NDLI: Predictions of Reversed-Phase Gradient Elution LC Separations Supported by QSRR

Content Provider	Springer Nature Link
Author	Bączek, Tomasz Bodzioch, Karolina Michalska, Elżbieta Kaliszan, Roman
Copyright Year	2008
Abstract	Previous studies demonstrated that quantitative structure-retention relationships (QSRR) combined with the linear solvent strength (LSS) model allow for prediction of gradient reversed-phase liquid chromatography retention time for any analyte of a known molecular structure under defined LC conditions. A QSRR model derived at the selected gradient time and at the same gradient time was tested. The aim the present study was to evaluate the accuracy of QSRR predictions used during the predictions of LC gradient retention times with variable gradient times. For this purpose, predictions of retention times at two gradient times were used to find the optimal, different gradient times. In the first step, experimental retention data for the model set of analytes were used to derive appropriate QSRR models at two gradient times. These QSRR models were further used to predict gradient retention times for another set of testing analytes at the two selected above gradient times. Then, applying linear solvent-strength (LSS) theory, the predicted retention times for test analytes were used to find other optimal gradient times for those analytes. Satisfactory predictions of gradient retention times for test analytes were obtained at gradient times different from those applied for model analytes.
Starting Page	161
Ending Page	166
Page Count	6
File Format	PDF
ISSN	00095893
Journal	Chromatographia
Volume Number	68
Issue Number	3-4
e-ISSN	16121112
Language	English
Publisher	Vieweg Verlag
Publisher Date	2008-06-10
Publisher Place	Wiesbaden
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Column liquid chromatography Quantitative structure–retention relationships Linear solvent strength model Prediction of retention Gradient elution Measurement Science, Instrumentation Plant Sciences Biochemistry Pharmacy Organic Chemistry Analytical Chemistry
Content Type	Text
Resource Type	Article
Subject	Organic Chemistry Analytical Chemistry Biochemistry Clinical Biochemistry

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