Smart graphene-enhanced ceramic material refractive index sensor simulation design developed for highly sensitive breast Cancer detection optimized with machine learning.

Based on the surface plasmon resonance (SPR) technique, the proposed biosensor is investigated as an SPR-based sensing platform for detecting breast cancer cells, specifically MCF-7 and MDA-MB-231 cells. Developed biosensor features an octagonal cylinder-shaped resonator design composed of two novel materials: an octagon-shaped structure made of gold (Au) and a cylinder-shaped structure made of silver (Ag). Graphene is also integrated to achieve high sensitivity in the detection for the two breast cancer cell lines based on the refractive index values, within the wavelength range of 1650-1700 nm, yielding sensitivity rates of 714.28 nm/RIU (MCF-7) and 785.71 nm/RIU (MDA-MB-231). The proposed Graphene Octagonal Cylinder-Shaped Surface Plasmon Resonance (GOCSPR) biosensor consists of two layers, with a ceramic substrate made of aluminum nitride (AlN), and exhibits good quality factors of 560 for MCF-7 and 557 for MDA-MB-231. The analysis of layer height and cylinder radius, along with optimization using a Linear Regression machine learning algorithm and the corresponding R2 values, is also presented in the manuscript. The designed graphene-based structure can be used for detecting breast cancer cell with high efficiency for medical applications.