This is an open access article under the CC BY license: Al-Khwarizmi Engineering Journal Al-Khwarizmi Engineering Journal ISSN (printed): 1818 – 1171, ISSN (online): 2312 – 0789 Vol. 20, No. 3, September, (2024), pp. 1-10 Electrochemical Extraction with Supported Liquid Membrane for Removing Copper from Synthetic Wastewater: Optimisation through Response Surface Methodology Noor R. Kadhim*, Hussain M. Flayeh**, Ali H. Abbar*** and Hasan F. Al-azzawie**** *,**Environmental Engineering Department, College of Engineering, University of Baghdad, Iraq ***Biochemical Engineering Department, Al-Khwarizmi College of Engineering, University of Baghdad, Iraq ****Lincoln university, Malysia *Email: noor.jabbar2011d@coeng.uobaghdad.edu.iq (Corresponding Author) **Email: Hussain-altemmimi@coeng.uobaghdad.edu.iq ***Email: ali.abbar@kecbu.uobaghdad.edu.iq ****Email: hazzawie2@yahoo.com (Received 26 November 2023; Revised 4 April 2024; Accepted 2 July 2024; Published 1 September 2024) https://doi.org/10.22153/kej.2024.07.001 Abstract In this study, copper was removed from an aqueous solution through electromembrane extraction (EME), a new approach that utilises a two-chamber electrochemical cell. It consists of two electrodes (stainless steel cathode and graphite anode) and a solid liquid membrane (SLM). SLM is composed of supporting polypropylene membrane impregnated with1-octanol as an organic solvent and bis(2-ethylhexyl) phosphate (DEHP) as a carrier. The effects of process parameters such as applied voltage, pH and copper concentration on the removal of copper were investigated. Response surface methodology (RSM) was applied to optimise these parameters and their interactions. Results indicated that pH has the major effect on the removal of copper, followed by applied voltage. The squared interaction term in the RSM model has the highest contribution (70.5%), followed by the linear term, thereby confirming the significant interaction among the variables. The optimum conditions include an applied voltage of 60V, pH of 5.18 and initial copper concentration of 5 ppm, which yield to a removal efficiency of 80% after 6 hours of operation. The findings demonstrate the use of electromembrane extraction as an efficient method for the removal of heavy metals and provide valuable insights for future application to other environmental and water treatment processes. Keywords: electromembrane extraction, copper; SLM; RSM, DEHP;1-octanol 1. Introduction Increasing environment pollution in the international ecosystem is a major concern that should be resolved [1]. Main contaminants of water are heavy metals, which cause several public health issues. Most heavy metals are present in the industrial wastewater and are highly resistant to degradation [2,3]. In addition to entering the body through the skin, these metals could enter through food and drink [4,5]. They are poisonous and can harm the brain and central nervous system as well as the kidneys, liver, lungs, blood and other essential organs [6]. Copper is a heavy metal that generates serious environmental hazards [6]. Wastewater from metal finishing, textile and electronic industries may contain copper at concentrations up to 500 mg/L. Based on the global environmental regulations, this concentration is higher than the permissible level; hence, wastewater containing copper must be treated before being discharged into the environment [7]. mailto:noor.jabbar2011d@coeng.uobaghdad.edu.iq mailto:Hussain-altemmimi@coeng.uobaghdad.edu.iq mailto:ali.abbar@kecbu.uobaghdad.edu.iq mailto:hazzawie2@yahoo.com https://doi.org/10.22153/kej.2024.07.001 Noor R. Kadhim Al-Khwarizmi Engineering Journal, Vol. 20, No.3, P.P. 1- 10 (2024) 2 Copper ions are removed using different methods, such as adsorption, chemical precipitation, membrane separation and electrochemical methods (electrocoagulation and/or cathodic deposition) [8]. Each method has its own advantages and disadvantages, but most of them can be costly and incapable of treating