Facet-Dependent Catalytic Performance of Au Nanocrystals for Electrochemical Nitrogen Reduction

Weiqing Zhang, Yongli Shen, Fangjie Pang, Darren Quek, Wenxin Niu*, Wenjun Wang, Peng Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)

Abstract

Nanostructured metal catalysts have attracted great interest due to their extraordinary performance for electrocatalysis including electrochemical nitrogen reduction (ENRR). However, their working mechanisms for ENRR are still not fully understood. Herein, seven monofaceted polyhedral Au nanocrystals were synthesized and systemically compared to elucidate the relation between Au crystal facets and NRR performance. It is found that polyhedra with high-index facets catalytically outperform those with low-index facets. Specifically, Au nanostars enclosed with (321) facets show a high NH3 production rate of 2.6 μg h-1 cm-2 (20 μg h-1 mg-2) and faradaic efficiency of 10.2% at -0.2 V, which are 3.1- and 5.1-folds larger than those of nanocubes enclosed with (100) facets. As revealed by theoretical investigation, a larger energy barrier for reduction of H+ to H∗ (ΔGH*) hinders occurrence of HER on the Au(321) surface, thus ensuring better NRR selectivity. Meanwhile, a lower energy barrier for formation of N2H2∗ on the catalyst surface and a larger energy barrier for decomposing the formed N2H2∗ back into N2 and 2H∗ jointly favor a higher NH3 production rate. This study provides mechanistic insights into ENRR and rational design of metal nanocrystals for electrocatalysis.

Original languageEnglish
Pages (from-to)41613-41619
Number of pages7
JournalACS Applied Materials and Interfaces
Volume12
Issue number37
DOIs
Publication statusPublished - Sept 16 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
Copyright © 2020 American Chemical Society.

ASJC Scopus Subject Areas

  • General Materials Science

Keywords

  • Au nanocrystals
  • electrochemical nitrogen reduction reaction
  • facet effect
  • high-index facets
  • low-index facets

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