Optimized SPR-PCF sensor for sucrose detection inspired by vertical pupil geometry

In this article, a surface plasmon resonance (SPR) sensor based on photonic crystal fiber (PCF) has been presented for use in detecting the concentration of sucrose solution. This sensor is expertly designed, drawing on the vertical pupil pattern found in the eyes of certain animals to optimize the concentration of the electromagnetic field at the center of the structure. The primary objective is achieving superior amplitude sensitivity (AS) while minimizing losses. To ensure this, we have applied the Nelder-Mead algorithm for precise optimization of the structural parameters. For the analysis of this structure, the finite element method based on the mode solver has been used. After analyzing and optimizing the sensor, maximum wavelength sensitivity (WS) of 12,000 nm/RIU, AS of -5430.24 RIU<sup>-1</sup>, and maximum figure of merit (FOM) of 315.9077 RIU<sup>-1</sup> were obtained. Finally, in order to investigate the application of this sensor as a sensor for determining the concentration of sucrose solution, it has shown the values ​​of 13,000 nm/RIU, -6202.62 RIU<sup>-1</sup>, and 356.93 RIU<sup>-1</sup> for WS, AS, and FOM respectively related to the concentration of 45%, which shows its excellent performance in refractive index (RI) detection applications. Due to the absence of structural complications and being immune to manufacturing errors caused by small air holes, this design is considered to be an excellent impression of natural elements by providing ultra-high sensitivity.

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Publication Details

Journal
Scientific Reports
Published
2025-08-08
DOI
https://doi.org/10.1038/s41598-025-15288-y
Citations
4
Primary Topic
Advanced Fiber Optic Sensors
Type
article
Field-Weighted Citation Impact
2.92

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article

Optimized SPR-PCF sensor for sucrose detection inspired by vertical pupil geometry

Saeed Olyaee, Mahmood Seifouri, Vahid Fallahi, Mohammad Reza Khodatars Dashtmian
4 citations
Scientific Reports
Advanced Fiber Optic Sensors
2.92
article

Optimized SPR-PCF sensor for sucrose detection inspired by vertical pupil geometry

Saeed Olyaee, Mahmood Seifouri, Vahid Fallahi, Mohammad Reza Khodatars Dashtmian
article en
4 citations

Abstract

In this article, a surface plasmon resonance (SPR) sensor based on photonic crystal fiber (PCF) has been presented for use in detecting the concentration of sucrose solution. This sensor is expertly designed, drawing on the vertical pupil pattern found in the eyes of certain animals to optimize the concentration of the electromagnetic field at the center of the structure. The primary objective is achieving superior amplitude sensitivity (AS) while minimizing losses. To ensure this, we have applied the Nelder-Mead algorithm for precise optimization of the structural parameters. For the analysis of this structure, the finite element method based on the mode solver has been used. After analyzing and optimizing the sensor, maximum wavelength sensitivity (WS) of 12,000 nm/RIU, AS of -5430.24 RIU<sup>-1</sup>, and maximum figure of merit (FOM) of 315.9077 RIU<sup>-1</sup> were obtained. Finally, in order to investigate the application of this sensor as a sensor for determining the concentration of sucrose solution, it has shown the values ​​of 13,000 nm/RIU, -6202.62 RIU<sup>-1</sup>, and 356.93 RIU<sup>-1</sup> for WS, AS, and FOM respectively related to the concentration of 45%, which shows its excellent performance in refractive index (RI) detection applications. Due to the absence of structural complications and being immune to manufacturing errors caused by small air holes, this design is considered to be an excellent impression of natural elements by providing ultra-high sensitivity.

Scientific ReportsVol. 15(1)
Shiraz University of Technology (IR), Shahid Rajaee Teacher Training University (IR)
Kharazmi University, Shahid Rajaee Teacher Training University
Openalex Percentile: Top 8%
Advanced Fiber Optic Sensors
2.92
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Optimized SPR-PCF sensor for sucrose detection inspired by vertical pupil geometry — Saeed Olyaee, Mahmood Seifouri, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS