Prediction of true critical pressure of multi-component mixtures: Extending fast estimation methods

- The fast methods for predicting critical pressure of mixtures were revisited.
- A large data set on true critical pressure of 351 binary mixtures were collected.
- The methods have been extended and new interaction parameters have been introduced.
- New correlations were developed to estimate the interaction parameters of mixtures.

Various fast estimation methods such as Chueh-Prausnitz, Kreglewski-Kay, modified Wilson, and Redlich-Kister are available for predicting vapor-liquid critical pressure of fluid mixtures. The majority of these methods are dependent on the binary interaction parameters. Therefore, to achieve better prediction results for a multi-component mixture, interaction parameters for each binary set of components must be extracted or correlated from a reliable experimental data source. In the present work, 2773 experimental data on true critical pressure of 351 binary mixtures were collected through comprehensive literature search. Based on this data set, the appropriate fast estimation methods have been extended or modified and new interaction parameters for each binary set have been introduced. Besides, new correlations have been developed to estimate the interaction parameters of organic mixtures. Finally, the capability of different methods has been evaluated for predicting true critical pressure of 34 different multi-component mixtures with 210 data points.