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Process optimization and kinetics analysis for photocatalytic degradation of emerging contaminant using N-doped TiO2-SiO2 nanoparticle: Artificial Neural Network and Surface Response Methodology approach
Environmental Technology & Innovation ( IF 7.1 ) Pub Date : 2021-07-01 , DOI: 10.1016/j.eti.2021.101761
Shimelis Kebede Kassahun , Zebene Kiflie , Hern Kim , Anteneh Fufa Baye

Antibiotics such as ciprofloxacin are very difficult to control or eliminate due to higher production and consumption related to rapid population growth. In conventional water treatment plants ciprofloxacin is not readily biodegradable but only moves from one phase to another. In the present study, we have synthesized visible light active N-doped TiO2-SiO2 nanoparticles by ultrasonic-assisted sol–gel process and investigated the performance on the photodegradation and mineralization of ciprofloxacin. The effects of operation parameters such as solution pH, irradiation time , catalyst dose and initial contaminant concentration were studied in the ranges 6 to 10, 60 to 120 min, 1 to 3 g/L and 5 to 15 mg/L, respectively. A combined Response Surface Methodology (RSM) and Artificial Neural Network (ANN) approach was used to obtain maximum CIP degradation and TOC removal efficiency. Accordingly, an optimum CIP degradation efficiency of 88.45 % and TOC removal efficiency of 75.18 % were estimated at the optimum operating parameters of solution pH of 5.45, irradiation time of 109.4 min, catalyst dose 2.44 g/L. at a targeted initial contaminant concentration of 10 mg/L with 0.89% desirability. Adsorption isotherm and chemical kinetic studies best fitted to Langmuir isotherm and pseudo-second-order kinetic models, respectively.



中文翻译:

使用 N 掺杂的 TiO 2 -SiO 2纳米颗粒光催化降解新兴污染物的工艺优化和动力学分析:人工神经网络和表面响应方法

由于与人口快速增长相关的较高产量和消费量,诸如环丙沙星之类的抗生素非常难以控制或消除。在传统的水处理厂中,环丙沙星不容易生物降解,只能从一个相转移到另一个相。在本研究中,我们合成了可见光活性的 N 掺杂 TiO 2 -SiO 2通过超声辅助溶胶-凝胶工艺制备纳米颗粒,并研究了环丙沙星的光降解和矿化性能。分别在 6 至 10、60 至 120 分钟、1 至 3 克/升和 5 至 15 毫克/升的范围内研究了操作参数(例如溶液 pH 值、辐照时间、催化剂剂量和初始污染物浓度)的影响。组合响应面方法 (RSM) 和人工神经网络 (ANN) 方法用于获得最大的 CIP 降解和 TOC 去除效率。因此,在溶液pH 5.45、辐照时间109.4 min、催化剂剂量2.44 g/L的最佳操作参数下,估计最佳CIP降解效率为88.45%,TOC去除效率为75.18%。目标初始污染物浓度为 10 毫克/升,合意性为 0.89%。

更新日期:2021-07-01
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