Scientific Reports (Jan 2025)

Development of an advanced multimode refractive index plasmonic optical sensor utilizing split ring resonators for brain cancer cell detection

  • Ali Khodaie,
  • Hamid Heidarzadeh,
  • Farrokhfar Valizadeh Harzand

DOI
https://doi.org/10.1038/s41598-024-84761-x
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 12

Abstract

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Abstract In this paper, we propose and theoretically investigate a novel multimode refractive index (MMRI) plasmonic optical sensor for detecting various brain cancer cells, leveraging the unique capabilities of split ring resonators (SRRs). The sensor, simulated using the finite-difference time-domain (FDTD) method, exhibits dual resonance modes in its reflection spectrum within the 1500 nm to 3500 nm wavelength range, marking a significant advancement in multimode plasmonic biosensing. Through detailed parametric analysis, we optimize critical dimensional parameters to achieve superior performance. The novelty of this work lies in the dual-mode sensing mechanism, which enables robust detection by exploiting the resonance characteristics of gold, silver, and aluminum. These materials provide tunable and highly sensitive interactions with light, enhancing the sensor’s adaptability for a wide range of applications. The results reveal exceptional sensitivity values of 1778.3 nm/RIU, a limit of detection (LOD) of 0.016 RIU, and a high figure of merit (FOM) of 7 RIU−1, along with a quality factor (QF) of 11.7 in the first resonance mode. The findings show that the designed optical biosensor exhibits high sensitivity, a good LOD, and an acceptable FOM in both resonance modes. So, this work paves the way for future research and development of susceptible, multimode optical sensors for medical diagnostics. The results indicate that the proposed sensor operates effectively across a range of temperatures and angles of radiant light, demonstrating its independence from these variables. This reliability in performance underscores its potential for use in diverse environments, making it a dependable tool for detecting biological samples, including brain cancer cells, irrespective of external conditions.

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