화학공학소재연구정보센터
홈 로그인 로그아웃 연락처 사이트맵
Journal of Industrial and Engineering Chemistry, Vol.31, 61-73, November, 2015
DOI10.1016/j.jiec.2015.06.008  Export Citation
Identification and optimization of key parameters in preparation of thin film composite membrane for water desalination using multi-step statistical method
H. Azizi Namaghi1, A. Haghighi Asl1, †, and M. Pourafshari Chenar2, 3
  • 1Faculty of Chemical, Petroleum and Gas Engineering, Semnan University, Semnan, Iran
  • 2Chemical Engineering Department, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
  • 3Membrane Processes and Membrane Research Center, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
E-mail:
This study seeks to address the influence of critical variables including casting thickness, polysulfone (PSf) concentration, m-phenylenediamine soaking time, curing time, curing temperature and interfacial polymerization (IP) time in the preparation of thin film composite (TFC) membrane. To properly track the effects of each parameter as well as their interactions on the performance of manufactured membranes, totally 22 experiments were conducted and evaluated by fractional factorial design (FFD). The results showed that due to the complexity of variables, the preliminary models based on the factorial experiments were not able to explain the response curvature. Therefore, a response surface methodology (RSM) based on Box.Behnken design (BBD) was tested to provide a quadratic model, by which the predicted responses were compared with the experimental ones. By the use of RSM, various contour and three-dimensional (3D) plots were constructed to predict optimal levels of the variables. All considered parameters have shown a significant effect on the performance of TFC membrane. The order of significance for permeate flux and rejection rate was ‘‘curing temperature > polysulfone concentra-tion > interfacial polymerization’’ and ‘‘interfacial polymerization > curing temperature > polysulfone concentration’’, respectively. The predicted values were in reasonable agreement with the experimental data, confirming the high predictability of the applied model.
Keywords:Thin film composite membrane;Fractional factorial design;Box-Behnken design;Permeate flux;Rejection rate
  1. Greenlee LF, Lawler DF, Freeman BD, Marrot B, Moulin P, Water Res., 43, 2317 (2009)
  2. Lee KP, Arnot TC, Mattia D, J. Membr. Sci., 370(1-2), 1 (2011)
  3. Eltawil MA, Zhengming Z, Yuan L, Twelfth International Water Technology Conference, IWTC12, 2008, p. 1.
  4. Li NN, Fane AG, Ho WSW, Matsuura T, Advanced Membrane Technology and Application, John Wiley & Sons, New Jersey, 2008.
  5. Ghosh AK, Hoek EMV, J. Membr. Sci., 336(1-2), 140 (2009)
  6. Abu Tarboush BJ, Rana D, Matsuura T, Arafat HA, Narbaitz RM, J. Membr. Sci., 325(1), 166 (2008)
  7. Wu CR, Zhang SH, Yang DL, Wei J, Yan C, Jian XG, J. Membr. Sci., 279(1-2), 238 (2006)
  8. Matsuura T, Desalination, 134(1-3), 47 (2001)
  9. Rana D, Kim Y, Matsuura T, Arafat HA, J. Membr. Sci., 367(1-2), 110 (2011)
  10. Misdan N, Lau WJ, Ismail AF, Matsuura T, Rana D, Desalination, 344, 198 (2014)
  11. Kaur S, Sundarrajan S, Rana D, Matsuura T, Ramakrishna S, J. Membr. Sci., 392-393, 101 (2012)
  12. Rana D, Narbaitz RM, Garand-Sheridan AM, Westgate A, Matsuura T, Tabe S, Jasim SY, J. Mater. Chem. A, 2, 10059 (2014)
  13. Matsuura T, Rana D, Qtaishat MR, Singh G, Encyclopedia of Desalination and Water Resources: Membrane Processes, vol. II. Available from (www.desware.-net/Sample-Chapters/D05/E6-144-46-00.pdf).
  14. Ghosh AK, Jeong BH, Huang XF, Hoek EMV, J. Membr. Sci., 311(1-2), 34 (2008)
  15. Rao AP, Desai NV, Rangarajan R, J. Membr. Sci., 124(2), 263 (1997)
  16. Xie W, Geise GM, Freeman BD, Lee HS, Byun G, McGrath JE, J. Membr. Sci., 403-404, 152 (2012)
  17. Gheshlaghi R, Scharer JM, Moo-Young M, Douglas PL, Anal. Biochem., 383, 93 (2008)
  18. Beydokhty AK, Namaghi HA, Heris SZ, Numer. Heat Transf. B-Fundam., 64, 480 (2013)
  19. Rahmanian B, Pakizeh M, Mansoori SAA, Abedini R, J. Hazard. Mater., 187(1-3), 67 (2011)
  20. Shojaeimehr T, Rahimpour F, Khadivi MA, Sadeghi M, J. Ind. Eng. Chem., 20(3), 870 (2014)
  21. Khayet M, Cojocaru C, Essalhi M, J. Membr. Sci., 368(1-2), 202 (2011)
  22. Rahmanian B, Pakizeh M, Maskooki A, Korean J. Chem. Eng., 29(6), 804 (2012)
  23. Idris A, Kormin F, Noordin MY, Sep. Purif. Technol., 49(3), 271 (2006)
  24. Gheshlaghi R, Optimization of Recombinant Protein Production by a Fungal Host, (Ph.D. Thesis), University of Waterloo, Ontario, Canada, 2007.
  25. Lundstedt T, Seifert E, Abramo L, Thelin B, Nystrom A, Pettersen J, Bergman R, Chemometrics Intell. Lab. Syst., 42, 3 (1998)
  26. Montgomery DC, Runger GC, Applied Statistics and Probability for Engineers, 3rd ed., John Wiley & Sons, USA, 2002.
  27. Yuan M, Joseph VR, Lin Y, Technometrics, 49, 430 (2007)
  28. Raudenbush SW, Bryk AS, Hierachical Linear Models Applications and Data Analysis Methods, 2nd ed., Sage, California, 2002.
  29. Hafizi A, Ahmadpour A, Koolivand-Salooki M, Heravi MM, Bamoharram FF, J. Ind. Eng. Chem., 19(6), 1981 (2013)
  30. Onsekizoglu P, Bahceci KS, Acar J, J. Membr. Sci., 349(1-2), 225 (2010)
  31. FILMTEC Reverse Osmosis Membranes Technical Manual, Dow Water & Process Solutions. Available from (http://www.dow.com/webapps/lit/litorder.asp?file-path=liquidseps/pdfs/noreg/609-00071.pdf&pdf=true).
  32. Boubakri A, Hafiane A, Tahar Bouguecha SA, J. Ind. Eng. Chem., 20(5), 3163 (2014)
  33. Misdan N, Lau WJ, Ismail AF, Matsuura T, Desalination, 329, 9 (2013)