Abstract

In this work, the photocatalytic removal of diclofenac (DCF) was investigated using TiO₂-P25 nanoparticles immobilized on glass beads in a packed bed photoreactor. DCF is one of the non-steroidal anti-inflammatory drugs used as an analgesic drug. DCF is monitored in urban sewage and surface waters as a stable contaminant that can harm the environment. Advanced oxidation processes (AOPs) are promising methods for degradation and removal of environmental pollutants. The heterogeneous photocatalysis process is one of the AOPs so that the contaminants are decompose in the presence of UV light and a photocatalyst (TiO₂). Holes and hydroxyl radicals are the main active species in the UV/TiO₂ process. A thin layer of TiO₂-P25 nanoparticles was immobilized by heat attachment method on glass beads. The effect of five operational parameters, the initial concentration of DCF, the power of the light source, the flow rate of the fluid in the photoreactor, irradiation time and pH, has been studied experimentally in the efficiency of the photoreactor. The DCF removal percent is 99% for the initial DCF concentration of 10 mg L^–1, the power of the light source of 16 W, the fluid flow rate of 240 mL min^–1 and pH 6 for 120 min irradiation time. The effect of operational parameters on the DCF removal percent was modeled using the artificial neural network (ANN). ANN modeling with a 5 : 9 : 1 feed-forward back propagation neural network demonstrated the appropriate consistency of the experimental and predicted data. The R² values for all data (training, validation and test) were close to 1, confirming ANN reasonable predictive performance. Using the weights of the ANN model in the Garson equation, indicated that pH and irradiation time had the highest effect on the DCF removal percent.

中文翻译：

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双氯芬酸作为药物污染物的光催化降解的人工神经网络建模

摘要

在这项工作中，使用固定在填充床光反应器中的玻璃珠上的TiO ₂ -P25纳米颗粒，研究了双氯芬酸（DCF）的光催化去除。DCF是用作镇痛​​药的非甾体抗炎药之一。DCF在城市污水和地表水中被监测为稳定的污染物，可能危害环境。先进的氧化工艺（AOP）是降解和去除环境污染物的有前途的方法。异质光催化过程是AOP之一，因此污染物会在紫外线和光催化剂（TiO ₂）的存在下分解。空穴和羟基自由基是UV / TiO ₂工艺中的主要活性物质。TiO ₂薄层-P25纳米颗粒通过热附接法固定在玻璃珠上。在光反应器的效率方面，已经通过实验研究了五个操作参数的影响：DCF的初始浓度，光源的功率，光反应器中流体的流速，照射时间和pH。初始DCF浓度为10 mg L ^–1，光源功率为16 W，流体流速为240 mL min ^–1时，DCF去除百分比为99％。pH值为6，持续120分钟的照射时间。使用人工神经网络（ANN）对操作参数对DCF去除率的影响进行建模。具有5：9：1前馈反向传播神经网络的ANN建模证明了实验数据和预测数据的适当一致性。所有数据（培训，验证和测试）的R ²值均接近1，从而确认了ANN合理的预测性能。在Garson方程中使用ANN模型的权重，表明pH和辐照时间对DCF去除率的影响最大。