Many of the features of SERS, such as its high sensitivity, molecular specificity and speed of analysis make it attractive as an analytical technique. However, SERS currently remains a specialist technique which has not yet entered the mainstream of analytical chemistry. Therefore, this review draws out the underlying principles for analytical SERS and provides practical tips and tricks for SERS quantitation. The aim is to show the readers how to rationally design their SERS experiments to improve quantitation performance. We begin by introducing the three core components in SERS analysis: (1) the enhancing substrate material, (2) the Raman instrument and (3) the processed data that is used to establish a calibration curve. This is followed by discussion of the analytical figures of merit relevant to SERS. In the following sections each of the three essential components in SERS quantitation and how they affect the quality of the analysis are described in more detail using examples from the literature. Finally, we highlight the current challenges in applying SERS to the analysis of complex real-life samples and briefly introduce the state-of-the-art developments on multifunctional substrates, digital SERS and AI-assisted data processing, which will help SERS rise to the challenge of moving out into routine real-world analysis.

中文翻译：

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定量分析表面增强拉曼光谱的实用方法


SERS 的许多特点，例如高灵敏度、分子特异性和分析速度，使其成为一种极具吸引力的分析技术。然而，SERS 目前仍然是一项尚未进入分析化学主流的专业技术。因此，本文总结了分析 SERS 的基本原理，并提供了 SERS 定量的实用技巧和窍门。目的是向读者展示如何合理设计他们的 SERS 实验以提高定量性能。我们首先介绍 SERS 分析中的三个核心组成部分：（1） 增强衬底材料，（2） 拉曼仪器和 （3） 用于建立校准曲线的处理数据。接下来讨论了与 SERS 相关的分析品质因数。在以下各节中，将使用文献中的示例更详细地描述 SERS 定量中的三个基本组成部分中的每一个以及它们如何影响分析质量。最后，我们强调了当前将 SERS 应用于复杂真实样品分析的挑战，并简要介绍了多功能基材、数字 SERS 和 AI 辅助数据处理的最新发展，这将帮助 SERS 迎接进入常规真实世界分析的挑战。