Abstract
The increasing global energy demand and environmental pollution necessitate the development of alternative, sustainable energy sources. Hydrogen production through electrochemical methods offers a carbon-free energy solution. In this study, we have designed novel boron nitride analogues (BNyne) and investigated their stability and electronic properties. Furthermore, the incorporation of transition metals (TM) at holey sites in these analogues was explored, revealing their potential as promising electrocatalysts for the hydrogen evolution reaction (HER). The inclusion of transition metals significantly enhances their structural stability and electronic properties. The TM-anchored BNynes exhibit optimal Gibbs free energy changes (ΔGH) for effective HER performance. Additionally, the favorable alignment of d-band centers near the Fermi level supports efficient hydrogen adsorption. Machine learning models, particularly the Random Forest model, have also been employed to predict ΔGH values with high accuracy, capturing the complex relationships between material properties and HER efficiency. This dual approach underscores the importance of integrating advanced computational techniques with material design to accelerate the discovery of effective HER catalysts. Our findings highlight the potential of these tailored boron nitride analogues to enhance electrocatalytic applications and improve HER efficiency.
| Original language | British English |
|---|---|
| Article number | e202401256 |
| Journal | Chemistry - An Asian Journal |
| Volume | 20 |
| Issue number | 3 |
| DOIs | |
| State | Published - 3 Feb 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 15 Life on Land
Keywords
- 2D-material
- Density functional theory
- Machine learning
- Single-atom catalyst
- Sustainable energy
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