Retention and Selectivity Differences due to Molecular Structure of Phenyl–Type Reversed–Phase HPLC Columns

When reversed–phase HPLC analysis using ODS columns does not provide sufficient separation, phenyl–type columns are considered an alternative, with the expectation that π–interactions will alter retention and selectivity. Phenyl–type columns come with various types of functional groups. However, there have been few studies on how differences in their molecular structures affect retention and selectivity. In this study, we compared the retention on HPLC columns containing alkylphenyl, naphthylethyl, pyrenylethyl, and biphenyl groups, due to π–interactions, using hydrophobic mobile phases. The results showed that the greater the value obtained by multiplying the modification density on the stationary phase surface by the number of π–electrons (referred to as “surface π–electron density”), the greater the retention factor of polycyclic aromatic hydrocarbons. On the other hand, the retention factor of compounds, which can be considered as having a certain molecular thickness, such as ferrocene, fullerene, and highly substituted polyhalogenated benzene, was specifically lower in biphenyl group–bound columns. Experiments with pentabromophenyl group–bound columns (PBr column) strongly suggested that this phenomenon is due to the molecular structure of the biphenyl group: unlike naphthyl and pyrenyl groups, the biphenyl group is not planar. The results of this study are expected to contribute to a better understanding of interactions on phenyl–type columns and assist HPLC analysts in selecting appropriate columns.

Authors

Institutions

Publication Details

Journal
Chromatography
Published
2025-05-26
DOI
https://doi.org/10.15583/jpchrom.2025.004
Citations
3
Primary Topic
Analytical Chemistry and Chromatography
Type
article
Field-Weighted Citation Impact
2.27
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Retention and Selectivity Differences due to Molecular Structure of Phenyl–Type Reversed–Phase HPLC Columns

Ashin Taniguchi, Motoshi Shimotsuma, Tsunehisa Hirose
3 citations
Chromatography
Analytical Chemistry and Chromatography
2.27
article

Retention and Selectivity Differences due to Molecular Structure of Phenyl–Type Reversed–Phase HPLC Columns

Ashin Taniguchi, Motoshi Shimotsuma, Tsunehisa Hirose
article en
3 citations

Abstract

When reversed–phase HPLC analysis using ODS columns does not provide sufficient separation, phenyl–type columns are considered an alternative, with the expectation that π–interactions will alter retention and selectivity. Phenyl–type columns come with various types of functional groups. However, there have been few studies on how differences in their molecular structures affect retention and selectivity. In this study, we compared the retention on HPLC columns containing alkylphenyl, naphthylethyl, pyrenylethyl, and biphenyl groups, due to π–interactions, using hydrophobic mobile phases. The results showed that the greater the value obtained by multiplying the modification density on the stationary phase surface by the number of π–electrons (referred to as “surface π–electron density”), the greater the retention factor of polycyclic aromatic hydrocarbons. On the other hand, the retention factor of compounds, which can be considered as having a certain molecular thickness, such as ferrocene, fullerene, and highly substituted polyhalogenated benzene, was specifically lower in biphenyl group–bound columns. Experiments with pentabromophenyl group–bound columns (PBr column) strongly suggested that this phenomenon is due to the molecular structure of the biphenyl group: unlike naphthyl and pyrenyl groups, the biphenyl group is not planar. The results of this study are expected to contribute to a better understanding of interactions on phenyl–type columns and assist HPLC analysts in selecting appropriate columns.

ChromatographyVol. 46(2)
Tesla (United States) (US)
Openalex Percentile: Top 12%
Analytical Chemistry and Chromatography
2.27
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.