Polyethylene-coated silica and zirconia stationary phases in view of quantitative structure-retention relationships

1996 ◽  
Vol 43 (9-10) ◽  
pp. 484-490 ◽  
Author(s):  
A. Nasal ◽  
P. Haber ◽  
R. Kaliszan ◽  
E. Forgács ◽  
T. Cserháti ◽  
...  
Keyword(s):  
Stationary Phases ◽  
Quantitative Structure ◽  
Structure Retention ◽  
Zirconia Stationary Phases ◽  
Quantitative Structure Retention Relationships

A Comparative Quantitative Structure-Retention Relationships Study for Lipophilicity Determination of Compounds with a Phenanthrene Skeleton on Cyano-, Reversed Phase-, and Normal Phase-Thin Layer Chromatography Stationary Phases

2015 ◽  
Vol 98 (2) ◽  
pp. 345-353 ◽  
Author(s):  
Krzesimir Ciura ◽  
Joanna Nowakowska ◽  
Piotr Pikul ◽  
Wiktoria Struck-Lewicka ◽  
Michał J Markuszewski
Keyword(s):  
Stationary Phases ◽  
Principal Component ◽  
Reversed Phase ◽  
Log P ◽  
Quantitative Structure ◽  
Chromatographic Data ◽  
Data Processing Method ◽  
Structure Retention ◽  
And Cluster Analysis ◽  
Quantitative Structure Retention Relationships

Abstract The phenanthrene skeleton is an important moiety in medical chemistry as it is present in steroidal drugs used as anti-inflammatory and anti-asthmatic agents as well as synthetic hormones or potassium sparing diuretics. Chromatographic properties of 14 derivatives containing the phenanthrene skeleton in their structure with known lipophilicityhave been studied. NP, RP, and cyano-bonded silica stationary phaseswith three binary mobile phases (acetonitrile–water, acetone–water, and acetone–petroleum ether) were tested. Obtained chromatographic data were correlated with the lipophilicity expressed as values of log partition coefficient (P). The presented study was undertaken to find the best TLC system and chromatographic data processing method in order to predict log P values. Correlations between chromatographic data and measurements of lipophilicity of compounds were presented as results of established quantitative structure-retention relationships. Principal component analysis and cluster analysis were used to investigate the similarities among chromatographic systems.

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