Key Takeaways
- UNSW Sydney researchers have enhanced green ammonia production using AI, achieving a sevenfold improvement in efficiency.
- The new process allows ammonia to be produced at ambient temperatures, reducing energy consumption significantly.
- Decentralized ammonia production units are being developed for on-site fertilization, minimizing transportation emissions.
Innovative AI-Driven Efficiency in Ammonia Production
Scientists and engineers at UNSW Sydney have applied artificial intelligence and machine learning to enhance their previously developed method for producing green ammonia. Ammonia, a vital component of fertilizers, has significantly contributed to global food security but comes with a substantial carbon footprint, accounting for 2% of worldwide greenhouse gas emissions. Traditional ammonia production requires high temperatures (over 400 °C) and severe pressure, making it an energy-intensive process with a major impact on the environment.
In 2021, a UNSW team demonstrated the feasibility of generating ammonia from air and water using renewable energy at much lower temperatures, resembling those of a warm summer day. However, Dr. Ali Jalili from the UNSW School of Chemistry noted the need for further improvements in efficiency, energy use, and ammonia yield.
To address these challenges, the team identified potential catalyst candidates—substances that accelerate chemical reactions without being consumed. They recognized this task could potentially involve over 8000 combinations of metals. By leveraging AI, the researchers trained a machine learning system to analyze metal behavior and identify optimal combinations, dramatically reducing the lab experiments needed to just 28.
The winning combination of metals—iron, bismuth, nickel, tin, and zinc—has led to a remarkable sevenfold increase in ammonia production rate with nearly 100% efficiency. This metric, known as Faradaic efficiency, indicates that the vast majority of electrical energy used in the process is converted into ammonia, minimizing waste. Notably, the production occurs at a comfortable 25 °C, below 10% of the temperature used in conventional methods like the Haber-Bosch process.
This low-energy and high-efficiency method positions green ammonia as a competitive alternative to fossil fuel-based production. The goal is to enable farmers to manufacture ammonia on-site, reducing costs and eliminating carbon emissions associated with transportation. Current trials have already initiated localized ammonia production through compact, shipping container-sized modules. These factory-built systems combine AI-optimized catalysts, plasma generators, and electrolysers for easy use.
Dr. Jalili pointed out that the historical reliance on large, centralized production facilities has often led to high costs and long development timelines. The new approach encourages smaller, decentralized units that require less initial investment and can rapidly adapt to changing energy markets.
Additionally, the new method of ammonia production can support the transition to a hydrogen economy. Liquid ammonia holds more hydrogen energy than liquid hydrogen, making it a more efficient choice for renewable energy storage and transportation. As the researchers implement their AI-identified catalyst in distributed ammonia modules, they aim to further reduce costs and enhance the global market’s acceptance of green ammonia as a sustainable resource for the future.
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