Optimized design of a surface plasmon resonance biosensor for Mycobacterium tuberculosis detection using the differential evolution algorithm.

This study presents a multilayer surface plasmon resonance (SPR) biosensor engineered for the sensitive detection of Mycobacterium tuberculosis bacteria. The suggested configuration includes aprism combined with successive layers ofphosphorus (BP). The optical properties were thoroughly investigated utilizing the transfer matrix method (TMM) and validated through finite element method (FEM) simulations. Through optimization of layer thicknesses, the sensor achieved a maximum angular sensitivity of 638°/RIU. Comparative analyses with alternative plasmonic metals, 2D materials, and prism substrates validated the superior sensing capability of the proposed design. Essential performance metrics comprised a minimum full width at half maximum (FWHM) of 3.55°, a peak signal-to-noise ratio (SNR) of 1.19, and a maximum quality factor of, indicating superior resolution and detection accuracy. The differential evolution (DE) algorithm was utilized to optimize essential structural dimensions, thereby improving the sensor's performance. This approach yielded an improved angular sensitivity of 654 deg./RIU. Distinct from existing SPR configurations, the proposed sensor integrates a simple multilayer architecture with DE algorithm-based optimization, thereby achieving high sensitivity and an extensive refractive index detection range (1.25-1.35), which together enable precise, label-free identification of diverse biological and chemical analytes.