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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,...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2021
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| Materias: | |
| 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 |