V. Latha, Anu Sukhdev, P. Bhaskar
2022
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Journal
Asian Journal of Chemistry
Abstract
The response surface methodology (RSM) is applied for predictive estimation and optimization of decolourization of safranine, a phenazine dye by a chemical oxidation process using iron(II) as homogeneous catalyst and chloramine B (CAB) as an oxidant in acid medium. All experiments were based on the statistical designs in order to develop the predictive regression models and for optimization. Four independent variables (temperature, catalyst, CAB and acid concentration) were chosen to optimize the decolourization of safranine. When variance was analyzed (ANOVA), values of R2 and adjusted R2 were 0.9618 and 0.9262, respectively. The data derived from the experiments were in alignment with a second order regression model. In order to achieve a maximum decolourization, the optimal settings were found to be 0.0178 M HClO4, 0.004 M CAB, 0.0016 M iron(II) and 43.1 ºC, respectively. Under optimal reaction conditions, effect of temperature (15, 25, 35, 45 ºC) on decolourization rate was studied. Data received were in congruence with the second order kinetics. Thermodynamic parameters were also computed for the decolourization process. Maximum percentage of decolourization of safranine was predicted and experimentally validated.