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

Yujiao Bai1, Shun Nie2, Luping Chang1

  • 1School of Chemistry and Chemical Engineering, University of Jinan, Jinan 250022, China.

Analytical Chemistry
|June 8, 2026
PubMed
Summary
This summary is machine-generated.

Researchers developed an adaptive nanozyme from a pentagonal covalent organic framework. This material exhibits switchable dual-enzyme activity, enabling sensitive detection of pollutants like catechol across various conditions for point-of-care testing.

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Analytical Chemistry

Background:

  • Intelligent pollutant monitoring requires advanced nanozymes with stable activity under diverse environmental conditions.
  • Conventional 2D covalent organic frameworks (COFs) face symmetry limitations, hindering optimal enzyme-mimicking microenvironments.

Purpose of the Study:

  • To construct a novel pentagonal 2D porphyrin-based COF (NiPor-BATA-COF) with tunable anisotropy and enhanced adaptive nanozyme properties.
  • To develop an adaptive colorimetric sensor for catechol (CC) detection utilizing the nanozyme's switchable dual-enzyme activity.
  • To create a portable platform with a deep learning model for real-time, automated CC quantification.

Main Methods:

  • Synthesis of a pentagonal 2D NiPor-BATA-COF via Schiff-base reaction.
  • Characterization of the COF's hierarchical pore architecture and tunable anisotropy.
  • Evaluation of switchable peroxidase (POD)-like and catalase (CAT)-like activities under varying pH and temperature.
  • Development of a colorimetric sensor for CC detection and a cascade molecular logic system.
  • Integration with a YOLO v5-CC deep learning model for a portable, automated sensing platform.

Main Results:

  • The NiPor-BATA-COF nanozyme demonstrated switchable "seesaw" dual-enzyme activity, favoring POD under acidic/cold conditions and CAT under alkaline/hot conditions.
  • An adaptive colorimetric sensor for CC achieved a wide linear range (2-300 μM) and low detection limits (0.16-0.23 μM) across broad pH/temperature windows.
  • A portable platform with a YOLO v5-CC model enabled automated CC quantification from real samples, achieving an integrated "sample-in-result-out" workflow.

Conclusions:

  • The study presents an adaptive design paradigm for pentagonal COF nanozymes with switchable dual-enzyme characteristics.
  • This work offers a promising strategy for sensitive and adaptive phenolic compound sensing in point-of-care testing applications.
  • The developed platform demonstrates the potential for intelligent environmental monitoring and diagnostics.