An Intelligent Self-Powered Covalent Organic Framework-Based Triboelectric Nanosensor Platform for On-site Picomolar...

Mercury (Hg2+) ions are persistent, highly toxic environmental pollutants that threaten ecosystems and human health through bioaccumulation and long-range transport. Conventional triboelectric nanosensors (TENS) for Hg2+ ion detection, despite being self-powered, suffer from three critical limitations: insufficient sensitivity due to limited ion transport efficiency, susceptibility to environmental interference from solid-solid contact interfaces, and non-intuitive signal outputs requiring specialized interpretation. Here, we reported an intelligent "material-device-algorithm" integrated platform that addresses these challenges. Structurally stable thiophene-based covalent organic framework (COF-S) was grown in-situ on the Cu wire surface to enhance Hg2+ ion recognition specificity and signal transduction efficiency. Leveraging the unique properties of COF-S, a solid-liquid triboelectric nanosensor (SL-TENS) was developed to eliminate solid-solid contact constraints. This architectural transformation enables picomolar limit of detection, a wide linear range spanning eight orders of magnitude (10-11 to 10-3 M), and robust environmental stability with excellent reusability. Finally, a dedicated deep learning model was constructed to decode complex electrical signals into intuitive, real-time quantitative readings, enabling true "sample-in, result-out" on-site analysis. This work establishes a paradigm for self-powered intelligent sensing platforms, demonstrating how the convergence of functional materials, advanced device architectures, and artificial intelligence can overcome fundamental limitations in environmental monitoring.