Abstract Kinetic modeling using multivariate curve resolution-alternating least squares (MCR-ALS) was performed successfully for the electro oxidation (EO) treatment of textile wastewater. The present study represents the monitoring of the % degradation and kinetics of the EO reaction during the treatment of textile effluent. Optimum condition was found to be t ​= ​130 ​min, i ​= ​1.41 A, pH ​= ​5.41 and Retention time ​= ​143 ​min. At this optimum condition, the degradation suggested by response surface methodology (RSM) under central composite design (CCD) was 86%. A good correlation was observed between the predicted and experimental % degradation at the optimum value of process parameters. Spectrophotometric data of EO process during the treatment of textile effluent was analyzed during MCR-ALS. ALS optimization was performed by applying a series of constraints. The initial and final concentration of the pollutants along with the kinetic parameters were successfully resolved. The performance of kinetic modeling on predicting EO treatment was evaluated by a lack of fit in % experimental (1.215) and explained variance (99.98%).

中文翻译：

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电氧化工艺处理纺织废水的参数优化及MCR-ALS动力学建模

摘要 使用多元曲线分辨率交替最小二乘法 (MCR-ALS) 的动力学建模已成功用于纺织废水的电氧化 (EO) 处理。本研究代表了在纺织废水处理过程中对 EO 反应的降解百分比和动力学的监测。发现最佳条件为 t = 130 分钟，i = 1.41 A，pH = 5.41 和保留时间 = 143 分钟。在此最佳条件下，中心复合设计 (CCD) 下响应面法 (RSM) 建议的退化为 86%。在工艺参数的最佳值下，在预测的和实验的降解百分比之间观察到了良好的相关性。在 MCR-ALS 过程中分析了 EO 过程在纺织废水处理过程中的分光光度数据。ALS 优化是通过应用一系列约束来执行的。污染物的初始浓度和最终浓度以及动力学参数都得到了成功解析。动力学模型在预测 EO 处理方面的性能通过实验百分比 (1.215) 和解释方差 (99.98%) 的不拟合来评估。