Artificial-intelligence-guided design of ordered gas diffusion layers for high-performing fuel cells via Bayesian machine learning
Abstract Rational design of gas diffusion layers (GDL) is an example of a long-standing pursuit to increase the power density and reduce the cost of proton exchange membrane fuel cells (PEMFC). However, current state-of-the-art GDLs are designed by trial-and-error, which is a time-consuming endeavor...
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| Asıl Yazarlar: | , , , , , , , , , , , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
Nature Portfolio
2025-07-01
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| Seri Bilgileri: | Nature Communications |
| Online Erişim: | https://doi.org/10.1038/s41467-025-61794-y |
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