Author: Li, Dongxiao; Zhou, Hong; Hui, Xindan; He, Xianming; Mu, Xiaojing
Title: Plasmonic Biosensor Augmented by a Genetic Algorithm for Ultra-Rapid, Label-Free, and Multi-Functional Detection of COVID-19 Cord-id: jtlhp054 Document date: 2021_6_25
ID: jtlhp054
Snippet: [Image: see text] The novel coronavirus (COVID-19) is spreading globally due to its super contagiousness, and the pandemic caused by it has caused serious damage to the health and social economy of all countries in the world. However, conventional diagnostic methods are not conducive to large-scale screening and early identification of infected persons due to their long detection time. Therefore, there is an urgent need to develop a new COVID-19 test method that can deliver results in real time
Document: [Image: see text] The novel coronavirus (COVID-19) is spreading globally due to its super contagiousness, and the pandemic caused by it has caused serious damage to the health and social economy of all countries in the world. However, conventional diagnostic methods are not conducive to large-scale screening and early identification of infected persons due to their long detection time. Therefore, there is an urgent need to develop a new COVID-19 test method that can deliver results in real time and on-site. In this work, we develop a fast, ultra-sensitive, and multi-functional plasmonic biosensor based on surface-enhanced infrared absorption for COVID-19 on-site diagnosis. The genetic algorithm intelligent program is utilized to automatically design and quickly optimize the sensing device to enhance the sensing performance. As a result, the quantitative detection of COVID-19 with an ultra-high sensitivity (1.66%/nm), a wide detection range, and a diverse measurement environment (gas/liquid) is achieved. In addition, the unique infrared fingerprint recognition characteristics of the sensor also make it an ideal choice for mutant virus screening. This work can not only provide a powerful diagnostic tool for the ultra-rapid, label-free, and multi-functional detection of COVID-19 but also help gain new insights into the field of label-free and ultrasensitive biosensing.
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