Biosorption of Pb(II) using Gundelia tournefortii: Kinetics, equilibrium, and thermodynamics

被引:16
作者
Rahimpour, Farshad [1 ]
Shojaeimehr, Tahereh [1 ]
Sadeghi, Marzieh [2 ]
机构
[1] Razi Univ, Fac Petr & Chem Engn, Biotechnol Res Lab, Kermanshah 6714967346, Iran
[2] Razi Univ, Analyt Chem Lab, Fac Chem, Kermanshah, Iran
关键词
Artificial neural network; Gundelia tournefortii; kinetic; Pb(II) adsorption isotherm; thermodynamic; ARTIFICIAL NEURAL-NETWORK; RESPONSE-SURFACE METHODOLOGY; AQUEOUS-SOLUTIONS; ACTIVATED CARBON; REMOVAL; ADSORPTION; LEAD; IONS; ADSORBENT; WASTE;
D O I
10.1080/01496395.2016.1260140
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
In this paper, the feasibility of Gundelia tournefortii was studied as a novel, high-capacity biosorbent for removing lead ions from synthetic wastewater in a batch system. The effects of various parameters such as temperature, initial concentration, initial pH, biosorbent dosage, and contact time were investigated. Based on batch results, the optimum operating conditions were found to be pH 5, biosorbent dosage of 25 mg, and temperature of 20 degrees C in the range of lead initial concentrations from 5 to 100 mg/L. The equilibrium contact time was 60 min. The biosorption mechanism can be well described by the Langmuir isotherm with a monolayer maximum adsorption capacity of 144.928 (mg/g) at 20 degrees C and a pseudo-second-order kinetic model. Thermodynamic studies proved that the sorption process was physical, spontaneous, feasible, random, and exothermic. In the second step, the ability of artificial neural network (ANN) to predict the adsorption capacity of Gundelia tournefortii for the removal of Pb(II) from aqueous solution was examined. The model was developed using a three-layer feed-forward back-propagation (BP) network with 5, 12, and 1 neurons in the first, second, and third layers, respectively. The Levenberg-Marquardt BP training algorithm (LMA) was found to be the best BP algorithm with a minimum mean squared error of 0.000867 and a minimum relative squared error of 0.032771. The comparison between the results of ANN and experimental data showed that ANN has a superior performance (R-2= of 0.998) in the prediction of the Pb(II) removal process.
引用
收藏
页码:596 / 607
页数:12
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