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Simulation and sensitivity analysis of a plasmonic FET based sensor in visible spectral range under different design conditions

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Abstract

In this work, an Si–SiO2–ZnO–Au nanoparticles (NPs) structure based plasmonic multilayer FET design is studied for sensing application. Here, Si is used as a substrate, ZnO is used as an active layer, and Au NPs are used to introduce the plasmonic enhancement effect in the proposed FET design. The simulation and analysis are carried out in the visible spectral range. The effect of design parameters such as the diameter of Au NPs, obliqueness of light incidence, and spacing between Au NPs is studied on the sensor’s sensitivity. Further, the effect of incorporating 3-mercapto propionic acid (3-MPA) with Au NPs has been studied while targeting an increase in sensitivity of the proposed device. The results indicate that the size of NPs and angle of light incidence have a coupled effect on the sensitivity. Further, at normal incidence, the larger size of Au NPs can be helpful in achieving greater sensitivity (finer limit of detection) and larger figure of merit. Also, smaller spacing between the NPs leads to enhanced absorption behaviour. Furthermore, the incorporation of 3-MPA has the capability to increase the sensitivity, particularly for the detection of low refractive index (RI) media (e.g., gaseous ones). The proposed device design can be helpful in gaseous and RI sensing along with biosensing (with 3-MPA) in the visible spectral range.

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Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The financial support to B. R. Muthu for this work was given by the College of Engineering Guindy, Anna University, Chennai, India (Grant No. Lr. No. CFR/ACRF/2016/20).

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Correspondence to Bharathi Raj Muthu.

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Muthu, B.R., Pushpa, E.P., Dhandapani, V. et al. Simulation and sensitivity analysis of a plasmonic FET based sensor in visible spectral range under different design conditions. Opt Quant Electron 54, 745 (2022). https://doi.org/10.1007/s11082-022-04131-7

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