Using COSMO-RS to Predict Solvatochromic Parameters for Deep Eutectic Solvents
authors Wojeicchowski, JP; Abranches, DO; Ferreira, AM; Mafra, MR; Coutinho, JAP
nationality International
journal ACS SUSTAINABLE CHEMISTRY & ENGINEERING
author keywords deep eutectic solvents; Kamlet-Taft; polarity; acidity; basicity
keywords HYDROGEN-BOND ACIDITY; IONIC LIQUIDS; EXTRACTION; SCALE; MIXTURES; COEFFICIENTS; SEPARATION; MOLECULES
abstract The development of novel green solvents demands the knowledge of their properties, such as polarity, which can be described through solvatochromic parameters. However, while these are available for a wide range of conventional solvents, there is a lack of data for the emergent ones. Considering the need for such data, predictive models to estimate the Kamlet-Taft (K-T) parameters for deep eutectic solvents (DES) are developed here. The models, based on the conductor-like screening model for real solvents (COSMO-RS) descriptors, were initially developed and tested for 175 organic solvents to validate the applicability of the proposed approach. This approach was then extended for DES, which were classified into two categories, acids and nonacids. The developed equations showed a very good performance for all three K-T parameters, and this is the first work to propose models for all K-T parameters for DES. Moreover, a comparison between polarity data of DES and organic compounds showed that DES, rather than replace common solvents, can extend their range of polarities, reinforcing their designer solvent ability.
publisher AMER CHEMICAL SOC
issn 2168-0485
year published 2021
volume 9
issue 30
beginning page 10240
ending page 10249
digital object identifier (doi) 10.1021/acssuschemeng.1c02621
web of science category 10
subject category Chemistry, Multidisciplinary; Green & Sustainable Science & Technology; Engineering, Chemical
unique article identifier WOS:000683000400022
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journal analysis (jcr 2019):
journal impact factor 7.632
5 year journal impact factor 7.741
category normalized journal impact factor percentile 90.792
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