Optimization of the photocatalytic degradation of phenol using superparamagnetic iron oxide (Fe3O4) nanoparticles in aqueous solutions

Abstract

The present work was carried out to remove phenol from aqueous medium using a photocatalytic process with superparamagnetic iron oxide nanoparticles (Fe₃O₄) called SPIONs. The photocatalytic process was optimized using a central composite design based on the response surface methodology. The effects of pH (3–7), UV/SPION nanoparticles ratio (1–3), contact time (30–90 minutes), and initial phenol concentration (20–80 mg L⁻¹) on the photocatalytic process were investigated. The interaction of the process parameters and their optimal conditions were determined using CCD. The statistical data were analyzed using a one-way analysis of variance. We developed a quadratic model using a central composite design to indicate the photocatalyst impact on the decomposition of phenol. There was a close similarity between the empirical values gained for the phenol content and the predicted response values. Considering the design, optimum values of pH, phenol concentration, UV/SPION ratio, and contact time were determined to be 3, 80 mg L⁻¹, 3, and 60 min, respectively; 94.9% of phenol was eliminated under the mentioned conditions. Since high values were obtained for the adjusted R² (0.9786) and determination coefficient (R² = 0.9875), the response surface methodology can describe the phenol removal by the use of the photocatalytic process. According to the one-way analysis of variance results, the quadratic model obtained by RSM is statistically significant for removing phenol. The recyclability of 92% after four consecutive cycles indicates the excellent stability of the photocatalyst for practical applications. Our research findings indicate that it is possible to employ response surface methodology as a helpful tool to optimize and modify process parameters for maximizing phenol removal from aqueous solutions and photocatalytic processes using SPIONs.