Tropp Joshua, Ihde Michael H, Crater Erin R, Bell Noel C, Bhatta Rimsha, Johnson Ian C, Bonizzoni Marco, Azoulay Jason D
Center for Optoelectronic Materials and Devices, School of Polymer Science and Engineering, The University of Southern Mississippi, 118 College Drive, Hattiesburg, Mississippi 39406, United States.
Department of Chemistry and Biochemistry, The University of Alabama, P.O. Box 870336, Tuscaloosa, Alabama 35487, United States.
ACS Sens. 2020 Jun 26;5(6):1541-1547. doi: 10.1021/acssensors.0c00342. Epub 2020 Jun 9.
Azo dyes are ubiquitous pollutants that contaminate water supplies and threaten human, biota, and ecosystem health. Their detection and discrimination are a considerable challenge owing to the numerous structural, chemical, and optical similarities between dyes, complexity of the wastewater in which they are found, and low environmental concentrations. Here, we demonstrate that the inner filter effect (IFE), in combination with conjugated polymer array-based sensing, offers a rapid approach for the quantitative profiling of these pollutants. The array was constructed using three anionic conjugated polyelectrolytes whose varying spectroscopic properties led to distinct IFE patterns in the presence of various dyes. These unique fluorescence response patterns were identified and processed using linear discriminant analysis (LDA), enabling the individual identification of 12 closely related azo dyes. To demonstrate the potential for utility in the environment, the array was used to differentiate between these dyes at nanomolar concentrations in water.
偶氮染料是普遍存在的污染物，会污染水源并威胁人类、生物群和生态系统健康。由于染料之间存在众多结构、化学和光学相似性、它们所处废水的复杂性以及环境浓度较低，对其进行检测和区分是一项巨大挑战。在此，我们证明内滤效应（IFE）与基于共轭聚合物阵列的传感相结合，为这些污染物的定量分析提供了一种快速方法。该阵列由三种阴离子共轭聚电解质构建而成，其不同的光谱特性在存在各种染料时会导致不同的IFE模式。使用线性判别分析（LDA）识别和处理这些独特的荧光响应模式，从而能够对12种密切相关的偶氮染料进行个体识别。为证明其在环境中的应用潜力，该阵列用于区分水中纳摩尔浓度的这些染料。
