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<p>In this paper, a comparative investigation is conducted on the performance of Photonic Crystal Fiber (PCF) sensors based on Surface Plasmon Resonance (SPR), employing a diverse range of active and functional layers. This study isolates the intrinsic sensing capabilities of twelve distinct materials, including traditional (Au, Ag, Cu, Al) and transition (Pt, Pd, Rh, Ti) plasmonic metals, refractory ceramic compounds (TiN), high-index oxides (TiO<sub>2</sub>, ZnO, ITO), and 2D materials (Graphene, MoS<sub>2</sub>) by evaluating them within a fixed PCF-SPR . The individual impact of each material on resonance wavelength, confinement loss, and spectral sensitivity is analyzed by using the Full-Vectorial Finite Element Method (FV-FEM). By eliminating geometry-induced biases, our standardized approach successfully decouples material performance from structural variables, addressing a critical research gap in current sensor literature. According to numerical analysis, ITO is identified as the most sensitive standalone candidate, while Cu demonstrates a superior sensitivity profile at higher refractive indices among the noble metals, and the 2D materials improve resonance stability across the visible to near-infrared spectrum. Ultimately, this work establishes a novel, unbiased material selection guideline for the optimization of PCF-SPR sensors, providing crucial insights for the development of next-generation, high-performance biochemical sensors.</p>

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Comparative investigation of various metals and their influence on PCF-based SPR sensors

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月17日

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  • Ahmet Yasli

摘要

In this paper, a comparative investigation is conducted on the performance of Photonic Crystal Fiber (PCF) sensors based on Surface Plasmon Resonance (SPR), employing a diverse range of active and functional layers. This study isolates the intrinsic sensing capabilities of twelve distinct materials, including traditional (Au, Ag, Cu, Al) and transition (Pt, Pd, Rh, Ti) plasmonic metals, refractory ceramic compounds (TiN), high-index oxides (TiO2, ZnO, ITO), and 2D materials (Graphene, MoS2) by evaluating them within a fixed PCF-SPR . The individual impact of each material on resonance wavelength, confinement loss, and spectral sensitivity is analyzed by using the Full-Vectorial Finite Element Method (FV-FEM). By eliminating geometry-induced biases, our standardized approach successfully decouples material performance from structural variables, addressing a critical research gap in current sensor literature. According to numerical analysis, ITO is identified as the most sensitive standalone candidate, while Cu demonstrates a superior sensitivity profile at higher refractive indices among the noble metals, and the 2D materials improve resonance stability across the visible to near-infrared spectrum. Ultimately, this work establishes a novel, unbiased material selection guideline for the optimization of PCF-SPR sensors, providing crucial insights for the development of next-generation, high-performance biochemical sensors.