Process Systems Engineering

Property prediction and consistency analysis by a reference series method

  1. Mordechai Shacham1,*,
  2. Inga Paster1,
  3. Neima Brauner2

Article first published online: 8 MAY 2012

DOI: 10.1002/aic.13813

Issue

AIChE Journal

AIChE Journal

Volume 59, Issue 2, pages 420–428, February 2013

Additional Information

How to Cite

Shacham, M., Paster, I. and Brauner, N. (2013), Property prediction and consistency analysis by a reference series method. AIChE J., 59: 420–428. doi: 10.1002/aic.13813

Author Information

  1. 1

    Dept. of Chemical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

  2. 2

    School of Engineering, Tel-Aviv University, Tel-Aviv, Israel

*Correspondence concerning this article should be addressed to M. Shacham at shacham@bgu.ac.il.

Publication History

  1. Issue published online: 23 JAN 2013
  2. Article first published online: 8 MAY 2012
  3. Accepted manuscript online: 9 APR 2012 09:30AM EST
  4. Manuscript Revised: 27 MAR 2012
  5. Manuscript Received: 5 JAN 2012

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Keywords:

  • property prediction;
  • homologous series;
  • QSPR;
  • reference series;
  • QPPR

Data analysis and prediction of pure component properties of long-chain substances is considered. The emphasis is on homologous series and properties for which insufficient data are available. A two-stage procedure is recommended, whereby a linear (or nonlinear) quantitative structure–property relationship (QSPR) is fitted to a “reference” series, for which an adequate amount of precise data is available. This QSPR should represent correctly both the available data and the asymptotic behavior of the property. In the second stage a quantitative property-property relationship (QPPR) is derived to represent the predicted property values of a “target” series in terms of the property values of the reference series. The procedure is applied for properties which are highly correlated with the number methylene groups in homologous series: inline image and inline image. It is shown that the method is very useful for consistency analysis of property data and enables a reliable prediction of inline image and inline image, and, thus, also of inline image for long-chain substances. © 2012 American Institute of Chemical Engineers AIChE J, 59: 420–428, 2013

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