A smartphone-based colorimetric reader coupled with a remote server for rapid on-site catechols analysis

IF 8.3 2区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY ACS Applied Materials & Interfaces Pub Date : 2016-11-01 DOI:10.1016/j.talanta.2016.07.012
Yun Wang , Yuanyuan Li , Xu Bao , Juan Han , Jinchen Xia , Xiaoyu Tian , Liang Ni
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引用次数: 43

Abstract

The search of a practical method to analyze cis-diol-containing compounds outside laboratory settings remains a substantial scientific challenge. Herein, a smartphone-based colorimetric reader was coupled with a remote server for rapid on-site analysis of catechols. A smallest-scale 2×2 colorimetric sensor array composed of pH indicators and phenylboronic acid was configured. The array was able to distinguish 13 catechols at 6 serial concentrations, through simultaneous treatment via principal component analysis, hierarchical cluster analysis, and linear discriminant analysis. After both the discriminatory power of the array and the prediction ability of the partial least squares quantitative models were proved to be predominant, the smartphone was coupled to the remote server. All the ΔRGB data were uploaded to the remote server wherein linear discriminant analysis and partial least squares processing modules were established to provide qualitative discrimination and quantitative calculation, respectively, of the analytes in real time. The applicability of this novel method to a real-life scenario was confirmed by the on-site analysis of various catechols from a water sample of the Yangtze River; the feedback result in the smartphone showed the method was able to identify the catechols with 100% accuracy and predict the concentrations to within 0.706–2.240 standard deviation.

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基于智能手机的比色阅读器与远程服务器相结合,用于快速现场儿茶酚分析
在实验室之外寻找一种分析含顺式二醇化合物的实用方法仍然是一项重大的科学挑战。在这里,基于智能手机的比色阅读器与远程服务器相结合,用于快速现场分析儿茶酚。配置了由pH指示剂和苯硼酸组成的小型2×2比色传感器阵列。通过主成分分析、层次聚类分析和线性判别分析的同时处理,该阵列能够区分6个系列浓度下的13种儿茶酚。在证明阵列的分辨能力和偏最小二乘定量模型的预测能力都占主导地位后,将智能手机与远程服务器耦合。将所有ΔRGB数据上传到远程服务器,建立线性判别分析和偏最小二乘处理模块,分别实时对分析物进行定性判别和定量计算。通过对长江水样中各种儿茶酚的现场分析,证实了这种新方法在现实生活中的适用性;智能手机上的反馈结果表明,该方法能够100%准确地识别儿茶酚,并预测浓度在0.706-2.240标准差范围内。
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来源期刊
ACS Applied Materials & Interfaces
ACS Applied Materials & Interfaces 工程技术-材料科学:综合
CiteScore
16.00
自引率
6.30%
发文量
4978
审稿时长
1.8 months
期刊介绍: ACS Applied Materials & Interfaces is a leading interdisciplinary journal that brings together chemists, engineers, physicists, and biologists to explore the development and utilization of newly-discovered materials and interfacial processes for specific applications. Our journal has experienced remarkable growth since its establishment in 2009, both in terms of the number of articles published and the impact of the research showcased. We are proud to foster a truly global community, with the majority of published articles originating from outside the United States, reflecting the rapid growth of applied research worldwide.
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