Optimization of process variables by response surface methodology for methylene blue dye removal using Spruce sawdust/MgO nanobiocomposite

The purpose of this investigation is to study the influence of Spruce sawdust (SD) coated by magnesium oxide (MgO) nanoparticles in the removing of methylene blue (MB) from an aqueous solution which is in a batch system. The adsorbent was characterized by FTIR, FE-SEM, BET and XRD analysis. The high adsorption potential of SD-MgO nano-biocomposite was revealed by these findings, therefore, it is usable for dye-containing wastewater treatment. By investigating the impact of particular conditions like MB concentrations, the dose of adsorbent and pH, it became possible to confirm the effectiveness of the process. The OOP (which stands for Optimum Operating Parameters) were evaluated by RSM (which stands for Response Surface Methodology) which is based on BBD (Box-Behnken design) and is used for removing MB dye. The adsorbent dosage is the highest effective degree of the individual factor on MB removal. Maximum removal of MB dye was detected at pH 11 with 3.50 g L-1 adsorbent dosage. The surface area of 0.873 m2 g-1 and mesoporous adsorbent prepared gave good adsorption capacity of 26.657 mg g-1 for MB. Furthermore, in order to predict the empirical variables’ significance, the variances’ analysis (ANOVA) was used. The predicated removal efficiency which is proved to be the potency of the process and its effectiveness was found to be 94.05%. Different equilibrium and kinetic models were utilized to the experimental data. Both Pseudo-second order kinetic model and Freundlich adsorption isotherm showed the better fitness to the experimental data.

Optimization of process variables by response surface methodology for methylene blue dye removal using Spruce sawdust/MgO nanobiocomposite Keywords:

Adsorption , Box-Behnken Design , Dye , Mgo Nanoparticles , Nano-Biocomposites