Journal of Chromatography A, 878 (2000) 115–124 www.elsevier.com / locate / chroma Revised linear solvation energy relationship coefficients for the 77-phase McReynolds data set based on an updated set of solute descriptors a b, b * M.H. Abraham , D.S. Ballantine , B.K. Callihan a Department of Chemistry, University College London, 20 Gordon Street, London WC1H OAJ, UK b Department of Chemistry and Biochemistry, Northern Illinois University, DeKalb, IL 60115, USA Received 1 September 1999; received in revised form 27 January 2000; accepted 27 January 2000 Abstract Linear solvation energy relationship (LSER) coefficients for the 77-phase McReynolds data set have been recalculated using updated solute descriptors in the revised solvation equation: H H H 16 log SP 5 c 1 rR 1 s p 1 a Oa 1 b O b 1 l log L 1 1 2 1 2 1 2 1 2 1 These revised LSER coefficients are presented and classified by cluster analysis into groupings of stationary phases which have comparable solubility properties. It was found that the groupings were similar to those proposed by Abraham using the original solvation equation and that any dissimilarities were readily explainable by the grouping methods that were applied. Comparison of the original coefficients with the revised set also shows that several stationary phases which had a statistically insignificant b value with the original equation now have significant b values when utilizing the revised solvation equation. 1 1 Published by Elsevier Science B.V. Keywords: Linear solvation energy relationships; Solute descriptors 1. Introduction retention data can be directly correlated with intrinsic thermodynamic properties, namely the thermody- Solubility phenomena play a major role in a namic partition coefficient, and because these prop- variety of chemical and biological processes; hence, erties are directly related to the intermolecular a thorough understanding of the factors that affect interactions between solute and solvent, extensive such phenomena is crucial for the utilization and / or analysis of several key sets of gas chromatographic optimization of solubility properties in systems under retention data [2,3] has been performed in order to investigation [1]. Ideally, a quantitative measure of develop relationships which predict solubility be- solubility processes provides better insight into the havior [3–5]. fundamental interactions which take place between Of the many sets of gas chromatographic retention solute and solvent. Because gas chromatographic data currently available, the McReynolds data set of 77 stationary phases has been utilized to develop *Corresponding author. several predictive relationships [4,5]. Among the 0021-9673 / 00 / $ – see front matter Published by Elsevier Science B.V. PII: S0021-9673(00)00143-6