当前位置:
X-MOL 学术
›
Int. J. Chem. React. Eng.
›
论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
The photocatalytic degradation kinetics of the anti-inflammatory drug ibuprofen in aqueous solution under UV/TiO2 system and neural networks modeling
International Journal of Chemical Reactor Engineering ( IF 1.6 ) Pub Date : 2022-04-14 , DOI: 10.1515/ijcre-2021-0170 M. Bennemla 1 , S. Bouafia-Chergui 1 , A. Amrane 2, 3 , M. Chabani 1
International Journal of Chemical Reactor Engineering ( IF 1.6 ) Pub Date : 2022-04-14 , DOI: 10.1515/ijcre-2021-0170 M. Bennemla 1 , S. Bouafia-Chergui 1 , A. Amrane 2, 3 , M. Chabani 1
Affiliation
Abstract In this study, the kinetic degradation of the anti-inflammatory drug Ibuprofen in aqueous solution by heterogeneous TiO2 photocatalytic was investigated. The data obtained were used for training an artificial neural network. Preliminary experiments of photolysis and adsorption were carried out to assess their contribution to the photocatalytic degradation. Both, direct photolysis and adsorption of Ibuprofen are very low-efficient processes (15,83% and 23,88%, respectively). The degradation efficiency was significantly elevated with the addition of TiO2 Catalyst (>94%). The photocatalytic degradation followed a pseudo-first-order reaction according to the L-H model. The hydroxyl radicals and photo-hole (h+) were found to contribute to the Ibuprofen removal. The higher the initial concentration of Ibuprofen resulted in the lower percentage of degradation. This can be credited to the fact that the created photon and radicals were constant. The higher the initial concentration of Ibuprofen the fewer radicals were shared for each Ibuprofen molecular and so the lower percentage of degradation. The maximum photoactivity from the available light is accomplished when the concentration of catalyst reaches to 1 g/L (0.8 g), which was adopted as the optimal amounts. Compared to the removal of ibuprofen, the mineralization was relatively lower. This decrease is due to the organic content of the treated solution, which is mainly composed of recalcitrant intermediate products. The network was planned as a Levenberg-Marquardt algorithm with three layer, four neurons in the input layer, fourteen neurons in the hidden layer and one neuron in the output layer (4:14:1). The artificial neural network was trained until the MSE value between the simulated data and the experimental results was 10−5. The best results (R 2 = 0.999 and MSE = 1.5 × 10−4) were obtained with a log sigmoid transfer function at hidden layer and a linear transfer function at output layer.
中文翻译:
UV/TiO2体系下抗炎药布洛芬水溶液光催化降解动力学及神经网络建模
摘要 本研究研究了异相二氧化钛光催化降解抗炎药布洛芬在水溶液中的动力学。获得的数据用于训练人工神经网络。进行了光解和吸附的初步实验,以评估它们对光催化降解的贡献。布洛芬的直接光解和吸附都是非常低效的过程(分别为 15.83% 和 23.88%)。添加 TiO2 催化剂 (>94%) 后降解效率显着提高。根据 LH 模型,光催化降解遵循准一级反应。发现羟基自由基和光孔 (h+) 有助于布洛芬的去除。布洛芬的初始浓度越高导致降解百分比越低。这可以归功于创造的光子和自由基是恒定的这一事实。布洛芬的初始浓度越高,每个布洛芬分子共享的自由基越少,因此降解百分比越低。当催化剂的浓度达到 1 g/L (0.8 g) 时,可用光的最大光活性实现,这是最佳用量。与去除布洛芬相比,矿化度相对较低。这种减少是由于处理溶液的有机物含量主要由顽固的中间产物组成。该网络被规划为具有三层的 Levenberg-Marquardt 算法,输入层中有四个神经元,隐藏层有 14 个神经元,输出层有 1 个神经元 (4:14:1)。训练人工神经网络,直到模拟数据与实验结果之间的 MSE 值为 10-5。最好的结果(R 2 = 0.999 和 MSE = 1.5 × 10−4)在隐藏层使用对数 sigmoid 传递函数,在输出层使用线性传递函数。
更新日期:2022-04-14
中文翻译:
UV/TiO2体系下抗炎药布洛芬水溶液光催化降解动力学及神经网络建模
摘要 本研究研究了异相二氧化钛光催化降解抗炎药布洛芬在水溶液中的动力学。获得的数据用于训练人工神经网络。进行了光解和吸附的初步实验,以评估它们对光催化降解的贡献。布洛芬的直接光解和吸附都是非常低效的过程(分别为 15.83% 和 23.88%)。添加 TiO2 催化剂 (>94%) 后降解效率显着提高。根据 LH 模型,光催化降解遵循准一级反应。发现羟基自由基和光孔 (h+) 有助于布洛芬的去除。布洛芬的初始浓度越高导致降解百分比越低。这可以归功于创造的光子和自由基是恒定的这一事实。布洛芬的初始浓度越高,每个布洛芬分子共享的自由基越少,因此降解百分比越低。当催化剂的浓度达到 1 g/L (0.8 g) 时,可用光的最大光活性实现,这是最佳用量。与去除布洛芬相比,矿化度相对较低。这种减少是由于处理溶液的有机物含量主要由顽固的中间产物组成。该网络被规划为具有三层的 Levenberg-Marquardt 算法,输入层中有四个神经元,隐藏层有 14 个神经元,输出层有 1 个神经元 (4:14:1)。训练人工神经网络,直到模拟数据与实验结果之间的 MSE 值为 10-5。最好的结果(R 2 = 0.999 和 MSE = 1.5 × 10−4)在隐藏层使用对数 sigmoid 传递函数,在输出层使用线性传递函数。