Boosting Electroreduction of Nitrate and CO<sub>2</sub> to Urea on a Tandem Fe<sub>1</sub>/MoS<sub>2</sub> Catalyst

Urea electrosynthesis by coelectrolysis of NO<sub>3</sub><sup>-</sup> and CO<sub>2</sub> (UENC) holds enormous promise for sustainable urea production, while the efficient UENC process relies on the rational design of high-performance catalysts to facilitate the electrocatalytic C-N coupling efficiency and the hydrogenation reaction process. Herein, Fe single atoms supported on MoS<sub>2</sub> (Fe<sub>1</sub>/MoS<sub>2</sub>) are developed as a highly effective and robust catalyst for UENC. Theoretical calculations and operando spectroscopic measurements reveal a tandem catalysis mechanism of the Fe<sub>1</sub>-S<sub>3</sub> motif and MoS<sub>2</sub>-edge to jointly promote the UENC process, where the Fe<sub>1</sub>-S<sub>3</sub> motif drives the early C-N coupling and subsequent *CO<sub>2</sub>NO<sub>2</sub>-to-*CO<sub>2</sub>NH<sub>2</sub> step. The generated *CO<sub>2</sub>NH<sub>2</sub> is then migrated from the Fe<sub>1</sub>-S<sub>3</sub> motif to the nearby MoS<sub>2</sub>-edge, which facilitates the *CO<sub>2</sub>NH<sub>2</sub> → *COOHNH<sub>2</sub> step for urea formation. Noticeably, Fe<sub>1</sub>/MoS<sub>2</sub> assembled in a flow cell reaches a maximum urea Faraday efficiency of 54.98% with a corresponding urea yield rate of 18.98 mmol h<sup>-1</sup> g<sup>-1</sup>, performing at the top level among all of the UENC catalysts reported to date.

Authors

Institutions

Publication Details

Journal
ACS Nano
Published
2024-09-23
DOI
https://doi.org/10.1021/acsnano.4c10187
Citations
20
Primary Topic
Ammonia Synthesis and Nitrogen Reduction
Type
article
Field-Weighted Citation Impact
2.14

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Boosting Electroreduction of Nitrate and CO2 to Urea on a Tandem Fe1/MoS2 Catalyst

Zeyi Sun, Kai Chen, Ke Chu, Shiyao Shang et al.
20 citations
ACS Nano
Ammonia Synthesis and Nitrogen Reduction
2.14
article

Boosting Electroreduction of Nitrate and CO2 to Urea on a Tandem Fe1/MoS2 Catalyst

Zeyi Sun, Kai Chen, Ke Chu, Shiyao Shang, Wenyu Du, Xing Yang
article en
20 citations

Abstract

Urea electrosynthesis by coelectrolysis of NO<sub>3</sub><sup>-</sup> and CO<sub>2</sub> (UENC) holds enormous promise for sustainable urea production, while the efficient UENC process relies on the rational design of high-performance catalysts to facilitate the electrocatalytic C-N coupling efficiency and the hydrogenation reaction process. Herein, Fe single atoms supported on MoS<sub>2</sub> (Fe<sub>1</sub>/MoS<sub>2</sub>) are developed as a highly effective and robust catalyst for UENC. Theoretical calculations and operando spectroscopic measurements reveal a tandem catalysis mechanism of the Fe<sub>1</sub>-S<sub>3</sub> motif and MoS<sub>2</sub>-edge to jointly promote the UENC process, where the Fe<sub>1</sub>-S<sub>3</sub> motif drives the early C-N coupling and subsequent *CO<sub>2</sub>NO<sub>2</sub>-to-*CO<sub>2</sub>NH<sub>2</sub> step. The generated *CO<sub>2</sub>NH<sub>2</sub> is then migrated from the Fe<sub>1</sub>-S<sub>3</sub> motif to the nearby MoS<sub>2</sub>-edge, which facilitates the *CO<sub>2</sub>NH<sub>2</sub> → *COOHNH<sub>2</sub> step for urea formation. Noticeably, Fe<sub>1</sub>/MoS<sub>2</sub> assembled in a flow cell reaches a maximum urea Faraday efficiency of 54.98% with a corresponding urea yield rate of 18.98 mmol h<sup>-1</sup> g<sup>-1</sup>, performing at the top level among all of the UENC catalysts reported to date.

ACS NanoVol. 18(40)
Lanzhou Jiaotong University (CN)
National Natural Science Foundation of China, Support Program for Longyuan Youth and Fundamental Research Funds for the Universities of Gansu Province
Openalex Percentile: Top 11%
Ammonia Synthesis and Nitrogen Reduction
2.14
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.