Machine learning for a sustainable energy future

Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it demands advances — at the materials, devices and systems levels — for the efficient harvesting, storage, conversion and management of renewable energy. Energy researchers have begun to incorporate machine...

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Detalles Bibliográficos
Autores principales: Yao, Zhenpeng, Lum, Yanwei, Johnston, Andrew, Mejia-Mendoza, Luis Martin, Zhou, Xin, Wen, Yonggang, Aspuru-Guzik, Alán, Sargent, Edward H., Seh, Zhi Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Perspective
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9579620/
https://www.ncbi.nlm.nih.gov/pubmed/36277083
http://dx.doi.org/10.1038/s41578-022-00490-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9579620/
https://www.ncbi.nlm.nih.gov/pubmed/36277083
http://dx.doi.org/10.1038/s41578-022-00490-5

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