Xin Liu^1*, Yan Jiao¹, Yao Zheng¹, Mietek Jaroniec², Shi-Zhang Qiao¹

1 School of Chemical Engineering and Advanced Materials, The University of Adelaide, Adelaide, SA 5005, Australia

2 Department of Chemistry and Biochemistry & Advanced Materials and Liquid Crystal Institute, Kent State University, Kent, OH 44242, USA

* Corresponding authors emails: liuxin_hit@163.com

DOI10.24435/materialscloud:8t-6e [version v1]

Publication date: Sep 26, 2022

How to cite this record

Xin Liu, Yan Jiao, Yao Zheng, Mietek Jaroniec, Shi-Zhang Qiao, Mechanism of C-N bonds formation in electrocatalytic urea production revealed by ab initio molecular dynamics simulation, Materials Cloud Archive 2022.120 (2022), doi: 10.24435/materialscloud:8t-6e.

Description

Electrosynthesis of urea from CO₂ and NO_X provides an exceptional opportunity for human society, given the increasingly available renewable energy. To raise the overall electrosynthesis efficiency, the most critical reaction step for such electrosynthesis, C-N coupling, needs to be significantly improved. The C-N coupling can only happen at a narrow potential window, generally in the low overpotential region, and a fundamental understanding of the C-N coupling is needed for further development of this strategy. In this regard, we performed ab initio Molecular Dynamics (AIMD) simulations to reveal the origin of C-N coupling under a small electrode potential window with both the dynamic nature of water as a solvent, and the electrode potentials considered. We explored the key reaction networks for urea formation on Cu(100) surface in neutral electrolytes. Our work shows excellent agreement with experimentally observed selectivity under different potentials on the Cu electrode. We discovered that the *NH and *CO are the key precursors for C-N bonds formation at low overpotential, while at high overpotential the C-N coupling occurs between adsorbed *NH and solvated CO. These insights provide vital information for future spectroscopic measurements and enable us to design new electrochemical systems for more value-added chemicals.

Materials Cloud sections using this data

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File name	Size	Description
traj.zip MD5md5:cec12038e378f0965f90bdd0383f7a8e	250.9 MiB	AIMD trajectory

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Keywords

Electrocatalysis AIMD NOx reduction