low concentrations of copper ions [8,9]. Recently, membrane extraction technology is regarded as an effective separation technique. It combines the advantages of extraction and membrane separation. In this method, heavy metals can diffuse from a high-concentration chamber (donor phase) through a membrane to a low- concentration chamber (acceptor phase) as a result of concentration difference across the membrane. Liquid–liquid extraction underlies the operation of liquid membrane (LM) technique and exhibits advantages such as excellent selectivity, energy efficiency and environmental protection [10]. This method offers a high extraction efficiency for metal ions. Different types of membranes include bulk liquid membranes (BLM), emulsion liquid membranes (ELM), supported liquid membranes (SLM) and polymer inclusion membranes (PIM) [11,12]. SLM is based on solid polymer materials and does not require the extensive use of extraction agents or intricate steps involved in traditional approaches, such as demulsification and emulsion preparation. Its advantages in selectively separating and enriching low concentrations of heavy metals in high-matrix background are numerous, energy-efficient, and environmentally friendly [13]. Fast heavy metal transport from the donor phase to the acceptor phase can occur when an electric field is applied over SLM [14]. The apparatus is known as electromembrane extraction (EME), where the donor and acceptor phases are submerged in two platinum electrodes that are powered by a power source [13,14]. The two types of EME used for extraction of heavy metals are hollow fibre and flat membrane, and the latter is preferred for scale up [15]. In the removal of heavy metals, EME is applied to remove diverse cations for different solutions [16,17]. However, literature on the application of flat membranes for removing copper is limited. Moreover, the most suitable type for scale up is rare and has limited supply. This work aims to apply a flat EME for removing copper from an aqueous medium on a laboratory scale. A brand-new two-chamber cell with a flat sheet membrane was adopted as an easy and cost-effective cell design because it used inexpensive electrodes (graphite anode and stainless-steel cathode) and SLM, instead of platinum electrodes. The effect of several parameters including applied voltage, donor pH and initial copper concentration on removal efficiency were investigated through response surface methodology (RSM). In this powerful experimental design, the interactions among variables can be recognised as impossible to be determined by the traditional one factor at one time approach, which requires a high number of runs. 2. Experimental 2.1 Chemicals All chemicals used were of analytical grade. CuNO3 was purchased from Central Thomas Baker, Mumbai, India. Deionised water was used as solvent to create acceptor and donor phase solutions. 1. Octanol was utilised as organic solvent in the liquid membrane and was obtained from Central Drug House, Delhi, India. Bis(2- Ethylhexyl) phosphate (DEHP) was purchased from Shanghai Macklin Biochemical and used as the carrier in SLM (Shanghai, China). A polypropylene membrane sheet with a pore diameter of 0.1 microns and a thickness of 0.18– 0.22 mm was utilised as supportive liquid membrane. It was supplied by Jian City Qing Feng Equipment Material Co. in China. HCl and NaOH were provided by Thomas Baker, Ambernath, India. 