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推动表面增强拉曼光谱(SERS)成为一种定量技术:挑战、考量因素以及有助于验证的相关方法

Advancing SERS as a quantitative technique: challenges, considerations, and correlative approaches to aid validation.

作者信息

Sloan-Dennison Sian, Wallace Gregory Q, Hassanain Waleed A, Laing Stacey, Faulds Karen, Graham Duncan

机构信息

Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, 99 George Street, Glasgow, G1 1RD, UK.

出版信息

Nano Converg. 2024 Aug 17;11(1):33. doi: 10.1186/s40580-024-00443-4.

DOI:10.1186/s40580-024-00443-4
PMID:39154073
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11330436/
Abstract

Surface-enhanced Raman scattering (SERS) remains a significant area of research since it's discovery 50 years ago. The surface-based technique has been used in a wide variety of fields, most prominently in chemical detection, cellular imaging and medical diagnostics, offering high sensitivity and specificity when probing and quantifying a chosen analyte or monitoring nanoparticle uptake and accumulation. However, despite its promise, SERS is mostly confined to academic laboratories and is not recognised as a gold standard analytical technique. This is due to the variations that are observed in SERS measurements, mainly caused by poorly characterised SERS substrates, lack of universal calibration methods and uncorrelated results. To convince the wider scientific community that SERS should be a routinely used analytical technique, the field is now focusing on methods that will increase the reproducibility of the SERS signals and how to validate the results with more well-established techniques. This review explores the difficulties experienced by SERS users, the methods adopted to reduce variation and suggestions of best practices and strategies that should be adopted if one is to achieve absolute quantification.

摘要

自50年前被发现以来,表面增强拉曼散射(SERS)仍然是一个重要的研究领域。这种基于表面的技术已被广泛应用于各种领域,最显著的是化学检测、细胞成像和医学诊断,在探测和定量选定的分析物或监测纳米颗粒的摄取和积累时具有高灵敏度和特异性。然而,尽管SERS前景广阔,但它大多局限于学术实验室,并未被视为一种金标准分析技术。这是由于在SERS测量中观察到的变化,主要是由表征不佳的SERS基底、缺乏通用校准方法以及结果不相关所致。为了让更广泛的科学界相信SERS应该成为一种常规使用的分析技术,该领域目前正专注于提高SERS信号重现性的方法,以及如何用更成熟的技术验证结果。本综述探讨了SERS用户所遇到的困难、为减少变化而采用的方法,以及如果要实现绝对定量应采用的最佳实践和策略建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/1a62957bd3a6/40580_2024_443_Fig10_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/b1eb932b18a8/40580_2024_443_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/84435ec6645c/40580_2024_443_Fig6_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/7be86bf1a92f/40580_2024_443_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/2dd10ac1ce06/40580_2024_443_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/1a62957bd3a6/40580_2024_443_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/6d2245a38c0a/40580_2024_443_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/2e6b29174f49/40580_2024_443_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/92d79d4f0cbe/40580_2024_443_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/621fc00e909c/40580_2024_443_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/b1eb932b18a8/40580_2024_443_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/84435ec6645c/40580_2024_443_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/500c39f9fdd1/40580_2024_443_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/7be86bf1a92f/40580_2024_443_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/2dd10ac1ce06/40580_2024_443_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70f9/11330436/1a62957bd3a6/40580_2024_443_Fig10_HTML.jpg

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