d‐Electron Asymmetry‐Driven CN Coupling on Heteronuclear Dual‐Atom Catalysts for Sustainable Urea Electrosynthesis
Source abstract
Abstract
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 x adsorption, facilitating C─N coupling. Leveraging symbolic regression via the sure independence screening and sparsifying operator (SISSO) algorithm, interpretable descriptors linking C─N coupling energy to atomic‐level electronic properties is established, highlighting the critical role of d‐electron asymmetry. This results uncover fundamental design principles for dual‐atom catalysts and provide a predictive framework for guiding the development of next‐generation electrocatalysts for sustainable urea synthesis.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Ammonia Synthesis and Nitrogen Reduction · Advanced Photocatalysis Techniques · Electrocatalysts for Energy Conversion
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mathematics and Physics Jingchu University of Technology Jingmen 448000 China
Zhuhai Beijing Institute of Technology (BIT) Beijing Institute of Technology Zhuhai 519088 China
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