Dual-band terahertz graphene–MXene–silver metasurface biosensor for brain tumor screening and early detection using machine learning

This paper proposes a novel terahertz biosensor employing a multi-layer architecture of graphene, MXene and silver to detect brain tumors with high sensitivity. The proposed structure comprises a silicon dioxide substrate with periodic rectangular resonator arrays which provide dual band operation at two frequency bands of 0.1–0.3 THz and 0.4–0.45 THz. Finite element simulations performed in COMSOL Multiphysics demonstrated that the absorption characteristics of the sensor are strongly modulated by both the graphene chemical potential and the electromagnetic wave angle of incidence; peak absorptances of 98.7% and 97.3% are achieved under optimal conditions for each parameter respectively, with all absorption values verified to satisfy energy conservation (R + T + A = 1) through cosine-corrected S-parameter normalization. The refractive index sensitivity of the biosensor was found to be exceptionally high at 1538 GHz/RIU over the refractive index range of 1.3333–1.4833 RIU, spanning the biologically validated contrast between healthy and tumor-affected brain tissue. A very strong linear relationship between the resonance frequency shift and the refractive index of the biosensor yields a calibration curve F = −0.1550n + 0.6402 with a correlation coefficient of 99.326%. Machine learning validation with Locally Weighted Linear Regression (LWLR), conducted on a noise-augmented dataset of 980 samples with 10-fold cross-validation and independent test-set evaluation, shows that the proposed biosensor has high prediction accuracy with R 2 values as high as 95%. These results demonstrate that the proposed biosensor has significant potential for early stage brain tumor diagnostics and supports an integrated sensor-to-inference pipeline suitable for future clinical deployment.