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Statistical modeling and optimization of heterogeneous Fenton-like removal of organic pollutant using fibrous catalysts: a full factorial design

Abstract 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.

مدل‌سازی آماری و بهینه‌سازی حذف غیر همگن فنتون - مانند آلاینده‌های آلی با استفاده از کاتالیست های فیبری: طراحی فاکتوریل کامل

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