2021Industrial & Engineering Chemistry ResearchOpen access

Predicting Activity Coefficients at Infinite Dilution for Varying Temperatures by Matrix Completion

Julie Damay, Fabian Jirasek, Marius Kloft, Michael Bortz, Hans Hasse

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Abstract

High Resolution Image Download MS PowerPoint Slide Activity coefficients describe the nonideality of liquid mixtures and are essential for calculating equilibria. The activity coefficients at infinite dilution in binary mixtures are particularly important as the activity coefficients at finite concentrations can be predicted based on their knowledge not only in binary mixtures but also in multicomponent mixtures. The available experimental data on these activity coefficients at infinite dilution in binary mixtures is readily accessible in databases and can be organized in a matrix with the rows representing the solutes and the columns representing the solvents or vice versa. As experimental data is lacking for many binary mixtures, this matrix is only sparsely populated. Filling its gaps using predictive methods is essential. Recently, matrix completion methods (MCMs) have been applied successfully for this purpose. However, only isothermal data sets have been considered. In the present work, we apply an MCM to predict activity coefficients at infinite dilution at varying temperatures. Furthermore, we show how one can incorporate physical knowledge on the nature of the temperature dependency of the activity coefficients at infinite dilution. The predictions obtained with this new approach outperform those obtained with the best currently available physical prediction method for activity coefficients at infinite dilution, the modified UNIFAC (Dortmund) method.

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High Resolution Image Download MS PowerPoint Slide Activity coefficients describe the nonideality of liquid mixtures and are essential for calculating equilibria. The activity coefficients at infinite dilution in binary mixtures are particularly important as the activity coefficients at finite concentrations can be predicted based on their knowledge not only in binary mixtures but also in multicomponent mixtures. The available experimental data on these activity coefficients at infinite dilution in binary mixtures is readily accessible in databases and can be organized in a matrix with the rows representing the solutes and the columns representing the solvents or vice versa. As experimental data is lacking for many binary mixtures, this matrix is only sparsely populated. Filling its gaps using predictive methods is essential. Recently, matrix completion methods (MCMs) have been applied successfully for this purpose. However, only isothermal data sets have been considered. In the present work, we apply an MCM to predict activity coefficients at infinite dilution at varying temperatures. Furthermore, we show how one can incorporate physical knowledge on the nature of the temperature dependency of the activity coefficients at infinite dilution. The predictions obtained with this new approach outperform those obtained with the best currently available physical prediction method for activity coefficients at infinite dilution, the modified UNIFAC (Dortmund) method.

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Available abstract

High Resolution Image Download MS PowerPoint Slide Activity coefficients describe the nonideality of liquid mixtures and are essential for calculating equilibria. The activity coefficients at infinite dilution in binary mixtures are particularly important as the activity coefficients at finite concentrations can be predicted based on their knowledge not only in binary mixtures but also in multicomponent mixtures. The available experimental data on these activity coefficients at infinite dilution in binary mixtures is readily accessible in databases and can be organized in a matrix with the rows representing the solutes and the columns representing the solvents or vice versa. As experimental data is lacking for many binary mixtures, this matrix is only sparsely populated. Filling its gaps using predictive methods is essential. Recently, matrix completion methods (MCMs) have been applied successfully for this purpose. However, only isothermal data sets have been considered. In the present work, we apply an MCM to predict activity coefficients at infinite dilution at varying temperatures. Furthermore, we show how one can incorporate physical knowledge on the nature of the temperature dependency of the activity coefficients at infinite dilution. The predictions obtained with this new approach outperform those obtained with the best currently available physical prediction method for activity coefficients at infinite dilution, the modified UNIFAC (Dortmund) method.

Key concepts: Activity coefficient, Dilution, UNIFAC, Binary number, Isothermal process, Matrix (chemical analysis), Thermodynamics, Work (physics)

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