Study of benzyl- or cyclohexyl-functionalized ionic liquids using inverse gas chromatography

Mutelet, Fabrice; Djebouri, Hamid; Baker, Gary A.; Ravula, Sudhir; Jiang, Bihan; Tong, Xin; Woods, D H; Acree, William E.

doi:10.1016/j.molliq.2017.07.036

Cited by 36 publications

(6 citation statements)

References 53 publications

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“…The data set comprised three series of experimental gas-ionic liquid partition coefficients (log K ) measured at 298 K for benzene, hexane and cyclohexane in various ionic liquids where bis(trifluoromethylsulfonyl)imide ([Tf2N] – ) was the common anion ( Tables S1–S3, Supplementary Material ) [ 42 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 ]. These three data series had similar sizes with 57, 60 and 60 partition coefficients for hexane, cyclohexane and benzene, respectively.…”

Section: Methodsmentioning

confidence: 99%

Machine Learning Quantitative Structure–Property Relationships as a Function of Ionic Liquid Cations for the Gas-Ionic Liquid Partition Coefficient of Hydrocarbons

Toots

Sild

Leis

et al. 2022

IJMS

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Ionic liquids (ILs) are known for their unique characteristics as solvents and electrolytes. Therefore, new ILs are being developed and adapted as innovative chemical environments for different applications in which their properties need to be understood on a molecular level. Computational data-driven methods provide means for understanding of properties at molecular level, and quantitative structure–property relationships (QSPRs) provide the framework for this. This framework is commonly used to study the properties of molecules in ILs as an environment. The opposite situation where the property is considered as a function of the ionic liquid does not exist. The aim of the present study was to supplement this perspective with new knowledge and to develop QSPRs that would allow the understanding of molecular interactions in ionic liquids based on the structure of the cationic moiety. A wide range of applications in electrochemistry, separation and extraction chemistry depends on the partitioning of solutes between the ionic liquid and the surrounding environment that is characterized by the gas-ionic liquid partition coefficient. To model this property as a function of the structure of a cationic counterpart, a series of ionic liquids was selected with a common bis-(trifluoromethylsulfonyl)-imide anion, [Tf2N]−, for benzene, hexane and cyclohexane. MLR, SVR and GPR machine learning approaches were used to derive data-driven models and their performance was compared. The cross-validation coefficients of determination in the range 0.71–0.93 along with other performance statistics indicated a strong accuracy of models for all data series and machine learning methods. The analysis and interpretation of descriptors revealed that generally higher lipophilicity and dispersion interaction capability, and lower polarity in the cations induces a higher partition coefficient for benzene, hexane, cyclohexane and hydrocarbons in general. The applicability domain analysis of models concluded that there were no highly influential outliers and the models are applicable to a wide selection of cation families with variable size, polarity and aliphatic or aromatic nature.

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Section: Methodsmentioning

confidence: 99%

Machine Learning Quantitative Structure–Property Relationships as a Function of Ionic Liquid Cations for the Gas-Ionic Liquid Partition Coefficient of Hydrocarbons

Toots

Sild

Leis

et al. 2022

IJMS

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“…From all activity co-efficient (γ ∞ )values, selectivity at infinite dilution ( ) were determined which was verified by LSER (Linear Solvation Energy Relationship) method following Abraham model which came out to be very helpful in optimizing and designing the separation process specially of aromatics, alcohols, and chloroalkanes from alkanes [89,90]. Acree Jr. et al studied the measurement of infinite dilution activity coefficients ( ) and gas-to-ionic liquid partition coefficient for a set of organic solutes dissolving in four ionic liquids with the help of inverse gas chromatography [91]. This group till now performed measurement of in more than 40 different ionic liquids with varying polarity and hydrogen bonding character based on inverse gas liquid chromatography methods and usually ionic liquids acted as a stationary phase in this type of chromatographic pathway.…”

Section: Inverse Gas Chromatographymentioning

confidence: 99%

Ionic Liquids: Recent Journey Through Chromatographic Separation

Sarkar

2021

JASR

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Ionic liquids (ILs), despite some of their crucial disadvantages, have been established to be the apt and relevant replacement of the volatile organic compounds (VOCs) in the industrial and academic sectors as solvents. Recent investigations on thriving multifaceted applications of ionic liquids have unleashed that they are really among beneficial “environmentally-benign” solvents as far as their impact on the ecosystem is concerned. This caused them to be an exciting and lucrative domain to explore in a wider fashion and many of the leading research groups are involved in the manifestation of their inherent undisclosed legacy. While exploring the efficacy of ILs, it was found that ILs or IL-based mixed solvent systems were very good alternative of conventional solvents and could act as mobile/stationary phases or additives in gas chromatography (GC), multidimensional gas chromatography (MDGC), inverse gas chromatography (IGC), high performance liquid chromatography (HPLC) and capillary electrophoresis (CE) very efficiently. Their (IL’s) efficacy in improvising and synchronizing the mode and nature of the chromatographic separation is well-established, undoubtedly commendable and unique in many ways. In this review we have put our concentration on the recent, beneficial and some less-explored aspects of the implementation of ILs in the above said chromatographic separation domain.

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“…A complete set of solute descriptors enables one to estimate a large number of physicochemical and thermodynamic properties using published Abraham model correlations. To date we have reported mathematical expressions for predicting log K and log P values for solutes dissolved in both traditional molecular organic solvents [39][40][41][42][43] and ionic liquid solvents, [64][65][66][67][68][69][70][71][72][73] molar solubility ratios, [39][40][41][42][43] blood-to-body tissue/fluid partition coefficients, [74][75][76][77][78] Draize scores and eye irritation thresholds, [79][80][81] enthalpies of solvation, [45][46][47][48][49][50][51][52][53][54][55] lethal median concentrations of organic compounds towards fish and other aquatic organisms, [82][83][84][85] nasal pungency, 79,[86]…”

Section: Prediction Of Molar Enthalpies Of Vaporization and Molar Entmentioning

confidence: 99%

Calculation of Abraham model L-descriptor and standard molar enthalpies of vaporization and sublimation for C9 - C26 mono-alkyl alkanes and polymethyl alkanes

Tirumala¹,

Huang²,

Eddula³

et al. 2020

ECB

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Study of benzyl- or cyclohexyl-functionalized ionic liquids using inverse gas chromatography

Cited by 36 publications

References 53 publications

Machine Learning Quantitative Structure–Property Relationships as a Function of Ionic Liquid Cations for the Gas-Ionic Liquid Partition Coefficient of Hydrocarbons

Machine Learning Quantitative Structure–Property Relationships as a Function of Ionic Liquid Cations for the Gas-Ionic Liquid Partition Coefficient of Hydrocarbons

Ionic Liquids: Recent Journey Through Chromatographic Separation

Calculation of Abraham model L-descriptor and standard molar enthalpies of vaporization and sublimation for C9 - C26 mono-alkyl alkanes and polymethyl alkanes

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