2.2 Electromembrane extraction system Figure 1 depicts the electrochemical apparatus, which consists of two symmetrical chambers with a volume of 137.44 cm3 each. The first chamber was utilised as a donor phase, while the second chamber was utilised as an acceptor phase and had an active volume of 100 cm3. Both chambers were 5 cm in diameter and 7 cm in length and had a lateral channel (3 cm in diameter and 3 cm in length) positioned 2 cm above the chamber base. Each chamber has a Teflon cup (4.8 cm in diameter and 10 mm in thickness). Graphite was adopted as the anode because it facilitates water decomposition by anodic oxidation[18]. Stainless steel, which is less expensive than platinum electrodes, was used as a cathodic material. SLM is composed of polypropylene membrane sheet with an active surface area of 7 cm2 and was impregnated for 15 minutes with 1-octanol solvent and a suitable carrier. SLM was fixed in the space between the chambers and secured via two Teflon Noor R. Kadhim Al-Khwarizmi Engineering Journal, Vol. 20, No.3, P.P. 1- 10 (2024) 3 cups, four screws and netting. Two magnetic stirrers (Metrohm AG Herisau, Switzerland, Type: 18490010) were placed inside the chambers for mixing at 1000 rpm. The EME was run at various applied voltages using a UNI-T/UTP3000 power supply (Hong Kong). The exact current value was determined with a UNI-T connected ammeter (Kowloon, Hong Kong) [15]. Magnetic stirrer Magnetic stirrer Power Supply Ammeter Donor Chamber Accepter Chamber Silicone Rubber Membrane Stainless steel Cathode Graphite Anode Fig. 1. EME system 2.3 Analysis and measurements The samples were analysed using an AA-7000 atomic absorption spectroscope (SHIMADZU, Japan) to ascertain the concentration of copper ions. The efficiency of copper removal was evaluated using Eq. 1 [18]: 𝑅𝐸(%) = 𝐶𝑖−𝐶𝑓 𝐶𝑖 × 100 … (1) where Ci is the initial concentration of Cu in part per million, and Cf is the final concentration of Cu measured after completing the run at time Δt. In this work, the electrolysis time was set to 6 hours based on a preliminary run conducted at the midpoint, during which a jump did not occur in the current. This finding demonstrated that the liquid membrane did not begin to leak into the solution [19]. 2.4 Experimental design RSM based on Box–Behnken design (BBD) is a widely used experimental tool to correlate process variables and response in statistical and mathematical settings. Compared with the conventional one factor at a time strategy, RSM requires fewer runs, resulting in an experimental program that is more economical and time efficient [20]. BBD, which is based on three-level parameters, was used to optimise the process parameters. RE percent was used as response, and process variables included voltage (X1), pH (X2) and initial copper concentration (X3). The maximum value of each process variable was set at (+1), the middle value was set at (0) and the lower value was set at (-1) [21]. The process variables and their chosen values are shown in Table 1. An array of runs based on BBD was created using Minitab- 17 software. Table 1, Process factors (coded and real levels). Process factors Range in BBD Coded levels Low(-1) Middle(0) High(+1) Applied voltage (Volt),X1 20 40 60 pH,X2 3 5 7 Concentration of copper (ppm),X3 5 15 25 Noor R. Kadhim Al-Khwarizmi Engineering Journal, Vol. 20, No.3, P.P. 1- 10 (2024) 4 A quadratic equation that relates the process factors with responses is shown in Eq. 2[22]. 𝑌 = 𝑎0 + ∑ 𝑎𝑖 𝑥𝑖 + ∑ 𝑎𝑖𝑖 𝑥𝑖 2 + ∑ 𝑎𝑖𝑗𝑥𝑖𝑥𝑗 …(2) The intercept term is 𝑎0, and j and i stand for the index numbers for the patterns. ai and aii represent the first-order (linear) and second-order effects. The interaction effects are represented by aij. the coded process factors are 𝑥1.,𝑥2..,𝑥𝑘. Finally, Y is the response term. Based on ANOVA, a regression coefficient (𝑅2) can be used to evaluate the fitting of Eq. 2. 3. Results and Discussion 3.1 Statistical results RSM with BBD was used to simulate and optimise the removal of copper by EME. Fifteen runs were completed, and the results are displayed in Table 2. A second-order quadratic model was built using RSM in terms of real values of the parameters (Eq. 3). Table 2 also presents the anticipated values of RE derived from Equation 3. 