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Machine learning-assisted benign transformation of three zinc states in zinc ion batteries
Energy Environ. Sci., 2025, Advance ArticleDOI: 10.1039/D5EE00650C, Paper Open Access   This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.Jianbo Dong, Guolang Zhou, Wenhao Ding, Jiayi Ji, Qing Wang, Tianshi Wang, Lili Zhang, Xiuyang Zou, Jingzhou Yin, Edison Huixiang AngA machine-learning-designed cerium-iron MOF layer enhances Zn anode stability, achieving over 4300 hours at 1 mA cm−2 and 99.8% coulombic efficiency over 1400 cycles at 2 mA cm−2, providing a cost-effective protective strategy.To cite this article before page numbers are assigned, use the DOI form of citation above.The content of this RSS Feed (c) The Royal Society of Chemistry
Energy Environ. Sci., 2025, Advance Article
DOI: 10.1039/D5EE00650C, Paper
DOI: 10.1039/D5EE00650C, Paper
Open Access
This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.Jianbo Dong, Guolang Zhou, Wenhao Ding, Jiayi Ji, Qing Wang, Tianshi Wang, Lili Zhang, Xiuyang Zou, Jingzhou Yin, Edison Huixiang Ang
A machine-learning-designed cerium-iron MOF layer enhances Zn anode stability, achieving over 4300 hours at 1 mA cm−2 and 99.8% coulombic efficiency over 1400 cycles at 2 mA cm−2, providing a cost-effective protective strategy.
To cite this article before page numbers are assigned, use the DOI form of citation above.
The content of this RSS Feed (c) The Royal Society of Chemistry
A machine-learning-designed cerium-iron MOF layer enhances Zn anode stability, achieving over 4300 hours at 1 mA cm−2 and 99.8% coulombic efficiency over 1400 cycles at 2 mA cm−2, providing a cost-effective protective strategy.
To cite this article before page numbers are assigned, use the DOI form of citation above.
The content of this RSS Feed (c) The Royal Society of Chemistry
