Study of the influence of electronic effects on the retention of substitutedN-benzylideneanilines in normal-phase liquid chromatography

Ounnar, S.; Righezza, Michel; Delatousche, B.; Chrétien, Jacques R.; Toullec, Jean

doi:10.1007/bf02466576

Cited by 3 publications

(1 citation statement)

References 48 publications

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“…The second allows a simultaneous projection of individuals and variables on the same map thus leading to a proximity analysis. In chromatography, CFA also offers the possibility of carefully exploiting the relations of proximity between the projections of the compounds and the chromatographic systems [25,32,33].…”

Section: Correspondence Factor Analysismentioning

confidence: 99%

Characterization of stationary phases based on monosubstituted benzene retention indices using correspondence factor analysis and linear solvation energy relationships in RPLC

2018

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In reversed-phase liquid chromatography (RPLC), the comparison of experimental results obtained from different columns is a complex problem. A correspondence factor analysis (CFA) and a linear solvation energy relationship (LSER) were applied on retention data to characterize second-order intermolecular interactions responsible for retention on a set of RPLC columns. Seven octadecyl-C 18 columns with different packing materials are obtained from different manufacturers and one octyl-C 8 column. The retention data were determined under isocratic conditions using a methanol-water (65:35, v/v) mobile phase. The chromatographic retention indices based on alkan-2-ones and alkyl aryl ketones retention index scales are calculated using a multiparametric least-squares regressions iterative method. The CFA and LSER results permitted to highlight that the retention indices were appropriate for studying the second-order retention mechanisms on the eight chromatographic systems investigated and exhibited the best reproducibility. Although many earlier studies have reported the use of chemometric methods to characterize chemical factors affecting retention in RPLC using retention factors as retention parameters, this is the first study based on retention indices.

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Section: Correspondence Factor Analysismentioning

confidence: 99%

Characterization of stationary phases based on monosubstituted benzene retention indices using correspondence factor analysis and linear solvation energy relationships in RPLC

2018

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Quantitative structure–(chromatographic) retention relationships

Héberger

2007

Journal of Chromatography A

366

188

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Since the pioneering works of Kaliszan (R. Kaliszan, Quantitative Structure-Chromatographic Retention Relationships, Wiley, New York, 1987; and R. Kaliszan, Structure and Retention in Chromatography. A Chemometric Approach, Harwood Academic, Amsterdam, 1997) no comprehensive summary is available in the field. Present review covers the period of 1996-August 2006. The sources are grouped according to the special properties of kinds of chromatography: Quantitative structure-retention relationship in gas chromatography, in planar chromatography, in column liquid chromatography, in micellar liquid chromatography, affinity chromatography and quantitative structure enantioselective retention relationships. General tendencies, misleading practice and conclusions, validation of the models, suggestions for future works are summarized for each sub-field. Some straightforward applications are emphasized but standard ones. The sources and the model compounds, descriptors, predicted retention data, modeling methods and indicators of their performance, validation of models, and stationary phases are collected in the tables. Some important conclusions are: Not all physicochemical descriptors correlate with the retention data strongly; the heat of formation is not related to the chromatographic retention. It is not appropriate to give the errors of Kovats indices in percentages. The apparently low values (1-3%) can disorient the reviewers and readers. Contemporary mean interlaboratory reproducibility of Kovats indices are about 5-10 i.u. for standard non polar phases and 10-25 i.u. for standard polar phases. The predictive performance of QSRR models deteriorates as the polarity of GC stationary phase increases. The correlation coefficient alone is not a particularly good indicator for the model performance. Residuals are more useful than plots of measured and calculated values. There is no need to give the retention data in a form of an equation if the numbers of compounds are small. The domain of model applicability of models should be given in all cases.

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Comparison of chromatographic properties of cyanopropyl-, diol- and aminopropyl- polar-bonded stationary phases by the retention of model compounds in normal-phase liquid chromatography systems

Waksmundzka‐Hajnos

Petruczynik

Hawrył

2001

Journal of Chromatography A

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Study of the influence of electronic effects on the retention of substitutedN-benzylideneanilines in normal-phase liquid chromatography

Cited by 3 publications

References 48 publications

Characterization of stationary phases based on monosubstituted benzene retention indices using correspondence factor analysis and linear solvation energy relationships in RPLC

Characterization of stationary phases based on monosubstituted benzene retention indices using correspondence factor analysis and linear solvation energy relationships in RPLC

Quantitative structure–(chromatographic) retention relationships

Comparison of chromatographic properties of cyanopropyl-, diol- and aminopropyl- polar-bonded stationary phases by the retention of model compounds in normal-phase liquid chromatography systems

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