Molecularly Engineered Ni–O–C Interfacial Sites on g-C <sub>3</sub> N <sub>4</sub> for Efficient Electrocatalytic Urea Synthesis from CO <sub>2</sub> and Nitrate

Nickel-based catalysts hold promise for urea electrosynthesis but often suffer from strong chemisorption of CO2, poor stability, and uncontrolled structural evolution under reaction conditions. In this study, we report a molecularly engineered electrocatalyst, Ni-PDA@g-C3N4, that contains highly dispersed Ni–O–C interfacial sites for the efficient and selective synthesis of urea from CO2 and nitrate under ambient conditions. The catalyst is synthesized by chelating Ni2+ ions with polydopamine (PDA) and anchoring them onto graphitic carbon nitride (g-C3N4), forming a robust hybrid interface. This architecture promotes the concurrent activation of CO2 and NO3–, thereby facilitating C–N bond formation. The Ni-PDA@g-C3N4 catalyst achieved a urea yield of 1190.3 μg h–1 mgcat–1 with a Faradaic efficiency of 18.03% and a nitrogen selectivity of 55.78% at −1.3 V vs RHE, along with excellent long-term stability. Density functional theory (DFT) calculations demonstrate that the Ni–O–C interface substantially reduces the energy barriers for key intermediates such as *NHO and *COOH, thus accelerating the C–N coupling process. This work highlights a molecular and interfacial design strategy that offers a promising route toward sustainable urea production from CO2 and nitrogenous wastes.

Authors

Institutions

Publication Details

Journal
ACS Sustainable Chemistry & Engineering
Published
2025-10-15
DOI
https://doi.org/10.1021/acssuschemeng.5c09552
Citations
2
Primary Topic
Ammonia Synthesis and Nitrogen Reduction
Type
article
Field-Weighted Citation Impact
0.78
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Molecularly Engineered Ni–O–C Interfacial Sites on g-C 3 N 4 for Efficient Electrocatalytic Urea Synthesis from CO 2 and Nitrate

Qingxiang Wang, Wei Chen, Yun Han Ling, Xuan Zheng et al.
2 citations
ACS Sustainable Chemistry & Engineering
Ammonia Synthesis and Nitrogen Reduction
0.78
article

Molecularly Engineered Ni–O–C Interfacial Sites on g-C 3 N 4 for Efficient Electrocatalytic Urea Synthesis from CO 2 and Nitrate

Qingxiang Wang, Wei Chen, Yun Han Ling, Xuan Zheng, Jing Tang, Yi Li, Xiaoping Chen, Hui Su
article en
2 citations

Abstract

Nickel-based catalysts hold promise for urea electrosynthesis but often suffer from strong chemisorption of CO2, poor stability, and uncontrolled structural evolution under reaction conditions. In this study, we report a molecularly engineered electrocatalyst, Ni-PDA@g-C3N4, that contains highly dispersed Ni–O–C interfacial sites for the efficient and selective synthesis of urea from CO2 and nitrate under ambient conditions. The catalyst is synthesized by chelating Ni2+ ions with polydopamine (PDA) and anchoring them onto graphitic carbon nitride (g-C3N4), forming a robust hybrid interface. This architecture promotes the concurrent activation of CO2 and NO3–, thereby facilitating C–N bond formation. The Ni-PDA@g-C3N4 catalyst achieved a urea yield of 1190.3 μg h–1 mgcat–1 with a Faradaic efficiency of 18.03% and a nitrogen selectivity of 55.78% at −1.3 V vs RHE, along with excellent long-term stability. Density functional theory (DFT) calculations demonstrate that the Ni–O–C interface substantially reduces the energy barriers for key intermediates such as *NHO and *COOH, thus accelerating the C–N coupling process. This work highlights a molecular and interfacial design strategy that offers a promising route toward sustainable urea production from CO2 and nitrogenous wastes.

ACS Sustainable Chemistry & EngineeringVol. 13(42)
Ministry of Education of the People's Republic of China (CN), Nankai University (CN), Fuzhou University (CN), Minnan Normal University (CN)
Openalex Percentile: Top 27%
Ammonia Synthesis and Nitrogen Reduction
0.78
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.