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

Fatemeh Ghanbary* [a] and Ahmed Jafarian [b]
* Author for corresponding; e-mail address: Ghanbary83@yahoo.com
Volume: Vol.44 No.2 (April 2017)
Research Article
DOI:
Received: 30 December 2014, Revised: -, Accepted: 23 May 2015, Published: -

Citation: Ghanbary F. and Jafarian A., Polyaniline/wheat Husk Ash Nanocomposite Preparation and Modeling Its Removal Activity with an Artificial Neural Network, Chiang Mai Journal of Science, 2017; 44(2): 533-543.

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.

Keywords: nanocomposite, polyaniline, wheat husk ash, neural network, modeling

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