화학공학소재연구정보센터
홈 로그인 로그아웃 연락처 사이트맵
Journal of Industrial and Engineering Chemistry, Vol.25, 168-175, May, 2015
DOI10.1016/j.jiec.2014.10.029  Export Citation
Fabrication modeling of industrial CO2 ionic liquids absorber by artificial neural networks
Yadollah Abdollahi1, 2, †, Nor Asrina Sairi2, Mohamed Khereddine Aroua3, Hamid Reza Fard Masoumi4, Hossein Jahangirian5, and Yatimah Alias2
  • 1Material Synthesis and Characterization Laboratory, Institute of Advanced Technology, University Putra Malaysia, UPM, 43400 Serdang, Selangor, Malaysia
  • 2Chemistry Department, Faculty of Science, University of Malaya, 50603 Kuala Lumpur, Malaysia
  • 3Department of Chemical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia
  • 4Department of Chemistry, Faculty of Science, University Putra Malaysia, UPM, 43400 Serdang, Selangor, Malaysia
  • 5Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, UPM, 43400, Serdang, Selangor, Malaysia
E-mail:
The fabrication of industrial CO2 blended solution absorber was modeled by artificial neutral network. First the generated model had been statistically evaluated and then its ability of prediction was confirmed by validation test. The validated model was used to predict the desirable density and relative importance of the fabrication's effective variables. In conclusion, the importance included x[H2O], 36.18%, x[gua], 25.37%, x[MDEA], 25.34% and temperature, 13.11% which showed none of them is negligible as well as the density (g cm?3) was validated by further experiment that showed the actual density, 1.101, was quite close to the predicted value, 1.017.
Keywords:Optimization;CO2 capture;Separation;Greenhouse gases;Ionic liquid
  1. Abdollahi Y, Zakaria A, Sairi NA, CLEAN-Soil, Air, Water, 42(9), 1292 (2014)
  2. Metz B, Carbon Dioxide Capture and Storage: Special Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, England, 2005.
  3. Taniewski M, CLEAN-Soil, Air, Water, 36(4), 393 (2008)
  4. Choi MJ, Cho DH, CLEAN-Soil, Air, Water, 36(5-6), 426 (2008)
  5. Rochelle GT, Science, 325(5948), 1652 (2009)
  6. Li MH, Shen KP, J. Chem. Eng. Data, 37(3), 288 (1992)
  7. Sartori G, Savage DW, Ind. Eng. Chem. Fundam., 22(2), 239 (1983)
  8. Riesenfeld F, Brocoff J, Oil Gas J., 84(39), 20 (1986)
  9. Chakravarty T, Phukan UK, Weilund RH, Chem. Eng. Prog., 81(4), 60 (1985)
  10. Seo DJ, Hong WH, J. Chem. Eng. Data, 41(2), 258 (1996)
  11. Kabo GJ, Blokhin AV, Paulechka YU, Kabo AG, Shymanovich MP, Magee JW, J. Chem. Eng. Data, 49(3), 453 (2004)
  12. Weiland RH, Dingman JC, Cronin DB, Browning GJ, J. Chem. Eng. Data, 43(3), 378 (1998)
  13. Gutmann G, Gutmann V, The Donor-Acceptor Approach to Molecular Interactions, Plenum Press, New York, NY, 1978.
  14. Wasserscheid P, Welton T, Ionic Liquids in Synthesis, Wiley Online Library, Weinheim, 2008.
  15. Marsh KN, Boxall JA, Lichtenthaler R, Fluid Phase Equilib., 219(1), 93 (2004)
  16. Wang JF, Li CX, Shen C, Wang ZH, Fluid Phase Equilib., 279(2), 87 (2009)
  17. Fredlake CP, Muldoon MJ, Aki SN, Welton T, Brennecke JF, Phys. Chem. Chem. Phys., 6(13), 3280 (2004)
  18. Sairi NA, Yusoff R, Alias Y, Aroua MK, Fluid Phase Equilib., 300(1), 89 (2011)
  19. Abdollahi Y, Zakaria A, Sairi NA, CLEAN-Soil, Air, Water, 42(9), 1292 (2014)
  20. Salari D, Daneshvar N, Aghazadeh F, Khataee A, J. Hazard. Mater., 125(1), 205 (2005)
  21. Aber S, Amani-Ghadim AR, Mirzajani V, J. Hazard. Mater., 171(1-3), 484 (2009)
  22. Hader R, Park SH, Technometrics, 20(4), 413 (1978)
  23. Palasota JADSN, J. Chem. Educ., 69(7), 560 (1992)
  24. Abdollahi Y, Zakaria A, Matori KA, Shameli K, Jahangirian H, Rezayi M, Abdollahi T, Chem. Cent. J., 6(100), 1 (2012)
  25. Abdollahi Y, Zakaria A, Abdullah AH, Masoumi HRF, Jahangirian H, Shameli K, Rezayi M, Banerjee S, Abdollahi T, Chem. Cent. J., 6(88), 1 (2012)
  26. Abdollahi Y, Zakaria A, Abbasiyannejad M, Masoumi HRF, Moghaddam MG, Matori KA, Jahangirian H, Keshavarzi A, Chem. Cent. J., 7(96), 1 (2013)
  27. Ghaffari A, Abdollahi H, Khoshayand, Bozchalooi IS, Dadgar A, Rafiee-Tehrani M, Int. J. Pharm., 327(1), 126 (2006)
  28. Moghaddam MG, Ahmad FBH, Basri M, Rahman MBA, Electron. J. Biotechnol., 13(3), 3 (2010)
  29. Aber S, Amani-Ghadim A, Mirzajani V, J. Hazard. Mater., 171(1), 484 (2009)
  30. Garson GD, AI Expert, 6(4), 46 (1991)
  31. Khare M, Nagendra SS, Artificial Neural Networks in Vehicular Pollution Modelling, Springer, New Delhi, India, 2007.
  32. Sakamoto H, Matsumoto K, Kuwahara A, Hayami Y, Commun. Comput. Sci., 88(7), 1971 (2005)
  33. Ortega JM, Rheinboldt WC, Iterative Solution of Nonlinear Equations in Several Variables, Siam, Philadelphia, PA, 2000.
  34. Kelley CT, Iterative Methods for Optimization, Siam, Philadelphia, PA, 1999.
  35. Bates DM, Watts DG, Nonlinear Regression: Iterative Estimation and Iinear Approximations, Wiley Online Library, 1988.
  36. Mandelbrot BB, Science, 156(3775), 636 (1967)
  37. Kasiri M, Aleboyeh H, Aleboyeh A, Environ. Sci. Technol., 42(21), 7970 (2008)
  38. Zhang J, Morris AJ, Martin EB, Kiparissides C, Chem. Eng. J., 69(2), 135 (1998)
  39. Aijun L, Hejun L, Kezhi L, Zhengbing G, Acta Mater., 52(2), 299 (2004)
  40. Sarle WS, SAS Institute Inc., Cary, NC, 2000 hftp://ftp.sas.com/pub/neural/importance.htmli.