𝑅𝐸% = −37.62 + 0.134 𝑥1 + 44.02 𝑥2 − 2.062 𝑥3 + 0.00301 𝑥1 ∗ 𝑥1 − 4.050 𝑥2 ∗ 𝑥2 + 0.04931 𝑥3 ∗ 𝑥3 − 0.0378 𝑥1 ∗ 𝑥2 + 0.00165 𝑥1 ∗ 𝑥3 + 0.0336𝑥2 ∗ 𝑥3 …(3) The results showed that RE% ranged from 40.98% to 80%. As a preliminary evaluation of the effects of parameters, increasing the applied voltage increased RE% (compared between runs 5 and 12). Increasing the concentration of copper decreased RE% (compared between runs 5 and 11). Increasing the pH from 3 to 7 led to higher removal of RE% (compared between runs 6 and 2). However, the real effects of these parameters and their interaction were only assessed using ANOVA combined with response surface plots. Table 2, Optimisation of copper removal by RSM Run Order Pt Type Blocks Applied potential (V) pH Initial concentration (ppm) RE% Actual Predicted 1 2 1 40 7 5 64.3 64.080 2 2 1 60 7 15 61.03 60.241 3 0 1 40 5 15 67.53 67.510 4 0 1 40 5 15 70 67.510 5 2 1 60 5 5 80 81.009 6 2 1 60 3 15 53.33 53.209 7 2 1 40 3 5 56.26 55.373 8 2 1 20 3 15 40.98 41.769 9 2 1 20 7 15 54.72 54.841 10 2 1 40 3 25 46.84 47.060 11 2 1 60 5 25 74.8 74.701 12 2 1 20 5 5 73.15 73.249 13 0 1 40 5 15 65 67.510 14 2 1 40 7 25 57.57 58.458 15 2 1 20 5 25 66.63 65.621 ANOVA was used to assess the acceptability of BBD. Fisher’s F and P tests were adopted to establish the significance of the model and its parameters [22]. In general, a high significance for the coefficient terms is indicated by large F values and small p values [23]. Table 3 presents the ANOVA for the response surface model. Contr. % indicates the percentage contribution of each variable; DF denotes the degree of freedom of the model and its parameters; the terms “the adjusted mean of square (Adj. MS)”, “adjusted sum of square (Adj. SS)” and “sum of square (Seq. SS)” represent the statistical terms for the model. The estimated F value of 50.09 and P value of 0.0001 indicated the high significance of the regression model. The regression R2 was 0.989 which is statistically significant and only (0.011) of the total variance not confirmed by the model [24]. Noor R. Kadhim Al-Khwarizmi Engineering Journal, Vol. 20, No.3, P.P. 1- 10 (2024) 5 Table 3, Analysis of variance for copper removal 𝐒𝐨𝐮𝐫𝐜𝐞 𝐃𝐅 𝐒𝐞𝐪. 𝐬𝐬 𝐂𝐨𝐧𝐭𝐫. % 𝐀𝐝𝐣. 𝐬𝐬 𝐀𝐝𝐣. 𝐌𝐬 F-value P-value Model 9 1578.01 98.90 1578.01 175.335 50.09 0.0001 Linear 3 440.99 27.64 440.99 146.997 42.00 0.001 (X1) 1 141.79 8.89 141.79 141.793 40.51 0.001 (X2) 1 202.11 12.67 202.11 202.106 57.74 0.001 (X3) 1 97.09 6.09 97.09 97.092 27.74 0.003 Square 3 1125.66 70.55 1125.66 375.218 107.20 0.0001 "X1 ∗ X1" 1 15.06 0.94 5.35 5.350 1.53 0.271 "X2 ∗ X2" 1 1020.81 63.98 968.86 968.860 276.80 0.0001 "X3 ∗ X3" 1 89.79 5.63 89.79 89.787 25.65 0.004 2-Way lnter. 3 11.37 0.71 11.37 3.788 1.08 0.436 X1 ∗ X2 1 9.12 0.57 9.12 9.120 2.61 0.167 X1 ∗ X3 1 0.44 0.03 0.44 0.436 0.12 0.739 X2 ∗ X3 1 1.81 0.11 1.81 1.809 0.52 0.504 Error 5 17.50 1.10 17.50 3.500 Lack of Fit 3 5.00 0.31 5.00 1.667 0.27 0.847 "Pure-Error" 2 12.50 0.78 12.50 6.250 Total 14 1595.51 100.00 Model-summary S. R2 R2(adj.) PRESS R2(pred.) 1.87088 98.90% 96.93% 108.133 93.22% Table 3 shows that pH has a high contribution to the linear part of the model, followed by applied voltage and initial copper concentration. However, the model’s second term showed a significant contribution of pH with high contribution of 63.98%. The applied voltage had a small impact with a contribution of 0.94%. The interaction term was the most dominant in the model, confirming that the relation between removal efficiency and operating parameters is not linear and a significant interaction exists. In this experiment, the lack of fit was statistically non-significant. The model produced reliable predictions that match well with the response values [25]. 