The efficient and energetically optimal design of thermodynamic processes requires an exact knowledge of the thermodynamic properties of the used fluids. For this reason, there is a need for accurate equations of state. Databases alone cannot meet the increasing demands of process engineering. Mapping the full thermodynamic properties of a given fluid based on laboratory experiments alone is often not possible because of the associated financial expense, time investment, and potentially extreme measurement conditions (e.g., toxicity, flammability, explosion hazard, or corrosivity). As a result, few experimental data sets are available for many fluids of interest to industry and academia. Molecular modeling and simulation have become a point of acceptance in the applied sciences and represent a potential solution to meet the need for thermodynamic data. Molecular simulation provides macroscopic properties (e.g., pressure, temperature, density, speed of sound, etc.) exclusively from microscopic information (e.g., bond lengths or angles, point charges, dipoles, etc.). Accordingly, their predictive capabilities are in principle limited only by the quality of the molecular interaction model representing the substance under study. Thus, molecular simulation can be used to fill gaps in experimental databases.

These hybrid data sets (experimental and simulated thermodynamic property data in combination) form the basis of this project and are used to develop fundamental equations. In this way, not only gaps in the experimental database are filled, but also the extrapolation behavior can be improved. This strategy has already been successfully applied to several pure fluids, e.g. ethylene oxide [1], dichloroethane [2] and siloxanes [3,4]. All these fluids are now described in the fluid range up to twice the critical temperature including vapor-liquid phase equilibrium. Based on investigations under extreme temperature, pressure and density conditions, the extrapolation behavior is demonstrated to be correct.

The problem of availability of property data is further aggravated in the case of mixture properties. In the case of mixtures, composition must be considered as a third independent variable, whereas pure fluid states are defined by only two independent properties (e.g., temperature and pressure). The N+2-dimensional surfaces of mixtures containing N components make the measurement of the entire surface extremely time consuming. Even the approach of measuring and modeling only binary mixtures is not feasible. Therefore, predicting thermophysical properties using molecular simulation could also be an answer to this problem at this point.

In this project, a class of empirical equations of state is developed using simulation data. The simulations are used to represent various microscopic effects such as bond lengths or angles, point charges, dipoles, etc. The resulting model combines the various influences in such a way that thermodynamic properties of real substances can be predicted when the molecular structure is known.

This is a joint project with the Department of Thermodynamics and Thermal Process Engineering at the Technical University of Berlin under the direction of Prof. Dr.-Ing. habil. Jadran Vrabec.