• Membrane and Water Treatment
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• 제3권2호
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• pp.123-131
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• 2012

This study investigated the extraction and stripping performance of PIMs consisting of PVC and Aliquat 336. Extraction and stripping of three representative heavy metals - namely $Cd^{2+}$, $Cu^{2+}$, and $Zn^{2+}$ - by the synthesized membranes were evaluated as a function of sodium chloride concentration and under different stripping solutions (0.01 M $HNO_3$, Milli-Q water, 0.01 M HCl and 0.01 M NaOH), respectively. Results reported here indicate that the formation of negatively charged metal chloride complex species was responsible for the extraction of the target metal to PIMs. Experimental results and thermodynamic modeling of the speciation of chloro metal complexes further confirm that the extraction selectivity between $Cd^{2+}$, $Cu^{2+}$ and $Zn^{2+}$ can be controlled by regulating the chloride concentration of the feed solution. An acidic solution without any chloride was the most effective stripping solution, followed by Milli-Q water, and a diluted hydrochloric acid solution. On the other hand, the stripping of metals from PIMs did not occur when a basic stripping solution was used.

• Membrane and Water Treatment
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• 제6권2호
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• pp.95-102
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• 2015

The presented research is about characterization of Cellulose Triacetate (CTA) based Polymer Inclusion Membranes (PIMs) which incorporated the commercial extractant Aliquat 336, Tributylphosphate (TBP) as modifier and 2-Nitro Phenyl Pentyl Ether (NPPE) as plasticizer, for the preparation of the membranes. Chemical and physical characteristics of the synthesized membranes especially membrane thickness and side difference effects were investigated. Different surface structures and membrane thickness affect the extraction efficiency of membranes. Membrane extraction experiments were studied where the glass-facing surface of the membranes placed next to feed phase and the air-facing surface to stripping phase. The membrane was characterized by means of AFM, FT-IR and SEM.

• Membrane and Water Treatment
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• 제7권3호
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• pp.223-240
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• 2016

In this study, poly(vinyl-alcohol) and water insoluble ${\beta}$-cyclodextrin polymer (${\beta}$-CDP) cross-linked with citric acid, have been used as macrocyclic carrier in the preparation of polymer inclusion membranes (PIMs) for aniline (as molecule model) extraction from aqueous media. The obtained membranes were firstly characterized by X-ray diffraction, Fourier transform infrared and water swelling test. The transport of aniline was studied in a two-compartment transport cell under various experimental conditions, such as carrier content in the membranes, stirring rate and initial aniline concentration. The kinetic study was performed and the kinetic parameters were calculated as rate constant (k), permeability coefficient (P) and flux (J). These first results demonstrated the utility of such polymeric membranes for environmental decontamination of toxic organic molecules like aniline. Predictive modeling of transport flux through these materials was then studied using design of experiments; the design chosen was a two level full factorial design $2^k$. An empirical correlation between aniline transport flux and independent variables (Poly ${\beta}$-CD membrane content, agitation speed and initial aniline concentration) was successfully obtained. Statistical analysis showed that initial aniline concentration of the solution was the most important parameter in the study domain. The model revealed the existence of a strong interaction between the Poly ${\beta}$-CD membrane content and the stirring speed of the source solution. The good agreement between the model and the experimental transport data confirms the model's validity.

• Environmental Engineering Research
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• 제25권3호
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• pp.418-425
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• 2020

In this study soft computing techniques including, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were investigated for the prediction of Cr(VI) transport efficiency by novel Polymer Inclusion Membranes (PIMs). Transport experiments carried out by varying parameters such as time, film thickness, carrier type, carier rate, plasticizer type, and plasticizer rate. The predictive performance of ANN and ANFIS model was evaluated by using statistical performance criteria such as Root Mean Standard Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R²). Moreover, Sensitivity Analysis (SA) was carried out to investigate the effect of each input on PIMs Cr(VI) removal efficiency. The proposed ANN model presented reliable and valid results, followed by ANFIS model results. RMSE and MAE values were 0.00556, 0.00163 for ANN and 0.00924, 0.00493 for ANFIS model in the prediction of Cr(VI) removal efficiency on testing data sets. The R² values were 0.973 and 0.867 on testing data sets by ANN and ANFIS, respectively. Results show that the ANN-based prediction model performed better than ANFIS. SA demonstrated that time; film thickness; carrier type and plasticizer type are major operating parameters having 33.61%, 26.85%, 21.07% and 8.917% contribution, respectively.