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Photocatalytic Degradation of Industrial Dye in Semi-Pilot Scale Prototype Solar Photoreactor: Optimization and Modeling Using ANN and RSM Based on Box–Wilson Approach
Topics in Catalysis ( IF 2.8 ) Pub Date : 2020-07-11 , DOI: 10.1007/s11244-020-01320-0
Mohammed Berkani , Mohammed Kheireddine Bouchareb , Mohammed Bouhelassa , Yassine Kadmi

Photodegradation of an industrial Azo dye C.I Basic Red 46, was examined in a semi-pilot scale prototype solar photoreactor under solar radiation. In our study, photodegradation of the dye was optimized using Response Surface Methodology (RSM) based on Box-Wilson approach. The Artificial Neural Network (ANN) was used to establish suitable modeling and optimal conditions for the Solar UV/Immobilized-TiO2 process in order to evaluate the individual effects of three factors that independently affect the effectiveness of the photodegradation process: (1) initial concentration of the dye, (2) pH, and (3) flow rate. The RSM was in good agreement with the prediction model (R2Dec = 0.95); meanwhile, the ANN approach revealed that the predicated model fit perfectly with the experimental data to yield the highest value of R2 = 0.999. The effects of these three factors could be estimated from a second-order polynomial equation, and the optimal parameters of photodegradation consisted of three main parameters: (1) initial concentration of colorant 10.65 mg.L−1, (2) pH 10.82, and (3) rate of fluid flow of 852 L h−1. The decolorization removal efficiency under these optimal conditions was 99%.



中文翻译:

半小规模原型太阳能光反应器中工业染料的光催化降解:基于Box-Wilson方法的ANN和RSM优化和建模

在半辐射规模的原型太阳光反应器中,在太阳辐射下检查了工业偶氮染料CI Basic Red 46的光降解。在我们的研究中,使用基于Box-Wilson方法的响应表面方法(RSM)对染料的光降解进行了优化。人工神经网络(ANN)用于为太阳UV /固定化TiO 2工艺建立合适的建模和最佳条件,以评估独立影响光降解工艺有效性的三个因素的单独影响:(1)初始染料浓度,(2)pH和(3)流速。RSM与预测模型非常吻合(R 2 Dec = 0.95);同时,人工神经网络方法表明,该预测模型与实验数据完全吻合,得出的最高R 2  = 0.999。这三个因素的影响可以通过一个二阶多项式方程来估算,并且光降解的最佳参数包括三个主要参数:(1)着色剂的初始浓度为10.65 mg.L -1,(2)pH为10.82,以及(3)流体流速为852 L h -1。在这些最佳条件下的脱色去除效率为99%。

更新日期:2020-07-13
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