Bilayer MN4-O-MN4 by bridge-bonded oxygen ligands: Machine learning to accelerate the design of bifunctional electrocatalysts
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- Type
- article
- Published
- 2022-12-01
- Cited by
- 31
- References
- 67
- OpenAlex
- https://openalex.org/W4313252350
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:254849936
Keywords
Overpotential, Bifunctional, Catalysis, Oxygen evolution, Bilayer
References
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Cited by
- Applying machine-learning screening of single transition metal atoms anchored on N-doped γ-graphyne for carbon monoxide electroreduction toward C1 products
- Theoretical Insights on the Charge State and Bifunctional OER/ORR Electrocatalyst Activity in 4d-Transition-Metal-Doped g-C3N4 Monolayers.
- High throughput screening for electrocatalysts for nitrogen reduction reaction using metal-doped bilayer borophene: A combined approach of DFT and machine learning
- Heterojunction of MXenes and MN4-graphene: Machine learning to accelerate the design of bifunctional oxygen electrocatalysts.
- Machine learning accelerates design of bilayer-modified graphene hydrogen storage materials
- Symbolic transform optimized convolutional neural network model for high-performance prediction and analysis of MXenes hydrogen evolution reaction catalysts
- Synergism between metal single-atom sites and S-vacant two-dimensional nanosheets for efficient hydrogen evolution uncovered by density functional theory and machine learning
- Important structural parameter for curvature effect of TM-N4 embeded C70 fullerenes as electrocatalysts for CO2 reduction interpreted with machine learning and first-principles calculations
- Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation.
- Bifunctional Oxygen Reduction/Evolution Reaction Activity of Transition Metal-Doped T-C3N2 Monolayer: A Density Functional Theory Study Assisted by Machine Learning
- Enhancing Electrocatalysis of CO2 to Ethanol via Intercalated Electron Boosters in an Atomically Dispersed Ca–N4-Doped Graphene Bilayer
- Understanding of the synergetic effect of FeCoN8C dual active centers catalyst for oxygen reduction reaction and oxygen evolution reaction: A density functional theory study
- Single-atom dissolution at the MN4/MXene interface and electric field-driven adsorption mechanisms: Unraveling catalytic descriptors using machine learning
- Engineering TM-N2@C15N5S3H5-Based Covalent-Organic Frameworks for Enhanced Water-Splitting and Oxygen Reduction Reactions: A Constant Potential and Feature Coevaluation Approach.
- Bridge‐Oxygen Bond: An Active Group for Energy Electrocatalysis
- Machine-learning-assisted Design of Cathode Catalysts for Metal-Sulfur/Oxygen/Carbon Dioxide Batteries
- (TM-O4)3@h-B12N12 for Hydrogen Evolution Reaction and Achieving Highly Efficient Single-Functional Oxygen Evolution Reaction Catalysis via Axial Ligand Modification
- Curvature effect of TMN4 sites on carbon nanotube for electrochemical reduction of carbon dioxide revealed by machine learning
- Single atom embedded ZnO monolayers as bifunctional electrocatalysts for the ORR/OER: a machine learning-assisted DFT study
- Exploring TMN4-Graphene and fullerene heterostructures (TMN4-O-C58BN) as bifunctional oxygen electrocatalysts: A computational study
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