Journal Article10.1002/adts.202200886
Computational Modeling for Intelligent Surface Plasmon Resonance Sensor Design and Experimental Schemes for Real‐Time Plasmonic Biosensing: A Review
Chandreyee Manas Das,Fan Yang,Zhenxu Yang,Xiaochen Liu,Kien Voon Kong,Ho P. Ho,Lining Ju,Jiaqing Xiong,Ken-Tye Yong +8 more
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TL;DR: The various SPR sensing schemes that researchers have explored to realize enhanced SPR sensitivity are reviewed and summarized and "unconventional" designs, specifically those involving hybrid localized surface plasmon resonance (LSPR)‐SPR excitation, may inspire those in the plAsmonic field.
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Abstract: The spectacular physical phenomenon of surface plasmon resonance (SPR) is the essence of present‐day plasmonic sensors. Meanwhile, the unique properties of the interaction between light and matter have been carved out into the development of modern‐day diagnostic biosensors. Plasmons, in simple terms, are oscillating free electrons in metallic nano‐structures triggered by an incoming electromagnetic (EM) wave. With the advantages of real‐time and label‐free bio‐sensing, plasmonic sensors are being utilized in multiple diverse areas of food technology, the bio‐medical diagnostic sector, and even the chemical industry. Although this review will be brief, readers can gain a comprehensive picture of the essential elements by taking a broader look into the exploration of SPR sensor design via simulated studies and representative experimental plasmonic schemes developed for bio‐sensing. In short, the various SPR sensing schemes that researchers have explored to realize enhanced SPR sensitivity are reviewed and summarized. Different experimental plasmonic sensors are also examined in which new SPR excitation schemes have been adopted. These "unconventional" designs, specifically those involving hybrid localized surface plasmon resonance (LSPR)‐SPR excitation, may inspire those in the plasmonic field.
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Citations
Ultra-Sensitive Visible-IR Range Fiber Based Plasmonic Sensor: A Finite-Element Analysis and Deep Learning Approach for RI Prediction
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TL;DR: Ultra-sensitive visible-IR range fiber-based plasmonic sensor for RI prediction using finite-element analysis and deep learning. High WS and FOM, low WR, and accurate ANN model for RI prediction.
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Design and Analysis of a Plasmonic Metasurface-Based Graphene Sensor for Highly Sensitive and Label-Free Detection of COVID-19 Biomarkers
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9
Towards cost-effective and lightweight surface plasmon resonance biosensing for H5N1 avian influenza virus detection: integration of novel near-infrared organic photodetectors
Yu-Ching Huang,Sheng-Fan Wang,Bo-Cheng Chen,Zih-Syuan Yang,Meng-Chi Li,Xun-Ying Wu,Meng-Jey Youh,Hui-Yun Chou,Yu Xen Lin,Wanchai Assavalapsakul,A. Thitithanyanont,Linling Su +11 more
- 01 Nov 2023
TL;DR: Researchers developed a cost-effective and lightweight surface plasmon resonance biosensor for detecting H5N1 avian influenza virus using near-infrared organic photodetectors, achieving a 37-fold higher sensitivity than commercial tests and rapid detection within 12 minutes.
9
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TL;DR: The findings suggested that LC-AgNPs could be used as antioxidant, antibacterial, and anticancer agents for the cure of free-radical-oriented bacterial and oncogenic diseases.
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