QSPR prediction of gas-to-ionic liquid partition coefficient of organic solutes dissolved in 1-(2-hydroxyethyl)-1-methylimidazolium tris(pentafluoroethyl)trifluorophosphate using the replacement method and support vector regression

Khooshechin, Sajad; Dashtbozorgi, Zahra; Golmohammadi, Hassan; Acree, William E.

doi:10.1016/j.molliq.2014.03.012

Cited by 15 publications

(5 citation statements)

References 29 publications

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“…1 These compounds are a novel class of solvents that have drawn industrial attention due to their interesting properties such as thermal and electrochemical stability, negligible vapor pressure, non-inflammability, satisfactory solvation behavior, high density, high thermal conductivity, a wide temperature range for the liquid state, high selectivity and tuneable properties. 2,3 Due to these advantages, ILs have found diverse uses as electrolytic media, in synthesis, catalysis and separation, as solvents and in engineering and biological applications. 4 Actually, ILs are no longer confined to academia because they are already present in a range of different commercial products and industrial processes.…”

Section: Introductionmentioning

confidence: 99%

Development of predictive QSAR models for Vibrio fischeri toxicity of ionic liquids and their true external and experimental validation tests

et al. 2016

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Despite possessing an interesting chemical nature and tuneable physicochemical properties, ionic liquids (ILs) must have their ecotoxicity tested in order to be commercialized. The water solubility of ILs allows their easy access to the aquatic compartment of the ecosystem creating a potential hazard to aquatic organisms. Hence, it is relevant to design ionic liquids with lower toxicity while keeping the desired properties of interest. Considering the possibility of an enormous number of combinations of different cations and anions, a rational guidance for the structural design of ionic liquids is essential in order to prioritize the synthesis as well as testing of selected molecules only. Predictive in silico models, such as quantitative structure-activity relationship (QSAR) models, can play a pivotal role in exploring the important chemical attributes contributing to the response activity. These models may then lead to the design of novel ionic liquids. The present study aims at developing predictive QSAR models for the ecotoxicity of ionic liquids using the bacteria Vibrio fischeri as an indicator response species. Instead of a single model, here we have used multiple models to capture more complete structural information of ionic liquids for toxicity towards Vibrio fischeri. The derived chemical attributes have been implemented in designing new analogues, some of which have been synthesized and had their ecotoxicity tested for the same model organism. The predictive QSAR models reported here can be used for ecotoxicity prediction of new IL chemicals and for data-gap filling. Moreover, the synthesized low-toxic ILs could be considered for evaluation as well as for application in suitable processes serving the purpose of industry and academia.

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Section: Introductionmentioning

confidence: 99%

Development of predictive QSAR models for Vibrio fischeri toxicity of ionic liquids and their true external and experimental validation tests

et al. 2016

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“…It should be noted that the best molecular descriptor of anions should be selected from a pool containing a huge number of different anion descriptors (i.e., 1098) along with the fixed X 2 and Pol variables. There are many methods for variable selection. − In the current study, the genetic algorithms (GAs) are applied for the selection of variables. The details of GA–MLR can be studied elsewhere. , It should be added that QSARINS software was employed to develop the GA–MLR models …”

Section: Qspr Methodsmentioning

confidence: 99%

How Anion Structures Can Affect the Thiophene Distribution between Imidazolium-Based Ionic Liquid and Hydrocarbon Phases? A Theoretical QSPR Study

Gorji

Sobati

2019

Energy Fuels

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In this study, the effects of different anion structures have been investigated on the thiophene distribution between ionic liquid (IL) and hydrocarbon phases in the ternary systems using quantitative structure−property relationship. The role of anion structures was investigated in the presence of different cations and hydrocarbons. In this regard, three different datasets were selected from the literature containing {([C n MIM/anion]−thiophene−different hydrocarbon solvents): n = 2, 4, and 8} with 445 data points. It was found that the "E1v" descriptor of anions, belonging to the WHIM descriptor category, can take into account the effect of anion structures on the thiophene distribution for the systems containing the IL with the [C 2 MIM] cation and different hydrocarbons. It was found that increasing the E1v values of anion structures leads to a decrease in the thiophene distribution coefficients. E1v reflects the unfilled space of the anion structure, which in turn affects the interactions of the anion and cation in the IL structure. More unfilled spaces of the anion structure lead to more powerful interaction with the cation, which in turn limit the cation interaction with thiophene and decrease the thiophene distribution coefficient. It was also found that the effect of the anion on the thiophene distribution is decreased by increasing the length of alkyl chains in the cation from [C 2 MIM] to [C 4 MIM] and [C 8 MIM]. This finding can be attributed to the higher free volumes of [C 4 MIM] and [C 8 MIM] cations in comparison with that of [C 2 MIM], which allows more efficient packing of thiophene in the IL structure.

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“…Many previous studies have revealed that it is indeed feasible to predict partition coefficients by establishing quantitative structureproperty relationships (QSPRs) [2,[21][22][23]. For K ILA , ideal QSPR models based on theoretically calculated descriptors have also been reported by different research groups [24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Gas‐to‐ionic liquid partition: QSPR modeling and mechanistic interpretation

Zou

Chang

Lou

et al. 2023

Molecular Informatics

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The present work was devoted to explore the quantitative structure‐property relationships for gas‐to‐ionic liquid partition coefficients (log KILA). A series of linear models were first established for the representative dataset (IL01). The optimal model was a four‐parameter equation (1Ed) consisting of two electrostatic potential‐based descriptors ( ΣVs,ind- ${{\rm { \Sigma }}{V}_{s,ind}^{-}}$ and Vs,max), one 2D matrix‐based descriptor (J_D/Dt) and dipole moment (μ). All of the four descriptors introduced in the model can find the corresponding parameters, directly or indirectly, from Abraham's linear solvation energy relationship (LSER) or its theoretical alternatives, which endows the model good interpretability. Gaussian process was utilized to build the nonlinear model. Systematical validations, including 5‐fold cross‐validation for the training set, the validation for test set, as well as a more rigorous Monte Carlo cross‐validation were performed to verify the reliability of the constructed models. Applicability domain of the model was evaluated, and the Williams plot revealed that the model can be used to predict the log KILA values of structurally diverse solutes. The other 13 datasets were also processed in the same way, and all of the linear models with expressions similar to equation 1Ed were obtained. These models, whether linear of nonlinear, represent satisfactory statistical results, which confirms the universality of the method adopted in this study in QSPR modeling of gas‐to‐IL partition.

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QSPR prediction of gas-to-ionic liquid partition coefficient of organic solutes dissolved in 1-(2-hydroxyethyl)-1-methylimidazolium tris(pentafluoroethyl)trifluorophosphate using the replacement method and support vector regression

Cited by 15 publications

References 29 publications

Development of predictive QSAR models for Vibrio fischeri toxicity of ionic liquids and their true external and experimental validation tests

Development of predictive QSAR models for Vibrio fischeri toxicity of ionic liquids and their true external and experimental validation tests

How Anion Structures Can Affect the Thiophene Distribution between Imidazolium-Based Ionic Liquid and Hydrocarbon Phases? A Theoretical QSPR Study

Gas‐to‐ionic liquid partition: QSPR modeling and mechanistic interpretation

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