Subject of Research: Not applicable
Article Title: Adaptive Cu Reconstruction in Heterostructure Drives High-Rate Nitrate-to-Ammonia Conversion
News Publication Date: 13-Jul-2026
Web References: http://dx.doi.org/10.1002/advs.76573
References:
Image Credits: Credit: Takeshi Fujita from Kochi University of Technology
Keywords
Adaptive reconstruction; nitrate-to-ammonia; electrochemical reduction; Cu–Co heterostructure; hydroxyl-rich CuO; hydrogen spillover; Faradaic efficiency; green ammonia
Converting polluted water into a valuable feedstock is getting a major boost. Nitrate contamination—from farming runoff, industrial discharges, and municipal wastewater—has become a persistent environmental threat. At the same time, ammonia is emerging as a cornerstone chemical for low-carbon industry and carbon-free energy storage. Turning nitrate into ammonia would combine cleanup with production in a single electrochemical step.
The conventional path to ammonia relies on Haber–Bosch synthesis, which demands high temperatures and pressures and generates substantial carbon dioxide emissions. Researchers have therefore been pursuing electrochemical nitrate reduction (NO₃RR) as an ambient alternative powered by renewable electricity. Yet a stubborn bottleneck remains: nitrate reduction requires many proton- and electron-transfer steps, so achieving both high activity and strong selectivity has proven difficult.
Now, a team from Kochi University of Technology and Nagoya University reports a catalyst design that takes a different route. Instead of treating the catalyst as a fixed material, they allow it to “evolve” during operation, reconstructing into the surface state that actually performs best under working conditions.
Their heterostructured catalyst pairs crystalline copper oxide with amorphous cobalt oxide, built through a room-temperature, atmospheric-pressure synthesis. When tested across compositions, the Cu–Co system delivered standout ammonia production performance, signaling that the interface is more than a passive boundary.
To reveal what happens during electrolysis, the team combined transmission electron microscopy, X-ray photoelectron spectroscopy, Raman and infrared spectroscopy, electron paramagnetic resonance, and density functional theory. The key discovery: metallic copper formed early does not remain stable. It undergoes spontaneous re-oxidation and hydroxylation, generating hydroxyl-rich copper oxide (Cu–OH) that strongly attracts nitrate ions and stabilizes crucial reaction intermediates.
In this reconstructed state, the division of labor becomes clear. Cu–OH sites handle nitrate adsorption and deoxygenation, while amorphous cobalt oxide accelerates water dissociation to create reactive hydrogen species. Hydrogen then migrates across the Cu–Co interface via hydrogen spillover, boosting hydrogenation of nitrogen-containing intermediates and steering the pathway toward ammonia.
The payoff is striking. The optimized catalyst reaches an ammonia production rate of 54.68 mg h⁻¹ mgcat⁻¹ with a Faradaic efficiency of 95.4% at an applied potential of −0.2 V vs. RHE. It also operates stably for more than 60 hours in a flow cell and reduces nitrate in simulated wastewater from 140 ppm to 7.45 ppm—well below the WHO drinking-water guideline of 50 ppm.
Beyond nitrate remediation, the authors argue that adaptive reconstruction could become a general catalyst strategy for electrochemical technologies ranging from carbon dioxide reduction to water electrolysis and hydrogen production. If catalysts can be engineered to self-optimize in real time, the next generation of “dynamic” electrocatalysts may finally match the ambition of sustainable chemistry.
Tags: ambient electrochemical ammonia synthesiscatalyst reconstruction during electrolysisCu–Co heterostructure catalystenvironmentally sustainable ammonia manufacturinggreen ammonia productionhigh Faradaic efficiency in nitrate reductionhydrogen spillover mechanismhydroxyl-rich CuO catalystnitrate pollution remediationnitrate to ammonia electrochemical conversionrenewable energy-driven nitrate reductionself-adaptive catalyst
