Japanese university researchers from Osaka and elsewhere developed technology using machine learning to accelerate the discovery of necessary substances for green energy production.
Using the new method, researchers managed to create two new candidate substances for use into solid oxide fuel cells, which can be used to generate energy through clean hydrogen.
According to the results published through Advanced Energy Materials, the method could be used to discover other substances four uses outside the energy sector.
The research team behind the concept expressed their support for hydrogen fuel-cell technologies as carbon-neutral sources of energy, that need more development to be viable.
Using machine learning to analyze the data structure of the substances needed to optimize and produce energy through hydrogen fuel cells was a genuine breakthrough that brought quick results.
Researchers formed two promising substances, each with unique structures, and each has proved capable of contributing to energy production efficiently through fuel cells.
However, practical applications of the method remains a bit far off, but the future is quite promising.
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