Pentagonal Porphyrin-Based Covalent Organic Framework with Switchable Dual-Enzyme Activity for Adaptive Catechol...

The development of intelligent pollutant-monitoring systems demands high-performance adaptive nanozymes with robust catalytic activity across broad pH and temperature windows. Herein, a pentagonal two-dimensional (2D) porphyrin-based covalent organic framework (NiPor-BATA-COF) with mcm topology and tunable anisotropy was constructed via a Schiff-base reaction, overcoming the symmetry constraints of conventional 2D COFs and furnishing an enzyme-mimicking microenvironment with a hierarchical pore architecture that enhances substrate enrichment and catalytic pathway regulation. As a result, the NiPor-BATA-COF nanozyme exhibits enhanced and switchable "seesaw" dual-enzyme activity, wherein peroxidase (POD)-like activity predominates under acidic and low-temperature conditions, whereas catalase (CAT)-like activity dominates under alkaline and high-temperature conditions. On this basis, an adaptive colorimetric sensor for catechol (CC) detection was developed, achieving a wide linear detection range of 2-300 μM and low detection limits of 0.16 and 0.23 μM across broad pH and temperature windows. Subsequently, a cascade molecular logic strategy featuring a "computing-unlocking" mechanism was constructed based on this adaptive behavior, in which pH and temperature function as primary logic selectors. To translate this strategy into practical applications, a portable platform was developed using a YOLO v5-CC deep learning model, which automatically selects enzyme activity according to the pH of the real sample and enables direct mobile-based quantification of CC, thereby realizing an integrated "sample-in-result-out" workflow. Overall, this work establishes an adaptive design paradigm for pentagonal COF nanozymes with switchable dual-enzyme activity and provides a promising strategy for phenolic compound sensing in point-of-care testing applications.