Issue 8, 2023

Hybridization of helical poly(phenylacetylene)s bearing l-proline tripeptide pendants into porous silica microspheres as a solvent-tolerable chiral stationary phase for liquid chromatography

Abstract

A novel one-handed helical copoly(phenylacetylene) (CPA) bearing L-proline tripeptide pendants and a few triethoxysilyl residues was synthesized and hybridized into SiO2 porous microspheres (PMSs) during microsphere growth through the hydrolytic polycondensation of ethoxysilyl groups. Nuclear magnetic resonance and Fourier transform infrared spectroscopy results verified the successful preparation of CPA and its hybrid product using SiO2 PMSs. The chiral recognition ability of the resulting CPA with a hybridized-type chiral stationary phase (HCSP) for high-performance liquid chromatography (HPLC) was investigated, revealing its high recognition ability for selected racemates. Moreover, the HCSP showed good solvent tolerability, thus broadening the selection of suitable eluents. The separation effect of the HCSP for the racemate N,N-diphenylcyclohexane-1,2-dicarboxamide (7) improved significantly after introducing CHCl3 in the eluent, resulting in separation factors equivalent or superior to common commercially available polysaccharide-based chiral stationary phases. The proposed preparation strategy provides a new and valuable method for obtaining poly(phenylacetylene)-based HCSPs suitable for a wide range of applications and eluent conditions.

Graphical abstract: Hybridization of helical poly(phenylacetylene)s bearing l-proline tripeptide pendants into porous silica microspheres as a solvent-tolerable chiral stationary phase for liquid chromatography

Supplementary files

Article information

Article type
Paper
Submitted
12 Jan 2023
Accepted
12 Mar 2023
First published
17 Mar 2023

Analyst, 2023,148, 1877-1886

Hybridization of helical poly(phenylacetylene)s bearing L-proline tripeptide pendants into porous silica microspheres as a solvent-tolerable chiral stationary phase for liquid chromatography

J. Huang, Z. Zhou, C. Zhang, C. Wang, Y. Zhou, L. Liu, J. Li, T. Satoh and Y. Okamoto, Analyst, 2023, 148, 1877 DOI: 10.1039/D3AN00061C

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