High-Sensitivity Surface Plasmon resonance Biosensor with Gold-Based Metasurfaces and polynomial regression Optimization for Early Breast Cancer Detection

Jacob Wekalao^1*Ahmed Mehaney²Bashir Salah³Mostafa R Abukhadra²Stefano Bellucci⁴Hussein Elsayed⁵Amuthakkannan Rajakannu⁶

• ¹University of Science and Technology of China, Hefei, China
• ²Beni-Suef University, Beni Suef, Egypt
• ³King Saud University, Riyadh, Saudi Arabia
• ⁴Laboratori Nazionali di Frascati, Frascati, Italy
• ⁵University of Hail, Hail, Saudi Arabia
• ⁶NATIONAL UNIVERSITY OF SCIENCE AND TECHNOLOGY, muscat, Oman

This investigation presents the design, simulation, and performance characterization of an advanced biosensing platform engineered for early-stage breast malignancy identification. The proposed sensor architecture integrates a simple graphene-enhanced metasurface configuration with metallic resonant elements comprised of gold and silver components. The structural design incorporates a cruciform-geometry resonator with gold metallization, encompassed by an annular silver-coated ring structure, designed upon a silicon dioxide substrate. Computational analysis conducted through finite element modelling via COMSOL Multiphysics software exemplifies superior performance characteristics, including a refractive index sensitivity of 929 GHz·RIU⁻¹, a figure of merit reaching 18.571 RIU⁻¹, and a minimum detectable refractive index change of 0.05 RIU. The biosensor-maintained quality factors exceeding 17 across three operational frequency ranges: 0.7-1.0 THz, 1.4-1.5 THz, and 1.62-1.8 THz. Additionally, the implementation of machine learning algorithms utilizing polynomial regression analysis demonstrates complete predictive accuracy for multiple operational parameters. The sensor architecture enables binary data encoding functionality through controlled modulation of graphene electrochemical potential, presenting opportunities for encrypted biosensing applications and secure data transmission protocols.