Engineering TM-N₂@C₁₅N₅S₃H₅-Based Covalent-Organic Frameworks for Enhanced Water-Splitting and Oxygen Reduction...

The development of highly active metal-based single-atom catalysts (SACs) is crucial for energy conversion and storage, offering optimized atom utilization and high catalytic activity, with bifunctional SACs for hydrogen evolution (HER) and oxygen evolution/reduction (OER/ORR) reactions providing greater efficiency and cost-effectiveness than monofunctional catalysts, making them scientifically and economically valuable. By integrating density functional theory and machine learning methods, we systematically evaluated the potential of TM-N₂@C₁₅N₅S₃H₅ monolayers as efficient HER/OER/ORR catalysts, revealing that 27 TM atoms remain stable on N₂@C₁₅N₅S₃H₅ with a TM-N₂ coordination environment. Rh-N₂@C₁₅N₅S₃H₅ outperforms Pt in HER, while Rh-N₂@C₁₅N₅S₃H₅ drives both HER and OER, while Ni-N₂@C₁₅N₅S₃H₅ catalyzes OER and ORR, making them bifunctional catalysts. Comparative activity analysis reveals that the Ni-d orbitals in Ni-N₂@C₁₅N₅S₃H₅ interact with O-p orbitals, pairing up electrons from antibonding states into downward bonding orbitals, thus fitting OH* adsorption and enhancing catalytic performance. We further examined the pH and applied potential effects on OER/ORR performance of Ni-N₂@C₁₅N₅S₃H₅ and Rh-N₂@C₁₅N₅S₃H₅ monolayers, both show enhanced OER in acidic conditions, with Ni-N₂@C₁₅N₅S₃H₅ excelling in ORR under alkaline conditions and Rh-N₂@C₁₅N₅S₃H₅ in acidic conditions. Moreover, machine learning techniques were applied to explore the correlation between catalytic activity and a range of structural and atomic properties.