eg occupancy as an effective descriptor for the catalytic activity of perovskite oxide-based peroxidase mimics

Xiaoyu Wang, Xuejiao J. Gao, Li Qin, Changda Wang, Li Song, Yong-Ning Zhou, Guoyin Zhu, Wen Cao, Shichao Lin, Liqi Zhou, Kang Wang, Huigang Zhang, Zhong Jin, Peng Wang, Xingfa Gao and Hui Wei ()
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Xiaoyu Wang: Nanjing University
Xuejiao J. Gao: Jiangxi Normal University
Li Qin: Nanjing University
Changda Wang: University of Science and Technology of China
Li Song: University of Science and Technology of China
Yong-Ning Zhou: Fudan University
Guoyin Zhu: Nanjing University
Wen Cao: Nanjing University
Shichao Lin: Nanjing University
Liqi Zhou: Nanjing University
Kang Wang: Nanjing University
Huigang Zhang: Nanjing University
Zhong Jin: Nanjing University
Peng Wang: Nanjing University
Xingfa Gao: Jiangxi Normal University
Hui Wei: Nanjing University

Nature Communications, 2019, vol. 10, issue 1, 1-8

Abstract: Abstract A peroxidase catalyzes the oxidation of a substrate with a peroxide. The search for peroxidase-like and other enzyme-like nanomaterials (called nanozymes) mainly relies on trial-and-error strategies, due to the lack of predictive descriptors. To fill this gap, here we investigate the occupancy of eg orbitals as a possible descriptor for the peroxidase-like activity of transition metal oxide (including perovskite oxide) nanozymes. Both experimental measurements and density functional theory calculations reveal a volcano relationship between the eg occupancy and nanozymes’ activity, with the highest peroxidase-like activities corresponding to eg occupancies of ~1.2. LaNiO3-δ, optimized based on the eg occupancy, exhibits an activity one to two orders of magnitude higher than that of other representative peroxidase-like nanozymes. This study shows that the eg occupancy is a predictive descriptor to guide the design of peroxidase-like nanozymes; in addition, it provides detailed insight into the catalytic mechanism of peroxidase-like nanozymes.

Date: 2019
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DOI: 10.1038/s41467-019-08657-5

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