SERS Sensors: Recent Developments and a Generalized Classification Scheme Based on the Signal Origin

Owing to its extreme sensitivity and easy execution, surface-enhanced Raman spectroscopy (SERS) now finds application for a wide variety of problems requiring sensitive and targeted analyte detection. This widespread application has prompted a proliferation of different SERS-based sensors, suggesting the need for a framework to classify existing methods and guide the development of new techniques. After a brief discussion of the general SERS modalities, we classify SERS-based sensors according the origin of the signal. Three major categories emerge from this analysis: surface-affinity strategy, SERS-tag strategy, and probe-mediated strategy. For each case, we describe the mechanism of action, give selected examples, and point out general misconceptions to aid the construction of new devices. We hope this review serves as a useful tutorial guide and helps readers to better classify and design practical and effective SERS-based sensors.

由于其极高的灵敏度和易于操作的特点，表面增强拉曼光谱（SERS）如今在众多需要灵敏且有针对性的分析物检测的问题中得到了应用。这种广泛的应用促使了不同的基于SERS的传感器大量涌现，这表明需要一个框架来对现有方法进行分类并指导新技术的开发。在简要讨论了一般的SERS模式之后，我们根据信号的来源对基于SERS的传感器进行分类。通过这种分析得出了三大类别：表面亲和策略、SERS标记策略和探针介导策略。对于每种情况，我们描述了作用机制，给出了选定的示例，并指出了常见的误解，以帮助构建新的设备。我们希望这篇综述能作为一个有用的指导教程，帮助读者更好地对基于SERS的实用且有效的传感器进行分类和设计。