光學共振⽣物感測器的計算和實驗⽅法：從LSPR到SPR - 拉曼積分和無⾦屬有損模式共振

Abstract

noneComputational studies have become an essential complement to research, enabling the exploration of physical phenomena that are challenging or even impossible to observe experimentally. In this thesis, computational and experimental studies were conducted in studying resonance-based optical biosensors, namely Localized Surface Plasmon Resonance (LSPR), integration of Surface Plasmon Resonance (SPR) and Raman, and non-metal optical sensors. In LSPR-based optical sensors, the investigation focuses on the interaction of the gold nanoparticle (AuNPs) transducer used for BSA detection. Experimental results reveal the presence of the Hook effect, characterized by a decrease in the LSPR signal response. From a computational perspective, the dielectric layer on the AuNPs surface enhances the electric field, disrupting the LSPR signal, particularly in the aggregated state.In the integration of SPR sensors with Raman technology, a one-dimensional (1D) gold grating chip was selected as the transducer. Reflectance map analysis identified a surface plasmon mode (SPM) at grating periods ranging from 644 nm to 800 nm. Additionally, a distinct resonance mode, known as cavity mode (CM), was observed, exhibiting a different signal response from the SPR mode when tested with varying refractive indices of the sensing medium. The experimental results further confirmed thatthe Raman signal can still be enhanced by utilizing the electric field generated due to SPR excitation.In the third study, the investigation focuses on finding material combinations that can replace SPR sensors, which heavily rely on gold as transducers. In this context, two-dimensional (2D) materials such as MoS2, and WS₂ have been selected as lossy layers, with their performance optimized by incorporating a matching layer of Cytop or MgF2. Computational results indicate that Lossy Mode Resonance (LMR) sensor utilizing Cytop and WS₂ exhibits excellent signal quality and stability. This sensoralso offers a wider dynamic range, capable of detecting refractive indices up to 1.5, which exceeds the detection capability of SPR sensors excited at either 633 nm or 670 nm. Additionally, the proposed structure provides a longer penetration depth than SPR sensors, making it highly promising for detecting analytes ranging from the nanoscale to the microscale.Overall, the findings of this study are expected to serve as a reference in designing more effective and accurate optical biosensors for biomedical and chemical applications, by understanding their signal characteristics and electric field characteristics to maximize sensor performance. The study's contributions include optimizing resonance-based biosensors to improve sensitivity and accuracy in detection applications, which can support the development of future diagnostic devices.