Exploring the Influence of Ionic Liquid Anion Structure\non Gas-Ionic Liquid Partition Coefficients of Organic Solutes Using\nMachine Learning

This article presents\nan in-depth investigation into the influence\nof anionic structures of ionic liquids (ILs) on gas-ionic liquid partition\ncoefficients (log <i>K</i>) of organic solutes in three\nILs. While the primary objective was to examine whether there is a\nrelationship between the molecular structure of the IL anion component\nand log <i>K</i>, additionally it was looked at whether\nthe molecular descriptors of the anion in the relationships encode\npossible molecular interactions during the miscibility and partitioning\nin the IL. The research involves the compilation of data series of\nexperimental log <i>K</i> values, where the cation component\nis constant. Such representative data series were obtained for three\nsolutesbenzene, cyclohexane, and methanolin three\nILs with a uniform cationic component of methylimidazoliums. Using\nmultiple linear regression models enhanced with machine learning techniques,\nthe relationship between anionic structures and log <i>K</i> values was successfully quantified and modeled. Systematically selected\nmolecular descriptors describing the anion structure show that in\nthe case of methanol log <i>K</i> is strongly dependent\non hydrogen bonds and Coulomb-dipolar interactions with the anion\ncomponent, while in the case of benzene and cyclohexane the dispersion\nforces of the anion component are dominant. The outlier analysis and\ndata interpretation highlight the need for extensive experimental\ndata. The results confirm the initial hypothesis and provide valuable\ninformation on the role of the structure of the anionic component\nin determining the partitioning behavior of organic solutes. This\nknowledge is important for the design and optimization of ILs for\nspecific applications, particularly as solvents in various industrial\nprocesses. The research also provides useful information about molecular\ninteractions taking place in the interfaces of IL and organic additives\nin complex liquid media such as multicomponent electrolyte solutions,\nfor example in energy storage applications.

Publication Details

Journal
Figshare
Published
2024-10-30
DOI
https://doi.org/10.1021/acs.langmuir.4c02628.s001
Primary Topic
Ionic liquids properties and applications
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article
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article

Exploring the Influence of Ionic Liquid Anion Structure\non Gas-Ionic Liquid Partition Coefficients of Organic Solutes Using\nMachine Learning

Figshare
Ionic liquids properties and applications
article

Exploring the Influence of Ionic Liquid Anion Structure\non Gas-Ionic Liquid Partition Coefficients of Organic Solutes Using\nMachine Learning

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Abstract

This article presents\nan in-depth investigation into the influence\nof anionic structures of ionic liquids (ILs) on gas-ionic liquid partition\ncoefficients (log <i>K</i>) of organic solutes in three\nILs. While the primary objective was to examine whether there is a\nrelationship between the molecular structure of the IL anion component\nand log <i>K</i>, additionally it was looked at whether\nthe molecular descriptors of the anion in the relationships encode\npossible molecular interactions during the miscibility and partitioning\nin the IL. The research involves the compilation of data series of\nexperimental log <i>K</i> values, where the cation component\nis constant. Such representative data series were obtained for three\nsolutesbenzene, cyclohexane, and methanolin three\nILs with a uniform cationic component of methylimidazoliums. Using\nmultiple linear regression models enhanced with machine learning techniques,\nthe relationship between anionic structures and log <i>K</i> values was successfully quantified and modeled. Systematically selected\nmolecular descriptors describing the anion structure show that in\nthe case of methanol log <i>K</i> is strongly dependent\non hydrogen bonds and Coulomb-dipolar interactions with the anion\ncomponent, while in the case of benzene and cyclohexane the dispersion\nforces of the anion component are dominant. The outlier analysis and\ndata interpretation highlight the need for extensive experimental\ndata. The results confirm the initial hypothesis and provide valuable\ninformation on the role of the structure of the anionic component\nin determining the partitioning behavior of organic solutes. This\nknowledge is important for the design and optimization of ILs for\nspecific applications, particularly as solvents in various industrial\nprocesses. The research also provides useful information about molecular\ninteractions taking place in the interfaces of IL and organic additives\nin complex liquid media such as multicomponent electrolyte solutions,\nfor example in energy storage applications.

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Ionic liquids properties and applications
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