Skip to main content
Log in

A novel mathematical method for prediction of rapid expansion of supercritical solution (RESS) processed ibuprofen powder size distribution

  • Published:
Korean Journal of Chemical Engineering Aims and scope Submit manuscript

Abstract

A fundamental understanding of the interplay among the variables involved in a rapid expansion of supercritical solution (RESS) process is necessary in order to achieve control of product within the desired specifications. A model is proposed where the experimental data are fitted to a 2-D Sp-line equation that results in a mathematical pattern matching function that can easily be processed analytically to yield a continuous motion estimate. This model presents a novel promising method to interpolate between any two experimental results. Comparison of the mean particles size values which are calculated as a function of nozzle temperature (T N ) and pre-expansion pressure (P pre-expansion ) with the experimental data, results in a ±8% accuracy. The optimum operational point that leads to the minimum mean particles diameter (40 nm) is determined through mathematical optimization of this equation and confirmed experimentally. Furthermore, 600 more values of mean particle size are predicted by varying the nozzle temperature and dissolution pressure and the results are presented in the form of a 3-dimesional curve.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Y. P. Sun, R. Guduru and F. Lin, Ind. Eng. Chem. Res., 39, 4663 (2000).

    Article  CAS  Google Scholar 

  2. T. L. Rogers, K. P. Johnston and R. O. Williams, Drug. Dev. Ind. Pharm., 27, 1003 (2001).

    Article  CAS  Google Scholar 

  3. R. S. Mohamed, P.G. Debenetti and R. K. Prud’home, AIChE J., 35, 325 (2002).

    Article  Google Scholar 

  4. S. Sethia and E. Squinlante, J. Pharm. Sci., 91, 1948 (2002).

    Article  CAS  Google Scholar 

  5. R. Thakur and R. B. Gupta, Ind. Eng. Chem. Res., 44, 7380 (2005).

    Article  CAS  Google Scholar 

  6. C. J. Chang and A. D. Radolph, AIChE J., 35, 1876 (1989).

    Article  CAS  Google Scholar 

  7. P. S. Bozic, S. Srcic and J. Kerk, Int. J. Pharmacology, 48, 543 (1997).

    Google Scholar 

  8. P. Pathak, M.J. Meziani, T. Desai and Y. P. Sun, J. Supercrit. Fluids, 37, 279 (2006).

    Article  CAS  Google Scholar 

  9. A. K. Lele and A. D. Shine, Ind. Eng. Chem. Res., 33, 1476 (1994).

    Article  CAS  Google Scholar 

  10. D.W. Matson, R. C. Petersen and R. D. Smith, J. Mater. Sci., 22, 1919 (1987).

    Article  CAS  Google Scholar 

  11. P. Hirunsit, Z. Huang, T. Srinophakon, M. Charoenchaitrakool and S, Kawi, J. Supercrit. Fluids, 9, 216 (1996).

    Article  Google Scholar 

  12. P.G. Debenetti, J.W. Tom, X. Kwauk and S. D. Yeo, Fluid Phase Equilibr., 82, 311 (1993).

    Article  Google Scholar 

  13. C. J. Chang and A. D. Radolph, AIChE J., 35, 1876 (1989).

    Article  CAS  Google Scholar 

  14. D.W. Matson, J. L. Folton, R. C. Peterson and R. D. Smith, Material Lett., 10, 429 (1986).

    Article  Google Scholar 

  15. E. Kosal, C. H. Lee and G. D. Holder, J. Supercrit. Fluids, 5, 169 (1992).

    Article  CAS  Google Scholar 

  16. H. Ksibi and P. Subra, Adv. Powder Technol., 7, 210 (1996).

  17. M. Charoenchaitracool, F. Dehghani and N. R. Foster, Ind. Eng. Chem. Res., 39, 4794 (2000).

    Article  Google Scholar 

  18. B.H. Soo, P.Y. Jin and L. J. Sung, J. Appl. Polym. Sci., 107, 1124 (2008).

    Article  Google Scholar 

  19. B. Helfgen, P. Hils, Ch. Holzknech, M. Turk and K. Schaber, Aerosol. Sci., 32, 295 (2001).