3.2 Influence of Process Factors on copper removal Efficiency The effects of particular variables on responses can be seen visually with the use of RSM graphics. The effects of applied voltage and initial copper concentration on the removal efficiency of copper at a constant pH of 5 are displayed in Figures (2-a and 2-b). Figure 2-a shows the surface response plot, while Figure 2-b shows the contour plot. The surface plot verifies that for all copper concentrations tested, an increase in RE percent occurs as the applied voltage increases, and the relationship appears to be linear. This phenomenon may be explained by the enhancement in the mass transfer of copper across the membrane between the two phases due to the formation of more Cu (II)-DEEHPA complexes inside SLM, where their movements increased by applying higher voltages. Similar findings were published by Meng et al. in 2021 [26] when they used EME for cadmium removal. They also discovered that 6.0 V was the optimal applied voltage. Similar observation was found by Kadhim et al. in 2023[9] for the removal of zinc by using EME with SLM. (a) 6 12 18 56 07 57 20 42 04 60 57 80 RE% ntial (V)etop deilppA ecnocI liatin tration(ppm)n Noor R. Kadhim Al-Khwarizmi Engineering Journal, Vol. 20, No.3, P.P. 1- 10 (2024) 6 (b) Fig. 2. Effect of applied potential and initial concentration on copper removal efficiency: a) surface plot, b) contour plot (hold: pH=5) The percentage of RE decreased when the initial copper concentration decreased from 25 ppm to 15 ppm, after which it began to gradually increase as the concentration further decreased down to 5 ppm. An exponential relationship was found between RE percent and starting concentration when the copper concentration decreased from 5 to 15 ppm. These findings are consistent with the findings of Swain et al. (2007) [27] and are true even when in the absence of an electrical current. This work also demonstrated how well the chosen carrier, DEHP, facilitated the diffusion-driven passage of copper ions across the membrane. The results provide evidence for the effectiveness and suitability of DEHP as a carrier for EME [27]. Based on the associated contour plots, an area with an applied voltage between 58 and 60 V and an initial concentration of (5–6 ppm) led to 80% RE. Figures 3-a and b show the effects of applied voltage and pH at an initial copper concentration of 15 ppm. The percentage of RE increased as the pH increased from 3 to 5 and then started to decrease thereafter (Figure 3-a). These results imply that the most apparent effective copper–DEHP bonding occurred at pH 5, suggesting that this is the ideal pH in 1-octanol [28]. Interestingly, DEHP undergoes more protonation when the pH is below 5, preventing it from effectively interacting with ions [26]. At high pH values, Cu (II) tends to form complex species, which hinders its passage across the membrane. Previous studies confirmed that releasing heavy metals into an acidic medium is better than releasing it in a neutral and/or an alkaline medium [28]. Meng et al. [26] reported the same behaviour in removal of Cd. Kadhim et al. [9] also stated similar behaviour in the removal of zinc using EME with SLM. Davarani et al. [15] found that an alkaline medium is preferred for the removal of Cd2+, Zn2+ and Co2+ by using membrane containing mixed carriers (DEHP and TEHP). The corresponding contour plots (3-b) indicate that RE% ≥70% occurred in a limited area with an applied voltage of 50–60 V and a pH range of 4.5– 5.5. (a) (b) Fig. 3. Effect of applied potential and pH on copper removal efficiency: a) surface plot, b) contour plot (Hold value: copper intail concentration of 15 ppm) Figures (4-a and b) shows the effect of initial concentration of copper and pH on RE%. A clear interaction was found between the pH and concentration of copper. In this regard, the ideal conditions differ from those found when applying the conventional one component at a time method. The corresponding contour plot (Fig. 4-b) shows that RE ≥75% exists within a limited region bounded by initial concentration ranging from 5 Initail concentration(ppm) A p p li e d p o te n ti a l (V ) 252015105 60 50 40 30 20 > – – – – – – < 65.0 65.0 67.5 67.5 70.0 70.0 72.5 72.5 75.0 75.0 77.5 77.5 80.0 80.0 RE% 0.3 4.5 6.0 04 50 60 02 7.5 04 60 07 %ER )V( laitnetop deilppA Hp pH A p p li e d p o te n ti a l (V ) 76543 60 50 40 30 20 > – – – – – < 45 45 50 50 55 55 60 60 65 65 70 70 RE% Noor R. Kadhim Al-Khwarizmi Engineering Journal, Vol. 20, No.3, P.P. 1- 10 (2024) 7 ppm to 6 ppm and pH from 4.5 