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利用表面增强拉曼散射检测废水中的抗生素。

Sensing Antibiotics in Wastewater Using Surface-Enhanced Raman Scattering.

机构信息

Department of Civil and Environmental Engineering, University of California, Irvine, Irvine, California 92697, United States.

Department of Materials Science and Engineering, University of California, Irvine, Irvine, California 92697, United States.

出版信息

Environ Sci Technol. 2023 Mar 28;57(12):4880-4891. doi: 10.1021/acs.est.3c00027. Epub 2023 Mar 19.

Abstract

Rapid and cost-effective detection of antibiotics in wastewater and through wastewater treatment processes is an important first step in developing effective strategies for their removal. Surface-enhanced Raman scattering (SERS) has the potential for label-free, real-time sensing of antibiotic contamination in the environment. This study reports the testing of two gold nanostructures as SERS substrates for the label-free detection of quinoline, a small-molecular-weight antibiotic that is commonly found in wastewater. The results showed that the self-assembled SERS substrate was able to quantify quinoline spiked in wastewater with a lower limit of detection (LoD) of 5.01 ppb. The SERStrate (commercially available SERS substrate with gold nanopillars) had a similar sensitivity for quinoline quantification in pure water (LoD of 1.15 ppb) but did not perform well for quinoline quantification in wastewater (LoD of 97.5 ppm) due to interferences from non-target molecules in the wastewater. Models constructed based on machine learning algorithms could improve the separation and identification of quinoline Raman spectra from those of interference molecules to some degree, but the selectivity of SERS intensification was more critical to achieve the identification and quantification of the target analyte. The results of this study are a proof-of-concept for SERS applications in label-free sensing of environmental contaminants. Further research is warranted to transform the concept into a practical technology for environmental monitoring.

摘要

快速且经济有效地检测废水中的抗生素并追踪其在废水处理过程中的去向,是开发有效去除抗生素策略的重要第一步。表面增强拉曼散射(SERS)具有用于环境中抗生素污染无标记实时感应的潜力。本研究报告了两种金纳米结构作为 SERS 基底的测试结果,用于对喹啉(一种在废水中常见的小分子抗生素)进行无标记检测。结果表明,自组装 SERS 基底能够定量检测废水中的喹啉,检测下限(LoD)为 5.01 ppb。SERStrate(一种具有金纳米柱的商业 SERS 基底)对纯水中喹啉的定量具有相似的灵敏度(LoD 为 1.15 ppb),但在废水中对喹啉的定量效果不佳(LoD 为 97.5 ppm),这是由于废水中的非目标分子存在干扰。基于机器学习算法构建的模型可以在一定程度上改善喹啉拉曼光谱与干扰分子光谱的分离和识别,但 SERS 增强的选择性对于实现目标分析物的识别和定量更为关键。本研究结果为 SERS 在环境污染物无标记传感中的应用提供了概念验证。需要进一步的研究将这一概念转化为环境监测的实用技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0118/10061928/7038c2d593a8/es3c00027_0002.jpg

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