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This study investigates the optimization of NbTa alloy coatings on SS316L bipolar plates for proton exchange membrane fuel cells (PEMFCs) using a combination of experimental methods and machine learning. The research identifies that a 2.5 μm coating significantly reduces corrosion current density and interfacial contact resistance, while a 1.7 μm coating meets U.S. DOE targets, providing a cost-effective solution. An artificial neural network model was developed to predict performance trends, achieving high

Author

vuphds

Language

EN