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Particle swarm optimization algorithm assisted general rule metamaterial SPR biosensor design for MMP-9 detection
Tingting Liu1, Bin Guan1, Chao Shen1
1Department of Optoelectronic Engineering, College of Physics and Optoelectronic Engineering, Jinan University, Guangzhou, 510632, China; Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Jinan University, Guangzhou, 510632, China.
Abstract:
Surface plasmon resonance (SPR) sensors offer in situ, label-free, and real-time detection. They are essential tools for quantitative detection. However, achieving the high sensitivity required for detecting small biomolecules remains highly challenging, particularly in the efficient design of optimized metamaterial-based SPR sensors. This study presents a design framework for general rule metamaterial SPR sensors. The framework transcends the constraints of current metamaterial designs. It enhances design flexibility and minimizes fabrication inaccuracies. The framework requires only the optical properties of 10 materials as input. It then efficiently selects the structure with optimal sensitivity from 1.07 × 1027 possible combinations. The sensitivity improves by 42.5%. The designed metamaterial SPR sensor reduces the detection limit for matrix metalloproteinase-9 (MMP-9) from 6.5042 to 0.083 fg/mL. This value is two orders of magnitude lower than that of traditional gold sensors. This design framework provides a universal and cost-effective approach for designing SPR sensors with optimized performance.
