Extensive Databases and Group Contribution QSPRs of Ionic Liquid Properties. 3: Surface Tension

Paduszyński, Kamil

doi:10.1021/acs.iecr.1c00783

Cited by 21 publications

(12 citation statements)

References 54 publications

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“…When experimental data for the relevant property parameters in the EoS are scarce, it may increase the calculation error of the u . Fortunately, the quantitative structure–property relationship (QSPR) method has ingeniously addressed the phenomenon of relying on other properties for u prediction modeling. − Based on 446 experimental data points (DPs) for 41 ILs, Sattari et al developed a QSPR model for estimating the u at atmospheric pressure with a satisfactory R 2 of 0.9862. Wu et al discussed the effects of temperature and alkyl chain length on the u of 96 ILs and proposed a second-order group contribution method (GCM) with an average absolute deviation of 2.34%.…”

Section: Introductionmentioning

confidence: 99%

QSPR Model to Predict the Speed of Sound of Ionic Liquids as a Function of Variable Temperature and Pressure

Liu

Wang

et al. 2023

Ind. Eng. Chem. Res.

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In this work, a u(T,P,I)-QSPR model utilizing the norm index (I) is developed to predict the speed of sound (u) of ionic liquids (ILs) over a wide range of pressures (P) and temperatures (T). During the modeling process, preprocessing is first performed against the collected data by using the equipartition rules for temperature and pressure. Temperature and pressure effects are introduced on the basis of cation, anion, and IL descriptors. The external and internal validations are used to evaluate the predictability and robustness of the u(T,P,I)-QSPR model. The statistical results show that the u(T,P,I)-QSPR model can accurately predict the u of ILs at variable temperature and pressure with R 2 test = 0.9952, Q 2 LOCO = 0.9917, and Q 2 LOAO = 0.9903. This facilitates the acquisition of property data (e.g., density and heat capacity) associated with u and the design of functional ILs.

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Section: Introductionmentioning

confidence: 99%

QSPR Model to Predict the Speed of Sound of Ionic Liquids as a Function of Variable Temperature and Pressure

Liu

Wang

et al. 2023

Ind. Eng. Chem. Res.

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“…The group contribution method (GCM) and the quantitative structure–property relationship (QSPR) are two available methods for obtaining the temperature-dependent properties of ILs. − For instance, a nonlinear GC model was developed by Sattari et al using the least squares support vector machine method to predict the speed of sound ( u ) with the average absolute relative deviation percent (AARD %) of 0.87 for a test set. Ahmadi et al proposed a GC model for predicting the C p of ILs based on the molecular weight and atoms information with an AARD % of 5.8 for the optimization data set and 5.6 for the validation data set.…”

Section: Introductionmentioning

confidence: 99%

Norm Indices-Driven Robust QSPR Model for Mining Temperature-Dependent Properties of Ionic Liquids

Liu,

Gu,

et al. 2023

ACS Sustainable Chem. Eng.

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As a green solvent, temperature-dependent properties of ionic liquids (ILs) are important for their application. The large number of ILs makes experimental measurements of temperature-dependent properties nearly impossible to complete, which drives the development of models for filling in the data gaps. In this work, f(T,I)-QSPR models for refractive index (n D ), heat capacity (C p ), surface tension (γ), and thermal conductivity (λ) are developed based on norm indices (I s ) and prescreened extensive data sets. Importantly, leave-one-ion-out cross-validation (LOIO-CV) is employed to assess the stability of the QSPR models, ensuring the robust prediction of ILs with new cations and anions. The superiority of the four models is also confirmed by various evaluation means, including external validation, Y-random analysis, and the comparison with results from the literature. Given the satisfactory accuracy, these models will be useful for the rapid screening of IL properties data for the design of environmentally friendly ILs.

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“…The surface tension of ILs is between those of alkanes and water [ 22 ]. It can be measured directly or predicted using, for example, the parachor formula [ 23 ] or group contribution methods [ 24 ]. This study predicts surface tension using an improved Lorentz-Lorenz equation.…”

Section: Introductionmentioning

confidence: 99%

A New Compartmentalized Scale (PN) for Measuring Polarity Applied to Novel Ether-Functionalized Amino Acid Ionic Liquids

Guo

et al. 2022

Molecules

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Functionalized and environmentally friendly ionic liquids are required in many fields, but convenient methods for measuring their polarity are lacking. Two novel ether-functionalized amino acid ionic liquids, 1-(2-methoxyethyl)-3-methylimidazolium alanine ([C1OC2mim][Ala]) and 1-(2-ethoxyethyl)-3-methylimidazolium alanine ([C2OC2mim][Ala]), were synthesized by a neutralization method and their structures confirmed by NMR spectroscopy. Density, surface tension, and refractive index were determined using the standard addition method. The strength of intermolecular interactions within these ionic liquids was examined in terms of standard entropy, lattice energy, and association enthalpy. A new polarity scale, PN, is now proposed, which divides polarity into two compartments: the surface and the body of the liquid. Surface tension is predicted via an improved Lorentz-Lorenz equation, and molar surface entropy is used to determine the polarity of the surface. This new PN scale is based on easily measured physicochemical parameters, is validated against alternative polarity scales, and is applicable to both ionic and molecular liquids.

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Extensive Databases and Group Contribution QSPRs of Ionic Liquid Properties. 3: Surface Tension

Cited by 21 publications

References 54 publications

QSPR Model to Predict the Speed of Sound of Ionic Liquids as a Function of Variable Temperature and Pressure

QSPR Model to Predict the Speed of Sound of Ionic Liquids as a Function of Variable Temperature and Pressure

Norm Indices-Driven Robust QSPR Model for Mining Temperature-Dependent Properties of Ionic Liquids

A New Compartmentalized Scale (PN) for Measuring Polarity Applied to Novel Ether-Functionalized Amino Acid Ionic Liquids

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