    Article  CAS  Google Scholar 

  20. P. Hirunsit, Z. Huang, T. Srinophakon, M. Charoenchaitrakool and S, Kawi, Powder Technol., 154, 83 (2005).

    Article  CAS  Google Scholar 

  21. D. Kyrak, U. Akman and O. Hortacsu, J. Supercrit. Fluids, 26, 17 (2003).

    Article  Google Scholar 

  22. E. Reverchon and P. Pallaodo, J. Supercrit. Fluids, 9, 216 (1996).

    Article  CAS  Google Scholar 

  23. J. Fages, H. Luchard, J. J. Letorneau and M. Sauceau, Powder Technol., 141, 219 (2004).

    Article  CAS  Google Scholar 

  24. N. Yildiz, S. Tuna and O. Duker, J. Supercrit. Fluids, 41, 440 (2007).

    Article  CAS  Google Scholar 

  25. G. A. Alvareza, W. Baumannb, M. B. Adaimeb and F. Neitzelb, Chemical & Pharmaceutical Bulletin, 641, 97 (2005).

    Google Scholar 

  26. J. H. Kim, T. E. Paxton and D. L. Tomasko, Biotechnol. Prog., 12, 650 (1996).

    Article  CAS  Google Scholar 

  27. Dean W. Matson, John L. Folton, Robert C. Peterson and Richard D. Smith, Ind. Eng. Chem. Res., 26, 2298 (1987).

    Article  CAS  Google Scholar 

  28. M. Türk, P. Hils, B. Helfgen, K. Schaber, H. J. Martin and M. A. Wahl, J. Supercrit. Fluids, 22, 75 (2002).

    Article  Google Scholar 

  29. Y. Kawashima and P. York, Advanced Drug Delivery Reviews, 60, 297 (2008).

    Article  CAS  Google Scholar 

  30. F. Zabihi, M. M. Akbarnejad, A. Vaziri, M. Arjomand and A. A. Seyfkordi, IJCCE, 28, 441 (2009).

    Google Scholar 

  31. P. Alessi, A. Cortesi, I. Kikic, N. R. Foster and I. Colombo, Ind. Eng. Chem. Res., 35, 4718 (1996).

    Article  CAS  Google Scholar 

  32. M. J. Meziani, P. Pathak and R. Hurezeanue, Angew. Chem. Int. Ed., 43, 704 (2004).

    Article  CAS  Google Scholar 

  33. J. Wang, J. Chen and Y. Yang, J. Supercrit. Fluids, 33, 159 (2005).

    Article  CAS  Google Scholar 

  34. A. Tandya, F. Dehghani and N. R. Foster, J. Supercrit. Fluids, 37, 272 (2006).

    Article  CAS  Google Scholar 

  35. N. Foster, F. Dehghani and B. Warwick, AAPS Pharm. Sci., 5, 77 (2003).

    Article  Google Scholar 

  36. S. D. Yeo and E. Kiran, J. Supercrit. Fluids, 34, 287 (2005).

    Article  CAS  Google Scholar 

  37. A. K. Gupta and M. Gupta, Biomaterials, 26, 3995 (2005).

    Article  CAS  Google Scholar 

  38. Y. P. Sun, M. J. Meziani and P. Pathak, J. Am. Chem. Soc., 12, 10824 (2004).

    Google Scholar 

  39. L.C. Galvao, A. G. Novae and J. E. Souza de Cursi, Computers and Operations Research, 33, 93 (2006).

    Article  Google Scholar 

  40. F. Vaiola, R. L. Coe and K. Owen, Ann. Biomed. Eng., 36, 1942 (2008).

    Article  Google Scholar 

  41. H. Spath, Biomed. Eng., 36, 1942 (2008).

    Article  Google Scholar 

  42. S. Afsharian and K. Keihani, Applied mathematics in chemical engineering, Puranpazhuh Publications, Tehran (2005).

    Google Scholar 

  43. H. Spath, Biomed. Eng., 36, 1942 (2008).

    Article  Google Scholar 

  44. R. Kharattian and M. Nikazar, Applied mathematics in chemical engineering, Amir Kabir University Publications, Tehran (2006).

    Google Scholar 

  45. Matlab, 7.5.0.342, R 2007 b.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Fatemeh Zabihi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zabihi, F., Vaziri, A., Akbarnejad, M.M. et al. A novel mathematical method for prediction of rapid expansion of supercritical solution (RESS) processed ibuprofen powder size distribution. Korean J. Chem. Eng. 27, 1601–1605 (2010). https://doi.org/10.1007/s11814-010-0265-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11814-010-0265-9

Key words

Navigation