Issue
Korean Journal of Chemical Engineering,
Vol.30, No.9, 1681-1686, 2013
Application of artificial neural network for vapor liquid equilibrium calculation of ternary system including ionic liquid: Water, ethanol and 1-butyl-3-methylimidazolium acetate
A feed forward three-layer artificial neural network (ANN) model was developed for VLE prediction of ternary systems including ionic liquid (IL) (water+ethanol+1-butyl-3- methyl-imidazolium acetate), in a relatively wide range of IL mass fractions up to 0.8, with the mole fractions of ethanol on IL-free basis fixed separately at 0.1, 0.2, 0.4, 0.6, 0.8, and 0.98. The output results of the ANN were the mole fraction of ethanol in vapor phase and the equilibrium temperature. The validity of the model was evaluated through a test data set, which were not employed in the training case of the network. The performance of the ANN model for estimating the mole fraction and temperature in the ternary system including IL was compared with the non-random-two-liquid (NRTL) and electrolyte non-randomtwo-liquid (eNRTL) models. The results of this comparison show that the ANN model has a superior performance in predicting the VLE of ternary systems including ionic liquid.
[References]
  1. Cehreli S, Gmehling J, Fluid Phase Equilib., 295(1), 125, 2010
  2. Pereiro AB, Rodriguez A, Sep. Purif. Technol., 62(3), 733, 2008
  3. Huang HJ, Ramaswamy S, Tschirner UW, Ramarao BV, Sep. Purif. Technol., 62(1), 1, 2008
  4. Simoni LD, Lin Y, Brennecke JF, Stadtherr MA, Ind. Eng. Chem. Res., 47(1), 256, 2008
  5. Alevizou EI, Pappa GD, Voutsas EC, Fluid Phase Equilib., 284(2), 99, 2009
  6. Bernardo-Gusmao K, Queiroz LFT, de Souza RF, Leca F, Loup C, Reau R, J. Catal., 219(1), 59, 2003
  7. Wang B, Kang YR, Yang LM, Suo JS, J. Mol. Catal. A:Chem., 35, 67, 2003
  8. Letcher TM, Deenadayalu N, J. Chem. Thermodyn., 35(1), 67, 2003
  9. Wasserscheid P, Welton T, Ionic liquids in synthesis, Wiley-VCH, Weinheim, 2003
  10. Rogers RD, Seddon KR, Ionic liquids-industrial applications to green chemistry, in: ACS Symposium Series 818: ACS, Washington DC, 2002
  11. Doker M, Gmehling J, Fluid Phase Equilib., 227(2), 255, 2005
  12. Shen C, Li XM, Lu YZ, Li CX, J. Chem. Thermodyn., 43(11), 1748, 2011
  13. Banerjee T, Singh MK, Sahoo RK, Khanna A, Fluid Phase Equilib., 234(1-2), 64, 2005
  14. Simoni LD, Lin Y, Brennecke JF, Stadtherr MA, Ind. Eng. Chem. Res., 47(1), 256, 2008
  15. Pereiro AB, Rodriguez A, J. Chem. Eng. Data, 53(6), 1360, 2008
  16. Pereiro AB, Rodriguez A, J. Chem. Thermodyn., 40(8), 1282, 2008
  17. Heintz A, J. Chem. Thermodyn., 37(6), 525, 2005
  18. Vega LF, Vilaseca O, Llovell F, Andreu JS, Fluid Phase Equilib., 294(1-2), 15, 2010
  19. Deng DS, Wang RF, Zhang LZ, Ge Y, Ji JB, Chin. J. Chem. Eng., 19(4), 703, 2011
  20. Lazzus JA, J. Taiwan Inst. Chem. Eng., 40, 213, 2009
  21. Safamirzaei M, Modarress H, Fluid Phase Equilib., 309(1), 53, 2011
  22. Beigzadeh R, Rahimi M, Shabanian SR, Fluid Phase Equilib., 331, 48, 2012
  23. Mehrabi M, Sharifpur M, Meyer JP, Int. Commun. Heat Mass., 39, 971, 2012
  24. Lee KJ, Chen WK, Ko JW, Lee LS, Chang CMJ, Taiwan Inst. Chem. Eng., 40, 573, 2009
  25. Haghtalab A, Paraj A, J. Mol. Liq., 171, 43, 2012
  26. Hagan MT, Demuth HB, Beale MH, Neural Network Design, PWS Publishing, Boston, MA, 1996
  27. Hussain MA, Artif. Intell. Eng., 13, 55, 1999
  28. Levenberg K, SIAM J. Numer. Anal., 16, 588, 1944
  29. Marquardt D, SIAM J. Appl. Math., 11, 431, 1963
  30. Hagan MT, Menhaj M, IEEE Transactions on Neural Networks., 5, 989, 1994
  31. Christov M, Dohrn R, Fluid Phase Equilib., 202(1), 153, 2002
  32. Zhang LZ, Deng DS, Han JZ, Ji DX, Ji JB, J. Chem. Eng. Data, 52(1), 199, 2007
  33. Zhang LZ, Yuan XC, Qiao BB, Qi RZ, Ji JB, J. Chem. Eng. Data, 53(7), 1595, 2008
  34. Haykin S, Neural networks: A comprehensive foundation, Prentice Hall, Upper Saddle River, NJ, 1999
  35. Hassibi B, Stork DG, in Advances in Neural Information Processing Systems, Hanson SJ, Cowan JD, Giles CL Eds., volume 5, pp. 164-171. Morgan Kaufmann, San Mateo, CA, 1993
  36. Le Cun Y, Denker JS, Solla SA, Optimal Brain Damage, In Touretzky DS (Ed.), Advances in Neural Information Processing Systems 2, Proceedings of the 1989 Conference, San Mateo, California, Morgan Kaufmann Publishers, 1990
  37. Moral H, Aksoy A, Golcay CF, Comput. Chem. Eng., 32(10), 2471, 2008
  38. Beigzadeh R, Rahimi M, Int. Commun. Heat Mass., 39, 1279, 2012
  39. Renon H, Prausnitz JM, AIChE J., 14, 135, 1968
  40. Vercher E, Rojo FJ, Martinez-Andreu A, J. Chem. Eng. Data., 44, 1216, 1999
  41. Gmehling J, Onken U, Rearey-Nies JR, Vapor-liquid equilibrium data collection, Vol. I, Part Ib, DECHEMA, Frankfurt, 1988