to 5.5). Hence, applying optimisation techniques would lead to the optimum value within the limits established. (b) Fig. 4. Effect of pH and initial concentration on copper removal efficiency: a) surface plot, b) contour plot 3.3 Optimisation and confirmation test Optimisation is a crucial step used to determine the optimum conditions that yield high removal with low energy consumption in electrochemical systems. During optimisation of any system, many factors should be considered to maximise desirability function (DF) and reach the intended outcome [28]. Options for optimisation were none, within the limit or maximise and minimize. With DF=1.0, the RE objective was set to ‘maximum’. After optimisation, the outcomes are displayed in Table 4. A confirmative run was carried out to verify the optimal conditions (Table 5). A RE of 80% was attained after electrolysis for 6 hours, starting with a copper concentration of 5 ppm and pH of 5.18 at 60 V. Consequently, BBD is helpful and efficient in determining the impacts of process variables and increasing the removal efficiency to an expected level. Table 4, Process parameter optimisation for copper removal 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐞 𝐆𝐨𝐚𝐥 𝐋𝐨𝐰𝐞𝐫 𝐓𝐚𝐫𝐠𝐞𝐭 𝐔𝐩𝐩𝐞𝐫 𝐖𝐞𝐢𝐠𝐡𝐭 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐜𝐞 𝐑𝐄 (%) 𝒎𝒂𝒙𝒊𝒎𝒖𝒎 40.98 Maximum 80 1 1 Solution: Parameters Results E (Volt) pH Cu2+ (ppm) RE (%) Fit DF SE Fit 95% CI 95% PI 60 5.18182 5 81.1334 1 1.62 (76.96, 85.31) (74.77, 87.50) Table 5, Confirmative run 6 12 18 50 60 70 4.5 0.3 24 0.6 4.5 5.7 70 80 %ER Hp )mpp(noitartnecnoc liatinI Initail concentration(ppm) p H 252015105 7 6 5 4 3 > – – – – – < 50 50 55 55 60 60 65 65 70 70 75 75 RE% Run E (Volt) pH Time (hr) Cu2+ (ppm) RE (%) Initial Final 1 60 5.18 6 5 1.6 80 Noor R. Kadhim Al-Khwarizmi Engineering Journal, Vol. 20, No.3, P.P. 1- 10 (2024) 8 The concentration of copper decreased to 0.05 ppm by refreshing the membrane with a new solvent and carrier. 4. Conclusions EME was successful in removing copper from an aqueous solution at high efficiency. The studied parameters were applied voltage, pH and copper concentration. RSM was used to determine the interactions among process parameters. Results revealed that the squared interaction had the most contribution to RE (70.5%), followed by the linear term while two-way interaction had no significant effect. pH had the greatest influence on removal. The optimum conditions were an applied voltage of 60, pH of 5.18 and an initial copper concentration of 5 ppm. The removal efficiency of 80% was achieved during 6 hours of operation when the copper concentration was reduced to 1.6 ppm. This work confirms the vital role of EME for removing heavy metals. Acknowledgment The technical personnel of the University of Baghdad’s Environmental Engineering Department is acknowledged by the authors for their invaluable help and support in this work. References [1] A. Kot and J. Namiesńik, “The role of speciation in analytical chemistry,” TrAC Trends in Analytical Chemistry, vol. 19, no. 2–3, pp. 69–79, 2000. [2] S. Mohan and G. Sreelakshmi, “Fixed bed column study for heavy metal removal using phosphate treated rice husk,” Journal of hazardous materials, vol. 153, no. 1–2, pp. 75–82, 2008. [3] A. Demirbas, “Adsorption of lead and cadmium ions in aqueous solutions onto modified lignin from alkali glycerol delignication,” Journal of hazardous materials, vol. 109, no. 1–3, pp. 221–226, 2004. [4] V. J. Inglezakis, M. D. Loizidou, and H. P. Grigoropoulou, “Ion exchange of Pb2+, Cu2+, Fe3+, and Cr3+ on natural clinoptilolite: selectivity determination and influence of acidity on metal uptake,” Journal of Colloid and Interface Science, vol. 261, no. 1, pp. 49– 54, 2003. [5] J. Rivera-Utrilla and M. Sanchez-Polo, “Adsorption of Cr (III) on ozonised activated carbon. Importance of Cπ—cation interactions,” Water Research, vol. 37, no. 14, pp. 3335–3340, 2003. [6] R. Verma and P. Dwivedi, “Heavy metal water pollution-A case study,” Recent