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基于聚芳基乙炔的微流控荧光传感器阵列用于多环芳烃的区分。

A poly(arylene ethynylene)-based microfluidic fluorescence sensor array for discrimination of polycyclic aromatic hydrocarbons.

机构信息

Department of Chemistry, Shiraz University, 719468 Shiraz, Iran.

Organisch-Chemisches Institut, Ruprecht-Karls-Universität Heidelberg, Im Neuenheimer Feld, 69120, Heidelberg, Germany.

出版信息

Analyst. 2022 Sep 26;147(19):4266-4274. doi: 10.1039/d2an01045c.

Abstract

Polycyclic aromatic hydrocarbons (PAHs) are persistent contaminants in the environment. Several of them have carcinogenic properties. There is considerable interest in their sensitive low-cost detection and monitoring. We present a simple paper-based microfluidic sensor for the rapid detection of PAHs. Craft punch patterning generated multiple detection zones inhabited by fluorescent poly(arylene ethynylene)s (PAEs). Changes in fluorescence image and/or intensity of the sensor array were recorded using a smartphone camera. The RGB color values of the photographed images were extracted through ImageJ software. 10 different PAHs were correctly identified using Principal Component Analysis and discrimination analysis (PCA-DA). 100% classification accuracy was achieved for model training, whereas validating the PCA-DA model by cross-validation resulted in 93% classification accuracy for 5.0 mg L analyte.

摘要

多环芳烃(PAHs)是环境中持久性的污染物。其中一些具有致癌性。人们对其进行灵敏、低成本的检测和监测非常感兴趣。我们提出了一种简单的基于纸张的微流控传感器,用于快速检测 PAHs。手工冲压图案生成了多个荧光多芳基乙炔聚合物(PAEs)占据的检测区域。使用智能手机相机记录传感器阵列的荧光图像和/或强度变化。通过 ImageJ 软件提取拍摄图像的 RGB 颜色值。使用主成分分析和判别分析(PCA-DA)正确识别了 10 种不同的 PAHs。通过交叉验证验证 PCA-DA 模型时,对于 5.0mg L 的分析物,分类准确率达到 100%。

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