QSPR modeling of selectivity at infinite dilution of ionic liquids.

ABSTRACT: The intelligent choice of extractants and entrainers can improve current mixture separation techniques allowing better efficiency and sustainability of chemical processes that are both used in industry and laboratory practice. The most promising approach is a straightforward comparison of selectivity at infinite dilution between potential candidates. However, selectivity at infinite dilution values are rarely available for most compounds so a theoretical estimation is highly desired. In this study, we suggest a Quantitative Structure-Property Relationship (QSPR) approach to the modelling of the selectivity at infinite dilution of ionic liquids. Additionally, auxiliary models were developed to overcome the potential bias from big activity coefficient at infinite dilution from the solute. Da

SUBMITTER: Klimenko K 

PROVIDER: S-EPMC8549394 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature