Synthesis of silver nanoparticles on polyacrylonitrile nonwoven substrates with the silver mirror reaction for effective SERS detection of 4-MBA and glucose†

IF 2.6 3区 化学 Q2 CHEMISTRY, ANALYTICAL
Viktoriia Bakal, Olga Gusliakova, Anastasia Kartashova, Mariia Saveleva, Valentina Plastun, Polina Demina, Ilya Kozhevnikov, Alexey Serdobintsev and Ekaterina Prikhozhdenko
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Abstract

We present a simple, fast, and efficient method for the production of silver nanoparticles (AgNP) for surface-enhanced Raman spectroscopy (SERS) applications. The method utilizes the classical silver mirror reaction, with ascorbic acid serving as the reducing agent, to produce AgNP on polyacrylonitrile non-woven substrates. Different protocols were used to functionalize the substrates with AgNP in situ. Optimization of the substrate modification procedure led to SERS-substrates with an enhancement factor (EF) of up to 106 (4-MBA detection) for samples treated with 1 M solutions of AgNO3 and NH3·H2O. The obtained substrates were further modified with glucose oxidase (GOx), and glucose sensing was carried out in a concentration range from 0.5 mM to 10 mM. Machine learning models, such as random forest and gradient boosting, were used for the analysis of Raman data. The resulting substrates have potential applications in various fields of analytical chemistry.

Abstract Image

用银镜像反应在聚丙烯腈无纺布基底上合成银纳米颗粒,用于4-MBA和葡萄糖的有效SERS检测。
我们提出了一种简单、快速、高效的方法来生产用于表面增强拉曼光谱(SERS)应用的银纳米颗粒(AgNP)。该方法采用经典的银镜像反应,以抗坏血酸为还原剂,在聚丙烯腈无纺布基材上制备AgNP。采用不同的方案,用AgNP原位功能化底物。通过优化底物修饰工艺,在1 M AgNO3和NH3·H2O溶液处理的样品中,sers底物的增强因子(EF)高达106 (4-MBA检测)。得到的底物进一步用葡萄糖氧化酶(GOx)修饰,并在0.5 mM至10 mM的浓度范围内进行葡萄糖传感。随机森林和梯度增强等机器学习模型用于拉曼数据分析。所得底物在分析化学的各个领域具有潜在的应用前景。
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来源期刊
Analytical Methods
Analytical Methods CHEMISTRY, ANALYTICAL-FOOD SCIENCE & TECHNOLOGY
CiteScore
5.10
自引率
3.20%
发文量
569
审稿时长
1.8 months
期刊介绍: Early applied demonstrations of new analytical methods with clear societal impact
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