Synthesis of TiO2 nanoparticles in different thermal conditions and modeling its photocatalytic activity with artificial neural network.

Titanium dioxide (TiO2) nanoparticles were prepared by sol gel route. The preparation parameters were optimized in the removal of 4-nitrophenol (4-NP). All catalysts were analyzed by X-ray diffraction (XRD) and scanning electron microscopy (SEM). An artificial neural network model (ANN) was developed to predict the photocatalytic removal of 4-NP in the presence of TiO2 nanoparticles prepared under desired conditions. The comparison between the predicted results by designed ANN model and the experimental data proved that modeling of the removal process of 4-NP using artificial neural network was a precise method to predict the extent of 4-NP removal under different conditions.

[1]  Ana P. Carvalho,et al.  Synthesis of anatase TiO2 nanoparticles with high temperature stability and photocatalytic activity , 2008 .

[2]  Roberto Guardani,et al.  Modeling the kinetics of a photochemical water treatment process by means of artificial neural networks , 1999 .

[3]  N. Modirshahla,et al.  Decolorization and mineralization of C.I. Acid Yellow 23 by Fenton and photo-Fenton processes , 2007 .

[4]  A. Khataee,et al.  Neural network modeling of biotreatment of triphenylmethane dye solution by a green macroalgae , 2011 .

[5]  Vishnu Pareek,et al.  Artificial neural network modeling of a multiphase photodegradation system , 2002 .

[6]  B. K. Dutta,et al.  Photocatalytic degradation of model textile dyes in wastewater using ZnO as semiconductor catalyst. , 2004, Journal of hazardous materials.

[7]  N. Modirshahla,et al.  A kinetic model for the decolorization of C.I. Acid Yellow 23 by Fenton process. , 2007, Journal of hazardous materials.

[8]  L. Palmisano,et al.  Photocatalytic activity of nanocrystalline TiO2 (brookite, rutile and brookite-based) powders prepared by thermohydrolysis of TiCl4 in aqueous chloride solutions , 2008 .

[9]  P. Sipos,et al.  Low temperature synthesis, characterization and substrate-dependent photocatalytic activity of nanocrystalline TiO2 with tailor-made rutile to anatase ratio , 2008 .

[10]  P. R. Rodrigues,et al.  SIMULATION OF AN INDUSTRIAL WASTEWATER TREATMENT PLANT USING ARTIFICIAL NEURAL NETWORKS , 2000 .

[11]  A. Khataee,et al.  The use of artificial neural networks (ANN) for modeling of decolorization of textile dye solution containing C. I. Basic Yellow 28 by electrocoagulation process. , 2006, Journal of hazardous materials.

[12]  A. Khataee,et al.  UV/peroxydisulfate oxidation of C. I. Basic Blue 3: modeling of key factors by artificial neural network. , 2010 .

[13]  Mohammad Rabbani,et al.  Photocatalytic degradation of an azo dye in a tubular continuous-flow photoreactor with immobilized TiO2 on glass plates , 2007 .

[14]  T. Albanis,et al.  Multivariate experimental design for the photocatalytic degradation of imipramine. Determination of the reaction pathway and identification of intermediate products , 2008 .

[15]  M. Olya,et al.  Prediction of azo dye decolorization by UV/H2O2 using artificial neural networks , 2008 .

[16]  J. Weber,et al.  Synthesis of photocatalytic TiO2 nanoparticles: optimization of the preparation conditions , 2003 .

[17]  Baomei Wen,et al.  Optimization of the preparation methods Synthesis of mesostructured TiO2 with high photocatalytic activities , 2005 .

[18]  Ali Hassanzadeh,et al.  The effect of operational parameters on the photocatalytic degradation of three textile azo dyes in aqueous TiO2 suspensions , 2005 .

[19]  Feng Wu,et al.  Photodegradation of acetaminophen in TiO(2) suspended solution. , 2008, Journal of hazardous materials.

[20]  Jure Zupan,et al.  The use of artificial neural network (ANN) for modeling of the H2O2/UV decoloration process: part I , 1999 .

[21]  M. Swaminathan,et al.  TiO2-UV photocatalytic oxidation of Reactive Yellow 14: effect of operational parameters. , 2006, Journal of hazardous materials.

[22]  A. Khataee,et al.  Photocatalytic removal of C.I. Basic Red 46 on immobilized TiO2 nanoparticles: Artificial neural network modelling , 2009, Environmental technology.

[23]  Jinlong Zhang,et al.  Preparation of controllable crystalline titania and study on the photocatalytic properties. , 2005, The journal of physical chemistry. B.

[24]  R. Juang,et al.  Influence of operating parameters on photocatalytic degradation of phenol in UV/TiO2 process , 2008 .

[25]  Optimization of parameters on photocatalytic degradation of chloramphenicol using TiO2 as photocatalyst by response surface methodology. , 2010, Journal of environmental sciences.

[26]  H. Ozaki,et al.  A novel use of TiO2 fiber for photocatalytic ozonation of 2,4-dichlorophenoxyacetic acid in aqueous solution. , 2008, Journal of environmental sciences.