(672e) Linear QSPRs for the Prediction of Acentric Factor and Critical Volume of Long-Chain Substances | AIChE

(672e) Linear QSPRs for the Prediction of Acentric Factor and Critical Volume of Long-Chain Substances


Brauner, N. - Presenter, Tel-Aviv University
Shacham, M. - Presenter, Ben Gurion University of the Negev
Paster, I. - Presenter, Ben Gurion University of the Negev

Physical property data are extensively used in chemical process design, environmental impact assessment, hazard and operability analysis, and additional applications. Critical properties and the acentric factor values are needed, for example, as parameters in equations of state that are widely used for phase equilibrium calculations, as they enable calculation of the entropy, enthalpy, fugacity coefficients and partial fugacity coefficients of the vapor and liquid phases. However, measured property values are available only for a small fraction of the chemicals used in the industry, as reactants, products or side products. Long chain substances pose special challenges, as their critical constants cannot be measured because of thermal instability. Nikitin et al. (2001) noted that critical temperatures (Tc) and pressures (Pc) of n-alkanes have been measured only up to hexatriacontane (C36H74) and for 1-alkanols up to 1-docosanol (C22H45OH). The critical constants of the heavier members of the homologous series can only be predicted. Current methods used to predict physical and thermodynamic properties can be classified into group contribution methods (GC, e.g., Marrero and Gani, 2001), asymptotic behavior correlations (ABCs, e.g., Marano and Holder, 1997, Nikitin et al., 2005)) and various quantitative-structure-property relationships (QSPRs, e.g., Brauner et al, 2008). All of these methods use available experimental data for low carbon number (nC) compounds in order to obtain either "group contribution" values or regression model parameter values. The so-obtained group contributions or regression models are used for prediction of properties of long chain members of homologous series by extrapolation. The ABCs are non-linear correlations in terms of nC , which use in addition to the experimental property data also an estimation of the property value at the limit nC -> infinity, y(inf). Kontogeorgis and Tassios, 1997 compared several GC methods and methods that converge to a finite y(inf) value, for predicting TC and PC of heavy alkanes. They concluded that only methods that converge to finite y(inf) values yield reliable predictions for TC and PC of heavy alkanes. Cholakov et al., 2008 have shown that various properties of several homologous series can be represented as linear functions of some molecular descriptors in the regions where experimental data are available. We have recently extended the application of linear QSPRs to prediction of properties of long chain substances in homologous series (Paster et al., 2010). Using this new method, molecular descriptors collinear with a particular property are identified based on available experimental data. From among these, the descriptors whose asymptotic behavior is similar to the property behavior are eventually used for prediction. In that work we have developed QSPRs for Tc and Pc for several homologous series and for melting points (Tm) for n-alkanes. In all cases the QSPRs developed represented the available experimental data satisfactorily and converge to theoretically accepted values for nC -> infinity. It has been also found that the limiting property values for different homologous series are very close in value to each other, as the effect of the particular functional groups (e.g., ?CH3, ?COOH, ?CO) diminishes with increasing nC, where the role of the ?CH2? chain becomes the dominant one. The objective of the present work is to apply the methodology of Paster et al.(2010) to predict the critical volume (VC) and acentric factor for long chain substances. Unlike Tc, Pc and Tm, the critical volume does not converge to a constant value, but goes to infinity for nC -> infinity. As for the acentric factor, there are contradictory opinions regarding its limiting value. We have shown that the acentric factor does not converge to a constant value either. Descriptors which are collinear with these properties in the regions where experimental data are available and go to infinity for infinite nC values have been identified. The prediction of VC and the acentric factor using QSPRs in terms of the selected descriptors was tested with several homologous series. In all cases the QSPR represented the published data satisfactorily and it provided the right trend of change for these properties for long chain molecules. Detailed results and discussions will be provided in the extended abstract and the presentation.


1. Brauner, N.; Cholakov, G. St.; Kahrs, O.; Stateva, R. P.; Shacham, M. Linear QSPRs for Predicting Pure Compound Properties in Homologous Series. AIChE J. 2008, 54(4), 978-990. 2. Cholakov, G.St.; Stateva, R.P.; Shacham, M.; Brauner, N; Estimation of Properties of Homologous Series with Targeted Quantitative Structure ? Property Relationships (TQSPRs). J Chem Eng Data. 2008; 53: 2510?2520. 3. Marano, J.J.; Holder, G.D. General Equations for Correlating the Thermo-physical Properties of n-Paraffins, n-Olefins and other Homologous Series. 2. Asymptotic Behavior Correlations for PVT Properties. Ind. Eng. Chem. Res. 1997A, 36, 1895. 4. Marrero, J.; Gani, R. Group-contribution based estimation of pure component properties. Fluid Phase Equilibria. 2001, 183. 5. Nikitin, E.D.; Pavlov, P.A.; Popov, A.P. Critical temperatures and pressures of some alkanoic acids (C2 to C22) using the pulse-heating method. Fluid Phase Equilibria. 2001;189:151-161. 6. Nikitin, E.D.; Popov, A.P.; Bogatishcheva, N.S. Critical properties of long-chain substances from the hypothesis of functional self-similarity. Fluid Phase Equilibria. 2005;235:1-6. 7. Paster, I.; Shacham, M.; Brauner, N. Adjustable QSPRs For Prediction of Properties of Long-Chain Substances. AIChE J, 2010 (in press)


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