Ultra-Sensitive Visible-IR Range Fiber Based Plasmonic Sensor: A Finite-Element Analysis and Deep Learning Approach for RI Prediction

In this paper, a relatively simple and ultra-sensitive Photonic crystal fiber (PCF) based surface plasmon resonance (SPR) sensor is proposed for detecting different analyte refractive indices (RIs) ranging from 1.33 to 1.43 over a wide range of wavelength spectrum spanning 0.55~\mu m to 3.50~\mu m...

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Veröffentlicht in:	IEEE access 2024, Vol.12, p.64727-64735
Hauptverfasser:	Al Mahfuz, Mohammad, Afroj, Sumaiya, Rahman, Afiquer, Azad Hossain, Md, Anwar Hossain, Md, Habib, Md Selim
Format:	Artikel
Sprache:	eng
Schlagworte:	artificial neural network Artificial neural networks Computer simulation Couplings Crystal fibers Deep learning Extreme values Figure of merit Finite element method Machine learning Optical fiber sensors Photonic crystal fiber Photonic crystals Refractive index Refractivity Resonance Sensitivity sensor Sensors Surface plasmon resonance Surface plasmons
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