Zhang Wanlin, Li Yao, Liang Yun, Gao Ning, Liu Chengcheng, Wang Shiqiang, Yin Xianpeng, Li Guangtao
Department of Chemistry , Key Laboratory of Organic Optoelectronics and Molecular Engineering , Tsinghua University , Beijing 100084 , PR China . Email:
Aerospace Research Institute of Special Material and Processing Technology , Beijing 100074 , PR China.
Chem Sci. 2019 Jun 5;10(27):6617-6623. doi: 10.1039/c9sc02266j. eCollection 2019 Jul 21.
Saccharides have strong hydrophilicities, and are complex molecular structures with subtle structure differences, and tremendous structural variations. The creation of one sensing platform capable of efficiently identifying such target systems presents a huge challenge. Using the integration of unique multiple noncovalent interactions simultaneously occurring in poly(ionic liquid)s (PILs) with multiple signaling channels, in this research an aggregation-induced emission (AIE)-doped photonic structured PIL sphere is constructed. It is found that such a sphere can serve as a highly integrated platform to provide abundant fingerprints for directly sensing numerous saccharides with an unprecedented efficiency. As a demonstration, 23 saccharides can be conveniently identified using only one sphere. More importantly, by using simple ion-exchanges of PIL receptors or/and increasing the AIE signaling channels, this platform is able to perform, on demand, different sensing tasks very efficiently. This is demonstrated by using it for the detection of difficult targets, such as greatly extended saccharides as well as mixed targets, in real-life examples on one or two spheres. The findings show that this new class of platform is very promising for addressing the challenges of identifying saccharides.
糖类具有很强的亲水性，是具有细微结构差异和巨大结构变化的复杂分子结构。创建一个能够有效识别此类目标系统的传感平台面临着巨大挑战。在本研究中，通过将聚离子液体（PILs）中同时发生的独特多重非共价相互作用与多个信号通道相结合，构建了一种聚集诱导发光（AIE）掺杂的光子结构化PIL球体。研究发现，这种球体可以作为一个高度集成的平台，以前所未有的效率为直接传感多种糖类提供丰富的指纹信息。作为一个例证，仅使用一个球体就可以方便地识别23种糖类。更重要的是，通过简单地对PIL受体进行离子交换或/和增加AIE信号通道，该平台能够按需非常高效地执行不同的传感任务。在一个或两个球体上的实际例子中，通过将其用于检测困难目标，如极大延伸的糖类以及混合目标，证明了这一点。研究结果表明，这类新型平台在应对糖类识别挑战方面非常有前景。
