JOURNAL ARTICLE

Atomically Dispersed CoN3C1‐TeN1C3 Diatomic Sites Anchored in N‐Doped Carbon as Efficient Bifunctional Catalyst for Synergistic Electrocatalytic Hydrogen Evolution and Oxygen Reduction

Abstract

Abstract A encapsulation–adsorption–pyrolysis strategy for the construction of atomically dispersed Co‐Te diatomic sites (DASs) that are anchored in N‐doped carbon is reported as an efficient bifunctional catalyst for electrocatalytic hydrogen evolution reaction (HER) and oxygen reduction reaction (ORR). The as‐constructed catalyst shows the stable CoN 3 C 1 ‐TeN 1 C 3 coordination structure before and after HER and ORR. The *OOH/*H intermediate species are captured by in situ Raman and in situ attenuated total reflectance‐surface enhanced infrared absorption spectroscopy, indicating that the reactant O 2 /H 2 O molecule has a strong interaction with the Co site, revealing that Co δ+ is an effective active site. Theoretical calculations show that the Co δ+ has adsorption‐activation function and the neighboring Te δ+ acts as an electron donor adjusting the electronic structure of Co δ+ , promoting the dissociation of H 2 O molecules and the adsorption of H and oxygen‐containing intermediates in HER and ORR. In the meanwhile, the nearest C atom around Co also profoundly affects the adsorption of H atoms. This results in the weakening of the OH adsorption and enhancement of H adsorption, as well as the more stable water molecule dissociation transition state, thus significantly boosting ORR and HER performance.

Keywords:
Bifunctional Catalysis Diatomic molecule Materials science Doping Electrocatalyst Carbon fibers Physical chemistry Chemical engineering Nanotechnology Inorganic chemistry Chemistry Electrochemistry Electrode Molecule Organic chemistry Optoelectronics Composite number

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55
Cited By
3.10
FWCI (Field Weighted Citation Impact)
35
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0.90
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Citation History

Topics

Electrocatalysts for Energy Conversion
Physical Sciences →  Energy →  Renewable Energy, Sustainability and the Environment
Fuel Cells and Related Materials
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Machine Learning in Materials Science
Physical Sciences →  Materials Science →  Materials Chemistry

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