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Consideration of mutual orientation structure in equations of state for mixtures

Subject Area Chemical and Thermal Process Engineering
Term from 2019 to 2023
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 425874380
 
For chemical separation processes, it is decisive that in each step from development over design to optimization, the thermodynamic properties of mixtures are known well. To this end, there is an increased usage of equations of state, since these allow the description and partially prediction of thermodynamic properties of mixtures in large pressure and temperature ranges. Though there has been substantial progress in the development and application of equations of state during the past decades, there are still many substances and mixtures that cannot be described with common theories. This is especially the case, if mixtures constituting substances with polar character and such with unpolar character are investigated. For the polar substances, especially such components in mixtures are complicated to treat that have a strongly asymmetric charge distribution in relation to the repulsive center. A well-known representative of this class of components is water. Such fluids tend to orient towards each other – they have a preferential orientation distribution. This orientation distribution can be considered using Co-Oriented Fluid Functional Equation for Electrostatic interactions (COFFEE), which was developed in preliminary work of the proposer, while common equations of state do not include this feature of fluid structure. In this project, the theory is to be extended to mixtures, where also the local concentration that differs from the global concentration in mixtures of interest, is considered. This is done with special attention to mixtures of polar and unpolar substances. This work is a substantial step to the description of complex aqueous mixtures with equations of state.
DFG Programme Research Grants
International Connection Austria
Co-Investigator Dr. Kerstin Münnemann
 
 

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