Using AI for sustainable ammonia production

03 March 2023

Fujitsu and Atmonia, an Icelandic start-up company developing a novel method for synthesising sustainable ammonia, have revealed the latest milestone in their joint research into catalysts for sustainable production of ammonia, by successfully developing a high-speed technology for quantum chemical simulations

By combining this technology with an AI technology for scientific discovery developed by Fujitsu, the two companies succeeded in more than halving the search time for a catalyst material that efficiently synthesises ammonia from water, air and electricity at ambient temperatures and pressures. Ammonia and amines are commonly used in water-based inks and coatings, as well as adhesives. They serve to “dissolve” the acidic resins and stabilise emulsions and pigment dispersions by charge repulsion.​

The two companies carried out various quantum chemical calculations using Fujitsu supercomputing resources based on simulation data for ammonia synthesis owned by Atmonia. Vast amounts of data derived from these calculations, including the structure of atomic configurations and the types and ratios of chemical elements that compose catalyst materials, were used to train an AI simulation model that can rapidly identify catalyst candidates. Fujitsu’s AI technology for scientific discovery was also used to identify trends in the properties of materials suitable as ammonia synthesis catalysts based on causal relationships among more than 10,000 candidates, helping to narrow down catalyst candidate data. The catalyst’s discovery search includes, for example, the type and position of the atoms in the catalysts and the free energies of intermediates in the nitrogen reduction reaction.

Going forward, the two companies will use the newly developed technology to select specific ammonia synthesis catalyst candidates and verify their effectiveness, with the ultimate goal of innovating a sustainable production method for ammonia.

Read the full article here: Fujitsu AI PPCJ March 2023

“By streamlining this time-consuming and labour intensive practice using the AI technology for scientific discovery, the two companies succeeded in reducing the search time for catalyst candidates by more than half.”

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