Skip to main content
Log in

Optimal Sampling Times for Leaching Experiments

  • Original Research Article
  • Published:
Metallurgical and Materials Transactions B Aims and scope Submit manuscript

Abstract

In this study, an optimal sampling schedule was developed for leaching experiments with the objective of improving the confidence of the kinetic parameters. This study shows that there is an improvement in the confidence interval from uniform sampling and the method presented here. The optimal sampling times were determined by reducing the determinant of the covariance matrix associated with the kinetic constant, which can be expressed through the covariance matrix of the extracted fraction, \(X,\) used to generate a function to distribute the sampling times in the experiment. The method presented here requires minimal knowledge a priori of the system to be characterized. Only the kinetic expression for the system is required. The methodology was applied to a simulated case and experimental case study of ammoniacal leaching of copper slags. The simulations conducted indicated a lower value of the standard deviation of 1.40·10−4 min−1 for optimized sampling times and a value of 1.78·10−4 min−1 for uniform distribution. The experimental validation results indicated a reduction of the coefficient of variation for optimized experiments of 9.3 pct (less uncertainty) from 29.7 pct (uniform sampling) to 14.6 pct (optimized sampling). Thus, the methodology proposed here is successful in decreasing the uncertainty in laboratory leaching experiments.

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.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. F. Habashi: Hydrometallurgy., 2005, vol. 79(1–2), pp. 15–22.

    Article  CAS  Google Scholar 

  2. R. Bartlett: Solution Mining 2e, Routledge, 2013.

    Book  Google Scholar 

  3. Rees, K. L. (2000). The leaching and adsorption behaviour of gold ores. PhD thesis, Department of Chemical Engineering, The University of Melbourne.

  4. F. Arroyo and C. Fernandez-Pereira: Ind. Eng. Chem. Res., 2008, vol. 47(9), pp. 3186–91.

    Article  CAS  Google Scholar 

  5. F. Arroyo, C. Fernández-Pereira, and P. Bermejo: Minerals., 2015, vol. 5(2), pp. 298–313.

    Article  CAS  Google Scholar 

  6. F.K. Crundwell: Hydrometallurgy., 2013, vol. 139, pp. 132–48.

    Article  CAS  Google Scholar 

  7. F.K. Crundwell: Hydrometallurgy., 1995, vol. 39(1–3), pp. 321–35.

    Article  CAS  Google Scholar 

  8. S. Vyazovkin and C.A. Wight: Annu. Rev. Phys. Chem., 1997, vol. 48(1), pp. 125–49.

    Article  CAS  Google Scholar 

  9. H.Y. Sohn: Metall. Trans. B., 1978, vol. 9(1), pp. 89–96.

    Article  Google Scholar 

  10. Brown, M., Dollimore, D., & Galwey, A. (1980). Comprehensive Chemical Kinetics (Vol. 22). Elsevier

  11. Faraji, F., Alizadeh, A., Rashchi, F., & Mostoufi, N.: Reviews in Chemical Engineering. 2020, pp. 000010151520190073

  12. W. Astuti, T. Hirajima, T. Sasaki, and N. Okibe: Miner. Metall. Process., 2015, vol. 32(3), pp. 176–85.

    Google Scholar 

  13. C. Thubakgale, R. Mbaya, and K. Kabongo: Int. J. Chem. Mol. Nucl. Mater. Metall. Eng., 2012, vol. 2012, pp. 228–32.

    Google Scholar 

  14. M.C. Fuerstenau and K.N. Han: Principles of Mineral Processing, Society for Mining, Metallurgy, and Exploration Inc, Colorado, 2009.

    Google Scholar 

  15. O. Levenspiel: Chemical Reaction Engineering, Wiley, 1999.

    Google Scholar 

  16. D.Z. D’Argenio: J. Pharmacokinet. Biopharm., 1981, vol. 9(6), pp. 739–56.

    Article  CAS  Google Scholar 

  17. G. Veloso, R. Simpson, H. Núñez, C. Ramírez, S. Almonacid, and A. Jaques: J. Food Eng., 2021, vol. 306, p. 110610.

    Article  CAS  Google Scholar 

  18. A.V. Jaques, M.B. Barraza, and J.C. Lacombe: J. Phase Equilib. Diffus., 2015, vol. 36(1), pp. 22–27.

    Article  CAS  Google Scholar 

  19. C.P. Kitsos: Optimal Experimental Design for Non-Linear Models: Theory and Applications, Springer, Berlín, 2013.

    Book  Google Scholar 

  20. P. Coursol, P.J. Mackey, and C.M. Diaz: Proc. Copper., 2010, vol. 2, pp. 649–68.

    CAS  Google Scholar 

  21. A. Aracena, E. Rodríguez, and O. Jerez: Hydrometallurgy., 2020, vol. 192, p. 105290.

    Article  CAS  Google Scholar 

  22. A. Aracena, A. Valencia, and O. Jerez: Metals., 2020, vol. 10(6), p. 712.

    Article  CAS  Google Scholar 

  23. M. Arzutug, M. Kocakerim, and M. Copur: Ind. Eng. Chem. Res., 2004, vol. 43(15), pp. 4118–23.

    Article  CAS  Google Scholar 

  24. Guo-dong, Z., & Qing, L.: International Conference on Chemistry and Chemical Engineering (ICCCE), 2010, 216-20.

  25. D. Li, C. Wang, Y. Chen, and X. Jie: Chin. J. Power Sources., 2009, vol. 33, pp. 454–57.

    CAS  Google Scholar 

  26. Z. Liu, Z. Yin, S. Xiong, Y. Chen, and Q. Chen: Hydrometallurgy., 2014, vol. 144–145, pp. 86–90.

    Article  Google Scholar 

  27. Y. Huang, Z. Yin, Z. Ding, J. Feng, and L. Chunxia: Hydrometallurgy., 2018, vol. 179, pp. 198–206.

    Article  CAS  Google Scholar 

  28. O. Furman, A. Teel, and R. Watts: Environ. Sci. Technol., 2010, vol. 44(16), pp. 6423–28.

    Article  CAS  Google Scholar 

  29. A. Ekmekyapar, R. Oya, and A. Kunkul: Chem. Biochem. Eng. Q., 2003, vol. 17(4), pp. 261–26.

    CAS  Google Scholar 

  30. A. Aracena, Y. Vivar, O. Jerez, and D. Vásquez: Miner. Process. Extr. Metall. Rev., 2015, vol. 36(5), pp. 317–23.

    Article  CAS  Google Scholar 

  31. L. Beckstead and J. Miller: Metall. Trans., 1977, vol. 8(1), pp. 19–29.

    Article  Google Scholar 

  32. Radmehr, V., Koleini, S., Khalesi, M., & Tayakoli, M.: J. Inst. Eng. (India), 2013, 94(2), 95-104.

  33. R.H. Myers, D.C. Montgomery, G. Geoffrey, and T.J. Robinson: Generalized Linear Models With Applications in Engineering and the Sciences, Wiley, New Jersey, 2010.

    Book  Google Scholar 

Download references

Acknowledgments

The authors are grateful for the support of ANID, via “FONDECYT INICIACIÓN, 11180432 project”.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. Jaques.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ojeda, C., Jaques, A. & Aracena, A. Optimal Sampling Times for Leaching Experiments. Metall Mater Trans B 53, 1082–1088 (2022). https://doi.org/10.1007/s11663-022-02426-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11663-022-02426-4

Navigation