Highly sensitive malaria detection using a graphene-coated dual circular ring resonator biosensor with behaviour prediction based on stacking ensemble

This study presents a biosensor incorporating graphene and copper for highly sensitive malaria detection. The sensor design features dual circular ring resonators surrounded by a rectangular resonator, all supported on a graphene-coated SiO₂ substrate. The sensor achieves a remarkable sensitivity of 800 GHzRIU^-1 within a refractive index range of 1.373–1.402. Comprehensive parameter optimization studies demonstrate the sensor's robust performance across various operating conditions, including graphene chemical potential, incident angle, and resonator dimensions. The integration of a stacking ensemble machine learning approach further enhances the sensor's predictive capabilities, achieving correlation coefficients (R²) up to 100 % for transmission spectra predictions. COMSOL Multiphysics simulations validate the sensor's detection mechanisms and field distribution characteristics. The proposed biosensor represents a significant advancement in malaria detection technology, offering high sensitivity, reliability, and practical fabrication feasibility.