Construction of a TiO2-Fe3O4-decorated molecularly imprinted polymer nanocomposite for tartrazine degradation: Response surface methodology modeling and optimization

被引:13
作者
Arabzadeh, Naghmeh [1 ]
Mohammadi, Ali [1 ,2 ,3 ]
Darwish, Maher [2 ,4 ]
Abuzerr, Samer [5 ]
机构
[1] Univ Tehran Med Sci, Fac Pharm, Dept Drug & Food Control, Tehran, Iran
[2] Univ Tehran Med Sci, Fac Pharm, Pharmaceut Qual Assurance Res Ctr, Int Campus, Tehran, Iran
[3] Univ Tehran Med Sci, Fac Pharm, Nanotechnol Res Ctr, POB 14155-6451, Tehran, Iran
[4] Al Safwa Univ Coll, Dept Pharm, Karbala, Iraq
[5] Univ Tehran Med Sci, Fac Publ Hlth, Dept Environm Hlth Engn, Int Campus, Tehran, Iran
关键词
molecularly imprinted polymer; nanocomposite; response surface methodology; tartrazine; PHOTOCATALYTIC DEGRADATION; SELECTIVE EXTRACTION; METHYLENE-BLUE; NANOPARTICLES; REMOVAL; PHOTODEGRADATION; ADSORPTION; COMPOSITE; MECHANISM; KINETICS;
D O I
10.1002/jccs.201800302
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
We synthesized a novel recoverable and reusable photocatalyst system for tartrazine degradation by one-step incorporation of Fe3O4 and TiO2 nanoparticles into a molecularly imprinted polymer through a facile precipitation polymerization method. The as-prepared samples were systematically characterized using X-ray diffraction, infrared spectroscopy, scanning electron microscopy, transmission electron microscopy, energy-dispersive spectroscopy, and vibrating sample magnetometry. Benefiting from the positive synergistic effect, tartrazine was almost completely degraded under UV-C within 180min by the multicomponent photocatalyst (Fe3O4 +TiO2 +MIP) in comparison with far fewer activities by the corresponding NIP system and the nonmagnetic and bare structures. On the other hand, the central composite design in response surface methodology was applied to optimize the tartrazine photocatalytic degradation process. Twenty experiments were conducted by adjusting three parameters (nanocomposite dosage, initial pH of the reaction solution, and initial dye concentration) in the multiple variable analysis method. A satisfactory correlation between the experimental and predicted values was obtained (R-2 = 0.956). Additionally, ANOVA analysis with a p value of 1.15x 10(-5) indicated that the model terms are highly significant. Under the determined optimum conditions, a verification experiment was conducted and shown the adequately approximate value between the predicted (99%) and the experimental (97%) results, which confirmed the validity of the model.
引用
收藏
页码:474 / 483
页数:10
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