异质结
催化作用
纳米材料
生物传感器
材料科学
纳米技术
分子
合理设计
接口(物质)
机制(生物学)
计算机科学
组合化学
化学
光电子学
有机化学
物理
量子力学
吉布斯等温线
作者
Yang Dang,Guangtu Wang,Gehong Su,Zhiwei Lu,Sheng Wang,Tao Liu,Xiang Pu,Xianxiang Wang,Wu Chun,Chang Song,Qingbiao Zhao,Hanbing Rao,Mengmeng Sun
出处
期刊:ACS Nano
[American Chemical Society]
日期:2022-03-03
卷期号:16 (3): 4536-4550
被引量:83
标识
DOI:10.1021/acsnano.1c11012
摘要
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.
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