Mutual diffusion coefficients of all 20 binary liquid mixtures that can be formed out of methanol, ethanol, acetone, benzene, cyclohexane, toluene, and carbon tetrachloride without a miscibility gap are studied at ambient conditions of temperature and pressure in the entire composition range. The considered mixtures show a varying mixing behavior from almost ideal to strongly non-ideal. Predictive molecular dynamics simulations employing the Green-Kubo formalism are carried out. Radial distribution functions are analyzed to gain an understanding of the liquid structure influencing the diffusion processes. It is shown that cluster formation in mixtures containing one alcoholic component has a significant impact on the diffusion process. The estimation of the thermodynamic factor from experimental vapor-liquid equilibrium data is investigated, considering three excess Gibbs energy models, i.e., Wilson, NRTL, and UNIQUAC. It is found that the Wilson model yields the thermodynamic factor that best suits the simulation results for the prediction of the Fick diffusion coefficient. Four semi-empirical methods for the prediction of the self-diffusion coefficients and nine predictive equations for the Fick diffusion coefficient are assessed and it is found that methods based on local composition models are more reliable. Finally, the shear viscosity and thermal conductivity are predicted and in most cases favorably compared with experimental literature values.

To gain an understanding of the transport and thermodynamic behavior of the highly non-ideal mixture methanol + cyclohexane, three complementary approaches, i.e. experiment, molecular simulation and predictive equations, are employed. The temperature and composition dependence of different diffusion coefficients is studied around the miscibility gap at ambient pressure. On the one hand Fick diffusion coefficients are measured experimentally by interferometric probing and on the other hand Maxwell-Stefan diffusion coefficients and intradiffusion coefficients are sampled by equilibrium molecular dynamics simulation at five temperatures below the upper critical temperature of ∼319 K. The spinodal curve is determined from extrapolation of the experimental Fick diffusion coefficient data and compared to predictions from excess Gibbs energy models. It is found that these models are not capable to correctly describe the activity coefficients over the whole composition range of the studied mixture. Thus, different parameter sets for a modified Wilson model are used for calculations of the thermodynamic factor, which is needed to transform Maxwell-Stefan into Fick diffusion coefficients and vice versa. Further, predictive equations for the Maxwell-Stefan diffusion coefficient, which are based on intradiffusion coefficients, are compared to simulation results. Using different approaches provides a clearer understanding of the relations between kinetic and thermodynamic properties contributing to the diffusion behavior of partially miscible mixtures.

A new version release (4.0) of the molecular simulation tool ms2 (Deublein et al., 2011; is presented. Version 4.0 of ms2 features two additional potential functions to address the repulsive and dispersive interactions in a more versatile way, i.e. the Mie potential and the Tang-Toennies potential. This version further introduces Kirkwood-Buff integrals based on radial distribution functions, which allow the sampling of the thermodynamic factor of mixtures with up to four components, orientational distribution functions to elucidate mutual configurations of neighboring molecules, thermal diffusion coefficients of binary mixtures for heat, mass as well as coupled heat and mass transport, Einstein relations to sample transport properties with an alternative to the Green-Kubo formalism, dielectric constant of non-polarizable fluid models, vapor-liquid equilibria relying on the second virial coefficient and cluster criteria to identify nucleation.

In spite of considerable research on the nature of aqueous alcohol mixtures that are characterized by microscopic inhomogeneity or incomplete mixing at the molecular level, transport properties have received little attention. We report the results of a study on diffusion in the ternary mixture of water with two alcohols, that is, water + methanol + ethanol, which is investigated on microscopic and macroscopic scales by means of molecular simulation and Taylor dispersion experiments. A novel protocol is developed for the comparison of mutual diffusion coefficients sampled by two fundamentally different approaches, which allows for their critical analysis. Because of complex intermolecular interactions, given by the presence of hydrogen bonding, the analysis of transport processes in this mixture is challenging for not only on the microscopic scale for simulation techniques but also on the macroscopic scale due to unfavorable optical properties. Binary limits of the Fick diffusion matrix are used for validation of the experimental ternary mixture results together with the verification of the validity of the phenomenological Onsager reciprocal relations. The Maxwell-Stefan diffusion coefficients and the thermodynamic factor are sampled by molecular simulation consistently on the basis of given force field models. The protocol for the comparison of the results from both approaches is also challenging because Fick diffusion coefficients of ternary mixtures depend on the frame of reference. Accordingly, the measured coefficients are transformed from the volume-averaged to the molar-averaged frame of reference, and it is demonstrated that both approaches provide not only similar qualitative behavior along two concentration paths but also strong quantitative agreement. This coordinated work using different approaches to study diffusion in multicomponent mixtures is expected to be a significant step forward for the accurate assessment of cross-diffusion.

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To better understand diffusion phenomena in highly nonideal ternary liquid mixtures, cyclohexane–toluene–methanol is studied by equilibrium molecular dynamics (EMD) simulation. Intradiffusion and Maxwell–Stefan (MS) diffusion coefficients, being strictly kinetic properties, are predicted by EMD over the entire composition range at ambient conditions. The thermodynamic contribution to the Fick diffusion coefficients is studied with an excess Gibbs energy model. Predictive results from the combination of these two approaches are in convincing agreement with experimental Fick diffusion coefficient data. Different aspects determining the composition dependence of diffusion coefficients, such as their behavior at the binary limits, hydrogen bonding, and stability criteria, are discussed. While the intradiffusion coefficients exhibit only a weak composition dependence, the MS diffusion coefficients are strongly affected by the nonideality of the present mixture. Fick diffusion coefficients reveal pronounced diffusive coupling effects and are mainly governed by the thermodynamic contribution, especially in the vicinity of the miscibility gap.

Measured main Fick diffusion coefficients are throughout positive. However, they may appear to be negative after transformation to the molar reference frame, if the excess volume is significant and the experimental uncertainties of the cross diffusion coefficients are large.

With laboratory and numerical work, we demonstrate that one of the main diffusion coefficients and the smaller eigenvalue of the Fick diffusion matrix are invariant to the number of methylene groups of the alcohol in ternary mixtures composed of an aromatic (benzene), a ketone (acetone) and one of three different alcohols (methanol, ethanol or 2-propanol). A critical analysis of the relationship between the kinetic and thermodynamic contributions to the diffusion coefficients allows us to explain this intriguing behaviour of this class of mixture. These findings are reflected by the diffusive behaviour of the according binary subsystems. Our approach provides a promising systematic framework for future investigations into the important and challenging problem of transport diffusion in multicomponent liquids. † Electronic supplementary information (ESI) available: Details on experimental and computational methods (PDF). See