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A mobile laboratory for rapid on-site analysis of catechols from water samples with real-time results production

机译:具有实时效果生产的水样的快速现场分析的移动实验室

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摘要

The search for a practical method to analyze cis-diol-containing compounds outside laboratory settings remains a substantially scientific challenge. Herein, we used a "mobile laboratory", wherein a filter paper-based colorimetric sensor array, a smartphone, and a remote server were combined together, for rapid on-site analysis of catechols from water samples with real-time results production. A smallest-scale filter paper-based 2 x 2 colorimetric sensor array composed of pH indicators and phenylboronic acid was configured. The array was able to distinguish 7 water-soluble catechols at 7 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 proven to be predominant, the smartphone was coupled to the remote server. All the Delta RGB 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 that the method was able to identify catechols with 100% accuracy and predict the concentrations to within 0.484-4.08 standard deviation.
机译:寻找分析实验室环境外的CIS-DIOL的化合物的实际方法仍然是一个基本上科学的挑战。这里,我们使用了一个“移动实验室”,其中基于滤纸的比色传感器阵列,智能手机和远程服务器组合在一起,用于快速现场分析来自水样的儿茶素与实时结果产生。构造了一种最小的滤纸基于基于pH指示剂和苯基硼酸的比色传感器阵列。该阵列能够通过主成分分析,分层聚类分析和线性判别分析通过同时处理将7个水溶性儿茶酚解物区分7个序列浓度。经过证明阵列的判别权力和局部最小二乘定量模型的预测能力,被证明是主要的,智能手机耦合到远程服务器。所有Delta RGB数据都上载到远程服务器,其中建立了线性判别分析和部分最小二乘处理模块,以实时分析分析物的定性辨别和定量计算。通过来自长江水样的各种儿茶酚对各种儿茶酚的现场分析证实了这种新方法对现实情况的适用性;智能手机的反馈结果表明,该方法能够识别100%精度的儿茶酚,并将浓度预测到0.484-4.08的标准偏差范围内。

著录项

  • 来源
    《RSC Advances》 |2016年第84期|共11页
  • 作者单位

    Jiangsu Univ Sch Chem &

    Chem Engn Zhenjiang 212013 Peoples R China;

    Jiangsu Univ Sch Chem &

    Chem Engn Zhenjiang 212013 Peoples R China;

    Jiangsu Univ Sch Chem &

    Chem Engn Zhenjiang 212013 Peoples R China;

    Jiangsu Univ Sch Food &

    Biol Engn Zhenjiang 212013 Peoples R China;

    Jiangsu Univ Sch Chem &

    Chem Engn Zhenjiang 212013 Peoples R China;

    Jiangsu Univ Sch Comp &

    Commun Engn Zhenjiang 212013 Peoples R China;

    Jiangsu Univ Sch Chem &

    Chem Engn Zhenjiang 212013 Peoples R China;

    Jiangsu Univ Sch Chem &

    Chem Engn Zhenjiang 212013 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 化学;
  • 关键词

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