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

Abstract

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.