Abstract
In this paper, the removal of reactive black 5 (RB5) from aqueous solutions was evaluated by sono-catalytic process combined with local yellow montmorillonite in the presence of H2O2 and optimized using response surface methodology (RSM). The structure and morphology of the catalyst were investigated using FTIR, SEM, and XRF techniques. The optimal condition for RB5 removal for pH, H2O2 concentration, catalyst dosage, reaction time, and dye concentration were determined as 3.13, 1.5 mL L−1, 1.9 g L−1, 90 min, and 25 mg L−1, respectively. Considering the value of R2: 0.9769 and adjusted R2: 0.9584 in the RSM model, it can be said that the selected model is suitable for data analysis (quadratic model). Moreover, “adequacy precision” of our results was measured by the signal-to-noise ratio, and it was found to be about 28 (far higher than 4 as a baseline), indicating an adequate signal. The coefficient of variation (CV) is another essential index to evaluate the reproducibility of the RSM model. It was found that the value of the CV is 7.8; thus, it can be stated that the model is reproducible. The independence of the errors of our data was obtained as 1.78 via the Durbin Watson test. Thus, the assumption of the absence of correlation between the errors is not rejected and regression can be used. The kinetics of RB5 adsorption followed a pseudo-first-order kinetic model (R2: 0.951), and the rate of mineralization obtained was equal to 78.52%. The present study showed that the sono-catalytic process combined with local yellow montmorillonite and hydrogen peroxide has a high efficiency in the removal of RB5.
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The authors would like to acknowledge the Ardabil University of Medical Sciences for financial and instrumental supports (IR.ARUMS.REC.1397.258).
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Rashtbari, Y., Abazari, M., Arfaeinia, L. et al. The optimization of reactive black 5 dye removal in the sono-catalytic process combined with local yellow montmorillonite and hydrogen peroxide using response surface methodology from aqueous solutions. Biomass Conv. Bioref. 13, 6067–6081 (2023). https://doi.org/10.1007/s13399-021-01773-7
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DOI: https://doi.org/10.1007/s13399-021-01773-7