Zwitterionic covalent organic nanosheets for selective analysis of domoic acid in marine environment

Domoic acid (DA) is a neurotoxic compound causing amnesic shellfish poisoning, secreted by red algae and diatoms. As a glutamate analogue, DA accumulates in filter-feeding marine organisms, posing significant health risks to humans upon consumption. Detecting DA in marine environments remains challenging due to its low concentration and interference from complex matrices. Effective detection and removal require materials with high efficiency and selectivity, which traditional inorganic ionic materials lack due to their limited adsorption capacity and selectivity. Ionic covalent organic frameworks (iCOFs) expected to become highly efficient DA adsorbents due to tunable ionic sites.

Thus, a zwitterionic covalent organic nanosheet (TGDB-iCONs) was synthesized to selectively capture DA. TGDB-iCONs was prepared by one-step Schiff-base reaction of the charged monomer triaminoguanidine hydrochloride. It uniformly distributed positively charged guanidinium and negatively charged chloride ions on the surface, forming zwitterionic binding sites. The self-peeling of TGDB-iCONs facilitated the exposure of active sites and improved the adsorption efficiency. Several binding forces were generated between TGDB-iCONs and DA, including complementary electrostatic hydrophilic interactions, which were verified by density functional theory (DFT) calculation. TGDB-iCONs exhibited ultra-fast adsorption kinetics (7 min) and relatively high adsorption capacity (66.48 mg/g) for DA. Furthermore, TGDB-iCONs exhibit strong salt resistance, which is attributed to the charge "shielding" effect of the zwitterionic ions present in TGDB-iCONs. TGDB-iCONs could highly selectively enrich DA and detect trace DA from marine environment including seawater, algae and marine organisms and the limit of detection as low as 0.3 ng/kg.

This comprehensive study not only sheds light on the vast potential of ionic covalent organic frameworks nanosheets (iCONs) in supporting early warning, control, and traceability of DA, but also lays a solid foundation for future research endeavors aimed at designing and harnessing the unique properties of iCONs.