Finite Element Method-Based Modeling of a Novel Square Photonic Crystal Fiber Surface Plasmon Resonance Sensor with a Au–TiO2 Interface and the Relevance of Artificial Intelligence Techniques in Sensor Optimization DOI Creative Commons
Ayushman Ramola, Amit Kumar Shakya, Arik Bergman

et al.

Photonics, Journal Year: 2025, Volume and Issue: 12(6), P. 565 - 565

Published: June 4, 2025

This research presents a novel square-shaped photonic crystal fiber (PCF)-based surface plasmon resonance (SPR) sensor, designed using the external metal deposition (EMD) technique, for highly sensitive refractive index (RI) sensing applications. The proposed sensor operates effectively over an RI range of 1.33 to 1.37 and supports both x- polarized y-polarized modes. It achieves wavelength sensitivity 15,800 nm/RIU 14,300 nm/RIU, amplitude sensitivities 11,584 RIU−1 11,007 RIU−1, respectively, x-pol. y-pol. also reports resolution in order 10−6 RIU strong linearity R2 ≈ 0.97 polarization modes, indicating its potential precision detection complex environments. Beyond sensor’s structural performance innovations, this work explores future integration artificial intelligence (AI) into PCF-SPR design. AI techniques such as machine learning deep offer new pathways calibration, material optimization, real-time adaptability, significantly enhancing reliability. convergence with not only opens doors smart, self-calibrating platforms but establishes foundation next-generation sensors capable operating dynamic remote

Language: Английский

Machine learning algorithms for predicting the photoionization cross section of CdS/ZnSe core/shell spherical quantum dots surrounded by dielectric matrices DOI Creative Commons

A. Cherni,

N. Zeiri, N. Yahyaoui

et al.

Results in Physics, Journal Year: 2025, Volume and Issue: unknown, P. 108186 - 108186

Published: March 1, 2025

Language: Английский

Citations

0
Finite Element Method-Based Modeling of a Novel Square Photonic Crystal Fiber Surface Plasmon Resonance Sensor with a Au–TiO2 Interface and the Relevance of Artificial Intelligence Techniques in Sensor Optimization DOI Creative Commons
Ayushman Ramola, Amit Kumar Shakya, Arik Bergman

et al.

Photonics, Journal Year: 2025, Volume and Issue: 12(6), P. 565 - 565

Published: June 4, 2025

This research presents a novel square-shaped photonic crystal fiber (PCF)-based surface plasmon resonance (SPR) sensor, designed using the external metal deposition (EMD) technique, for highly sensitive refractive index (RI) sensing applications. The proposed sensor operates effectively over an RI range of 1.33 to 1.37 and supports both x- polarized y-polarized modes. It achieves wavelength sensitivity 15,800 nm/RIU 14,300 nm/RIU, amplitude sensitivities 11,584 RIU−1 11,007 RIU−1, respectively, x-pol. y-pol. also reports resolution in order 10−6 RIU strong linearity R2 ≈ 0.97 polarization modes, indicating its potential precision detection complex environments. Beyond sensor’s structural performance innovations, this work explores future integration artificial intelligence (AI) into PCF-SPR design. AI techniques such as machine learning deep offer new pathways calibration, material optimization, real-time adaptability, significantly enhancing reliability. convergence with not only opens doors smart, self-calibrating platforms but establishes foundation next-generation sensors capable operating dynamic remote

Language: Английский

Citations

0