Separation of lead ions from wastewater using electrodialysis: Comparing mathematical and neural network modeling

Sadrzadeh, Mohtada; Mohammadi, Toraj; Ivakpour, Javad; Kasiri, Norollah

doi:10.1016/j.cej.2008.02.023

Cited by 109 publications

(46 citation statements)

References 65 publications

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“…The most applied neural network topology for solving the multiple regression problems (i.e. function approximations) is the multi-layer feed-forward structure also known as multi-layer perceptron MLP [17][18][19]21]. This topology is detailed elsewhere [19].…”

Section: Ann Theoreticalmentioning

confidence: 99%

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Artificial neural network model for desalination by sweeping gas membrane distillation

Khayet

Cojocaru

2013

Desalination

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Sweeping gas membrane distillation process (SGMD) has been used for desalination and its performance index, defined as the product of the distillate flux and the salt rejection factor, has been modeled using artificial neural network (ANN) methodology. A feed-forward ANN has been developed for prediction of the performance index based on a set of 53 different experimental SGMD tests. A feed solution of 30 g/L sodium chloride was used in all experiments and the salt rejection factors were found to be greater than 99.4%. The individual and interaction effects of the input variables, namely the feed inlet temperature, the feed flow rate or the feed circulation velocity, and the air flow rate or the air circulation velocity, on the SGMD performance index have been investigated. The optimum point was determined by means of Monte Carlo simulation. The obtained optimal conditions were a feed inlet temperature of 69°C, an air flow rate of 34.5 L/min (i.e. 2.02 m/s air circulation velocity) and a feed flow rate of 160 L/h (i.e. 0.155 m/s liquid circulation velocity). Under these operating conditions a performance index of 1.493×10−3 kg/m 2 .s has been achieved experimentally being the maximal SGMD performance index obtained inside the region of experimentation.

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Section: Ann Theoreticalmentioning

confidence: 99%

“…The most used transfer functions to solve multiple regression problems are the linear transfer function (purelin), log-sigmoid transfer function (logsig) and hyperbolic tangent sigmoid transfer function (tansig) [17][18][19][20][21][22].…”

Section: Ann Theoreticalmentioning

confidence: 99%

Artificial neural network model for desalination by sweeping gas membrane distillation

Khayet

Cojocaru

2013

Desalination

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“…Consequently, the treatment of effluents containing Pb(II) and Cd(II) is quite imperative. Various treatment techniques such as precipitation (Ku and Jung 2001), electrochemical (Cooper et al 2007), ion-exchange (Dąbrowski et al 2004), coagulation/electrocoagulation El-Samrani et al 2008), and electrodialysis (Sadrzadeh et al 2008) are rather inept and/or cost prohibitive. Biosorption, using sustainable resources, is considered a promising process due to its high removal efficiency, low cost, mild operating conditions and good performance in the removal and recovery of heavy metal ions/dyes from dilute aqueous solution (Khan et al , 2014Lou et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Isotherm and kinetics modeling of Pb(II) and Cd(II) adsorptive uptake from aqueous solution by chemically modified green algal biomass

Khan

Mukhlif

Khan³

et al. 2016

Model. Earth Syst. Environ.

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In this study, the adsorption efficiency of epichlorohydrin modified fresh water green algal biomass was assessed for Pb(II) and Cd(II) uptake from aqueous solution. The process parameters such as contact time, dose, initial metal concentration, solution pH and temperature were optimized. The Langmuir, Freundlich, Temkin and Dubnin-Redushkevich isotherm model was applied to the equilibrium data, which best fitted the Langmuir isotherm indicating homogenous distribution of adsorption sites. The monolayer adsorption capacity was 100.00 for Pb (II) and 72.46 mg/g for Cd(II) adsorption. The kinetic data was best described by pseudo-second order model, with intraparticle and liquid film diffusion controlled mechanism. The negative values of Gibbs free energy change (ΔG º ) and positive enthalpy change (ΔH º ) showed that adsorption process was spontaneous and endothermic. The functional groups, surface morphology and elemental composition of adsorbent, before and after adsorption, was evaluated using FTIR spectra, SEM and EDS studies. The study revealed that the modified algal biomass can effectively and efficiently remove the title metal ions from aqueous solution.

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“…Therefore, it is necessary to treat waste containing Pb(II). Many methods have been developed to process the contaminated waste into an acceptable limit quality of waste water, such as coagulation 4,5 , electrodialysis 6,8 and adsorption 9,10 . Adsorption has been shown to be an economically practicable alternative method for lead removal from wastewater 11 .…”

Section: Introductionmentioning

confidence: 99%

Synthesis of C–4–Allyloxy–3 Methoxyphenylcalix[4] resorcinarene from Vanillin and Its Application as Adsorbent of Pb(II) Metal Cation

Kesuma¹,

Jumina²,

Ohto³

et al. 2016

Orient. J. Chem

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C-4-allyloxy-3-methoxyphenylcalix[4]resorcinarene had been synthesized from vanillin and its application as adsorbent for Pb(II) metal ion had been carried out. The synthesis was conducted in three steps to obtain the product as pink solid in 78.17% yield. The structure elucidation of the product was performed by IR, 1 H-NMR and 13 C-NMR. Adsorption experiments were carried out in a batch system under variation of medium acidity, interaction time and initial metal concentration. Adsorption kinetics was studied using Lagergren and Ho model, while adsorption isotherm was analyzed by Langmuir and Freundlich equations. The result showed that the Pb(II) adsorption was optimum at pH 4 and at interaction time of 30 minutes. The kinetic study showed that the adsorption of Pb(II) followed pseudo-second order of Ho model with adsorption rate (k) of 1.176 g mg -1 minute -1 . The adsorption followed the Langmuir isotherm model with equilibrium constant (K) was 7.28×10 -5 L mol -1 , adsorption capacity (q m ) was 1.538 mmol g -1 (318.67 mg/g) and adsorption energy was 33.67 kJ mol -1 .

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Separation of lead ions from wastewater using electrodialysis: Comparing mathematical and neural network modeling

Cited by 109 publications

References 65 publications

Artificial neural network model for desalination by sweeping gas membrane distillation

Artificial neural network model for desalination by sweeping gas membrane distillation

Isotherm and kinetics modeling of Pb(II) and Cd(II) adsorptive uptake from aqueous solution by chemically modified green algal biomass

Synthesis of C–4–Allyloxy–3 Methoxyphenylcalix[4] resorcinarene from Vanillin and Its Application as Adsorbent of Pb(II) Metal Cation

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