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Keywords = emulsified liquid membrane (ELM)

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15 pages, 2455 KiB  
Article
Optimization and Prediction of Stability of Emulsified Liquid Membrane (ELM): Artificial Neural Network
by Meriem Zamouche, Hichem Tahraoui, Zakaria Laggoun, Sabrina Mechati, Rayene Chemchmi, Muhammad Imran Kanjal, Abdeltif Amrane, Amina Hadadi and Lotfi Mouni
Processes 2023, 11(2), 364; https://doi.org/10.3390/pr11020364 - 24 Jan 2023
Cited by 25 | Viewed by 2809
Abstract
In this work, the emulsified liquid membrane (ELM) extraction process was studied as a technique for separating different pollutants from an aqueous solution. The emulsified liquid membrane used consisted of Sorbitan mono-oleate (Span 80) as a surfactant with n-hexane (C6H14 [...] Read more.
In this work, the emulsified liquid membrane (ELM) extraction process was studied as a technique for separating different pollutants from an aqueous solution. The emulsified liquid membrane used consisted of Sorbitan mono-oleate (Span 80) as a surfactant with n-hexane (C6H14) as a diluent; the internal phase used was nitric acid (HNO3). The major constraint in the implementation of the extraction process by an emulsified liquid membrane (ELM) is the stability of the emulsion. However, this study focused first on controlling the stability of the emulsion by optimizing many operational factors, which have a direct impact on the stability of the membrane. Among the important parameters that cause membrane breakage, the surfactant concentration, the emulsification time, and the stirring speed were demonstrated. The optimization results obtained showed that the rupture rate (Tr) decreased until reaching a minimum value of 0.07% at 2% of weight/weight of Span 80 concentration with an emulsification time of 3 min and a stirring speed of 250 rpm. On the other hand, the volume of the inner phase leaking into the outer phase was predicted using an artificial neural network (ANN). The evaluation criteria of the ANN model in terms of statistical coefficient and RMSE error revealed very interesting results and the performance of the model since the statistical coefficients were very high and close to 1 in the four phases (R_training = 0.99724; R_validation = 0.99802; R_test = 0.99852; R_all data = 0.99772), and also, statistical errors of RMSE were minimal (RMSE_training= 0.0378; RMSE_validation = 0.0420; RMSE_test = 0.0509; RMSE_all data = 0.0406). Full article
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13 pages, 7438 KiB  
Article
The Effect of Emulsifiers on the Emulsion Stability and Extraction Efficiency of Cr(VI) Using Emulsion Liquid Membranes (ELMs) Formulated with a Green Solvent
by Katia Anarakdim, Gemma Gutiérrez, Ángel Cambiella, Ounissa Senhadji-Kebiche and María Matos
Membranes 2020, 10(4), 76; https://doi.org/10.3390/membranes10040076 - 21 Apr 2020
Cited by 33 | Viewed by 6968
Abstract
The stability of emulsion liquid membranes (ELMs) and their ability to extract Cr(VI) were investigated. The objective of this study is to compare different ELM formulations using combinations of two hydrophilic (Tween 20 and Tween 80) and two lipophilic (polyglycerol polyricinoleate (PGPR) and [...] Read more.
The stability of emulsion liquid membranes (ELMs) and their ability to extract Cr(VI) were investigated. The objective of this study is to compare different ELM formulations using combinations of two hydrophilic (Tween 20 and Tween 80) and two lipophilic (polyglycerol polyricinoleate (PGPR) and Span 80) emulsifiers. TOPO (tri-n-octylphosphine oxide) as a carrier and a green solvent (sunflower oil) were used to provide high extraction efficiency of Cr(VI). All these double emulsions were characterized in droplet size distribution, zeta potential, visual inspection with a microscope, and stability. The best formulation was obtained with PGPR as the inner stabilizer and Tween 80 as the outer stabilizer, leading to Cr(VI) ion removal efficiency of up to 96%. Full article
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