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Statistical modeling and optimization of heterogeneous Fenton-like removal of organic pollutant using fibrous catalysts: a full factorial design
Scientific Reports ( IF 3.8 ) Pub Date : 2020-09-30 , DOI: 10.1038/s41598-020-72401-z
Mohammad Neaz Morshed 1, 2, 3, 4 , Md Nahid Pervez 5 , Nemeshwaree Behary 2, 3 , Nabil Bouazizi 2 , Jinping Guan 4 , Vincent A Nierstrasz 1
Affiliation  

This work focuses on the optimization of heterogeneous Fenton-like removal of organic pollutant (dye) from water using newly developed fibrous catalysts based on a full factorial experimental design. This study aims to approximate the feasibility of heterogeneous Fenton-like removal process and optionally make predictions from this approximation in a form of statistical modeling. The fibrous catalysts were prepared by dispersing zerovalent iron nanoparticles on polyester fabrics (PET) before and after incorporation of either polyamidoamine (PAMAM, –NH2) dendrimer, 3-(aminopropyl) triethoxysilane (APTES, –Si–NH2) or thioglycerol (SH). The individual effect of two main factors [pH (X1) and concentration of hydrogen peroxide-[H2O2]μl (X2)] and their interactional effects on the removal process was determined at 95% confidence level by an L27 design. The results indicated that increasing the pH over 5 decreases the dye removal efficiency whereas the rise in [H2O2]μl until equilibrium point increases it. The principal effect of the type of catalysts (PET–NH2–Fe, PET–Si–NH2–Fe, and PET–SH–Fe) did not show any statistical significance. The factorial experiments demonstrated the existence of a significant synergistic interaction effect between the pH and [H2O2]μl as expressed by the values of the coefficient of interactions and analysis of variance (ANOVA). Finally, the functionalization of the resultant fibrous catalysts was validated by electrokinetic and X-ray photoelectron spectroscopy analysis. The optimization made from this study are of great importance for rational design and scaling up of fibrous catalyst for green chemistry and environmental applications.



中文翻译:


使用纤维催化剂异质类芬顿去除有机污染物的统计建模和优化:全析因设计



这项工作的重点是基于全析因实验设计,使用新开发的纤维催化剂优化多相类芬顿去除水中的有机污染物(染料)。本研究旨在近似非均质类芬顿去除过程的可行性,并可选择以统计模型的形式根据该近似值进行预测。纤维催化剂是通过在掺入聚酰胺胺(PAMAM,–NH 2 )树枝状聚合物、3-(氨丙基)三乙氧基硅烷(APTES,–Si–NH 2 )或硫代甘油( SH)。通过 L 27设计以 95% 的置信水平确定两个主要因素 [pH (X1) 和过氧化氢浓度 - [H 2 O 2 ] μl (X2)] 的单独影响及其对去除过程的相互作用影响。结果表明,增加pH值超过5会降低染料去除效率,而增加[H 2 O 2 ] μl直到平衡点会增加染料去除效率。催化剂类型(PET-NH 2 -Fe、PET-Si-NH 2 -Fe 和 PET-SH-Fe)的主效应没有表现出任何统计显着性。析因实验表明,pH 和 [H 2 O 2 ] μl之间存在显着的协同相互作用效应,如相互作用系数和方差分析 (ANOVA) 的值所表示的。最后,通过电动和X射线光电子能谱分析验证了所得纤维催化剂的功能化。 这项研究的优化对于绿色化学和环境应用的纤维催化剂的合理设计和放大具有重要意义。

更新日期:2020-09-30
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