Single Atomic Cu-N2 Catalytic Sites for Highly Active and Selective Hydroxylation of Benzene to Phenol

Ting Zhang, Xiaowa Nie, Weiwei Yu, Xinwen Guo, Chunshan Song, Rui Si, Yuefeng Liu, Zhongkui Zhao

Research output: Contribution to journalArticle

Abstract

Searching for an efficient single-atom catalyst for benzene hydroxylation to phenol is of critical importance, but it still remains a challenge. Herein, a single-atom catalyst with unique Cu-N2 moieties (Cu1-N2/HCNS) was prepared and confirmed by HAADF-STEM and EXAFS. Turnover number (TON) over Cu1-N2/HCNS (6,935) is 3.4 times of Cu1-N3/HCNS (2,034) under the same reaction conditions, and both exhibit much higher phenol selectivity (close to 99%) and stability compared with Cu nanoparticles and nanoclusters. Experiments and DFT calculations reveal that atomically dispersed Cu species are active sites for benzene hydroxylation to phenol, and the Cu-N2 is more active than Cu-N3 owing to its much lower energy barrier concerning the activation of H2O2 led by its unique coordination state of local atomic structure. We envision that this work opens a new window for modulating coordination environments of single metallic atoms in catalysis design. Catalysis; Materials Synthesis; Nanomaterials

Original languageEnglish (US)
Pages (from-to)97-108
Number of pages12
JournaliScience
Volume22
DOIs
StatePublished - Dec 20 2019

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Hydroxylation
Phenol
Benzene
Atoms
Catalysis
Catalysts
Nanoclusters
Energy barriers
Nanostructured materials
Discrete Fourier transforms
Chemical activation
Nanoparticles
Experiments

All Science Journal Classification (ASJC) codes

  • General

Cite this

Zhang, Ting ; Nie, Xiaowa ; Yu, Weiwei ; Guo, Xinwen ; Song, Chunshan ; Si, Rui ; Liu, Yuefeng ; Zhao, Zhongkui. / Single Atomic Cu-N2 Catalytic Sites for Highly Active and Selective Hydroxylation of Benzene to Phenol. In: iScience. 2019 ; Vol. 22. pp. 97-108.
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Single Atomic Cu-N2 Catalytic Sites for Highly Active and Selective Hydroxylation of Benzene to Phenol. / Zhang, Ting; Nie, Xiaowa; Yu, Weiwei; Guo, Xinwen; Song, Chunshan; Si, Rui; Liu, Yuefeng; Zhao, Zhongkui.

In: iScience, Vol. 22, 20.12.2019, p. 97-108.

Research output: Contribution to journalArticle

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AU - Guo, Xinwen

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AU - Si, Rui

AU - Liu, Yuefeng

AU - Zhao, Zhongkui

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