Issue 20, 2024

Recent advances of MOF-based SERS substrates in quantitative analysis of food contaminants: a review

Abstract

Advancements in food-contaminant detection technologies can significantly improve food safety and human health. Surface-enhanced Raman spectroscopy (SERS) has become the preferred analytical method for food-safety detection owing to its numerous advantages, which include unique ‘molecular fingerprinting’ features, high sensitivity, rapid responses, and non-invasive characteristics. Raman-signal enhancements rely heavily on high-performance SERS substrates. In recent years, metal–organic framework (MOF)-based SERS substrates have gained attention as promising candidates for developing SERS technologies owing to their distinctive structures and functions. This review comprehensively examines recent advances in MOF-based SERS substrates, focusing on the main role of MOFs in SERS substrates as well as their typical categories and structures, construction methods, and representative applications in food-contaminant detection. First, the primary roles of MOFs in SERS substrates are briefly introduced. Next, a comprehensive overview of the typical categories and structures of MOF-based SERS substrates is discussed. Subsequently, a fundamental view of the general construction methods for MOF-based SERS substrates is presented. Next, the main applications of MOF-based SERS substrates for food-contaminant detection are summarised. Finally, challenges and perspectives, including improvements in SERS performance and stability, and the unification of SERS mechanisms, are addressed and discussed.

Graphical abstract: Recent advances of MOF-based SERS substrates in quantitative analysis of food contaminants: a review

Article information

Article type
Critical Review
Submitted
26 jun 2024
Accepted
16 sep 2024
First published
18 sep 2024

Analyst, 2024,149, 4997-5013

Recent advances of MOF-based SERS substrates in quantitative analysis of food contaminants: a review

Y. Gu, X. Pu, J. Chen, L. Yi, J. Bi, F. Duan and K. Ge, Analyst, 2024, 149, 4997 DOI: 10.1039/D4AN00897A

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