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中子成像在观察锂电池内部各种物质状态中的应用。

Application of neutron imaging in observing various states of matter inside lithium batteries.

作者信息

Gao Lei, Han Songbai, Ni Haijin, Zhu Jinlong, Wang Liping, Gao Song, Wang Yonggang, Huang Dubin, Zhao Yusheng, Zou Ruqiang

机构信息

School of Materials Science and Engineering, Peking University, Beijing 100871, China.

Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen 518055, China.

出版信息

Natl Sci Rev. 2023 Sep 15;10(11):nwad238. doi: 10.1093/nsr/nwad238. eCollection 2023 Nov.

Abstract

Lithium batteries have been essential technologies and become an integral part of our daily lives, powering a range of devices from phones to electric vehicles. To fully understand and optimize the performance of lithium batteries, it is necessary to investigate their internal states and processes through various characterization methods. Neutron imaging has been an indispensable complementary characterization technique to X-ray imaging or electron microscopy because of the unique interaction principle between neutrons and matter. It provides particular insights into the various states of matter inside lithium batteries, including the Li concentration in solid electrodes, the Li plating/stripping behavior of Li-metal anodes, the Li diffusion in solid ionic conductors, the distribution of liquid electrolytes and the generation of gases. This review aims to highlight the capabilities and advantages of neutron imaging in characterizing lithium batteries, as well as its current state of application in this field. Additionally, we discuss the potential of neutron imaging to contribute to the ongoing development of advanced batteries through its ability to visualize internal evolution.

摘要

锂电池已成为关键技术,并成为我们日常生活中不可或缺的一部分,为从手机到电动汽车等一系列设备提供动力。为了全面了解并优化锂电池的性能,有必要通过各种表征方法来研究其内部状态和过程。由于中子与物质之间独特的相互作用原理,中子成像一直是X射线成像或电子显微镜不可或缺的补充表征技术。它能特别深入地了解锂电池内部物质的各种状态,包括固体电极中的锂浓度、锂金属负极的锂电镀/脱镀行为、锂在固体离子导体中的扩散、液体电解质的分布以及气体的产生。本综述旨在突出中子成像在表征锂电池方面的能力和优势,以及其在该领域的当前应用状况。此外,我们还讨论了中子成像通过可视化内部演变促进先进电池持续发展的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26b5/10581545/d2e083502af8/nwad238fig1.jpg

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