Xia Zhenzhen, Teng Xinghua, Cheng Yuqi, Huang Yujie, Zheng Liwen, Ji Lei, Wang Leilei
Shandong Province Key Laboratory of Applied Microbiology, Ecology Institute of Shandong Academy of Sciences, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China.
Molecules. 2024 May 8;29(10):2189. doi: 10.3390/molecules29102189.
Facile and sensitive methods for detecting neonicotinoids (NEOs) in aquatic environments are crucial because they are found in extremely low concentrations in complex matrices. Herein, nitrogen-based magnetic conjugated microporous polymers (FeO@N-CMP) with quaternary ammonium groups were synthesized for efficient magnetic solid-phase extraction (MSPE) of NEOs from tap water, rainwater, and lake water. FeO@N-CMP possessed a suitable specific surface area, extended π-conjugated system, and numerous cationic groups. These properties endow FeO@N-CMP with superior extraction efficiency toward NEOs. The excellent adsorption capacity of FeO@N-CMP toward NEOs was attributed to its π-π stacking, Lewis acid-base, and electrostatic interactions. The proposed MSPE-HPLC-DAD approach based on FeO@N-CMP exhibited a wide linear range (0.1-200 µg/L), low detection limits (0.3-0.5 µg/L), satisfactory precision, and acceptable reproducibility under optimal conditions. In addition, the established method was effectively utilized for the analysis of NEOs in tap water, rainwater, and lake water. Excellent recoveries of NEOs at three spiked levels were in the range of 70.4 to 122.7%, with RSDs less than 10%. This study provides a reliable pretreatment method for monitoring NEOs in environmental water samples.
由于新烟碱类物质(NEOs)在复杂基质中的浓度极低,因此开发简便灵敏的方法来检测水环境中的新烟碱类物质至关重要。在此,合成了带有季铵基团的氮基磁性共轭微孔聚合物(FeO@N-CMP),用于从自来水、雨水和湖水中高效磁固相萃取(MSPE)新烟碱类物质。FeO@N-CMP具有合适的比表面积、扩展的π共轭体系和众多阳离子基团。这些特性赋予FeO@N-CMP对新烟碱类物质卓越的萃取效率。FeO@N-CMP对新烟碱类物质的优异吸附能力归因于其π-π堆积、路易斯酸碱和静电相互作用。基于FeO@N-CMP所提出的MSPE-HPLC-DAD方法在最佳条件下呈现出宽线性范围(0.1-200μg/L)、低检测限(0.3-0.5μg/L)、令人满意的精密度和可接受的重现性。此外,所建立的方法有效地用于分析自来水、雨水和湖水中的新烟碱类物质。在三个加标水平下新烟碱类物质的回收率极佳,范围为70.4%至122.7%,相对标准偏差小于10%。本研究为监测环境水样中的新烟碱类物质提供了一种可靠的预处理方法。