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Polyaniline/wheat Husk Ash Nanocomposite Preparation and Modeling Its Removal Activity with an Artificial Neural Network


Paper Type 
Contributed Paper
Title 
Polyaniline/wheat Husk Ash Nanocomposite Preparation and Modeling Its Removal Activity with an Artificial Neural Network
Author 
Fatemeh Ghanbary* [a] and Ahmed Jafarian [b]
Email 
Ghanbary83@yahoo.com
Abstract:
In this work the removal efficiency of malachite green (MG) by using a nanocomposite was investigated. For preparation this nanocomposite the polyaniline (PANI) was coated on wheat husk ash (WHA). This nanocomposite was analyzed by X-ray diffraction (XRD) and scaning electron microscopy (SEM). The removal rate is strongly dependent on the PANI/WHA initial dosage, MG initial concentration, UV light intensity and irradiation time. The effect of these parameters has been studied and the optimum operational conditions was found. To predict the removal of MG in the presence of PANI/WHA nanocomposite an artificial neural network model (ANN) was developed. The comparison between the predicted results by designed model and the experimental data proved that modeling for removal process of MG using ANN was a precise method to predict the extent of MG removal under different conditions.

Start & End Page 
533 - 543
Received Date 
2014-12-30
Revised Date 
Accepted Date 
2015-05-23
Full Text 
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Keyword 
nanocomposite, polyaniline, wheat husk ash, neural network, modeling
Volume 
Vol.44 No.2 (April 2017)
DOI 
Citation 
Ghanbary F. and Jafarian A., Polyaniline/wheat Husk Ash Nanocomposite Preparation and Modeling Its Removal Activity with an Artificial Neural Network, Chiang Mai J. Sci., 2017; 44(2): 533-543.
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Chiang Mai Journal of Science

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