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The hydrophobic-subtraction model of reversed-phase column selectivity
Authors:Snyder L R  Dolan J W  Carr P W
Institution:LC Resources, 26 Silverwood Ct., Orinda, CA 94563, USA. snyder0036@comcast.net
Abstract:A recently developed treatment of reversed-phase column selectivity (the hydrophobic-subtraction model) is reviewed and extended, including its characterization of the selectivity of different column types (e.g., C1-C30, cyano, phenyl, etc.). The application of this model to retention data for various solutes and columns has provided new insights into the nature of different solute-column interactions and their relative importance in affecting sample retention and separation. Reversed-phase columns can be characterized by five selectivity parameters (H, S*, A, B and C), values of which are summarized here for more than 300 different columns. The selection of columns of either equivalent or different selectivity is readily achievable on the basis of their values of H, S*, etc. The development of the hydrophobic-subtraction model, its use in characterizing the selectivity of different reversed-phase liquid chromatography (RP-LC) columns, and its application to various practical problems as described here began in 1998. The original inspiration for this project owes much to Jack Kirkland, who also contributed actively to the initial studies that laid the foundation of this model; he has since provided other important support to this project. Jack and one of the authors (LRS) have enjoyed a strong professional relationship and personal friendship for the past 35 years, and it is the privilege of the authors to dedicate this paper and the work that it represents to Jack. His contributions to HPLC column technology have extended from the mid-1960s into the present century, and it is impossible to conceive of present day HPLC practice without Jack's contributions over the years. In this and other ways, his position as a pioneer and key implementer of HPLC is widely recognized. We wish Jack well in the years to come.
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