Mixture Models and a New Form of Empirical Fundamental Equations of State by Means ofMolecular Simulation and Hybrid Data Sets

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Today, empirical multiparameter models are successfully used to accurately describe properties of well measured mixtures. However, models of this kind are limited with regard to the description of multicomponent mixtures, in which relevant binary subsystems are not or poorly experimentally described. The observed problems are related both to the underlying multi-fluid corresponding states approach and to features of the equations of state used to describe the pure components. Theoretically it is obvious that interaction between unlike molecules cannot be described by corresponding states approaches. In fact, different features on a molecular level yield different contributions to the total interaction both in a pure fluid and in a mixture. However, these contributions can hardly be separated based on experimental data for real fluids. At this point molecular simulation has a severe advantage: molecular parameter can be varied systematically. Based on the approach by Lustig it is possible to directly analyse the impact of molecular features on the Helmholtz energy and its derivatives. On this basis it becomes possible to develop functional forms for empirical multiparameter equations of state, which reflect the influence of molecular parameters. To achieve high accuracy, the final equations have to be fitted to hybrid data sets (data sets containing both experimental and molecular simulation data). With this new type of empirical multiparameter equations of state mixture models can be developed, which describe interactions based on a combination of contributions that result from interactions of unlike molecular features. If the approach by Lustig can be adapted to molecular simulations for mixtures, it becomes possible to directly investigate the influence of molecular interactions on derivatives of the Helmholtz energy. This would establish the basis for the development of molecularly founded mixing rules for multiparameter equations of state. To achieve the aimed at high accuracy, fitting to hybrid data sets will be required for mixtures as well. However, poorly or not experimentally investigated binary subsystems can be described correctly (even though less accurately) on the basis of molecular parameters or on the basis of molecular simulation data. The proposed project aims to develop a new generation of accurate (semi-)empirical property models, which are based on results of extensive and novel molecular simulations, and which are clearly superior to existing models with regard to the description of properties of poorly experimentally investigated pure fluids and binary subsystems of multicomponent mixtures.