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Application of the COSMO−SAC−BP Solvation Model to Predictions of Normal Boiling Temperatures for Environmentally Significant Substances

Authors :
Wang, Shu
Lin, Shiang-Tai
Chang, Jaeeon
A. Goddard III, William
I. Sandler, Stanley
Source :
Industrial & Engineering Chemistry Research; August 2006, Vol. 45 Issue: 16 p5426-5434, 9p
Publication Year :
2006

Abstract

We recently reported the COSMO−SAC−BP model for predicting vapor pressure and its temperature derivative, the enthalpy of vaporization. This COSMO−SAC−BP model, which contains no compound specific parameters, is based on determining three major solvation components:  (i) an electrostatic contribution, calculated using the quantum mechanical COSMO (conductor-like-screening-model) method with a statistical mechanical correction for solution nonideality (deviation from a perfect conductor); (ii) a dispersion contribution, obtained from a mean field treatment; and (iii) a cavity formation contribution determined from thermodynamic perturbation theory. This COSMO−SAC−BP model was previously validated to successfully correlate normal boiling point temperatures and enthalpies of vaporization for 369 molecules. In this present study, we have extended the COSMO−SAC−BP model to describe large and more-complex molecules, including pollutants, herbicides, insecticides, and drugs,. The average absolute deviation in the predicted boiling points of these complex molecules, which spans the range of 266−708 K is 17.8 K, or 3.7%. This is similar to the value of 3.2% that was obtained for the 369 molecules in the earlier study, indicating that this method can be applied well outside the systems used to train the model. More importantly, we report here the predicted the normal boiling temperatures for 10 pesticides for which no experimental data are available. This illustrates the advantage to the COSMO−SAC−BP model:  predicting several properties for a wide variety of molecules simultaneously in a unified framework with few parameters (unlike group contribution methods (or quantitative structure−property relationships).

Details

Language :
English
ISSN :
08885885 and 15205045
Volume :
45
Issue :
16
Database :
Supplemental Index
Journal :
Industrial & Engineering Chemistry Research
Publication Type :
Periodical
Accession number :
ejs9550324
Full Text :
https://doi.org/10.1021/ie050352k