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<p>This study presents a numerical analysis of a surface plasmon resonance (SPR) biosensor with enhanced sensitivity, figure of merit (FoM), and penetration depth (PD) at infrared wavelengths. The sensor design incorporates a carbon nanotube (CNT) layer combined with a graphene layer, optimized for biomolecule detection at an excitation wavelength of 1550&#xa0;nm. The graphene layer functions as a biorecognition element (BRE), enabling biomolecule attachment due to its strong adhesive properties. The proposed sensor achieves a maximum sensitivity of 354.08°/RIU and a PD of 1298.11&#xa0;nm with minor refractive index (RI) changes in the sensing medium (1.37–1.38). The structure is effective for RI values ranging from 1.32 to 1.42. With notable improvements in FoM and limit of detection (LoD), the biosensor demonstrates a high potential for precise biomolecule detection. Further, as an application, the proposed biosensor’s performance is evaluated for detecting cancers such as skin, cervical, blood, and breast cancer. Although this study is based exclusively on simulations, experimental studies can be carried out in the future to validate the numerical results obtained.</p>

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A Theoretical Approach for Sensitivity Enhancement Using Refractive Index-Based Surface Plasmon Resonance Sensor

  • 期刊论文

  • 发表日期：

    2025年6月3日

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  • Rajeev Kumar,
  • Shivam Singh,
  • Yogendra Pratap Pundir,
  • Lalit Garia,
  • Hiba Bouandas

摘要

This study presents a numerical analysis of a surface plasmon resonance (SPR) biosensor with enhanced sensitivity, figure of merit (FoM), and penetration depth (PD) at infrared wavelengths. The sensor design incorporates a carbon nanotube (CNT) layer combined with a graphene layer, optimized for biomolecule detection at an excitation wavelength of 1550 nm. The graphene layer functions as a biorecognition element (BRE), enabling biomolecule attachment due to its strong adhesive properties. The proposed sensor achieves a maximum sensitivity of 354.08°/RIU and a PD of 1298.11 nm with minor refractive index (RI) changes in the sensing medium (1.37–1.38). The structure is effective for RI values ranging from 1.32 to 1.42. With notable improvements in FoM and limit of detection (LoD), the biosensor demonstrates a high potential for precise biomolecule detection. Further, as an application, the proposed biosensor’s performance is evaluated for detecting cancers such as skin, cervical, blood, and breast cancer. Although this study is based exclusively on simulations, experimental studies can be carried out in the future to validate the numerical results obtained.