One-pot construction of monodisperse core-shell silica microsphere with quinine-containing hybrid fibrous shell for racemates separation

Background The traditional chiral stationary phases (CSPs) preparation process involved two main parts: matrix microsphere structure regulation and surface bonding of chiral selector, demonstrating cumbersome preparation steps and long time consumption, while the currently spherical chiral hybrid CSPs could easily solve this problem by using chiral selectors as silicone precursors to participate in hybridization of CSPs directly, the preparation efficiency would be significantly improved, while the development of chiral hybrid core-shell silica CSPs with excellent monodispersity, uniform shell thickness and suitable pore structure was a challenging problem. Results In this work, an oil-water bi-phase method was been precisely designed to fabricate the sub-2 μm core-shell silica microspheres with quinine-containing hybrid fibrous shell (SiO 2 @SiO 2 - t -BuCQN) in one-pot process, the hybrid shell thickness and specific surface area were measured about 171 nm and 120.4 m 2  g −1 . By selecting appropriate oil solvents in the oil phase, the average pore size of these hybrid SiO 2 @SiO 2 - t -BuCQN microspheres could be carefully regulated in 7.5–10.6 nm. Most importantly, when the dosage of quinine silicone precursor did not exceed 30 mol%, the hybrid microspheres would exhibit excellent monodispersity without amorphous nanoparticles. These SiO 2 @SiO 2 - t -BuCQN as CSPs, performed lower chromatographic back pressure (13.8 MPa at 1 mL min −1 ) and efficient separation ability for six amino acid racemates, in which demonstrated typical reversed-phase retention and weak anion exchange chromatography mechanism. Significance The oil-water bi-phase method was simple, efficient and practical, that could significantly shorten the preparation procedures of hybrid core-shell silica CSPs. The advanced monodisperse silica stationary phases could be facilely prepared by this method for high-throughput separation and analysis of complex tasks.