Literature DB >> 22894112

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

Fatemeh Ghanbary1, Nasser Modirshahla, Morteza Khosravi, Mohammad Ali Behnajady.   

Abstract

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.

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Year:  2012        PMID: 22894112     DOI: 10.1016/s1001-0742(11)60815-2

Source DB:  PubMed          Journal:  J Environ Sci (China)        ISSN: 1001-0742            Impact factor:   5.565


  3 in total

1.  Artificial Neural Network Modeling and Genetic Algorithm Optimization for Cadmium Removal from Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zero-Valent Iron (nZVI/rGO) Composites.

Authors:  Mingyi Fan; Tongjun Li; Jiwei Hu; Rensheng Cao; Xionghui Wei; Xuedan Shi; Wenqian Ruan
Journal:  Materials (Basel)       Date:  2017-05-17       Impact factor: 3.623

2.  Comparison of linear model and artificial neural network using antler beam diameter and length of white-tailed deer (Odocoileus virginianus) dataset.

Authors:  Sunday O Peters; Mahmut Sinecen; George R Gallagher; Lauren A Pebworth; Suleima Jacob; Jason S Hatfield; Kadir Kizilkaya
Journal:  PLoS One       Date:  2019-02-22       Impact factor: 3.240

3.  Artificial Intelligence Based Optimization for the Se(IV) Removal from Aqueous Solution by Reduced Graphene Oxide-Supported Nanoscale Zero-Valent Iron Composites.

Authors:  Rensheng Cao; Mingyi Fan; Jiwei Hu; Wenqian Ruan; Xianliang Wu; Xionghui Wei
Journal:  Materials (Basel)       Date:  2018-03-15       Impact factor: 3.623

  3 in total

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