Scholarlink

<p>In this paper, a PCF-based plasmonic sensor with hybrid circular and elliptical air holes is designed and optimized using the Nelder-Mead algorithm. The optimized structure achieves a wavelength sensitivity of 17,000&#xa0;nm/RIU and an amplitude sensitivity of 16,900 RIU⁻¹. A machine learning-based artificial neural network (ANN) is trained for inverse prediction; estimating the unknown refractive index of an analyte from its resonance wavelength. This combination of optimization and ANN-based prediction enables rapid, real-time refractive index sensing.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Advanced sensing with PCF integrating structural optimization and neural network for analyte prediction

  • 期刊论文

  • 发表日期：

    2026年6月19日

查看全文
  • Seyede Mahboobeh Mousavi Monazah,
  • Mohammad Reza Salehi,
  • Vahid Fallahi,
  • Zoheir Kordrostami,
  • Mehdi Hosseini

摘要

In this paper, a PCF-based plasmonic sensor with hybrid circular and elliptical air holes is designed and optimized using the Nelder-Mead algorithm. The optimized structure achieves a wavelength sensitivity of 17,000 nm/RIU and an amplitude sensitivity of 16,900 RIU⁻¹. A machine learning-based artificial neural network (ANN) is trained for inverse prediction; estimating the unknown refractive index of an analyte from its resonance wavelength. This combination of optimization and ANN-based prediction enables rapid, real-time refractive index sensing.