Li Dongxiao, Xu Cheng, Xie Junsheng, Lee Chengkuo
Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore.
Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore 117608, Singapore.
Nanomaterials (Basel). 2023 Aug 19;13(16):2377. doi: 10.3390/nano13162377.
Infrared absorption spectroscopy is an effective tool for the detection and identification of molecules. However, its application is limited by the low infrared absorption cross-section of the molecule, resulting in low sensitivity and a poor signal-to-noise ratio. Surface-Enhanced Infrared Absorption (SEIRA) spectroscopy is a breakthrough technique that exploits the field-enhancing properties of periodic nanostructures to amplify the vibrational signals of trace molecules. The fascinating properties of SEIRA technology have aroused great interest, driving diverse sensing applications. In this review, we first discuss three ways for SEIRA performance optimization, including material selection, sensitivity enhancement, and bandwidth improvement. Subsequently, we discuss the potential applications of SEIRA technology in fields such as biomedicine and environmental monitoring. In recent years, we have ushered in a new era characterized by the Internet of Things, sensor networks, and wearable devices. These new demands spurred the pursuit of miniaturized and consolidated infrared spectroscopy systems and chips. In addition, the rise of machine learning has injected new vitality into SEIRA, bringing smart device design and data analysis to the foreground. The final section of this review explores the anticipated trajectory that SEIRA technology might take, highlighting future trends and possibilities.
红外吸收光谱法是检测和识别分子的有效工具。然而，其应用受到分子红外吸收截面低的限制，导致灵敏度低和信噪比差。表面增强红外吸收（SEIRA）光谱法是一种突破性技术，它利用周期性纳米结构的场增强特性来放大痕量分子的振动信号。SEIRA技术的迷人特性引起了极大的兴趣，推动了各种传感应用。在这篇综述中，我们首先讨论了三种优化SEIRA性能的方法，包括材料选择、灵敏度增强和带宽改善。随后，我们讨论了SEIRA技术在生物医学和环境监测等领域的潜在应用。近年来，我们迎来了一个以物联网、传感器网络和可穿戴设备为特征的新时代。这些新需求促使人们追求小型化和集成化的红外光谱系统及芯片。此外，机器学习的兴起为SEIRA注入了新的活力，将智能设备设计和数据分析推到了前台。这篇综述的最后一部分探讨了SEIRA技术可能的发展轨迹，突出了未来的趋势和可能性。
