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用于电池动力学原位成像的磁显微镜

Magnetic microscopy for operando imaging of battery dynamics.

作者信息

Pollok Stefan, Khoshkalam Mohamad, Ghaffari-Tabrizi Fardin, Kurnia Fran, Wang Danni, Li Siqi, Bucher Dominik B, Rupp Jennifer L M, Christensen Dennis V

机构信息

Department of Energy Conversion and Storage, Technical University of Denmark, Kongens Lyngby, Denmark.

Department of Chemistry, School of Natural Sciences, Technical University of Munich, Garching, Germany.

出版信息

Nat Commun. 2025 Sep 17;16(1):8303. doi: 10.1038/s41467-025-63409-y.

DOI:10.1038/s41467-025-63409-y
PMID:40962807
Abstract

Battery development pivots around understanding the complex processes governing battery operation and degradation. Most degradation pathways link structural and chemical inhomogeneities with strongly heterogeneous carrier transport at the nano- and microscale, which remains challenging to resolve with current operando imaging techniques. Here, we provide a data-driven perspective on using operando magnetic microscopy to examine the charge and discharge cycles in lithium and post-lithium batteries. Through quantitatively imaging ionic and electronic current distributions and probing the associated chemical reactions at the nanoscale, valuable insights into battery inhomogeneities and degradations can be gained. The approach facilitates spatially resolving heterogeneous redox reactions, buried current distributions, and mechanistic contributions to short-circuit endurance in batteries.

摘要

电池的发展围绕着理解控制电池运行和退化的复杂过程展开。大多数退化途径将结构和化学不均匀性与纳米和微观尺度上强烈的非均匀载流子传输联系起来,而利用当前的原位成像技术解决这一问题仍具有挑战性。在此,我们从数据驱动的角度提供了关于使用原位磁显微镜来研究锂及锂后电池的充电和放电循环的观点。通过在纳米尺度上对离子和电子电流分布进行定量成像并探测相关的化学反应,可以获得有关电池不均匀性和退化的有价值见解。该方法有助于在空间上解析电池中的非均匀氧化还原反应、埋藏的电流分布以及对短路耐久性的机理贡献。

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Sensing spin wave excitations by spin defects in few-layer-thick hexagonal boron nitride.通过几层厚的六方氮化硼中的自旋缺陷感知自旋波激发。
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The new car batteries that could power the electric vehicle revolution.能够推动电动汽车革命的新型汽车电池。
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Chemo-mechanical failure mechanisms of the silicon anode in solid-state batteries.固态电池中硅负极的化学-机械失效机制
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Quantum Logic Enhanced Sensing in Solid-State Spin Ensembles.固态自旋系综中的量子逻辑增强传感
Phys Rev Lett. 2023 Sep 8;131(10):100801. doi: 10.1103/PhysRevLett.131.100801.
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Learning heterogeneous reaction kinetics from X-ray videos pixel by pixel.逐像素学习 X 射线视频中的多相反应动力学。
Nature. 2023 Sep;621(7978):289-294. doi: 10.1038/s41586-023-06393-x. Epub 2023 Sep 13.
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