Machine learning-assisted fluorescence/smartphone dual-mode platform for lead ion detection using the novel polyimide covalent organic framework.

Unintended leakage of toxic and lead ion (Pb) ions poses high harmful to human health and environment, hence its monitoring and detection is of utmost significance. Here, we developed a covalent organic framework (COFs) that was first synthesized by condensation of monomers 4,4',4''-(1,3,5-triazine-2,4,6-triyl) triphenylamine (TTA) and perylene-3,4,9,10-tetracarboxylic dianhydride (PTCA), and then fluorescence/smartphone dual-mode point-of-care testing (POCT) platform based on COFs combined with machine learning was successfully constructed to detect Pb. The morphology, chemical structure, fluorescent properties, sensing competition and selectivity behaviors of COFs-Pb were systematically analyzed.