A statistical modeling-optimization approach for efficiency photocatalytic degradation of textile azo dye using cerium-doped mesoporous ZnO: A central composite design in response surface methodology

Abstract

This paper investigates a new modeling approach of central composite design (CCD) in Response Surface methodology (RSM) for the optimization of methyl orange (MO) photodegradation based to the prepared materials under UV–vis irradiation. Mesoporous zinc oxide (ZnO) have been synthesized at different cerium (Ce) contents (2, 5 and 7wt%) through a single step sol gel method. Subsequently, cerium nanoparticles (CeNPs) have been impregnated on mesoporous ZnO. The physico-chemical characteristics of each catalyst are described through several approaches. The photocatalytic activity of the prepared catalysts shows that CeNPs enhance the photocatalytic performance of ZnO at 2wt% Ce content. MO photodergadation processes of the optimal catalyst can be mathematically described as a function of pH-solution, catalyst dosage and MO concentration being modeled by a CCD-RSM.Based on a statistical modeling (quadratic regression) and an optimization process (ANOVA analysis), the optimum conditions were achieved for pH of solution of 5.58, MO concentration of 20.72mgL−1and catalyst dosage of 0.63gL−1 which allowed reaching 100% of photodegradation. Overall, the value of the adjusted coefficient of determination (R2=0.9901) indicates that the considered model was quite suitable and that the selected CCD-RSM was successful in optimizing the photodegradation conditions of MO.