Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Qianli Si"'
Publikováno v:
Advanced Science, Vol 11, Iss 33, Pp n/a-n/a (2024)
Abstract Achieving precise estimates of battery cycle life is a formidable challenge due to the nonlinear nature of battery degradation. This study explores an approach using machine learning (ML) methods to predict the cycle life of lithium‐metal
Externí odkaz:
https://doaj.org/article/079ff3eb66c941439bd17add70eecad0
Publikováno v:
ACS Applied Electronic Materials. 4:3154-3165
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6836ffdbf298042d21a6eef5e24f81f7
https://doi.org/10.1021/acsaelm.2c00663
https://doi.org/10.1021/acsaelm.2c00663
Publikováno v:
The Journal of Physical Chemistry C. 125:17019-17030
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e5cffe87bcd292f241e0e524d3f6421
https://doi.org/10.1021/acs.jpcc.1c04096
https://doi.org/10.1021/acs.jpcc.1c04096
Autor:
Qianli Si, Long Hu, Yifeng Jiang, Gang Xiao, Liang Qiao, Jack Yang, Xiaotao Zu, Qi Lei, Sean Li, Ji Zhang
Publikováno v:
Applied Energy. 305:117958
Thermochemical energy storage via metal oxide redox cycling is a potential cost-effective approach to store solar energy both chemically and thermally at high temperatures, enabling efficient solar thermal power production round-the-clock and on-dema
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a999ce67a1dbc8eb359793378ff17e11
https://doi.org/10.1016/j.apenergy.2021.117958
https://doi.org/10.1016/j.apenergy.2021.117958