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Nickel–Iron Catalysts Boost Clean Hydrogen Efficiency

A study has demonstrated how nickel–iron molecular catalysts can significantly accelerate water oxidation, laying the groundwork for more efficient and scalable hydrogen production.

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The study, published in Nature Chemistry, explored metal-hydroxyl groups that facilitate intramolecular proton transfer during the oxygen evolution reaction (OER).

Researchers focused on bimetallic nickel-iron (Ni-Fe) sites anchored to an aza-fused π-conjugated microporous polymer (Aza-CMP) to understand how these molecular catalysts improve water-oxidation kinetics. By analyzing the interactions among Ni, Fe, and hydroxyl intermediates, they clarified key steps governing proton transfer and overall OER performance.

These findings provide important guidance for designing more efficient catalysts for electrochemical water splitting and other clean energy technologies.

Challenges in Water Electrolysis Efficiency

Water electrolysis is a promising technique for sustainable hydrogen production, mainly as the world transitions toward clean energy. However, its efficiency is often constrained by the slow kinetics of OER, where water molecules are oxidized to generate oxygen gas (O2) and protons. Traditional catalysts, including noble and transition-metal oxides, are costly and limited in stability, especially during the formation of the oxygen-oxygen (O-O) bond.

In recent years, researchers have shifted toward molecular catalysts that can be engineered to enhance proton and electron transfer. Bimetallic systems provide synergistic interactions between metal centers, and the incorporation of metal-hydroxyl groups accelerates water oxidation by facilitating intramolecular proton transfer (IPT). These advancements highlight the potential of molecular catalyst design to address challenges in OER efficiency.

Synthesis and Characterization of Aza-CMP-NiFe Catalyst

This study synthesized and characterized Aza-CMP-NiFe, a bimetallic catalyst containing Ni and Fe sites. Researchers first prepared the Aza-CMP catalytic framework and introduced Ni ions through ultrasonic treatment. They then developed the dual-metal Aza-CMP-NiFe catalyst by electrochemical conditioning in a Fe-saturated alkaline solution.

The catalyst was tested in 1.0 M potassium hydroxide (KOH) using cyclic voltammetry (CV) and linear sweep voltammetry (LSV), providing insights into redox behavior and oxygen evolution. Operando X-ray absorption spectroscopy (XAS) and Mössbauer spectroscopy monitored changes in the oxidation states of Ni and Fe during reaction. Additionally, density functional theory (DFT) calculations modeled reaction pathways and assessed the energetics of intramolecular proton transfer and water nucleophilic attack during the OER.

Key Findings into Catalyst Performance

The experimental outcomes demonstrated that the Aza-CMP-NiFe catalyst exhibited significantly higher OER activity than its single-metal counterpart. It achieved an onset overpotential of 222 mV, comparable to benchmark catalysts such as ruthenium(IV) oxide (RuO2). The turnover frequency reached 18.7 s-1 at 300 mV, confirming its high catalytic efficiency.

The Tafel slope measured 31 mV dec-1, indicating fast reaction kinetics. Additionally, metal-hydroxyl groups played a crucial role in enhancing activity by supporting IPT, stabilizing charged intermediates, and facilitating proton movement during the reaction. Operando analysis confirmed the formation of high-valent Fe4+ species, demonstrating that Fe actively participates in O-O bond formation. Researchers also observed that Ni sites effectively relay protons to the Fe center, enabling efficient proton-coupled electron transfer.

The results also highlighted the impact of the catalyst’s coordination environment. Placing hydroxyl near the metal sites improved coupling between proton and electron transfer. The observed volcano-type relationship between the potential of hydrogen ions (pH) and activity emphasized that proton transfer rates depend strongly on the reaction environment.

Practical Applications for Clean Energy Technologies

This research has significant implications for developing efficient catalysts for water electrolysis and other clean energy technologies. Improving OER kinetics through molecular design can support more sustainable hydrogen production methods. As the demand for clean energy continues to grow, advanced molecular catalysts such as Aza-CMP–NiFe may play a key role in achieving the efficiency required for large-scale hydrogen generation.

Beyond water splitting, the principles of metal-hydroxyl-mediated proton transfer and dual-metal cooperation could inform the design of catalysts for carbon dioxide (CO2) reduction and other electrochemical processes. Understanding how metal sites and hydroxyl groups interact can lead to more effective materials for energy conversion and storage.

Conclusion and Future Directions

In summary, this study provides a deeper understanding of the mechanisms governing water-oxidation catalysis. It demonstrates that dual-metal systems can promote efficient OER by enhancing IPT, highlighting the importance of metal-hydroxyl interactions in accelerating reaction kinetics. The findings highlight the importance of strategic molecular design, particularly the incorporation of bimetallic centers, in enhancing catalytic performance.

Future work could explore alternative metal pairings and different ligand environments for practical applications. Integrating computational modeling with experimental validation will be essential for optimizing catalyst structures and understanding their behavior under operational conditions. Overall, this research contributes to ongoing efforts to develop efficient and robust catalysts that support clean and sustainable energy systems.

Journal Reference

Yang, H., &. et al. (2025). Metal-hydroxyls mediate intramolecular proton transfer in heterogeneous O-O bond formation. Nat. Chem. DOI: 10.1038/s41557-025-01993-8, https://www.nature.com/articles/s41557-025-01993-8

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Muhammad Osama

Written by

Muhammad Osama

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence.

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