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

摘要

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.