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新型磁性胺功能化碳纳米管/金属有机骨架纳米复合材料:从绿色超声辅助合成到二元体系中详细的选择性污染物去除模拟。

Novel magnetic amine functionalized carbon nanotube/metal-organic framework nanocomposites: From green ultrasound-assisted synthesis to detailed selective pollutant removal modelling from binary systems.

机构信息

Department of Environmental Research, Institute for Color Science and Technology, Tehran, Iran.

Department of Environmental Research, Institute for Color Science and Technology, Tehran, Iran.

出版信息

J Hazard Mater. 2019 Apr 15;368:746-759. doi: 10.1016/j.jhazmat.2019.01.107. Epub 2019 Jan 31.

Abstract

Herein, magnetic amine functionalized carbon nanotube (NH-CNT/FeO)-zeolitic imidazolate framework-8 (ZIF-8) nanocomposites (NH-CNT/FeO/ZIF-8: NCFZ) with different amounts of NH-CNT/FeO (5, 10, and 15 wt% denoted as NCFZ-5, NCFZ-10, and NCFZ-15) were synthesized. The synthesized nanomaterials including ZIF-8, FeO, CNT/FeO, NH-CNT/FeO, CNT/FeO/ZIF-8, NCFZ-5, NCFZ-10, and NCFZ-15 were characterized using BET, TEM, XRD, SEM, FTIR, VSM and zeta potential. The synthesized nanomaterials were applied for selective removing cationic dyes (MG: Malachite Green and RhB: Rhodamine B) from a binary system. Response surface methodology (RSM) and artificial neural networks (ANN) were used for optimizing dye removal. The BET data showed that the surface area of nanocomposite (NH-CNT/FeO/ZIF-8: 1659 m/g) was higher than that of pure ZIF-8 (1485 m/g). Contaminant removal obeyed the Freundlich isotherm and pseudo-second order kinetic models. The optimum adsorption condition predicted by RSM was pH = 6, dye concentration = 25 mg/L, Dosage = 0.004 g and at time = 145 min. The outputs of ANN model well overlapped with the experimental data. The binary system dye removal data indicated the synthesized nanocomposite with recycling and regeneration ability could be used for treating wastewater.

摘要

在此,合成了不同比例的磁性胺功能化碳纳米管(NH-CNT/FeO)-沸石咪唑酯骨架-8(ZIF-8)纳米复合材料(NH-CNT/FeO/ZIF-8:NCFZ),其中 NH-CNT/FeO 的含量分别为 5、10 和 15wt%(分别表示为 NCFZ-5、NCFZ-10 和 NCFZ-15)。采用 BET、TEM、XRD、SEM、FTIR、VSM 和 ζ 电位对合成的纳米材料进行了表征。将合成的纳米材料应用于从二元体系中选择性去除阳离子染料(MG:孔雀石绿和 RhB:罗丹明 B)。采用响应面法(RSM)和人工神经网络(ANN)对染料去除进行了优化。BET 数据表明,纳米复合材料(NH-CNT/FeO/ZIF-8:1659m/g)的比表面积高于纯 ZIF-8(1485m/g)。污染物去除符合 Freundlich 等温线和准二级动力学模型。RSM 预测的最佳吸附条件为 pH=6、染料浓度=25mg/L、剂量=0.004g 和时间=145min。ANN 模型的输出与实验数据很好地重叠。二元体系染料去除数据表明,具有回收和再生能力的合成纳米复合材料可用于处理废水。

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