Rational Construction of a Ni/CoMoO4 Heterostructure with Strong Ni-O-Co Bonds for Improving Multifunctional Nanozyme Activity

Due to the lack of a general descriptor to predict the activity of nanomaterials, the current exploration of nanozymes mainly depended on trial-and-error strategies, which hindered the effective design of nanozymes. Here, with the help of a large number of Ni-O-Co bonds at the interface of heterostructures, a prediction descriptor was successfully determined to reveal the double enzyme-like activity mechanisms for Ni/CoMoO4. Additionally, DFT calculations revealed that interface engineering could accelerate the catalytic kinetics of the enzyme-like activity. Ni-O-Co bonds were the main active sites for enzyme-like activity. Finally, the colorimetric signal and intelligent biosensor of Ni/CoMoO4 based on deep learning were used to detect organophosphorus and ziram sensitively. Meanwhile, the in situ FTIR results uncovered the detection mechanism: the target molecules could block Ni-O-Co active sites at the heterostructure interface leading to the signal peak decreasing. This study not only provided a well design strategy for the further development of nanozymes or other advanced catalysts, but it also designed a multifunctional intelligent biosensor platform. Furthermore, it also provided preferable ideas regarding the catalytic mechanism and detection mechanism of heterostructure nanozymes.

Automated summary

This study successfully predicted the activity of nanomaterials and revealed the double enzyme-like activity mechanisms for Ni/CoMoO4. It also demonstrated that interface engineering can enhance the catalytic kinetics of enzyme-like activity. Furthermore, a colorimetric signal and intelligent biosensor based on deep learning were used to detect specific substances. The study provides valuable insights for the development of nanozymes and other advanced catalysts, as well as the understanding of their catalytic and detection mechanisms.