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Genetic Algorithm-Optimized Hyperbolic Metamaterial SPR Sensors for Ultrasensitive Biosensing Applications
Biao Zhao1,2,3, Luxiao Sang1,2, Zuxing Zhang1,2
1Shanxi Key Laboratory of Micro-Nano Sensors & Artificial Intelligence Perception, College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan 030024, China.
Analytical Chemistry
|April 15, 2026
Summary
Researchers developed a novel surface plasmon resonance (SPR) sensor using hyperbolic metamaterials (HMMs) for enhanced sensitivity. This advanced sensor platform significantly improves detection limits for crucial biomarkers like Alzheimer's disease indicators.
Area of Science:
- Nanotechnology
- Biomedical Engineering
- Materials Science
Background:
- Surface Plasmon Resonance (SPR) sensors are vital for biomolecular detection.
- Enhancing SPR sensitivity is crucial for detecting low concentrations and subtle interactions.
- Conventional SPR sensors have limitations in field enhancement and sensitivity.
Purpose of the Study:
- To design and develop a highly sensitive SPR sensor platform utilizing hyperbolic metamaterials (HMMs).
- To optimize HMMs-based SPR sensor parameters using a genetic algorithm (GA).
- To demonstrate the platform's capability for detecting Alzheimer's disease biomarkers.
Main Methods:
- Fabrication of an SPR sensor platform with Ag/Al2O3 multilayer hyperbolic metamaterials.
- Application of a genetic algorithm (GA) for systematic optimization of sensor parameters.
- Theoretical analysis using finite element analysis to understand field enhancement mechanisms.
- Experimental validation of sensor performance and biomarker detection.
Main Results:
- The HMMs-based SPR sensor demonstrated a refractive index (RI) sensitivity of 43.62 μm/RIU, an order of magnitude improvement over traditional sensors.
- Theoretical analysis revealed significant electric field enhancement within the dielectric layers of the HMMs.
- The platform achieved an ultralow limit of detection (LOD) of 0.18 pg/mL for the Alzheimer's biomarker β-amyloid 1-42 (Aβ1-42).
Conclusions:
- The developed HMMs-based SPR sensor platform offers superior sensitivity and field enhancement compared to conventional SPR sensors.
- The GA-driven design approach provides a generalized method for optimizing sensor performance.
- This technology holds significant promise for advancing early disease diagnosis and sensitive biomolecular detection.
