Early Warning of Battery Thermal Runaway Enabled by Ag-Decorated SnO₂ and Machine Learning: Diethyl Carbonate Recognition.

已完结 10 由蟹黄发布于 2026/6/10 16:44:26

DOI:10.1002/smtd.70764
作者：Hu Ma,?Yan Liu,?Jiuyu Li,?Zhenyang Zhang,?Bailing Li,?Changwei Jia,?Zhangqi Chai,?Ruihua Zhao,?Jianping Du
文献类型：期刊论文
补充材料：只需要正文
文献链接：https://doi.org/10.1002/smtd.70764

Wiley

Abstract：The safe utilization of lithium-ion batteries depends on the management of thermal runaway to avoid electrolyte leakage. It is crucial to make early warning by developing sensors for rapid d

应助信息

9小时前

蟹黄

202606101644385495703.pdf 已采纳

9小时前

Book学术机器人

2026/6/10 16:44:26 未找到该文献，机器人已退出，请等待人工下载

2026/6/10 16:44:26 Book学术AI机器人收到请求，开始寻找文献

2026/6/10 16:44:26 已向机器人发送请求

9小时前

蟹黄发布求助

上一个求助:其它数据库Naturally Fractured Carbonate Reservoir Characterization: A Case Study of a Mature High-Pour Point Oil Field in Hungary 下一个求助:Institute of Electrical and Electronics Engineers (IEEE)Challenging Steam: Early Electric Railways [Historical]

Early Warning of Battery Thermal Runaway Enabled by Ag-Decorated SnO2 and Machine Learning: Diethyl Carbonate Recognition.

Early Warning of Battery Thermal Runaway Enabled by Ag-Decorated SnO₂ and Machine Learning: Diethyl Carbonate Recognition.