Property prediction and consistency analysis by a reference series method

Mordechai Shacham, Inga Paster, Neima Brauner

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


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: ΔHf0 and ΔSf0. It is shown that the method is very useful for consistency analysis of property data and enables a reliable prediction of ΔHf0 and ΔSf0, and, thus, also of ΔGf0 for long-chain substances.

Original languageEnglish
Pages (from-to)420-428
Number of pages9
JournalAICHE Journal
Issue number2
StatePublished - 1 Feb 2013


  • Homologous series
  • Property prediction
  • QPPR
  • QSPR
  • Reference series

ASJC Scopus subject areas

  • Biotechnology
  • Environmental Engineering
  • General Chemical Engineering


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