Research in Science and Technology, vol. 5, no. 5, 2013. [7] K. Dermentzis, A. Davidis, D. Papadopoulou, A. Christoforidis, and K. Ouzounis, “Copper removal from industrial wastewaters by means of electrostatic shielding driven electrodeionization,” Journal of Engineering Science and Technology Review, vol. 2, no. 1, pp. 131–136, Jun. 2009, doi: 10.25103/jestr.021.24. [8] C. Ahmed Basha, N. S. Bhadrinarayana, N. Anantharaman, and K. M. Meera Sheriffa Begum, “Heavy metal removal from copper smelting effluent using electrochemical cylindrical flow reactor,” Journal of Hazardous Materials, vol. 152, no. 1, pp. 71– 78, Mar. 2008, doi: 10.1016/j.jhazmat.2007.06.069. [9] N. R. Kadhim, H. M.Flayeh, and A.H. Abbar, "Zinc (II) removal from simulated wastewater by electro-membrane extraction approach: Adopting an electrolysis cell with a flat sheet supported liquid membrane", Journal of Electrochemical Science and Engineering, vol.13,no.6, pp.1097-1112, 2023. [10] M. Gheju, I. Balcu, and G. Mosoarca, “Removal of Cr (VI) from aqueous solutions by adsorption on MnO2,” Journal of hazardous materials, vol. 310, pp. 270–277, 2016. [11] C. Onac, A. Kaya, D. Ataman, N. A. Gunduz, and H. K. Alpoguz, “The removal of Cr (VI) through polymeric supported liquid membrane by using calix [4] arene as a carrier,” Chinese journal of chemical engineering, vol. 27, no. 1, pp. 85–91, 2019. [12] X. Meng, Y. Song, Y. Lv, X. Xin, T. Ren, and X. Wang, “Study on stable mass transfer and enrichment of phenol by 1- octanol/kerosene/polyvinyl chloride polymer inclusion membrane,” Environmental Pollution, vol. 253, pp. 1100–1106, 2019. [13] A. Garcia-Rodríguez, V. Matamoros, S. D. Kolev, and C. Fontàs, “Development of a polymer inclusion membrane (PIM) for the preconcentration of antibiotics in environmental water samples,” Journal of Membrane Science, vol. 492, pp. 32–39, 2015. Noor R. Kadhim Al-Khwarizmi Engineering Journal, Vol. 20, No.3, P.P. 1- 10 (2024) 9 [14] A. Gjelstad, K. E. Rasmussen, and S. Pedersen-Bjergaard, “Electrokinetic migration across artificial liquid membranes,” Journal of Chromatography A, vol. 1124, no. 1–2, pp. 29–34, Aug. 2006, doi: 10.1016/j.chroma.2006.04.039. [15] S. S. Hosseiny Davarani, N. Sheikhi, S. Nojavan, R. Ansari, and S. Mansori, “Electromembrane extraction of heavy metal cations from aqueous media based on flat membrane: method transfer from hollow fiber to flat membrane,” Analytical Methods, vol. 7, no. 6, pp. 2680–2686, 2015, doi: 10.1039/C5AY00243E. [16] C. Basheer, S. H. Tan, and H. K. Lee, “Extraction of lead ions by electromembrane isolation,” Journal of Chromatography A, vol. 1213, no. 1, pp. 14–18, Dec. 2008, doi: 10.1016/j.chroma.2008.10.041. [17] L. Strieglerová, P. Kubáň, and P. Boček, “Electromembrane extraction of amino acids from body fluids followed by capillary electrophoresis with capacitively coupled contactless conductivity detection,” Journal of Chromatography A, vol. 1218, no. 37, pp. 6248–6255, Sep. 2011, doi: 10.1016/j.chroma.2011.07.011. [18] Z. A. Kadhim and A. H. Abbar, “Nickel removal from simulated wastewater using a novel bio-electrochemical cell with packed bed rotating cylinder cathode,” Chemical Engineering Research and Design, vol. 190, pp. 157–173, Feb. 2023, doi: 10.1016/j.cherd.2022.12.025. [19] X. Meng, J. Li, Y. Lv, Y. Feng, and Y. Zhong, “Electro-membrane extraction of cadmium(II) by bis(2-ethylhexyl) phosphate/kerosene/polyvinyl chloride polymer inclusion membrane,” Journal of Hazardous Materials, vol. 386, p. 121990, Mar. 2020, doi: 10.1016/j.jhazmat.2019.121990. [20] H. Ceylan, S. Kubilay, N. Aktas, and N. Sahiner, “An approach for prediction of optimum reaction conditions for laccase- catalyzed bio-transformation of 1-naphthol by response surface methodology (RSM),” Bioresource technology, vol. 99, no. 6, pp. 2025–2031, 2008. [21] A. El-Ghenymy, S. Garcia-Segura, R. M. Rodríguez, E. Brillas, M. S. El Begrani, and B. A. Abdelouahid, “Optimization of the electro-Fenton and solar photoelectro-Fenton