Literature DB >> 22552202

Generalized linear solvation energy model applied to solute partition coefficients in ionic liquid-supercritical carbon dioxide systems.

Josef Planeta1, Pavel Karásek, Barbora Hohnová, Lenka Sťavíková, Michal Roth.   

Abstract

Biphasic solvent systems composed of an ionic liquid (IL) and supercritical carbon dioxide (scCO(2)) have become frequented in synthesis, extractions and electrochemistry. In the design of related applications, information on interphase partitioning of the target organics is essential, and the infinite-dilution partition coefficients of the organic solutes in IL-scCO(2) systems can conveniently be obtained by supercritical fluid chromatography. The data base of experimental partition coefficients obtained previously in this laboratory has been employed to test a generalized predictive model for the solute partition coefficients. The model is an amended version of that described before by Hiraga et al. (J. Supercrit. Fluids, in press). Because of difficulty of the problem to be modeled, the model involves several different concepts - linear solvation energy relationships, density-dependent solvent power of scCO(2), regular solution theory, and the Flory-Huggins theory of athermal solutions. The model shows a moderate success in correlating the infinite-dilution solute partition coefficients (K-factors) in individual IL-scCO(2) systems at varying temperature and pressure. However, larger K-factor data sets involving multiple IL-scCO(2) systems appear to be beyond reach of the model, especially when the ILs involved pertain to different cation classes.
Copyright © 2012 Elsevier B.V. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2012        PMID: 22552202     DOI: 10.1016/j.chroma.2012.04.016

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  1 in total

1.  Evaluation of an amide-based stationary phase for supercritical fluid chromatography.

Authors:  Amaris C Borges-Muñoz; Luis A Colón
Journal:  J Sep Sci       Date:  2016-08-26       Impact factor: 3.645

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.