Abstract
In the present study, we propose a high sensitive refractive index (RI) liquid biosensor. The arrayed arrangement of gold spherical nanoparticles (NP) laid on a grating surface made of silicon nitride (Si3N4) is implemented. The organization of NP arrays stimulate wave coupling to manage new operation in optical range. Designing the device can be followed through monitoring subtle changes in the refraction indices (RI) of the operating surfaces. The performance of the device is numerically investigated in near-infrared region, yielding a sensitivity value of as large as 470.3 nm/RIU (refractive index unit). It shows a figure of merit more than 59 RIU−1 within the operating wavelength of 900 nm. These results emphasize the role of plasmonic occurrence in the optimizing of NP pattern for biosensor dominance over nonoptic counterparts. The variations of optical response based on changing the geometry of gold nanoparticles (Au NPs) and grating configuration create a significant capability in sensing the RI of various bio analyte materials. Analyses of the results successfully show optimum performance of the proposed biochemical sensing ability for common biosensing applications. First, the present study would lead to the development of a new type of plasmonic device capable of detecting single bacterium and effective in determining the concentration level of bacterial spectrum in drinking water. Afterwards, we proceed with a cleverly designed RI biosensor optimized for waterborne infection due to Escherichia coli (E. coli), Serratia marcescens (S. marcescens), and Mierococcus lysodeikticus (M. lysodeikticus) pathogen. These bacterial pathogens at varied concentrations would be detectable by the proposed biosensor.
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Shima Pirhaghshenasvali and Rahim Ghayour wrote the main manuscript text and Shima Pirhaghshenasvali, Rahim Ghayour and Mahsa Vaghefi prepared figures and tables. All authors reviewed the manuscript.
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Pirhaghshenasvali, S., Ghayour, R. & Vaghefi, M. Highly sensitive biosensor based on nanoparticle/grating: a case study on detecting waterborne bacteria in drinking water. Opt Quant Electron 56, 602 (2024). https://doi.org/10.1007/s11082-023-06204-7
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DOI: https://doi.org/10.1007/s11082-023-06204-7