Review of algorithms for modeling metal distribution equilibria in liquid-liquid extraction processes

Authors

  • L. J. Lozano Department of Chemical & Environmental Engineering. Polytechnic University of Cartagena
  • F. J. Alguacil National Centre for Metallurgical Research (CENIM-CSIC)
  • M. Alonso National Centre for Metallurgical Research (CENIM-CSIC)
  • C. Godínez Department of Chemical & Environmental Engineering. Polytechnic University of Cartagena

DOI:

https://doi.org/10.3989/revmetalm.2005.v41.i5.227

Keywords:

Liquid-liquid extraction, statistical methods, artificial neural nets.

Abstract


This work focuses on general guidelines to be considered for application of least-squares routines and artificial neural networks (ANN) in the estimation of metal distribution equilibria in liquid-liquid extraction process. The goal of the procedure in the statistical method is to find the values of the equilibrium constants (Kj) for the reactions involved in the metal extraction which minimizes the differences between experimental distribution coefficient (Dexp) and theoretical distribution coefficients according to the mechanism proposed (Dtheor)- In the first part of the article, results obtained with the most frequently routine reported in the bibliography are compared with those obtained using the algorithms previously discussed. In the second part, the main features of a single back-propagation neural network for the same purpose are discussed, and the results obtained are compared with those obtained with the classical methods.

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Published

2005-10-30

How to Cite

Lozano, L. J., Alguacil, F. J., Alonso, M., & Godínez, C. (2005). Review of algorithms for modeling metal distribution equilibria in liquid-liquid extraction processes. Revista De Metalurgia, 41(5), 374–383. https://doi.org/10.3989/revmetalm.2005.v41.i5.227

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Section

Articles