ZnO/Mg-Al Layered Double Hydroxides as a Photocatalytic Bleaching of Methylene Orange - A Black Box Modeling by Artificial Neural Network

被引:2
作者
Hosseini, Seyed Ali [1 ]
Akbari, Mansor [1 ]
机构
[1] Urmia Univ, Dept Appl Chem, Fac Chem, Orumiyeh, Iran
关键词
layered double hydroxide; photo catalyst; artificial neural network; response surface methodology; nano composite;
D O I
10.9767/bcrec.11.3.570.299-315
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The paper reports the development of ZnO-MgAl layered double hydroxides as an adsorbent-photo catalyst to remove the dye pollutants from aqueous solution and the experiments of photo catalytic study were designed and modeled by response surface methodology ( RSM) and artificial neural network ( ANN). The co-precipitation and urea methods were used to synthesize the ZnO-MgAl layered double hydroxides and FT-IR, XRD and SEM analysis were done for characterization of the catalyst. The performance of the ANN model was determined and showed the efficiency of the model in comparison to the RSM method to predict the percentage of dye removal accurately with determination coefficient ( R-2) of 0.968. The optimized conditions were obtained as follows: 600 degrees C, 120 min, 0.05 g and 20 ppm for the calcination temperature, irradiation time, catalyst amount and dye pollutant concentration, respectively. Copyright (C) 2016 BCREC GROUP. All rights reserved
引用
收藏
页码:299 / 315
页数:17
相关论文
共 48 条
[1]   Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research [J].
Agatonovic-Kustrin, S ;
Beresford, R .
JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS, 2000, 22 (05) :717-727
[2]  
Al-Rasheed R.A., 2005, 4 SWCC ACQ EXP S HEL
[3]   Advanced oxidation processes (AOP) for water purification and recovery [J].
Andreozzi, R ;
Caprio, V ;
Insola, A ;
Marotta, R .
CATALYSIS TODAY, 1999, 53 (01) :51-59
[4]   Optimization and Modeling of the Photocatalytic Degradation of the Insect Repellent DEET in Aqueous TiO2 Suspensions [J].
Antonopoulou, Maria ;
Konstantinou, Ioannis .
CLEAN-SOIL AIR WATER, 2013, 41 (06) :593-600
[5]   Modelling and optimization of syngas production from methane dry reforming over ceria-supported cobalt catalyst using artificial neural networks and Box-Behnken design [J].
Ayodele, Bamidele V. ;
Cheng, Chin Kui .
JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY, 2015, 32 :246-258
[6]   Modeling and optimization of cross-flow ultrafiltration using hybrid neural network-genetic algorithm approach [J].
Badrnezhad, Ramin ;
Mirza, Behrooz .
JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY, 2014, 20 (02) :528-543
[7]   Modeling and optimization II: Comparison of estimation capabilities of response surface methodology with artificial neural networks in a biochemical reaction [J].
Bas, Deniz ;
Boyaci, Ismail H. .
JOURNAL OF FOOD ENGINEERING, 2007, 78 (03) :846-854
[8]   Photoelectrocatalytic Oxidation of Textile Dye Effluent: Modeling Using Response Surface Methodology [J].
Basha, C. Ahmed ;
Saravanathamizhan, R. ;
Manokaran, P. ;
Kannadasan, T. ;
Lee, Chang Woo .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2012, 51 (07) :2846-2854
[9]   Response surface methodology (RSM) as a tool for optimization in analytical chemistry [J].
Bezerra, Marcos Almeida ;
Santelli, Ricardo Erthal ;
Oliveira, Eliane Padua ;
Villar, Leonardo Silveira ;
Escaleira, Luciane Amlia .
TALANTA, 2008, 76 (05) :965-977
[10]   An experimental design approach employing artificial neural networks for the determination of potential endocrine disruptors in food using matrix solid-phase dispersion [J].
Boti, Vasiliki I. ;
Sakkas, Vasilios A. ;
Albanis, Triantafyllos A. .
JOURNAL OF CHROMATOGRAPHY A, 2009, 1216 (09) :1296-1304