吸附
共价有机骨架
共价键
化学
化学工程
朗缪尔吸附模型
结晶度
热稳定性
氢键
复合数
材料科学
有机化学
分子
复合材料
结晶学
工程类
作者
Yulian Yang,Qiuyi Liu,Yuemeng Zou,Meng Tian,Luchun Wang,Lingling Li,Mingyue Wang,Yongqing Tao,Junji Wang,Zeng Wen,Famin Ke,Dandan Wang,Die Gao
标识
DOI:10.1016/j.jece.2023.110975
摘要
Widespread use of fluoroquinolones (FQs) leads to its continuous excretion and release into the environment, resulting in the accumulation in water, animal-derived food etc., and posing a threat to environment and humans. Thus, the development of highly efficient FQs removal methods is of great significance. Herein, a composite (COF@MXene) was manufactured using a covalent assembly synthesis strategy by connecting covalent organic frameworks (COF) and NH2-MXene through a Schiff-base reaction. COF@MXene had the advantages of both COF and MXene, not only had good crystallinity, thermal stability and rich functional group properties, but also had high protein exclusion ability (Exclusion efficiency>97%) and good adsorption capacities for FQs including ciprofloxacin (CIP), lomefloxacin (LOM), moxifloxacin (MOX), gatifloxacin (GAT) and levofloxacin (LEV). The maximal adsorption capacities for them ranged from 54.63 to 147.91 mg·g−1, which were higher than those of COF (15.99–64.06 mg·g−1) and MXene (27.58–33.92 mg·g−1). The adsorption experimental data of adsorption isotherm and kinetics separately followed the Langmuir and pseudo-second-order models. Through density functional theory (DFT), Forcite calculation, UV-Vis and XPS analyses, pore size selectivity, electrostatic and hydrogen bond interactions were determined as the main driving forces for FQs adsorption. Finally, COF@MXene coupled with HPLC-DAD was employed for the analysis of FQs from water, egg and drug samples, and the recoveries were satisfactory. This work reported a covalent assembly synthesis strategy for the preparation of COF@MXene composite for FQs removal. This approach may establish a viable route for gentle fabrication of COF and MXene based composites for various applications.
科研通智能强力驱动
Strongly Powered by AbleSci AI