Equations of state (EoS) are essential in the modeling of a wide range of industrial and natural processes. Desired qualities of EoS are accuracy, consistency, computational speed, robustness, and predictive ability outside of the domain where they have been fitted. In this work, we review present challenges associated with established models, and give suggestions on how to overcome them in the future. The most accurate EoS available, multiparameter EoS, have a second artificial Maxwell loop in the two-phase region that gives problems in phase-equilibrium calculations and excludes them from important applications such as treatment of interfacial phenomena with mass-based density functional theory. Suggestions are provided on how this can be improved. Cubic EoS are among the most computationally efficient EoS, but they often lack sufficient accuracy. We show that extended corresponding state EoS are capable of providing significantly more accurate single-phase predictions than cubic EoS with only a doubling of the computational time. In comparison, the computational time of multiparameter EoS can be orders of magnitude larger. For mixtures in the two-phase region, however, the accuracy of extended corresponding state EoS has a large potential for improvement. The molecular-based SAFT family of EoS is preferred when predictive ability is important, for example, for systems with strongly associating fluids or polymers where few experimental data are available. We discuss some of their benefits and present challenges. A discussion is presented on why predictive thermodynamic models for reactive mixtures such as CO2–NH3 and CO2–H2O–H2S must be developed in close combination with phase- and reaction equilibrium theory, regardless of the choice of EoS. After overcoming present challenges, a next-generation thermodynamic modeling framework holds the potential to improve the accuracy and predictive ability in a wide range of applications such as process optimization, computational fluid dynamics, treatment of interfacial phenomena, and processes with reactive mixtures.

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A one-dimensional multi-phase flow model for thermomagnetically pumped ferrofluid with heat transfer is proposed. The thermodynamic model is a combination of a simplified particle model and thermodynamic equations of state for the base fluid. The magnetization model is based on statistical mechanics, taking into account non-uniform particle size distributions. An implementation of the proposed model is validated against experiments from the literature, and found to give good predictions for the thermomagnetic pumping performance. However, the results reveal a very large sensitivity to uncertainties in heat transfer coefficient predictions.

We construct a model to investigate the interfacial stability of film boiling, and discover that instability of very thin vapour films and subsequent large interface superheating is only possible if thermocapillary instabilities are present. The model concerns horizontal saturated film boiling, and includes novel features such as non-equilibrium evaporation based on kinetic theory, thermocapillary and vapour thrust stresses and van der Waals interactions. From linear stability analysis applied to this model, we are led to suggest that vapour film collapse depends on a balance between thermocapillary instabilities and vapour thrust stabilization. This yields a purely theoretical prediction of the Leidenfrost temperature. Given that the evaporation coefficient is in the range 0.7–1.0, this model is consistent with the average Leidenfrost temperature of every fluid for which data could be found. With an evaporation coefficient of 0.85, the model can predict the Leidenfrost point within 10 % error for every fluid, including cryogens and liquid metals where existing models and correlations fail.