Data-driven insights into protonic-ceramic fuel cell and electrolysis performance

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Data-driven insights into protonic-ceramic fuel cell and electrolysis performance

Cell reproducibility remains a significant challenge for emerging proton-conducting ceramic electrochemical fuel cell and electrolyzer technologies. This study investigates the factors contributing to cell-to-cell performance variation. Gaussian process and random forest regressor machine learning m...

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Bibliographic Details
Main Authors:	Meisel, C., Huang, J.D., Le, L.Q., Kim, Y.D., Stockburger, S., Luo, Z., Zhu, T., Wang, Z., Shao, Zongping, O'Hayre, R., Sullivan, N.P.
Format:	Journal Article
Published:	2025
Online Access:	http://hdl.handle.net/20.500.11937/97513

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