Modelling of cefixime (CFIX) removal using photocatalyst/UV/polyurethane by response surface methodology (RSM): optimisation and kinetic study

ABSTRACT

The present study investigated the cefixime removal from aqueous solution using TiO₂ and ZnO photocatalyst immobilised at polyurethane (PU) as well-asoptimized the effective parameters using response surface methodology (RSM). In this study, firstly, the polyurethane was synthesised and then photocatalysts were incorporated into the polyurethane. The experimental design was used to first determine the concentration of effective variables (pH, initial cefixime, catalyst dosage, and reaction time) and then optimize the independent variables based on the response (cefixime removal efficiency). The characteristics of photocatalyst were determined through scanning electron microscopy (SEM) equipped with energy-dispersive X-ray spectroscopy (EDX) and X-ray diffraction (XRD). The optimum variables for cefixime removal efficiency were pH of 4.80, catalyst dosage of 2.60 g/m²; initial cefixime concentration of 25.90 mg/L, and reaction time of 85 min for TiO₂/ultraviolet (UV)/polyurethane (TiO₂/UV/PU) process. In addition, the optimum conditions for the ZnO/ultraviolet/polyurethane (ZnO/UV/PU) process for pH of the solution, the dosage of ZnO, CFIX concentration, and reaction time were found to be6.70, 2.40 g/m², 25 mg/L, and 89 min, respectively. The results of the kinetic model showed that experimental values were best fitted with the first-order model. Also, the results of a scavenger study represented that degradation of antibiotics and the generation of free radicals of hydroxide play an important role in the cefixime removal. Therefore, it is demonstrated that the CFIX antibiotic should significantly be removed from the aqueous solution using a photocatalyst/ultraviolet/polyurethane process.

KEYWORDS:

• Photocatalyst/UV/PU
• antibiotic removal
• kinetic study
• optimisation
• immobilised photocatalyst

Acknowledgments

This study is derived from a PhD dissertation and has been financially supported by Islamic Azad University with a project No: 94-04-46-28520. The authors would like to appreciate the Department of Environmental Engineering, School of Environment, for their collaborations. The authors are grateful for the contributions from Vida Alvani, Algae R&D Centre, School of Veterinary and Life Sciences, Murdoch University, Western Australia 6150, Australia.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Islamic Azad University [No: 94-04-46-28520].