent. The SNPs were characterized by UV–visible spectroscopy, dynamic light scattering, and field emission scanning electron microscopy equipped with energy-dispersive X-ray spectroscopy measurement techniques and showed spherical morphology with an average particle size of 38 nm and a localized surface plasmon resonance (LSPR) peak around 400 nm. The plasmonic effects of the silver nanostructures were also investigated for detection of glucose as a model analyte, with a concentration range of 0.0–2.603 mol/L. Wavelength shifts of 0.033 and 12.04 nm were obtained for glucose concentrations of 0.0039 and 2.603 mol/L, respectively; these shifts yielded the sensitivities of 482.75 and 189.02 nm/RIU and figures of merit (FOMs) of 13.5 and 5.24, respectively. The simulation results indicated the ability of SNPs of 30 nm to detect glucose concentrations as low as 0.0039 mol/L with an LSPR wavelength shift of about 0.033 nm. Also, the sensitivity and FOM were calculated for a 10 × 10 array of non-uniform size nanoparticles according to the experimental sizes. The simulation results revealed the significance of both the nanoparticle size and the particle size uniformity of a realistic array on the sensitivity and LSPR peak shift of SNPs. These findings show that it is possible to use an LSPR-based sensor to detect other biological samples by tuning their plasmonic features.