Temperature-dependent structure-property modeling of viscosity for ionic liquids

Barycki, Maciej; Sosnowska, Anita; Gajewicz, Agnieszka; Bobrowski, Maciej; Wileńska, Dorota; Skurski, Piotr; Giełdoń, Artur; Czaplewski, Cezary; Uhl, Stefanie; Laux, Edith; Journot, Tony; Jeandupeux, Laure; Keppner, H.; Puzyn, Tomasz

doi:10.1016/j.fluid.2016.06.043

Cited by 34 publications

(38 citation statements)

References 48 publications

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“…Considering that a thorough and accurate characterization of these materials has a direct impact on the knowledge of their structure and in the design of their potential applications, we have performed an exhaustive compilation of some of the most relevant physical properties. Thus, we have reviewed the state of the art of density, viscosity, electrical conductivity, refractive index and surface tension for EAN and PAN at different temperatures [ 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 ,…”

Section: Introductionmentioning

confidence: 99%

Influence of Small Quantities of Water on the Physical Properties of Alkylammonium Nitrate Ionic Liquids

Ausín

Parajó

Trenzado

et al. 2021

IJMS

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This paper presents a comprehensive study of two alkylammonium nitrate ionic liquids. As part of this family of materials, mainly ethylammonium nitrate (EAN) and also propylammonium nitrate (PAN) have attracted a great deal of attention during the last decades due to their potential applications in many fields. Although there have been numerous publications focused on the measurement of their physical properties, a great dispersion can be observed in the results obtained for the same magnitude. One of the critical points to be taken into account in their physical characterization is their water content. Thus, the main objective of this work was to determine the degree of influence of the presence of small quantities of water in EAN and PAN on the measurement of density, viscosity, electrical conductivity, refractive index and surface tension. For this purpose, the first three properties were determined in samples of EAN and PAN with water contents below 30,000 ppm in a wide range of temperatures, between 5 and 95 °C, while the last two were obtained at 25 °C. As a result of this study, it has been concluded that the presence of water is critical in those physical properties that involve mass or charge transport processes, resulting in the finding that the absolute value of the average percentage change in both viscosity and electrical conductivity is above 40%. Meanwhile, refractive index (≤0.3%), density (≤0.5%) and surface tension (≤2%) present much less significant changes.

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Section: Introductionmentioning

confidence: 99%

Influence of Small Quantities of Water on the Physical Properties of Alkylammonium Nitrate Ionic Liquids

Ausín

Parajó

Trenzado

et al. 2021

IJMS

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“…Various computational methods such as group contribution methods (GCM), quantitative structure−property relationships (QSPR), and intelligent approaches (IA) can be used to predict the viscosity of ILs [ 35 , 36 ]. To this end, Gardas and Coutinho [ 37 ] performed a modeling investigation of viscosity of ILs by applying GCM for 500 data points from 29 ILs (based on imidazolium, pyrrolidinium, and pyridinium) in a wide range of temperature (293–393 K).…”

Section: Introductionmentioning

confidence: 99%

Viscosity of Ionic Liquids: Application of the Eyring’s Theory and a Committee Machine Intelligent System

et al. 2020

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Accurate determination of the physicochemical characteristics of ionic liquids (ILs), especially viscosity, at widespread operating conditions is of a vital role for various fields. In this study, the viscosity of pure ILs is modeled using three approaches: (I) a simple group contribution method based on temperature, pressure, boiling temperature, acentric factor, molecular weight, critical temperature, critical pressure, and critical volume; (II) a model based on thermodynamic properties, pressure, and temperature; and (III) a model based on chemical structure, pressure, and temperature. Furthermore, Eyring’s absolute rate theory is used to predict viscosity based on boiling temperature and temperature. To develop Model (I), a simple correlation was applied, while for Models (II) and (III), smart approaches such as multilayer perceptron networks optimized by a Levenberg–Marquardt algorithm (MLP-LMA) and Bayesian Regularization (MLP-BR), decision tree (DT), and least square support vector machine optimized by bat algorithm (BAT-LSSVM) were utilized to establish robust and accurate predictive paradigms. These approaches were implemented using a large database consisting of 2813 experimental viscosity points from 45 different ILs under an extensive range of pressure and temperature. Afterward, the four most accurate models were selected to construct a committee machine intelligent system (CMIS). Eyring’s theory’s results to predict the viscosity demonstrated that although the theory is not precise, its simplicity is still beneficial. The proposed CMIS model provides the most precise responses with an absolute average relative deviation (AARD) of less than 4% for predicting the viscosity of ILs based on Model (II) and (III). Lastly, the applicability domain of the CMIS model and the quality of experimental data were assessed through the Leverage statistical method. It is concluded that intelligent-based predictive models are powerful alternatives for time-consuming and expensive experimental processes of the ILs viscosity measurement.

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“…Quantitative structure-property/activity relationship (QSPR/QSAR) research is a widely used alternative to traditional experiments, and also have been applied to some studies on the prediction of the property of ILs. [6][7][8][9][10][11][12] Such as the imidazole ionic liquids were analyzed with QSPR techniques and melting temperature were estimated with clustering methods; [13] the melting point of 126 structurally diverse pyridinium bromides was predicted by QSPR models with the CODESSA program; [14] the viscosity of ILs was predicted using group contribution method with artificial neural network; [15] and the signs of specific optical rotations of chiral ILs were qualitatively predicted to assign absolute configuration, as well as their values were quantitatively predicted by several of the authors. [16] The quantitative structural-activity relationship studies (QSAR) have been used to predict the toxicity of ILs.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Ionic Liquids Toxicity against Leukemia Rat Cell Line IPC‐81 based on the Empirical‐like Models using Intuitive and Explainable Fingerprint Descriptors

Chen

et al. 2020

Molecular Informatics

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Ionic liquids as green solvents have been paid extensive attention in recent years. However, mostly it is cost and time-consuming to measure their properties. Thus, theorical methods, especially ultrafast chemoinformatics methods were introduced into these studies. Instead of abstract and complex models in some QSPR studies, in this study, the 2D structural features related to the toxicity of ionic liquids were discussed at first, and then the corresponding intuitive and meaningful descriptors were suggested to construct quantitative chemoinformatics models, finally a multiple linear regression (MLR) based on the empirical-like models were applied to the estimation of toxicities of 304 ionic liquids. For the test sets, the relationship coefficients reached up to R = 0.90. An external test set of 11 ionic liquids collected from other literatures was submitted to the achieved MLR equations, and the satisfactory result (R = 0.94) was obtained.

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Temperature-dependent structure-property modeling of viscosity for ionic liquids

Cited by 34 publications

References 48 publications

Influence of Small Quantities of Water on the Physical Properties of Alkylammonium Nitrate Ionic Liquids

Influence of Small Quantities of Water on the Physical Properties of Alkylammonium Nitrate Ionic Liquids

Viscosity of Ionic Liquids: Application of the Eyring’s Theory and a Committee Machine Intelligent System

Estimation of Ionic Liquids Toxicity against Leukemia Rat Cell Line IPC‐81 based on the Empirical‐like Models using Intuitive and Explainable Fingerprint Descriptors

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