Integrating Ordered Two-Dimensional Covalent Organic Frameworks to Solid-State Nanofluidic Channels for Ultrafast and Sensitive Detection of Mercury.

Grafting specific recognition moieties onto solid-state nanofluidic channels is a promising way for selective and sensitive sensing of analytes. However, the time-consuming interaction between recognition moieties and analytes is the main hindrance to the application of nanofluidic channel-based sensors in rapid detection. Here, we show the integration of ordered two-dimensional covalent organic frameworks (2D COFs) to solid-state nanofluidic channels to achieve rapid, selective, and sensitive detection of contaminants. As a proof of concept, a thiourea-linked 2D COF (JNU-3) as the recognition unit is covalently bonded on the stable artificial anodic aluminum oxide nanochannels (AAO) to fabricate a JNU-3@AAO-based nanofluidic sensor. The rapid and selective interaction of Hg(II) with the highly ordered channels of JNU-3 allows the JNU-3@AAO-based nanofluidic sensor to realize ultrafast and precise determination of Hg(II) (90 s) with a low limit of detection (3.28 fg mL -1 ), wide linear range (0.01-100 pg mL -1 ), and good precision (relative standard deviation of 3.8% for 11 replicate determination of 10 pg mL -1 ). The developed method was successfully applied to the determination of mercury in a certified reference material A072301c (rice powder), real water, and rice samples with recoveries of 90.4-99.8%. This work reveals the great potential of 2D COFs-modified solid-state nanofluidic channels as a sensor for the rapid and precise detection of contaminants in complicated samples.