Self-adaptive Cu–Co catalyst converts nitrate pollution into green ammonia through dynamic catalyst reconstruction
Nitrate contamination originating from agricultural runoff, industrial wastewater and municipal effluents is a growing global environmental problem. At the same time, ammonia has emerged as a key chemical feedstock and an attractive carbon-free energy carrier for a sustainable society.
Industrial ammonia production currently relies on the Haber–Bosch process, which requires high temperatures and pressures and is responsible for substantial energy consumption and carbon dioxide emissions. Electrochemical nitrate reduction (NO₃RR), driven by renewable electricity under ambient conditions, has therefore attracted increasing attention because it simultaneously removes nitrate pollutants while producing green ammonia.
Converting nitrate pollution into a valuable resource
However, converting nitrate into ammonia requires multiple proton- and electron-transfer steps, making it difficult to achieve both high catalytic activity and high product selectivity.
Researchers at Kochi University of Technology and Nagoya University have developed a catalyst that addresses this challenge through a fundamentally different strategy: Rather than remaining structurally static, the catalyst continuously evolves into its most active state during operation. The research is published in the journal Advanced Science.
In the new study, the researchers synthesized a heterostructured copper–cobalt oxide catalyst using a simple chemical synthesis performed entirely at room temperature and atmospheric pressure.
Catalyst reconstruction creates the true active phase
After systematically optimizing the catalyst composition, they found that the Cu–Co catalyst exhibited the highest ammonia production performance among the compositions investigated.
Using transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, infrared spectroscopy, electron paramagnetic resonance (EPR) and density functional theory (DFT) calculations, the researchers monitored structural changes occurring during electrolysis.
They discovered that metallic copper generated during the initial reduction step does not remain in the catalytically active phase. Instead, the surface undergoes spontaneous reoxidation and hydroxylation to form hydroxyl-rich copper oxide species (Cu–OH), which strongly adsorb nitrate ions and stabilize key reaction intermediates.
This adaptive reconstruction continuously creates the catalyst's most active surface during operation.
Cooperative roles of copper and cobalt
The study further revealed a cooperative catalytic mechanism. The Cu–OH active sites primarily adsorb nitrate ions and catalyze deoxygenation reactions, while amorphous cobalt oxide efficiently dissociates water to generate reactive hydrogen species.
These hydrogen atoms migrate across the Cu–Co interface through hydrogen spillover, significantly accelerating the hydrogenation of nitrogen-containing intermediates and promoting ammonia production.
The synergistic interaction between copper and cobalt enables both high ammonia production rates and excellent selectivity.
Outstanding catalytic performance
The optimized catalyst achieved:
- Ammonia production rate: 54.68 mg h⁻¹ mgcat⁻¹
- Faradaic efficiency: 95.4%
- Applied potential: −0.2 V vs. RHE
The catalyst also maintained stable operation for more than 60 hours in a flow-cell configuration.
When tested using simulated wastewater containing 140 ppm nitrate, the catalyst reduced the nitrate concentration to 7.45 ppm, well below the World Health Organization (WHO) drinking-water guideline of 50 ppm.
These results demonstrate the catalyst's capability to simultaneously purify wastewater and recover ammonia as a valuable chemical resource.
Practical significance
The catalyst can be synthesized entirely under ambient conditions, making large-scale manufacturing straightforward.
Beyond nitrate reduction, the adaptive reconstruction strategy introduced in this work may provide a new catalyst design principle for a wide range of electrochemical technologies, including carbon dioxide reduction, water electrolysis and hydrogen production.
Future studies will evaluate catalyst performance using real wastewater, investigate long-term durability, scale up electrolyzer systems and integrate renewable electricity into practical green ammonia production systems.
"Rather than designing catalysts that remain static, we found that allowing catalysts to adapt dynamically during operation leads to substantially higher activity and selectivity. We believe this adaptive reconstruction concept can inspire catalyst development well beyond nitrate reduction," said Professor Takeshi Fujita
Why this matters
Electrochemical nitrate reduction offers a sustainable alternative to conventional ammonia production by simultaneously removing nitrate pollutants from wastewater and producing green ammonia under ambient conditions.
This study demonstrates that catalysts can dynamically reconstruct into their most active state during operation, introducing a new design strategy for next-generation electrocatalysts.
Publication details
Chunyu Yuan et al, Adaptive Cu Reconstruction in Heterostructure Drives High‐Rate Nitrate‐to‐Ammonia Conversion, Advanced Science (2026). DOI: 10.1002/advs.76573
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Citation: Self-adaptive Cu–Co catalyst converts nitrate pollution into green ammonia through dynamic catalyst reconstruction (2026, July 28) retrieved 28 July 2026 from https://phys.org/news/2026-07-cuco-catalyst-nitrate-pollution-green.html
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