Juergen Rarey

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Jürgen Rarey is a physical properties and chemical process simulation specialist with a diploma in chemistry and PhD in chemical engineering from the Technical University of Dortmund (Germany). He held a researcher position at the University of Oldenburg (Germany) since 1989 in the group of Prof. Jürgen Gmehling, co-founded DDBST GmbH (www.ddbst.com) and acted as managing director from 1989 to 2017. Jürgen Rarey conducted his research on predictive models for important physical properties within his honorary professor position (2005-2018) at the University of Kwazulu-Natal in Durban (South Africa) in cooperation with Prof. Deresh Ramjugernath.In addition he was temporarily employed in industry within specific projects and was involved in a number of international research cooperations.Since 2016 Jürgen Rarey is a faculty member at ChEPS-KMUTT, Thonburi (Thailand), where he teaches regular courses on chemical thermodynamics.Besides his experimental and theoretical work, Jürgen Rarey has been teaching 5 to 10 courses per year for academia and industry on chemical thermodynamics (since 1989), process simulation (CHEMCAD and Aspen Plus) (since 1995) and chemical process development (since 2012, 2 months full day). Jürgen Rarey has authored about 50 publications in international journals, 4 books of the DECHEMA Chemistry Data Series and the textbook “Chemical Thermodynamics for Process Simulation”, Wiley (2012, 2018).Selected research interests include:•Development of automated equipment for determination of phase equilibria and physical properties.•Simultaneous correlation of mixture data (software development).•Chemical process simulation, process optimization and visualization.•Predictive models for pure component and mixture behavior.•COSMO-RS-type models.•Simulation and optimization of biorefinery processes.

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Papers by Juergen Rarey

A New Group Contribution Method For The Estimation Of Thermal Conductivity For Non-Electrolyte Organic Compounds

Optimum design of heat and mass transfer equipment form an integral part of cost-effective plant ... more Optimum design of heat and mass transfer equipment form an integral part of cost-effective plant design. For this purpose, reasonably accurate data on thermal conductivity is required for all phases. During the determination of thermal conductivity of fluid phases, convective heat transport has to be strictly avoided. Modern reliable equipment is now available for the routine measurement of liquid thermal conductivity but due to the large amount of data needed and the costs of experiments, alternative sources such as predictive methods are often employed. Substantial effort has been invested into the development of models for prediction or correlation of liquid thermal conductivity. Prediction of liquid thermal conductivity based only on a theoretical basis does not provide reliable results as the theories used to describe the liquid state are seldom satisfactory (Rodenbush et al. 1999). Therefore, prediction of thermo-physical properties is most often based upon empirical approaches like group contribution methods, whereby the property is calculated using contributions of the different structural groups within the compound. Group contribution methods still have the potential to produce more reliable results than other approaches. Methods for the estimation of the normal boiling point (Rarey and Cordes 2002 and Nannoolal et al. 2004), critical property data (Nannoolal et al. 2007), vapour pressures (Nannoolal et al. 2008 and Moller et al. 2008) and liquid viscosity (Nannoolal et al. 2009) have previously been developed in our group using the group contribution approach. Based on these methods a more accurate and precise method with a better temperature dependency is under development for liquid thermal conductivity prediction. The data used to formulate the method will be obtained from the extensive Dortmund Data Bank (DDB) (Gmehling et al. 2007), which contains approximately 110000 thermal conductivity data points for almost 900 different compounds. The model should therefore have a wider range of applicability than previous correlations and models, which were based on a smaller set of experimental data.

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Shortcut Method for the Prediction of the Cocrystal Solubility Line

Crystal Growth & Design

Chemical Thermodynamics for Process Simulation

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DDBPC: A Program System for the Management, Correlation and Calculation of Thermodynamic Properties of Pure Components and Mixtures

Software Development in Chemistry 5, 1991

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Dortmunder Datenbank — Organisation, Stand und Anwendungsmöglichkeiten

Software-Entwicklung in der Chemie 1, 1987

Physical Property Prediction in Organic Chemistry, 1988

Application of the bio-inspired Krill Herd optimization technique to phase equilibrium calculations

Computers & Chemical Engineering, 2015

ABSTRACT The Krill Herd optimization technique, which is based on the simulated herding behaviour... more ABSTRACT The Krill Herd optimization technique, which is based on the simulated herding behaviour of the krill crustacean, is applied to calculations involving phase equilibrium and phase stability, as the application of this emerging technique is extremely limited in the literature. In this work, the Krill Herd algorithm (KH)1 and the modified Lévy-Flight Krill Herd algorithm (LKH)2 has been applied to phase stability (PS)3 and phase equilibrium calculations in non-reactive (PE)4 and reactive (rPE)5 systems, where global minimization of the total Gibbs energy is necessary. Several phase stability and phase equilibrium systems were considered for the analysis of the performance of the technique that includes both vapour and liquid phase conditions.

Saturation Vapor Pressures and Transition Enthalpies of Low-Volatility Organic Molecules of Atmospheric Relevance: From Dicarboxylic Acids to Complex Mixtures

Chemical reviews, 2015

Aerosol particles are important constituents of the atmosphere. They impact modern society throug... more Aerosol particles are important constituents of the atmosphere. They impact modern society through their effects on visibility, 1 human health 2 and global climate. 3 Despite this great importance, they continue to represent a challenge to scientists due to their complexity. Atmospheric aerosols have both natural and anthropogenic sources and consist of both organic and inorganic molecules. Organic compounds constitute 20-90% of the atmospheric aerosol particle mass, depending on location. 4 The term primary aerosol particle is used to describe particles that are emitted directly into the atmosphere as particles. These primary particles are transformed in the atmosphere through the continuous exchange between the gas and particle phases via evaporation and condensation. Additionally, a large fraction of the organic particulate mass results from condensation of vapors that are produced by chemical reactions in the gas phase 4-5 and is termed secondary organic aerosol (SOA). To predict the temporal and spatial distribution of aerosols, particularly SOA, it is necessary to understand the fundamental parameters that govern the distribution of organic compounds between the gas and particle phases. Key thermodynamic properties describing the equilibrium gas-particle partitioning of organic compounds are the saturation vapor pressures 6 and the enthalpies of vaporization and sublimation. The majority of organic molecules, especially those produced from chemical reactions, that are partitioned to the condensed phase in the atmosphere are characterized as being oxidized and multifunctional, 7 and likely have molecular weights between 150-300 g mol-1 and relatively low saturation vapor pressures (< 10-2 Pa). 8 Recent laboratory and field observations have brought

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Development of a New Group Contribution Method for the Product Design of Biofuels

Proceedings of the Seventh International Conference on the Foundations of Computer-Aided Process Design, 2009

... E. Olivier a , J. Rarey a,b,c,* , BC Moller a and D. Ramjugernath a ... Current estimation an... more