Evidence map›Paper›PMID 40729676›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

d-Electron Asymmetry-Driven CN Coupling on Heteronuclear Dual-Atom Catalysts for Sustainable Urea Electrosynthesis.

Zaifu Jiang, Jingjing Wang, Dingmei Zhang, Panlong Kong, Xiaotao Zhang

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zaifu JiangSchool of Mathematics and Physics, Jingchu University of Technology, Jingmen, 448000, China.ORCID https://orcid.org/0009-0002-5978-405X
Jingjing WangSchool of Mathematics and Physics, Jingchu University of Technology, Jingmen, 448000, China.
Dingmei ZhangSchool of Mathematics and Physics, Jingchu University of Technology, Jingmen, 448000, China.
Panlong KongSchool of Mathematics and Physics, Jingchu University of Technology, Jingmen, 448000, China.
Xiaotao ZhangZhuhai Beijing Institute of Technology (BIT), Beijing Institute of Technology, Zhuhai, 519088, China.ORCID https://orcid.org/0009-0008-8980-4078

Funding

Guiding Project of the Scientific Research Plan by the Hubei Provincial Department of Education B2023222Guiding Project of the Scientific Research Plan by the Hubei Provincial Department of Education B2023227Project of the Program for Outstanding Young and Middle-aged Scientific and Technological Innovation Teams in Higher Education Institutions of Hubei Province T2024029Scientific Research Project of Jingchu University of Technology YY202401Scientific Research Project of Jingchu University of Technology YY202409Young Talent Project of the Scientific Research Plan by the Hubei Provincial Department of Education Q20234301
6 · The paper itself

Abstract

The transition toward carbon-neutral chemical manufacturing calls for innovative strategies to produce nitrogen-based compounds with minimal environmental impact. Urea, a key nitrogen-rich chemical, is currently synthesized via the energy-intensive Bosch-Meiser process, which relies heavily on fossil fuel-derived ammonia. As a sustainable alternative, electrochemical urea synthesis (ECUS) enables the direct coupling of nitrogenous and carbonaceous precursors under ambient conditions, yet remains hampered by sluggish kinetics and poor selectivity-particularly in the critical C─N bond formation step. Here, density functional theory (DFT) calculations is integrated with data-driven machine learning to systematically explore the activity landscape of nitrogen-doped graphene-supported dual-metal-atom catalysts (M'M@NC) for C─N coupling. A comprehensive reaction network is evaluated across 45 M'M@NC configurations, revealing three heteronuclear catalysts-VNi@NC, CoNi@NC and CoCu@NC-with consistently favorable thermodynamic and kinetic performance. Electronic structure analysis indicates that heteronuclear coordination promotes *CO activation and optimizes *NH

Indexed as

C─N couplingd‐electron asymmetrydual‐atom catalystselectrochemical urea synthesisinterpretable machine learning

Identifiers

PMID40729676
PMCPMC12561354

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.