Tropp Joshua, Ihde Michael H, Williams Abagail K, White Nicholas J, Eedugurala Naresh, Bell Noel C, Azoulay Jason D, Bonizzoni Marco
Center for Optoelectronic Materials and Devices , School of Polymer Science and Engineering , The University of Southern Mississippi , 118 College Drive #5050 , Hattiesburg , MS 39406 , USA . Email:
Department of Chemistry and Biochemistry , The University of Alabama , P.O. Box 870336 , Tuscaloosa , AL 35487 , USA . Email:
Chem Sci. 2019 Oct 7;10(44):10247-10255. doi: 10.1039/c9sc03405f. eCollection 2019 Nov 28.
Natural and anthropogenic activities result in the production of polycyclic aromatic hydrocarbons (PAHs), persistent pollutants that negatively impact the environment and human health. Rapid and reliable methods for the detection and discrimination of these compounds remains a technological challenge owing to their relatively featureless properties, structural similarities, and existence as complex mixtures. Here, we demonstrate that the inner filter effect (IFE), in combination with conjugated polymer (CP) array-based sensing, offers a straightforward approach for the quantitative and qualitative profiling of PAHs. The sensor array was constructed from six fluorescent fluorene-based copolymers, which incorporate side chains with peripheral 2-phenylbenzimidazole substituents that provide spectral overlap with PAHs and give rise to a pronounced IFE. Subtle structural differences in copolymer structure result in distinct spectral signatures, which provide a unique "chemical fingerprint" for each PAH. The discriminatory power of the array was evaluated using linear discriminant analysis (LDA) and principal component analysis (PCA) in order to discriminate between 16 PAH compounds identified as priority pollutants by the US Environmental Protection Agency (EPA). This array is the first multivariate system reliant on the modulation of the spectral signatures of CPs through the IFE for the detection and discrimination of closely related polynuclear aromatic species.
自然活动和人为活动都会导致多环芳烃（PAHs）的产生，这些持久性污染物会对环境和人类健康产生负面影响。由于这些化合物相对缺乏特征、结构相似且以复杂混合物形式存在，因此快速可靠地检测和区分它们的方法仍然是一项技术挑战。在此，我们证明内滤效应（IFE）与基于共轭聚合物（CP）阵列的传感相结合，为PAHs的定量和定性分析提供了一种直接的方法。该传感器阵列由六种基于芴的荧光共聚物构建而成，这些共聚物含有带有外围2-苯基苯并咪唑取代基的侧链，这些取代基与PAHs产生光谱重叠并引起明显的内滤效应。共聚物结构中的细微结构差异导致不同的光谱特征，为每种PAH提供了独特的“化学指纹”。使用线性判别分析（LDA）和主成分分析（PCA）评估该阵列的辨别能力，以区分美国环境保护局（EPA）确定为优先污染物的16种PAH化合物。该阵列是首个依赖通过内滤效应调节CP光谱特征来检测和区分密切相关的多核芳烃物种的多变量系统。
