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

Abstract

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.