Machine learning for guiding high-temperature PEM fuel cells with greater power density

High-temperature polymer electrolyte membrane fuel cells (HT-PEMFCs) are enticing energy conversion technologies because they use low-cost hydrogen generated from methane and have simple water and heat management. However, proliferation of this technology requires improvement in power density. Here,...

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Detalles Bibliográficos
Autores principales: Briceno-Mena, Luis A., Venugopalan, Gokul, Romagnoli, José A., Arges, Christopher G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892359/
https://www.ncbi.nlm.nih.gov/pubmed/33659908
http://dx.doi.org/10.1016/j.patter.2020.100187

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892359/
https://www.ncbi.nlm.nih.gov/pubmed/33659908
http://dx.doi.org/10.1016/j.patter.2020.100187

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