A boronic acid-functionalized covalent organic framework core-shell composite for online solid-phase extraction and...

A novel core-shell structured boronic acid-functionalized covalent organic framework composite (SiO₂@COF-PBA) was designed for the selective extraction of monoamine neurotransmitters (MNTs). The material was synthesized via a Schiff base reaction between 2,5-divinylbenzene-1,4-dicarbaldehyde (DD) and 2,4,6-tris(4-aminophenyl)-1,3,5-triazine (TAT) on the SiO₂-NH₂ surface, followed by covalent grafting of 4-mercaptophenylboronic acid (4-MPBA) through thiol-ene click chemistry. The resulting SiO₂@COF-PBA exhibited uniform spherical morphology, high specific surface area, and excellent chemical stability. Owing to the specific boronate affinity toward cis-diol moieties, the material demonstrated high adsorption capacity and favorable selectivity for MNTs compared with commercial adsorbents. The adsorption isotherms and kinetics of the four MNTs were systematically investigated. An online solid-phase extraction method coupled with high-performance liquid chromatography-fluorescence detection (online SPE-HPLC-FLD) was established using the SiO₂@COF-PBA packed column. The parameters influencing the online extraction efficiency, including the pH of the sample solution, the extraction and desorption flow rates, and the desorption volume, were investigated. Under optimized conditions, the enrichment factors for the four MNTs reached 37-225. The developed method exhibited wide linear ranges (0.10-100.0 ng mL^-1, R² ≥ 0.9991), low limits of detection (0.035-0.054 ng mL^-1), and good precision (RSDs of 1.7-4.8%, n = 5). When applied to human urine and mouse plasma samples, trace MNTs were detected with good accuracy, with spiked recoveries of 73.68-102.1% and 74.26-105.1%, respectively, and RSDs of 0.8-8.7% and 2.2-8.0%. This work provides a promising strategy for designing highly selective functionalized COF materials and an efficient online approach for the sensitive detection of trace MNTs in complex biological matrices.