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Vol. 25 No. 2 (2013): Vol 25 Issue 2

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Artificial Neural Network, Equilibrium, Kinetics and Thermodynamics Modeling of Reactive Orange 12 Dye Using Rice Husk

https://doi.org/10.14233/ajchem.2013.12925
A.M. Ghaedi
Department of Applied Chemistry, Gachsaran Branch, Islamic Azad University, P.O. Box 75818- 63876, Gachsaran, Iran
A. Vafaei
Department of Applied Chemistry, Gachsaran Branch, Islamic Azad University, P.O. Box 75818- 63876, Gachsaran, Iran
S. Hafezi
Department of Applied Chemistry, Gachsaran Branch, Islamic Azad University, P.O. Box 75818- 63876, Gachsaran, Iran
M. Mohagheghian
Department of Applied Chemistry, Gachsaran Branch, Islamic Azad University, P.O. Box 75818- 63876, Gachsaran, Iran

Corresponding Author(s) : A.M. Ghaedi

abm_ghaedi@yahoo.com

Asian Journal of Chemistry, Vol. 25 No. 2 (2013): Vol 25 Issue 2

Abstract

The aim of this work was to study artificial neural network (ANN), equilibrium, kinetics, mechanism modeling of reactive orange 12 using rice husk. A batch system was employed for all experiments. The optimum operating conditions for adsorption reactive orange 12 dye using rice husk were 3 g adsorbent dose, 150 μm particle size, 10 mg/L initial concentration of dye, 2 h contact time, 35 ºC temperature and pH 3. A three layer back propagation artificial neural network (BP-ANN) model with a tangent sigmoid function (tansig) at hidden layer with 10 neurons, a linear transfer function (pureline) at output layer and the Levenberg-Marquardt algorithm (LMA) was used to predict the adsorption efficiency (%) of reactive orange 12 using rice husk. The optimal ANN model was found with a minimum mean square error (MSE) of 0.00011 and a determination coefficient (R2) of ca. 0.966 between the network outputs and experimental data. Langmuir isotherm was found to be optimum isotherm (R2 = 0.993) as compared with Freundlich, Temkin and Dubinin-Radushkevich (D-R) isotherms. The pseudo second order model (R2 = 0.9993) affected the kinetics better than pseudo first order model (R2 = 0.9652). The positive value of DHº (32.94 J/mol) displays the endothermic adsorption. The rate of adsorption was controlled by both boundary layer and pore diffusion. Coefficient of pore diffusion (D = 1.23 × 10-8 cm2/s) confirms the boundary layer diffusion (mass transfer) as the controlling step in the dye adsorption process.

Keywords

Adsorption Reactive orange 12 Rice husk Artificial neural network
Ghaedi, A., Vafaei, A., Hafezi, S., & Mohagheghian, M. (2012). Artificial Neural Network, Equilibrium, Kinetics and Thermodynamics Modeling of Reactive Orange 12 Dye Using Rice Husk. Asian Journal of Chemistry, 25(2), 817–826. https://doi.org/10.14233/ajchem.2013.12925
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