Ammonia is one of the most important chemicals produced in the world, ranking second only to sulfuric acid in the total volume produced each year. It is used mostly to make fertilizer, which is essential to feeding the world’s population. Yet its production accounts for up to 2 percent of the world’s energy consumption and about 1.5 percent of greenhouse gas emissions, so the search has been underway for ways to produce ammonia more sustainably.
The traditional way of making ammonia, in use for more than a century and accounting for the vast majority of production, is the Haber-Bosch process, which relies on fossil fuels to provide the needed heat. Hydrogen used in the process is also largely produced from fossil fuels.
There is another way, using electrochemistry instead of heat and pressure, but so far this method has not been anywhere near economically competitive at the scales needed.
Now, researchers at MIT have developed a way to predict which materials could be most promising as catalysts in electrochemical ammonia production. Catalysts help drive chemical reactions, and their properties determine how efficiently those reactions proceed. Rather than using trial and error to test each possible combination out of the millions of possible alloys — which can take years — the new approach could greatly speed up the search for materials that could make this low-emissions method competitive with the Haber-Bosch process.
“Our approach identifies the key physical properties that drive catalytic activity in ammonia production,” says Bilge Yildiz, the Breen M. Kerr Professor in the departments of Nuclear Science and Engineering and Materials Science and Engineering (DMSE). The results can guide the search for new and more effective catalyst compounds.
The open-access findings were published Aug. 11 in the Royal Society of Chemistry journal EES Catalysis, in a paper by Yildiz and doctoral students Constantine Athanitis of DMSE and Filip Grajkowski of the Department of Chemistry.
The challenge of greener ammonia
As the world’s population grows, Athanitis says, “we’re just going to need more and more food, and the only reason why we’re able to sustain so many people is because of fertilizer.” But more than 90 percent of the ammonia needed for fertilizer is still made by that energy-intensive Haber-Bosch process, which “has been hyper-optimized since it first came out more than a century ago,” he says.
“If we’re trying to keep in line with society’s sustainability and energy targets and climate change targets, we really need to come up with another alternative,” he explains. The world currently uses about 200 million metric tons of ammonia each year, “so ideally we want to be able to find a way to produce the same amount of ammonia, or even more, but in a more energy-efficient way and also with lower CO2 emissions,” he says.
Using electricity to produce ammonia is not a new idea. “It’s really just the electrochemical reaction between proton-electron pairs and nitrogen gas. And these technologies exist,” he says. The approach uses the same basic principles as electrolyzers, which use electricity to drive chemical reactions in devices.
But while the process works, it’s not efficient enough for industrial-scale production. “Production rates and yields are still too low,” Athanitis says. “Even though a technology might be better for the world or for the climate, companies and capitalism won’t really allow it unless it’s cost competitive.”
How to make it more competitive? The key ingredient in the electrochemical process is a metallic catalyst, whose properties govern the reaction that takes place on its surface. “If we can somehow find a catalyst that reduces the energy needed and is more selective for ammonia production,” Athanitis says, “then we could essentially hit the jackpot.” A more selective catalyst would produce more ammonia while reducing unwanted side reactions.
Finding better catalysts
But finding that ideal catalyst is not simply a matter of identifying one perfect material. Different materials can improve different parts of the reaction, and researchers are seeking combinations that can make ammonia production efficient, affordable, and practical at large scale.
“Metal nitride compounds make an ideal material system for this reaction and for identifying the electronic, chemical, and structural properties that determine reactivity in nitrogen reduction and ammonia electrosynthesis,” Yildiz says.
Transition metals could form promising nitride alloys for this purpose, and historically, “materials research has been pretty much trial and error,” Athanitis says.
The usual process is to take some existing material and “tweak it in some way,” he says. “It’s all somewhat guided by scientific and chemical intuition.”
Now, increasingly, computational tools are being used to model the physical interactions and predict outcomes. A method called density functional theory uses quantum mechanics to simulate the properties and behavior of materials, allowing researchers to predict how different atomic arrangements may perform before making them in the lab. Rather than searching randomly through every possible alloy combination, Yildiz says, “we first assessed what microscopic properties of the material make them tick for nitrogen reduction.”
For ammonia-producing catalysts, “we’re looking at transition metal nitrides,” Athanitis says, because they have been found to be effective in these electrochemical nitrogen reactions. They are especially effective because “the nitrogen inherent to the catalyst itself becomes part of the reaction.”
This produces a series of chemical steps in which one step provides part of the energy needed to drive the next, reducing the amount of input energy needed. This helps solve one of the major bottlenecks in the nitrogen reduction reaction: the high energy required to break the strong bonds in nitrogen molecules, he says.
But the process is far from perfect, Athanitis says. It is “still limited by certain steps throughout the reaction pathway, including nitrogen dissociation and hydrogen transfer.” The study attempted to identify those bottlenecks and, with the help of machine learning, determine which alloys of these metals might overcome them.
With that understanding, “it can give us insights and open up potential strategies for how we can tune these materials to create next-generation better nitride catalysts,” Athanitis says.
