Ammonia fuels agriculture, supports industry, and is increasingly viewed as a key player in future clean-energy systems. Yet producing it is heat and pressure intensive. A research team has developed an electrocatalyst that helps turn nitrate--a common pollutant found in groundwater and agricultural runoff--into ammonia under far milder conditions.
Details of their findings were published in the journal Advanced Functional Materials on November 4, 2025.
"Our new catalyst has two main benefits: first, it reduces the emissions linked to fertilizer and chemical manufacturing, and second, it enables us to essentially recycle nitrate, which would otherwise pollute our water," points out Hao Li, Distinguished Professor at Tohoku University's Advanced Institute for Materials Research (WPI-AIMR).
The catalyst is made from an atomically ordered alloy of ruthenium (Ru) and gallium (Ga), forming a ruthenium-gallium intermetallic compound supported on carbon (RuGa IMC/C). Its structure places individual ruthenium atoms in precise positions surrounded by gallium, which does not react directly but shapes the environment in which each ruthenium site operates. This fine-tuned arrangement helps guide nitrate (NO₃⁻) toward the reaction steps that produce ammonia (NH₃).
Even at low nitrate concentrations, the catalyst converts nitrate efficiently at a very gentle voltage. It maintains strong selectivity across a broad concentration range and continues operating with steady performance, showing that careful atomic design can support nitrate conversion under realistic environmental conditions.
Computer simulations conducted by the researchers revealed why the structure worked so well. By introducing gallium, the electronic characteristics of ruthenium shift, affecting how nitrogen-containing molecules attach and transform on the surface. This adjustment also slows down hydrogen formation, a competing reaction that often limits ammonia yields.
The catalyst was also evaluated in a zinc-nitrate battery. The system generated consistent power and ran for hundreds of hours, showing that the material can support both chemical production and energy-related applications.
"We hope to convert a widespread pollutant into a valuable product and offer guidance for designing future catalysts that take advantage of controlled atomic ordering," adds Li.
Looking ahead, the researchers plan to expand their theoretical modeling, integrating machine-learning tools to more effectively map reaction pathways. This work aims to accelerate the design of next-generation electrocatalysts for sustainable chemical production.