Machine Learning Speeds Discovery of New Fuel Cell Materials
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Researchers used machine learning to identify 2 new materials with unique crystal structures that could enhance proton conductivity for fuel cells.
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Their approach speeds up the discovery process by predicting optimal base and dopant combinations.
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While current performance of these materials is low, further research could improve their efficiency.
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This contributes to the development of a hydrogen-based society and carbon neutrality.
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The framework has potential to accelerate advancement in solid oxide fuel cells and discovery of innovative materials beyond the energy sector.