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Peer-reviewedCC BY-NC 4.0Angewandte Chemie (International Ed. in English)

Axial Boron Coordination Reconstructs Stereostructure of Cu Single‐Atom Nanozymes for Efficient Water‐Phase Chemical Sensing

  • Qijun Sun1,2
  • Hongyu Shi2
  • Si Liu2
  • Ziping Li2
  • Yu Yang3
  • Fengwang Li3
  • Wenli Wu1
  • Qiongzheng Hu1
  • Kang Liang2,4
4 affiliations
  1. 1Shandong Analysis and Test Center Qilu University of Technology (Shandong Academy of Sciences) Jinan P.R. China
  2. 2School of Chemical Engineering and Australian Centre for NanoMedicine The University of New South Wales Sydney NSW Australia
  3. 3School of Chemical and Biomolecular Engineering and ARC Centre of Excellence for Green Electrochemical Transformation of Carbon Dioxide The University of Sydney Sydney NSW Australia
  4. 4School of Biomedical Engineering The University of New South Wales Sydney NSW Australia
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Abstract

Developing single‐atom nanozymes with stereoconfigurations is a new paradigm for biomimetic construction of next‐generation natural enzyme alternatives and for achieving high enzyme‐like selectivity and activity. This work developed a high‐temperature pyrolysis tandem chemical vapor deposition technique to produce Cu SAzymes (Cu‐B/N‐C) with axial B coordination as laccase mimics, with Cu‐BaxialN3‐C as the core structure. Axial ligands modulate the d‐band center of Cu SAzymes to identify the equilibrium point between the energy barriers of reactant adsorption and product desorption. Transforming product desorption from an endothermic process to a spontaneously exothermic process promotes the regeneration of nanozymes after catalytic cycles. This results in Cu‐B/N‐C exhibiting higher kinetic parameters and specific activity than natural laccase. Subsequently, a sensor array for high‐throughput detection of phenolic pollutants in seawater was constructed based on the time‐dependent changes in the laccase‐like catalytic kinetics of Cu SAzymes before and after modification. On this basis, a stepwise prediction model was further developed using machine‐learning artificial neural network algorithms to enhance the sensor array's detection accuracy for blind samples. Overall, this work provides new insights into the rational design of artificial enzymes from a stereochemical perspective.

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Cite

BibTeXRIS
BibTeX
@article{sun2026axial,
  title = {{Axial Boron Coordination Reconstructs Stereostructure of Cu Single‐Atom Nanozymes for Efficient Water‐Phase Chemical Sensing}},
  author = {Qijun Sun and Hongyu Shi and Si Liu and Ziping Li and Yu Yang and Fengwang Li and Wenli Wu and Qiongzheng Hu and Kang Liang},
  journal = {Angewandte Chemie (International Ed. in English)},
  year = {2026},
  month = sep,
  doi = {10.1002/anie.8789610},
  url = {https://doi.org/10.1002/anie.8789610},
  note = {CC BY-NC 4.0},
}
RIS
TY  - JOUR
TI  - Axial Boron Coordination Reconstructs Stereostructure of Cu Single‐Atom Nanozymes for Efficient Water‐Phase Chemical Sensing
AU  - Qijun Sun
AU  - Hongyu Shi
AU  - Si Liu
AU  - Ziping Li
AU  - Yu Yang
AU  - Fengwang Li
AU  - Wenli Wu
AU  - Qiongzheng Hu
AU  - Kang Liang
PY  - 2026
DA  - 2026/09/15
JO  - Angewandte Chemie (International Ed. in English)
DO  - 10.1002/anie.8789610
UR  - https://doi.org/10.1002/anie.8789610
AB  - Developing single‐atom nanozymes with stereoconfigurations is a new paradigm for biomimetic construction of next‐generation natural enzyme alternatives and for achieving high enzyme‐like selectivity and activity. This work developed a high‐temperature pyrolysis tandem chemical vapor deposition technique to produce Cu SAzymes (Cu‐B/N‐C) with axial B coordination as laccase mimics, with Cu‐BaxialN3‐C as the core structure. Axial ligands modulate the d‐band center of Cu SAzymes to identify the equilibrium point between the energy barriers of reactant adsorption and product desorption. Transforming product desorption from an endothermic process to a spontaneously exothermic process promotes the regeneration of nanozymes after catalytic cycles. This results in Cu‐B/N‐C exhibiting higher kinetic parameters and specific activity than natural laccase. Subsequently, a sensor array for high‐throughput detection of phenolic pollutants in seawater was constructed based on the time‐dependent changes in the laccase‐like catalytic kinetics of Cu SAzymes before and after modification. On this basis, a stepwise prediction model was further developed using machine‐learning artificial neural network algorithms to enhance the sensor array's detection accuracy for blind samples. Overall, this work provides new insights into the rational design of artificial enzymes from a stereochemical perspective.
SN  - 1433-7851
SN  - 1521-3773
ER  -