Machine Learning Augmented VOC Identification by Mid-Infrared Nanoantennas with Microfluidics Chambers

Zhihao Ren, Zixuan Zhang, Jingxuan Wei, Haibo Wang, B. Dong, Chengkuo Lee
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引用次数: 2

Abstract

Infrared vibrational spectroscopy enhanced by plasmonic nanoantenna (PNA) become attractive sensing platforms for molecular recognition and characterization. With the rich information provided by IR fingerprint absorption and wavelength shift by broadband PNA, machine learning serves as a powerful tool to classify the complementary physical (refractive index) and chemical (chemical bond vibration) information and recognize the molecules. We propose an ultrasensitive broadband hook nanoantenna platform integrated with microfluidics channels and perform machine learning analysis to identify chemically similar alcoholic molecules in low concentrations. Our platform paves the way to advanced IR spectroscopic sensing for a wide range of chemical identification.
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机器学习增强中红外微流控室纳米天线VOC识别
等离子体纳米天线(PNA)增强的红外振动光谱成为分子识别和表征的重要传感平台。利用红外指纹吸收和宽带PNA波长移提供的丰富信息,机器学习可以作为一种强大的工具,对互补的物理(折射率)和化学(化学键振动)信息进行分类,并识别分子。我们提出了一种集成微流体通道的超灵敏宽带挂钩纳米天线平台,并进行机器学习分析,以识别低浓度化学相似的酒精分子。我们的平台为广泛的化学鉴定铺平了先进的红外光谱传感道路。
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