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Area of Science:

  • Materials Science
  • Nanotechnology
  • Catalysis

Background:

  • Developing efficient nanozymes with enhanced catalytic activities is crucial for environmental monitoring.
  • Single-atom catalysts often face limitations in mimicking complex enzymatic functions.
  • Nitrogen-doped carbon scaffolds provide a robust platform for stabilizing dual-atom catalysts.

Purpose of the Study:

  • To engineer a novel Fe-Cu dual-atom nanozyme (FeCu-N-C) with synergistic multienzymatic activities.
  • To elucidate the mechanism behind the enhanced catalytic synergy using computational methods.
  • To develop a sensitive and accurate sensor array for pesticide detection.

Main Methods:

  • Formamide self-condensation synthesis of Fe-Cu dual-atom nanozyme.
  • Characterization of catalytic activities (peroxidase, oxidase, laccase-like).
  • Density Functional Theory (DFT) calculations for mechanistic insights.
  • Development of a colorimetric sensor array integrated with an Artificial Neural Network (ANN).

Main Results:

  • The FeCu-N-C nanozyme exhibited significantly enhanced triple-mimetic enzyme activities compared to single-atom controls.
  • DFT calculations revealed that adjacent Cu sites optimize the Fe d-band center, enhancing substrate adsorption.
  • The sensor array successfully discriminated five distinct pesticides with 100% accuracy when coupled with an ANN.
  • Compound-specific interactions between pesticides and the nanozyme were identified.

Conclusions:

  • The Fe-Cu dual-atom nanozyme presents a pioneering platform for advanced multienzyme mimics.
  • The rational design strategy effectively enhances catalytic synergy for improved performance.
  • This technology demonstrates high potential for precise and reliable environmental monitoring of pesticides.