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人工智能在锂离子电池研发中的应用
朱振威1, 邱景义1, 王莉2, 曹高萍1, 何向明2, 王京3, 张浩1,*()
Application of Artificial Intelligence to Lithium-Ion Battery Research and Development
Zhen-Wei Zhu1, Jing-Yi Qiu1, Li Wang2, Gao-Ping Cao1, Xiang-Ming He2, Jing Wang3, Hao Zhang1,*()

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Figure 11. Schematic exhibiting present (green) and future (orange) workflows about conducting experiment, data acquisition, interpretation, and model extraction/simulation[65]. The large and increasing amount of data generated using modern characterization techniques, new generation of detectors, and the emergence of AI/ML methods are likely to transform the way that experiments are performed and data analyzed. Figures reproduced with permission from ref 65. Copyright 2021 American Chemical Society. (color on line)