Predicting a Wide Variety of Constant Pure Compound Properties for Long Chain Substances Using a " Reference Series" Method

Inga Paster, Mordechai Shacham, Neima Brauner

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

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) QSPR is fitted to a " reference" series, for which 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.

Original languageEnglish
Title of host publicationComputer Aided Chemical Engineering
PublisherElsevier B.V.
Pages602-606
Number of pages5
DOIs
StatePublished - 1 Jan 2012

Publication series

NameComputer Aided Chemical Engineering
Volume30
ISSN (Print)1570-7946

Keywords

  • Homologous series
  • Property prediction
  • QPPR
  • QSPR

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