Predictive ability of the MOSCED and UNIFAC activity coefficient estimation methods

Park, Jung Hag.; Carr, Peter W.

doi:10.1021/ac00148a015

Cited by 31 publications

(22 citation statements)

References 56 publications

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“…The Modified Separation of Cohesive Energy Density (MOSCED) model may be one of the most-extensive solvation models. 21 In the MOSCED model, additional contributions to the Flory−Huggins parameter are considered that arise from significant variations in the cybotactic region due to the local organization, as a result of electrostatic interactions, such as hydrogen bonding. This local organization causes the geometric mean assumption not to be valid anymore for highly polar and associating compounds.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Model Performances Evaluated for Infinite Dilution Activity Coefficients Prediction at 298.15 K

Brouwer

Schuur

2019

Ind. Eng. Chem. Res.

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The infinite dilution activity coefficient (γ i ∞) is often applied to characterize solvent–solute interactions, and, when accurately predicted, it can also serve as an early-stage solvent selection tool. Ample data are available on the use of a variety of models, which complicates decision making on which model to apply and when to apply it. A comparative study was performed for eight predictive models at 298.15 K, including the Hildebrand parameter and the Hansen solubility parameters. Also, three group contribution methods based on UNIFAC, COSMO-RS, the Abraham model, and the MOSCED model were evaluated. Overall, the MOSCED model and the Abraham model are most accurate for molecular solvents and ionic liquids, respectively, with average relative deviations of 16.2% ± 1.35% and 65.1% ± 4.50%. Therefore, cautious decision making based on predicted γ i ∞ in ionic liquids should always be done, because of the expected significant deviations. A MOSCED model for ionic liquids could be a potential approach for higher accuracy.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Model Performances Evaluated for Infinite Dilution Activity Coefficients Prediction at 298.15 K

Brouwer

Schuur

2019

Ind. Eng. Chem. Res.

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“…In the present study we will use the solubility parameter method MOSCED [12,[19][20][21][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44]. The use of solubility parameter-based methods is advantageous because they allow one to not only predict phase behavior using a simple analytic equation, but they can help offer an explanation in terms of the responsible molecular-level interactions.…”

Section: Introductionmentioning

confidence: 99%

Predicting the Solubility of Nonelectrolyte Solids Using a Combination of Molecular Simulation with the Solubility Parameter Method MOSCED: Application to the Wastewater Contaminants Monuron, Diuron, Atrazine and Atenolol

et al. 2022

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Methods to predict the equilibrium solubility of nonelectrolyte solids are indispensable for early-stage process development, design, and feasibility studies. Conventional analytic methods typically require reference data to regress parameters, which may not be available or limited for novel systems. Molecular simulation is a promising alternative, but is computationally intensive. Here, we demonstrate the ability to use a small number of molecular simulation free energy calculations to generate reference data to regress model parameters for the analytical MOSCED (modified separation of cohesive energy density) model. The result is an efficient analytical method to predict the equilibrium solubility of nonelectrolyte solids. The method is demonstrated for the wastewater contaminants monuron, diuron, atrazine and atenolol. Predictions for monuron, diuron and atrazine are in reasonable agreement with MOSCED parameters regressed using experimental solubility data. Predictions for atenolol are inferior, suggesting a potential limitation in the adopted molecular models, or the solvents selected to generate the necessary reference data.

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“…The common approach for the S ∞ prediction is predicting the IDAC for the solute and raffinate at the same temperature and pressure separately and use those values to derive S ∞ . There have been numerous approaches for S ∞ prediction for the liquid solutes based on very different principles, such as solvation models (SM) [8,9], group contribution method (GCM) [10,11], Conductorlike Screening Model for Real Solvents (COSMO-RS) [12] and Quantitative Structure-Activity Relationship (QSPR) [13][14][15][16]. SM and GCM require prior knowledge of experimental and thermodynamic parameters of solute and solvent (e.g.…”

Section: Introductionmentioning

confidence: 99%

QSPR modeling of selectivity at infinite dilution of ionic liquids

Klimenko

Carrera

2021

J Cheminform

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The intelligent choice of extractants and entrainers can improve current mixture separation techniques allowing better efficiency and sustainability of chemical processes that are both used in industry and laboratory practice. The most promising approach is a straightforward comparison of selectivity at infinite dilution between potential candidates. However, selectivity at infinite dilution values are rarely available for most compounds so a theoretical estimation is highly desired. In this study, we suggest a Quantitative Structure–Property Relationship (QSPR) approach to the modelling of the selectivity at infinite dilution of ionic liquids. Additionally, auxiliary models were developed to overcome the potential bias from big activity coefficient at infinite dilution from the solute. Data from SelinfDB database was used as training and internal validation sets in QSPR model development. External validation was done with the data from literature. The selection of the best models was done using decision functions that aim to diminish bias in prediction of the data points associated with the underrepresented ionic liquids or extreme temperatures. The best models were used for the virtual screening for potential azeotrope breakers of aniline + n-dodecane mixture. The subject of screening was a combinatorial library of ionic liquids, created based on the previously unused combinations of cations and anions from SelinfDB and the test set extractants. Both selectivity at infinite dilution and auxiliary models show good performance in the validation. Our models’ predictions were compared to the ones of the COSMO-RS, where applicable, displaying smaller prediction error. The best ionic liquid to extract aniline from n-dodecane was suggested.

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Predictive ability of the MOSCED and UNIFAC activity coefficient estimation methods

Cited by 31 publications

References 56 publications

Model Performances Evaluated for Infinite Dilution Activity Coefficients Prediction at 298.15 K

Model Performances Evaluated for Infinite Dilution Activity Coefficients Prediction at 298.15 K

Predicting the Solubility of Nonelectrolyte Solids Using a Combination of Molecular Simulation with the Solubility Parameter Method MOSCED: Application to the Wastewater Contaminants Monuron, Diuron, Atrazine and Atenolol

QSPR modeling of selectivity at infinite dilution of ionic liquids

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