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DOI 10.3791/70455

Медицинская библиотека · Journal of visualized experiments : JoVE · 2026

Cryogenic Scanning Electron Nanobeam Diffraction Workflows for Structural Characterization of Beam-Sensitive Battery Interfaces.

Koh Hyeongjun, Stach Eric A

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Observation of battery interfaces is critical, as they govern electron and ion transport and influence electrochemical processes in energy storage. Despite this importance, they are challenging to characterize due to their nanometer-scale thickness and extreme sensitivity to electron beam damage. This paper presents a dose-controlled cryogenic scanning electron nanobeam diffraction (cryo-SEND) protocol that enables structural analysis of beam-sensitive battery interfaces while preserving their native state. The central advance of this workflow is the integration of ice-free cryogenic handling with diffraction-based analysis that decouples structural sensitivity from high-dose image formation. The workflow begins with air-free sample preparation inside an inert-atmosphere glovebox, followed by cryogenic focused ion beam/scanning electron microscopy (cryo-FIB/SEM) milling to produce electron-transparent lamellae. We describe optimized cryogenic transfer procedures from the FIB to the transmission electron microscope, emphasizing the use of a cryo-shuttle equipped with a protective lid to suppress ice contamination during transport. Within the TEM, SEND is performed at cryogenic temperatures to probe interfacial structures at vitrified electrolyte-lithium metal interfaces. SEND enables crystallographic and structural analysis while significantly reducing total accumulated electron dose compared to conventional imaging. Overall, this protocol provides an approach for studying battery interfaces and is broadly applicable to cryogenic electron microscopy investigations of beam-sensitive materials.

Для цитирования: Koh Hyeongjun, Stach Eric A. Cryogenic Scanning Electron Nanobeam Diffraction Workflows for Structural Characterization of Beam-Sensitive Battery Interfaces.. Journal of visualized experiments : JoVE. 2026. DOI: 10.3791/70455.

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