Statistical Optimization and Modeling Approach for Fenton-like Discoloration of Methyl Orange using Green Zero-valent Iron Nanoparticle Catalysts

Abstract

Wastewater treatment is extremely beneficial to the environment by minimizing pollution. Water pollution caused by textile industries deteriorates ecosystems and threatens the environment. In this study, we fabricated nanoscale zerovalent iron nanoparticle (NZVI-NPs) catalysts that act as Fenton-like adsorbents, which remove methyl orange (MO) dye from wastewater much faster than microscale nanoparticles. The analysis of variance (ANOVA) led us to derive a quadratic model with R2=0.973. According to the central composite design in response surface methodology (CCD-RSM) statistical optimization, 99.65 % of predicted decolorization was achieved with 1.0 g/L catalyst loading, pH initialization of 3.0, reaction temperature of 25 °C, and 22 mmol/L H2O2 concentration. By fitting a pseudo-second-order kinetic model, we calculated the rate constant of dye adsorption. The Langmuir isotherm demonstrated an excellent correlation between dye adsorption and catalyst with a maximum adsorption capacity (50.45 mg/g). The activation energy of the catalyst (62.26 kJ/mol) predicts a physical adsorption process. Newly developed catalysts are green efficient adsorbents suitable for significant dye removal from wastewater for the safety of aquatic life and human life. Moreover, these newly developed materials could be more suitable for the remediation of other harmful pollutants and the production of hydrogen, energy and water splitting applications.