Critical Data

Estimation of pure component properties: Part 2. Estimation of critical property data by group contribution

Yash Nannoolala, Jürgen Rareya, b,, Deresh Ramjugernatha

a School of Chemical Engineering, University of Kwa-Zulu Natal, Durban 4041, South Africa

b Industrial Chemistry, Carl von Ossietzky University Oldenburg, 26111 Oldenburg, Federal Republic of Germany

Received 13 September 2005, Revised 20 November 2006, Accepted 22 November 2006, Available online 30 November 2006


A new group contribution method for the estimation of critical property data has been developed. The method is based on structural group definitions, with minor modifications, of a method recently published for the estimation of the normal boiling point by Nannoolal et al. [Y. Nannoolal, J. Rarey, D. Ramjugernath, W. Cordes, Fluid Phase Equilib. 226 (2004) 45–63]. Special care was taken to ensure physically meaningful extrapolation to large and multifunctional compounds, as it could be shown that such extrapolation may lead to very improbable or unrealistic results in the case of some methods published earlier. Regression of group increments was not performed simultaneously but with great care one group at a time. With all other group increments fixed, all data for components with a specific group led to approximately the same group increment. This allowed one to determine group increments for cases where only one reliable experimental value was available. For the case of more than one strongly associating group, a group interaction contribution was required as these groups do not observe simple additivity. The estimation of the critical temperature requires knowledge of the normal boiling point. Critical pressure and volume can be estimated from chemical structure alone. The performance of the new model has been compared with 10 well-known estimation methods from literature and the results indicate that the new model is significantly more reliable. To enable comparison, chemical family definitions have been developed that allow one to automatically classify new components and thus, inform the user about the expected reliability of the different methods for a component of interest. Chemical family definitions are based on the kind and frequency of the different structural groups in the molecule. In addition to these advantages, the range of applicability of the new method is larger than that of comparable methods.

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