treatments of sulfanilic acid solutions using a pre-pilot flow plant by response surface methodology,” Journal of hazardous materials, vol. 221, pp. 288–297, 2012. [22] J. Segurola, N. S. Allen, M. Edge, and A. Mc Mahon, “Design of eutectic photoinitiator blends for UV/visible curable acrylated printing inks and coatings,” Progress in Organic Coatings, vol. 37, no. 1–2, pp. 23– 37, 1999. [23] R. Arunachalam and G. Annadurai, “Optimized response surface methodology for adsorption of dyestuff from aqueous solution.,” Journal of environmental science and technology, vol. 4, no. 1, pp. 65–72, 2011. [24] Q. Zhao et al., “Optimization of ultrasonic circulating extraction of polysaccharides from Asparagus officinalis using response surface methodology,” International journal of biological macromolecules, vol. 49, no. 2, pp. 181–187, 2011. [25] E. Ahmadi et al., “Synergistic effects of α- Fe2O3-TiO2 and Na2S2O8 on the performance of a non-thermal plasma reactor as a novel catalytic oxidation process for dimethyl phthalate degradation,” Separation and Purification Technology, vol. 250, p. 117185, 2020. [26] X. Meng, Y. Long, Y. Tian, W. Li, T. Liu, and S. Huo, “Electro-membrane extraction of lithium with D2EHPA/TBP compound extractant,” Hydrometallurgy, vol. 202, p. 105615, 2021. [27] B. Swain, J. Jeong, J. Lee, and G.-H. Lee, “Extraction of Co(II) by supported liquid membrane and solvent extraction using Cyanex 272 as an extractant: A comparison study,” Journal of Membrane Science, vol. 288, no. 1–2, pp. 139–148, Feb. 2007, doi: 10.1016/j.memsci.2006.11.012. [28] W. A.Khan, M. B.Arain, H. Bibi, M.Tuzen, N. Shah, and A. Zada, "Selective electromembrane extraction and sensitive colorimetric detection of copper (II)" Zeitschrift für Physikalische Chemie, vol. 235, no.9, pp.1113-1128, 2021. [29] W. Feitknecht and P. Schindler, “Solubility constants of metal oxides, metal hydroxides and metal hydroxide salts in aqueous solution,” Pure and Applied Chemistry, vol. 6, no. 2, pp. 125–206, Jan. 1963, doi: 10.1351/pac196306020125. Noor R. Kadhim Al-Khwarizmi Engineering Journal, Vol. 20, No.3, P.P. 1- 10 (2024) 10 رف الص االستخالص الكهروكيميائي باستخدام الغشاء السائل المدعوم إلزالة النحاس من مياه االصطناعية: التحسين من خالل منهجية سطح االستجابة ****، حسن العزاوي***، علي حسين عبار **حسين فليح مجيد ،*نور راغب كاظم جامعة بغداد، بغداد، العراققسم هندسة البيئة، كلية الهندسة، *،** الهندسة الخوارزمي، جامعة بغداد، بغداد، العراق ةميائية االحيائية، كلييقسم الهندسة الك*** جامعة لنكولن، ماليزيا**** noor.jabbar2011d@coeng.uobaghdad.edu.iqالبريد االلكتروني:* altemmimi@coeng.uobaghdad.edu.iq-Hussainالبريد االلكتروني:** ali.abbar@kecbu.uobaghdad.edu.iqالبريد االلكتروني:*** hazzawie2@yahoo.comالبريد االلكتروني:**** المستخلص ستخدام الخلية ( كنهج جديد تم فيه اEMEدراسة إزالة النحاس من محلول مائي باستخدام استخالص الغشاء الكهربائي ) تفي هذه الدراسة، تم (.SLMل صلب )شاء سائغ فضالً عنالكهروكيميائية ذات الغرفتين. تتكون الخلية من قطبين كهربائيين )كاثود الفوالذ المقاوم للصدأ وأنود الجرافيت( راسة تأثير دوتمت ( كحامل. DEHPيل هكسيل( )إيث-2أوكتانول كمذيب عضوي وفوسفات مكرر )-1من غشاء بولي بروبيلين داعم مشرب بـ SLMيتكون إليجاد الظروف (RSMتم تطبيق منهجية سطح االستجابة )وإزالة النحاس. فيمعلمات العملية مثل الجهد المطبق، ودرجة الحموضة، وتركيز النحاس تلك مصطلح د المطبق. يمليه الجهيإزالة النحاس فيه تأثير كبير لهذه المعلمات وكذلك التفاعالت فيما بينها. أظهرت النتائج أن الرقم الهيدروجيني ل األمثل مثلكانت الظروف األو٪ يليه المصطلح الخطي الذي يؤكد وجود تفاعل كبير بين المتغيرات. 70.5بنسبة شاركةأكبر م RSMالتفاعل التربيعي في نموذج ً فولت 60هي الجهد الكهربي المطبق 6% خالل 80لة قدرها تم تحقيق كفاءة إزا إذجزء في المليون 5، وتركيز النحاس األولي 5.18، ودرجة الحموضة ا لمستقبلي مة للتطبيق ارؤى قي ساعات من التشغيل. توضح نتائج هذا العمل نشاط استخراج الغشاء الكهربائي كوسيلة فعالة إلزالة المعادن الثقيلة التي توفر في العمليات البيئية ومعالجة المياه األخرى.لهذه الطريقة mailto:noor.jabbar2011d@coeng.uobaghdad.edu.iq mailto:Hussain-altemmimi@coeng.uobaghdad.edu.iq mailto:ali.abbar@kecbu.uobaghdad.edu.iq mailto:hazzawie2@yahoo.com