基于UV-Vis吸收光谱的活性大红BES的光催化降解BPNN模拟研究

以对Plackett-Burman设计实验结果筛选确定的TiO2用量、溶液初始浓度co、光照射时间t、溶液初始pH值4个因素为自变量,脱色率为因变量,采用BP神经网络基于Box-Behnken设计和U10(10×52×2)设计实验数据建模,对活性大红BES溶液进行光催化降解模拟研究.降解过程中BES溶液的脱色率通过紫外-可见分光光度法测定后计算获得.建立的BPNN模型对训练集和预测集计算结果相关系数r分别为0.996 4和0.963 6,脱色率实验值与预测值的平均相对误差MRE分别为6.14%和7.76%.将该模犁用于分析各因素对BES光催化降解的影响,表明初始浓度较低时,pH 5.0和适当的cTIO2条件下有利于提高BES的降解率.根据该模型分析得出c0为40 mg·L-1时的优化实验条件为pH 5.0,cTiO2=1.20 g·L-1,t=35min,该条件下BES脱色率的模型计算值为99.16%.经实验验证获得的脱色率为98.20%,脱色率计算值与实验值十分接近,相对误差仅为-0.96%.

BPNN Simulation of Photocatalytic Degradation of Reactive Scarlet BES by UV-Vis Spectrophotometer

The use of chemometric techniques and multivariate experimental designs for the photoeatalytic reaction of reactive scarlet BES in aqueous solution under ultraviolet light irradiation is described. The efficiency of photocatalytic degradation was evaluated by the analysis of the parameter of deeoloration efficiency determined by UV absorption at 540 nm using a UV-Vis spectrophotometer in different conditions. Five factors, such as the amount of titanium oxide (TiO2]), the concentrations of reactive searlet BES (c0), irradiation time (t), the pH value (pH) and temperature (T), were studied. TiO2]. c0, t and pH selected on the basis of the results of variance analysis by Plaekett-Burman design were used as independent variables. Training sets and test sets of back propagation neural network (BPNN) were formed by Box-Behnken design and uniform design U10 (10× 52 ×2) respectively. The process of photoeatalytie degradation of the target object was simulated by the BPNN model. The correlation coefficient (r) of the calculation results for training set and test set by BPNN is 0. 996 4 and 0. 963 6 respectively, and the mean relative errors between the predictive value and experimental value of deeoloration efficiency are 6. 14 and 7. 76, respectively. The modeled BPNN was applied to analyze the influence of four factors on deeoloration efficiency. The results showed that the initial conditions of co being lower, pH 5.0 and appropriate amount of TiO2] contribute to improving the deeoloratione fficiency of reactive scarlet BES. Under the condition of c0 =40 mg · L^-1, the optimized experimental condition of the system was obtained. TiO2 ] = 1.20 g · L^-1 and pH 5.0. Under the optimized experimental condition, the experimental value of decoloration efficiency is 98. 20% when irradiation time is 35 minutes and the predictive value of decoloration efficiency is 99. 16% under the same condition. The relative error of decoloration efficiency between the predictive value and experimental value is only -0. 96%. The experimental value is very close to the model predicted value.