Zhang Yang, Li Yanhui, Wang Mingzhen, Chen Bing, Sun Yaohui, Chen Kewei, Du Qiujv, Pi Xinxin, Wang Yuqi
College of Mechanical and Electrical Engineering, Qingdao University, 308 Ningxia Road, Qingdao 266071, China.
Laboratory of Fiber Materials and Modern Textile, The Growing Base for State Key Laboratory, Qingdao University, 308 Ningxia Road, Qingdao 266071, China.
Nanomaterials (Basel). 2022 Jul 23;12(15):2533. doi: 10.3390/nano12152533.
A novel gelatin-based functionalized carbon nanotubes@metal-organic framework (F-CNTs@MOF@Gel) adsorbent was prepared by the green and simple method for the adsorption of methylene blue (MB). Cu-BTC (also known as HKUST-1) was selected as the MOF type. F-CNTs@Cu-BTC particles were fixed by gelatin, thus avoiding the secondary pollution of carbon nanomaterial particles to the environment. CNTs were used as the connecting skeleton to make more effective adsorption sites exposed on the surface of the internal pore structure of the adsorbent. In this paper, scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), powder X-ray diffraction (XRD), thermogravimetry (TGA) and BET analysis methods were used to characterize the new adsorbent. The effects of time, temperature, pH, dosage and initial concentration on the adsorption process were investigated by batch adsorption experiments. The adsorption mechanism was further analyzed by several commonly used kinetic and isotherm models, and the reliability of several fitting models was evaluated by the Akaike information criterion (AIC), Bayesian information criterion (BIC) and Hannan information criterion (HIC). After five regeneration experiments, the adsorbent still had 61.23% adsorption capacity. In general, the new adsorbent studied in this paper has an optimistic application prospect.
通过绿色简便的方法制备了一种新型的基于明胶的功能化碳纳米管@金属有机框架(F-CNTs@MOF@Gel)吸附剂,用于吸附亚甲基蓝(MB)。选择Cu-BTC(也称为HKUST-1)作为MOF类型。F-CNTs@Cu-BTC颗粒通过明胶固定,从而避免了碳纳米材料颗粒对环境的二次污染。碳纳米管用作连接骨架,使更多有效的吸附位点暴露在吸附剂内部孔结构的表面。本文采用扫描电子显微镜(SEM)、傅里叶变换红外光谱(FTIR)、粉末X射线衍射(XRD)、热重分析(TGA)和BET分析方法对新型吸附剂进行了表征。通过批量吸附实验研究了时间、温度、pH值、剂量和初始浓度对吸附过程的影响。采用几种常用的动力学和等温线模型进一步分析了吸附机理,并通过赤池信息准则(AIC)、贝叶斯信息准则(BIC)和汉南信息准则(HIC)对几种拟合模型的可靠性进行了评估。经过五次再生实验后,吸附剂仍具有61.23%的吸附容量。总体而言,本文研究的新型吸附剂具有乐观的应用前景。