Pushing past theory
The approach is “exciting work” that could help develop a foundation for designing new catalysts for ammonia production, says Dane Morgan, a professor of engineering at the University of Wisconsin who was not involved in this study.
“This work helps clarify how fundamental electronic properties of a material relate to its role as a catalyst in making ammonia,” Morgan says. “Such understanding can help guide researchers in designing new catalysts, both through better qualitative understanding and by accelerating computational screening.”
So far, the study is purely theoretical: The researchers have used computer models to identify promising alloys, but those materials still need to be made and tested. Morgan notes that “translating these calculations into practical catalysts will require many additional steps, so meaningful real-world impact is likely still some distance away.”
The next step will be to build a working reaction cell, a laboratory device that uses the catalyst to produce ammonia and test its performance under real operating conditions. “For this to really make an impact in society, we need to bring it to the experimental lab,” Athanitis says.
“There have always been pushes at the frontiers of what’s possible,” he adds. “We like to think we’ve pushed the boundary of candidate materials here beyond what was thought of before, and hopefully we’re almost there. But even if we’re not almost there, we’re still pushing in the right direction.”
Facts Only
* Ammonia production is ranked second only to sulfuric acid in total annual volume.
* Ammonia is primarily used to make fertilizer.
* The traditional method is the Haber-Bosch process, which uses fossil fuels for heat and hydrogen.
* Production of ammonia accounts for up to 2 percent of world's energy consumption and about 1.5 percent of greenhouse gas emissions.
* A new approach focuses on electrochemical ammonia production rather than high heat and pressure.
* Researchers at MIT developed a method to predict promising catalyst materials for electrochemical ammonia production.
* The research identifies key physical properties that drive catalytic activity in ammonia production.
* Findings were published on August 11 in the Royal Society of Chemistry journal EES Catalysis.
* The proposed catalysts focus on transition metal nitride compounds.
* The study attempted to use machine learning to identify alloys that overcome bottlenecks like nitrogen dissociation and hydrogen transfer.
Executive Summary
Ammonia is a crucial chemical, ranking second only to sulfuric acid in annual production, primarily used for fertilizer. Its current production method, the Haber-Bosch process, relies on fossil fuels for heat and hydrogen, contributing significantly to global energy consumption and greenhouse gas emissions. Researchers are exploring an alternative electrochemical method to produce ammonia using electricity instead of high heat and pressure, a method that has not yet reached economic competitiveness at industrial scales. A research approach developed at MIT seeks to accelerate the search for catalysts for this low-emissions electrochemical production by predicting promising material properties rather than relying on trial and error.
The challenge facing sustainable ammonia production stems from the reliance on the energy-intensive Haber-Bosch process, which currently accounts for over 90 percent of fertilizer ammonia production. While electrochemical methods exist based on basic principles of electrolysis, they suffer from low production rates and yields for industrial application. The path to competitiveness requires finding a metallic catalyst that reduces the energy demands and increases selectivity during the reaction. Current research focuses on transition metal nitride compounds, leveraging computational methods like density functional theory to predict catalytic activity by assessing fundamental physical properties, aiming to overcome kinetic bottlenecks in nitrogen reduction.
Full Take
The narrative presents a classic tension between established, large-scale industrial processes and theoretically superior, yet practically unproven, alternatives. The core pattern is the friction between current energy-intensive realities (Haber-Bosch dominance) and future sustainability goals (decarbonization). The focus on catalysts shifts the bottleneck from thermodynamics (the reaction *can* happen) to kinetics and materials science (the reaction *can* happen efficiently under practical constraints).
The reliance on computational methods, such as density functional theory, to guide material discovery reflects a modern shift in scientific practice away from empirical trial-and-error toward predictive modeling. This introduces an implicit assumption that complex chemical systems can be sufficiently mapped by fundamental physical properties—a powerful claim that hinges on the validity of the underlying quantum mechanical models. The subsequent acknowledgment that theoretical success does not immediately translate to industrial viability—the gap between laboratory prediction and cost-competitive scale—highlights a systemic challenge often faced in technological transitions: bridging the "valley of death" between proof-of-concept and scalable implementation.
The focus on transition metal nitrides suggests a specific material hypothesis, which is then refined by computational screening. This pattern illustrates how scientific inquiry progresses: from broad observation (pollution/energy use) to targeted mechanism identification (catalysis), to proposing novel solutions, and finally, confronting the practical limitations of scale and economic integration. The implication for agency is whether the current push toward computationally guided material design can effectively force the necessary industrial adoption rates required by societal targets, or if external economic structures will perpetually constrain scientific potential regardless of theoretical breakthroughs.
Bridge Questions: If computational models successfully predict optimal catalyst properties, what specific, measurable criteria must be established to transition materials from predicted performance to viable industrial cost-competitiveness? What mechanisms outside of pure material science—such as policy levers or market incentives—will be necessary to overcome the economic hurdle that prevents the adoption of theoretically superior but currently inefficient processes? How can research effectively bridge the gap between theoretical optimization and experimental validation at an industrial scale without introducing further delays?