详细信息
Conjugated Polymer Nanoparticles Based Fluorescent Electronic Nose for the Identification of Volatile Compounds ( SCI-EXPANDED收录 EI收录)
文献类型:期刊文献
英文题名:Conjugated Polymer Nanoparticles Based Fluorescent Electronic Nose for the Identification of Volatile Compounds
作者:Zhao, Peng[1];Wu, Yusen[1];Feng, Chuying[1];Wang, Lili[1];Ding, Yun[1];Hu, Aiguo[1]
机构:[1]East China Univ Sci & Technol, Shanghai Key Lab Adv Polymer Mat, Sch Mat Sci & Engn, Shanghai 200237, Peoples R China
年份:2018
卷号:90
期号:7
起止页码:4815
外文期刊名:ANALYTICAL CHEMISTRY
收录:;EI(收录号:20181504996152);WOS:【SCI-EXPANDED(收录号:WOS:000429385800079)】;
基金:Dedicated to Prof. Ji-tao Wang on the occasion of his 100th birthday. The authors gratefully acknowledge the financial support from National Natural Science Foundation of China (21674035) and Shanghai Leading Academic Discipline Project (B502). A.H. thanks the "Eastern Scholar Professorship" support from Shanghai local government.
语种:英文
外文关键词:Chemical analysis - Conjugated polymers - Colorimetry - Electronic structure - Nanoparticles - Quenching - Volatile organic compounds - Amines - Electronic nose - Indicators (chemical) - Principal component analysis
摘要:A fluorescence sensing array (or fluorescent electronic nose) is designed on a disposable paper card using 36 sets of soluble conjugated polymeric nanoparticles (SCPNs) as sensors to easily identify wide ranges of volatile analytes, including explosives and toxic industrial chemicals (amines and pungent acids). A 108-dimensional vector obtained from the fluorescent color change in the sensing array is defined and directly treated as an index in a standard chemical library (30 kinds of volatile analytes and a control group). Hierarchical clustering analysis (HCA) and principal component analysis (PCA) indicated the diversity in electronic structures; saturated vapor pressure and miscibility of analytes are keys in differentiating the analytes, with electron-rich arenes and alkylamines enhancing fluorescence and electrondeficient analytes attenuating fluorescence. A support vector machine (SVM) works well to predict an unknown sample, reaching 99.5% accuracy. The excellent fluorescence stability (no fluorescence quenching after being exposed in air for one month) and high sensitivity (emission color changes within minutes when exposed to analytes) suggest that the fluorescent polymer-based electronic nose will play an important role in field detection and identification of a wide spreading of hazardous substances.
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