Performance Prediction of DMF Chemical Wastewater Electrocatalytic Oxidation Technology Treatment Based on Optimized RUSBoost Integrated Model

In response to the high biological toxicity and difficult degradation of chemical wastewater containing dimethylformamide (DMF), this study uses electrocatalytic oxidation technology to treat it. The effects of electrode type, electrolyte type, electrode spacing, current, and solution pH on the degradation efficiency of DMF containing wastewater in electrocatalytic oxidation are investigated. By constructing an integrated machine learning model, the mechanism of multiparameter synergy is analyzed and the process limit performance is predicted. The results showed that when Ti/RuO2-IrO was used as the anode material and NaCl was used as the electrolyte, under the conditions of 9 g/LCl− concentration, 4 A current, 1 cm electrode spacing, and 8 pH value, the removal rates of TOC and TN of wastewater were 92.9% and 93.4%. In the prediction results of the integrated model, the determination coefficients for the removal rates of TOC and TN were 0.96 and 0.95, with root mean square error of 2.1% and 2.4%. The model predicted data validated the global optimality of experimental parameters, revealing that the interaction effect between current intensity and electrode spacing can improve mass transfer efficiency by 37%, providing a quantitative control basis for process enhancement. The research results can offer technical support and theoretical reference for the treatment of DMF containing wastewater in the synthetic fiber industry.