شماره ركورد كنفرانس :
3834
عنوان مقاله :
DECOLORIZATION OF TEXTILE AZO DYES BY Ni DOPED FERRIC OXY HYDROXIDE NANOWIRES: MODELLING AND OPTIMIZATION
پديدآورندگان :
Ahmadi Azqhandi Mohammad Hossein m.ahmadi@yu.ac.ir Applied Chemistry Department, Faculty of Gas and Petroleum (Gachsaran), Yasouj University, Gachsaran, Iran; , Ghaedi Mehrorang Department of Chemistry, Yasouj University, Yasouj Iran
كليدواژه :
Nanowires , Derivative spectrophotometry , Artificial neural network , Ni doped FeO(OH) , NWs , AC , Response surface methodology , Ternary adsorption.
عنوان كنفرانس :
نوزدهمين سمينار شيمي فيزيك ايران
چكيده فارسي :
We report the adsorption efficiency of Chrysoidine G, Rhodamine B and Disulfine blue by Ni doped Ferric Oxy Hydroxide FeO(OH) nanowires on activated carbon. The X-ray diffraction and FE- SEM analysis of this adsorbent were investigated. Response surface methodology was applied to evaluate the main effects and interactions among initial pH, adsorbent mass, sonication time and initial Chrysoidine G (CG), Rhodamine B (RB) and Disulfine blue (DB) concentration, while design results was also utilized as training set of ANN. Using the ANN analysis, the optimum topologies of the ANN model for modeling of adsorption process was found to be (6: (4-6):3). After predicting the model using RSM and ANN, two methodologies were statistically compared by coefficient of determination, root mean square error, absolute average deviation and mean absolute error based on the validation data set. Results suggest that ANN has better prediction performance as compared to RSM. The adsorption mechanism and rate of processes was investigated by analyzing time dependency data to various conventional kinetic models and best fitting quality was obtained by pseudo-second-order kinetic model. The experimental results revealed of dyes adsorption with high linearity follow Langmuir isotherm model with maximum adsorption capacities of 187.420 (CG), 210.170 (RB) and 235.650 mg g-1 (DB).