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A single dual-mode gas sensor for early safety warning of Li-ion batteries:Micro-scale Li dendrite and electrolyte leakage
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作者 闫文君 金志燊 +4 位作者 林政扬 周诗瑜 杜永海 陈宇龙 周后盘 《Chinese Physics B》 SCIE EI CAS CSCD 2022年第11期291-296,共6页
Li dendrites and electrolyte leakage are common causes of Li-ion battery failure.H_(2),generated by Li dendrites,and electrolyte vapors have been regarded as gas markers of the early safety warning of Li-ion batteries... Li dendrites and electrolyte leakage are common causes of Li-ion battery failure.H_(2),generated by Li dendrites,and electrolyte vapors have been regarded as gas markers of the early safety warning of Li-ion batteries.SnO_(2)-based gas sensors,widely used for a variety of applications,are promising for the early safety detection of Li-ion batteries,which are necessary and urgently required for the development of Li-ion battery systems.However,the traditional SnO_(2)sensor,with a single signal,cannot demonstrate intelligent multi-gas recognition.Here,a single dual-mode(direct and alternating current modes)SnO_(2)sensor demonstrates clear discrimination of electrolyte vapors and H_(2),released in different states of Li-ion batteries,together with principal component analysis(PCA)analysis.This work provides insight into the intelligent technology of single gas sensors. 展开更多
关键词 gas sensors single dual-mode multivariable sensors Li-batteries early safety warning
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Disaster assessment for the“Belt and Road”region based on SDG landmarks
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作者 Li Wang Yuanhuizi He +7 位作者 Yuelin Zhang Lei Wang Huicong Jia Quan Zhou Bo Yu Meimei Zhang zhengyang lin Fang Chen 《Big Earth Data》 EI 2022年第1期3-17,共15页
In this study,based on the EM-DAT(The Emergency Events Database)database,disaster assessment for the“Belt and Road”region was carried out in relation to the SDG_(13.1.1)indicator of the Sustainable Development Goals... In this study,based on the EM-DAT(The Emergency Events Database)database,disaster assessment for the“Belt and Road”region was carried out in relation to the SDG_(13.1.1)indicator of the Sustainable Development Goals(SDGs)agenda launched in 2015.A new method for diagnosing trends in the SDG_(13.1.1)indicators based on the Theil-Sen median method is proposed.In addition,using the data available in the EM-DAT,an overview of disaster records is used to quantify disasters for a total of 73 countries.The disaster trends for the period 2015‒2019 were found to demon-strate the following.(1)As a result of geological and climate con-ditions,Asia and Africa are high-risk disaster areas and disasters have caused considerable economic losses and affected the popu-lations in developing and underdeveloped countries in these regions.(2)The clear positive value ofΔs_(13.1.1)found for China reflects the country’s encouraging achievements in disaster preven-tion and mitigation.(3)The value of SDG_(13.1.1)was observed to be increasing in South Asia,northwest Africa and South Africa,with the increase in India and Mauritania being the most serious.The new method proposed in this paper allows the real trend in the SDG_(13.1.1)indicator in various countries to be derived and provides critical intelligence support for international disaster risk reduction plans and sustainable development goals. 展开更多
关键词 EM-DAT database the Belt and Road region Sustainable Development Goals SDG13.1.1 indicator disaster risk reduction
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