## Abstract

In this paper, we compared seven diffusion models in terms of prediction performances. Using vapour-liquid equilibrium (VLE) data, we calculate the thermodynamic correction factor as a function of composition for eleven binary liquid mixtures using non-random two-liquid and Redlich-Kister models. These data, together with intra-diffusion coefficients, and viscosity values are used to predict mutual diffusivity.

The Darken-based models, which consider a scaling power on the thermodynamic factor, give accurate predictions, with absolute average relative deviation (AARD) values between 1 and 20 %. The removal of the scaling power leads to a decrease in prediction accuracy. The viscosity-based models with (Vis-SF) and without (Vis-nSF) scaling factor have AARD of 14 and 30 %, respectively. The dimerization model is inaccurate for most mixtures except those containing water, while the Vignes-based model (V-Gex), which is based on the Gibbs free energy, gave high AARD values of 25 %, hence, not as reliable when compared to the other models.

The Darken-based models, which consider a scaling power on the thermodynamic factor, give accurate predictions, with absolute average relative deviation (AARD) values between 1 and 20 %. The removal of the scaling power leads to a decrease in prediction accuracy. The viscosity-based models with (Vis-SF) and without (Vis-nSF) scaling factor have AARD of 14 and 30 %, respectively. The dimerization model is inaccurate for most mixtures except those containing water, while the Vignes-based model (V-Gex), which is based on the Gibbs free energy, gave high AARD values of 25 %, hence, not as reliable when compared to the other models.

Original language | English |
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Article number | 119930 |

Pages (from-to) | 1-15 |

Number of pages | 15 |

Journal | Chemical Engineering Science |

Volume | 291 |

Issue number | 2024 |

Early online date | 28 Feb 2024 |

DOIs | |

Publication status | Published - 5 Jun 2024 |

## Keywords

- Vapour-liquid equilibrium data,
- Liquid-phase diffusion
- Mutual diffusion coefficient
- Darken equation
- Binary mixtures