Eco-friendly methods, the ultrasound-assisted oxidation (UAO) and the subcritical water oxidation (SWO) methods, were applied to mineralise the widely used commercial reactive azo dye, Procion Crimson H-EXL in the presence of H2O2. 72.20% and 72.86% of total organic carbon removal were achieved in the UAO and SWO methods, respectively. The Box-Behnken design (BBD) was applied to design the experimental processes and optimise both methods. ANOVA and validation tests were performed to assess the employed models. F and P values were obtained as 36.72 and <0.0001 in the UAO method, respectively, and 605.97 and <0.0001 in the SWO method, respectively. The artificial neural network (ANN) was applied in both the UAO and the SWO methods. The predictive performance of the BBD and ANN models were evaluated and compared to each other over R2, root mean square error and absolute average deviation values.
Keywords: ANN; Procion Crimson; RSM; mineralisation; oxidation; subcritical water; ultrasound.