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Predicting optimal membrane hydration and ohmic losses in operating fuel cells with machine learning

Joshua Paciocco, Taylr Cawte, Aimy Bazylak

2023Journal of Power Sources16 citationsDOI

Topics & Concepts

Dielectric spectroscopyElectrolyteProton exchange membrane fuel cellArtificial neural networkElectrochemistryElectrodeMaterials scienceBiological systemComputer scienceChemical engineeringArtificial intelligenceChemistryFuel cellsEngineeringPhysical chemistryBiologyFuel Cells and Related MaterialsAdvanced Battery Technologies ResearchElectrocatalysts for Energy Conversion
Predicting optimal membrane hydration and ohmic losses in operating fuel cells with machine learning | Litcius