Scholarlink

<p>Early-stage detection of brain tumors remains a significant clinical challenge, requiring sensing platforms capable of resolving subtle variations in the optical properties of biological tissues and fluids. In this work, a multimodal terahertz (THz) surface plasmon resonance (SPR) metasurface biosensor is proposed, integrating a multi-resonator metallic architecture with a vertically stacked graphene/WS₂ two-dimensional heterostructure. This design enables enhanced electromagnetic field confinement and the generation of multiple sharp resonance features within a compact footprint. The sensor is numerically investigated using full-wave COMSOL Multiphysics simulations, demonstrating high sensitivity (up to 1538&#xa0;GHz/RIU), a quality factor of 44, and a figure of merit of 134, indicating strong spectral selectivity and detection precision. To improve computational efficiency, a Random Forest regression model is developed to predict refractive index variations with high accuracy (≈ 98%) and low error (RMSE ≈ 0.0012 RIU), enabling data-driven sensing and rapid design optimization. The investigated refractive index range (1.33–1.45 RIU) corresponds to reported values for cerebrospinal fluid, normal brain tissue, and malignant glioma tissues, supporting the potential applicability of the proposed sensor for biomedical diagnostics. Overall, the proposed platform combines structural, material, and machine learning innovations to provide a scalable and high-performance solution for terahertz biosensing applications.</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

A multimodal SPR metasurface biosensor using 2D heterostructures and random forest modeling for enhanced refractive index sensing in brain tumor diagnostics

  • 期刊论文

  • 发表日期：

    2026年5月30日

查看全文
  • Boopathy Tamilselvan,
  • Kavitha Maruthai

摘要

Early-stage detection of brain tumors remains a significant clinical challenge, requiring sensing platforms capable of resolving subtle variations in the optical properties of biological tissues and fluids. In this work, a multimodal terahertz (THz) surface plasmon resonance (SPR) metasurface biosensor is proposed, integrating a multi-resonator metallic architecture with a vertically stacked graphene/WS₂ two-dimensional heterostructure. This design enables enhanced electromagnetic field confinement and the generation of multiple sharp resonance features within a compact footprint. The sensor is numerically investigated using full-wave COMSOL Multiphysics simulations, demonstrating high sensitivity (up to 1538 GHz/RIU), a quality factor of 44, and a figure of merit of 134, indicating strong spectral selectivity and detection precision. To improve computational efficiency, a Random Forest regression model is developed to predict refractive index variations with high accuracy (≈ 98%) and low error (RMSE ≈ 0.0012 RIU), enabling data-driven sensing and rapid design optimization. The investigated refractive index range (1.33–1.45 RIU) corresponds to reported values for cerebrospinal fluid, normal brain tissue, and malignant glioma tissues, supporting the potential applicability of the proposed sensor for biomedical diagnostics. Overall, the proposed platform combines structural, material, and machine learning innovations to provide a scalable and high-performance solution for terahertz biosensing applications.