Statistical analysis and optimization of photodegradation efficiency of methyl orange from aqueous solution using cellulose/zinc oxide hybrid aerogel by response surface methodology (RSM)

The photodegradation efficiency of cellulose-X/zinc oxide-Y (CA-X/ZnO-Y) aerogels was studied to degrade methyl orange (MO) as an organic dye pollutant from an aqueous solution under UV light irradiation. In this study, the initial pH of the solution (3, 7, and 11), the photocatalyst dosage (3, 6, and 9 g L-1), the initial concentration of solution MO (10, 20, and 30 ppm), and the concentration of cellulose in CA-X/ZnO-Y hybrid aerogel (3, 6, and 9 wt%) were selected as four variable parameters, whereas the photoderadation performance was selected as the response. Moreover, the response surface methodology (RSM) analysis was carried out to investigate the influence of four various experimental factors at different times on the degradation of MO. The adequacy result of the proposed models displays that total of the proposed models can predict the photodegradation efficiency of MO by CA-x/ZnO-y aerogel. The optimization results of the process showed that pH = 3 and concentration of MO = 10 ppm, photocatalyst dosage (9 g L-1), and MCC concentration (9 g) are the optimal level of the studied parameters. Also, the results showed that desirability of 0.96 confirms the acceptance and applicability of the model where the RSM model is a helpful technique for the optimum conditions design. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of King Saud University.

Automated summary

The photodegradation efficiency of CA-X/ZnO-Y aerogels for degrading MO pollutant from aqueous solution was studied, and RSM analysis was used to investigate the influence of experimental factors on MO degradation. The proposed models showed good predictability and the optimization results indicated the best conditions for the process. The desirability of 0.96 confirmed the acceptance and applicability of the model, demonstrating the effectiveness of RSM in designing optimal conditions.