A STUDY ON THE MODELS FOR INFINITE DILUTION PARTIAL MOLAR VOLUMES OF SOLUTES IN SUPERCRITICAL FLUIDS

• Type: Article in International Scientific Journal
• Date: 1995

Authors

LIU, HQ (Author) Other; Maria Eugénia Macedo (Author) FEUP

Journal

Title: Industrial & Engineering Chemistry Research

Vol. 34

Pages: 2029-2037

ISSN: 0888-5885

Publisher: American Chemical Society

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ISI Web of Knowledge - 20 Citations

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Scopus - 23 Citations

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Other information

Authenticus ID: P-001-GTA

DOI: 10.1021/ie00045a012

Abstract (EN): Infinite dilution partial molar volumes (PMV) of solutes in supercritical fluids (SCF) are very important thermodynamic properties of SCF mixtures. But until recently very few works have been dedicated to the measurements and the prediction or correlation of these properties. In this paper we present a systematic study on various models for the representation of PMV. First, we tried to predict the PMV using model parameters regressed from solubility data. Four models have been tested, and it is found that all these models can only be used qualitatively, not quantitatively. After that, we used 11 models for the correlations with temperature-dependent parameters. It is found that the model based on Wang and Tavlarides's (WT) dilute solution expression and a three-parameter empirical equation derived in this work give the best results. Some simple correlations also give acceptable,results, It is surprising that some theoretical models, e.g., Wheeler's decorated lattice gas model and the models based on the fluctuation theory do not work as well as expected. Moreover, we have used six models for correlations with temperature-independent parameters. We conclude that the model proposed in this work with three parameters based on the WT dilute solution expression gives the best results. The modified Peng-Robinson equation of state (EoS) and an empirical correlation proposed by O'Connell give acceptable results. The main conclusion of this work is that it is possible to correlate the PMV by using a simple model, although no available model is recommended for quantitative predictions.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9