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Updated: Jan 30, 2026

Reverse Microemulsion-mediated Synthesis of Monometallic and Bimetallic Early Transition Metal Carbide and Nitride Nanoparticles
Published on: November 27, 2015
Transition-Metal-Doped Hexagonal Boron Nitride for Efficient and Selective Nitrate-to-Ammonia Electrocatalysis:
Lina Yin1, Myounwoo Kim1, Hongguang Liu2
1Department of Chemistry, Sungkyunkwan University, Suwon, Republic of Korea.
Researchers developed new catalysts for electrochemical nitrate reduction, converting harmful nitrates into valuable ammonia. Iron and Iridium-doped boron nitride show exceptional promise for efficient and selective ammonia production, aiding water remediation and sustainable chemical synthesis.
Area of Science:
- Materials Science
- Electrochemistry
- Computational Chemistry
- Catalysis
Background:
- Nitrate contamination poses a significant threat to water resources, necessitating effective remediation strategies.
- Electrochemical nitrate reduction reaction (NO3RR) offers a promising pathway for both nitrate removal and ammonia (NH3) production.
- Developing efficient and selective electrocatalysts is crucial for advancing NO3RR technology.
Purpose of the Study:
- To computationally screen transition-metal-doped hexagonal boron nitride (TM@h-BN) monolayers as potential single-atom catalysts for NO3RR.
- To identify catalysts with low overpotentials and high selectivity for ammonia synthesis.
- To establish design principles for next-generation electrocatalysts for sustainable ammonia production.
Main Methods:
- First-principles density functional theory (DFT) calculations were performed to evaluate the catalytic performance of various TM@h-BN systems.
- Key reaction parameters, including limiting potentials and binding energies, were systematically analyzed.
- A SISSO-based machine learning framework was integrated to identify descriptor-performance relationships.
Main Results:
- Fe@h-BN and Ir@h-BN were identified as highly promising catalysts, with limiting potentials of -0.45 V and -0.31 V, respectively.
- These catalysts demonstrate balanced interaction with nitrate, efficient ammonia production, and suppressed hydrogen evolution reaction (HER).
- High selectivity towards NH3 was observed due to elevated byproduct formation potentials.
- Machine learning identified key descriptors and established a predictive equation for NO3RR catalyst performance.
Conclusions:
- Fe@h-BN and Ir@h-BN represent advanced single-atom catalysts for efficient electrochemical nitrate reduction to ammonia.
- The study provides valuable mechanistic insights and a transferable design principle for developing novel electrocatalysts.
- This work contributes to sustainable ammonia production and effective water resource management.
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