利用藻类衍生多孔碳去除选定药物：实验、建模及密度泛函理论见解

Selected pharmaceuticals removal using algae derived porous carbon: experimental, modeling and DFT theoretical insights.

作者信息

Ouasfi N, Zbair M, Bouzikri S, Anfar Z, Bensitel M, Ait Ahsaine H, Sabbar E, Khamliche L

机构信息

Laboratory of Organic Chemistry, Bioorganic and Environment, Chemistry Department, Faculty of Science, University Chouaib Doukkali El Jadida Morocco

Laboratory of Physico-Chemistry of Materials (LPCM), ChemistryDepartment, Faculty of Sciences, University of Chouaïb Doukkali El Jadida Morocco.

出版信息

RSC Adv. 2019 Mar 28;9(17):9792-9808. doi: 10.1039/c9ra01086f. eCollection 2019 Mar 22.

Porous carbon from algae activated using NaOH (PCLD@NaOH) was prepared by a chemical activation approach and has been tested for the adsorption of ketoprofen and aspirin molecules. The prepared PCLD@NaOH was characterized using XPS, FTIR, Raman, N-physisorption, SEM, acidic/basic character (Boehm), and pH. The batch adsorption of ketoprofen and aspirin was investigated under different parameters. The adsorption kinetics on PCLD@NaOH were well described by the Avrami-fractional kinetic model and the equilibrium data by Liu isotherm model. The adsorption capacity of aspirin (970.88 mg g at 25 °C) was higher than ketoprofen (443.45 mg g at 25 °C). The thermodynamic values indicate that the adsorption of ketoprofen and aspirin is exothermic and spontaneous. These results were in good agreement with DFT calculation that shows that the aspirin molecule presents high reactivity, electrophilicity, and softness compared to the ketoprofen molecule. Finally, the response surface methodology was used to optimize the removal efficiency of ketoprofen and aspirin.

采用化学活化法制备了经氢氧化钠活化的藻类多孔碳（PCLD@NaOH），并对其吸附酮洛芬和阿司匹林分子的性能进行了测试。采用XPS、FTIR、拉曼光谱、N-物理吸附、SEM、酸碱性质（Boehm法）和pH值对制备的PCLD@NaOH进行了表征。研究了不同参数下酮洛芬和阿司匹林的间歇吸附情况。Avrami分数动力学模型很好地描述了PCLD@NaOH上的吸附动力学，Liu等温线模型很好地描述了平衡数据。阿司匹林在25℃时的吸附容量（970.88 mg/g）高于酮洛芬在25℃时的吸附容量（443.45 mg/g）。热力学值表明酮洛芬和阿司匹林的吸附是放热且自发的。这些结果与DFT计算结果高度一致，DFT计算表明阿司匹林分子与酮洛芬分子相比具有更高的反应活性、亲电性和柔软性。最后，采用响应面法优化了酮洛芬和阿司匹林的去除效率。