Correlative microscopy techniques have become indispensable in the analysis of battery materials, particularly for understanding their three-dimensional (3D) structure and composition at multiple length scales. Among these, the combination of scanning electron microscopy (SEM), focused ion beam (FIB), and transmission electron microscopy (TEM) enables comprehensive characterization, from bulk properties to atomic-scale details. This article outlines the methodologies and applications of these integrated approaches, focusing on FIB-SEM tomography, lamella preparation, and multi-modal data fusion for advanced battery material analysis.

FIB-SEM tomography is a powerful technique for reconstructing 3D microstructures of battery materials with nanoscale resolution. The process involves sequential milling of the sample surface using a focused ion beam, followed by SEM imaging of the freshly exposed cross-section. This cycle is repeated hundreds or thousands of times to generate a stack of 2D images, which are then reconstructed into a 3D volume. In battery research, this method is particularly useful for analyzing porous electrode architectures, solid-electrolyte interphase (SEI) layer formation, and lithium dendrite growth. For example, FIB-SEM tomography has been employed to quantify the tortuosity of lithium-ion battery electrodes, a critical parameter influencing ion transport and overall cell performance. The technique provides statistically representative data on pore connectivity, particle size distribution, and phase distribution, which are difficult to obtain through standalone SEM or TEM.

Lamella preparation via FIB is a crucial step for enabling high-resolution TEM analysis of battery materials. The process involves extracting a thin, electron-transparent section from a specific region of interest identified during SEM or FIB-SEM tomography. Precise site-specific sampling is essential for investigating localized phenomena such as grain boundaries, phase transformations, or chemical segregation in battery electrodes and electrolytes. Modern FIB systems equipped with gas injection systems (GIS) can deposit protective layers to minimize ion beam damage during milling, preserving the native structure of sensitive materials like lithium metal anodes or solid-state electrolytes. The prepared lamella can then be transferred to a TEM for atomic-scale imaging, diffraction, or spectroscopy, correlating the microstructural features observed in SEM with crystallographic and compositional data from TEM.

Multi-modal data fusion integrates information from SEM, FIB, and TEM to provide a holistic understanding of battery materials. For instance, energy-dispersive X-ray spectroscopy (EDS) in SEM can map elemental distribution across a large field of view, while electron energy loss spectroscopy (EELS) in TEM offers finer chemical details with higher energy resolution. Combining these datasets allows researchers to correlate bulk compositional trends with local chemical environments, such as transition metal oxidation states in cathode materials or lithium distribution in anode particles. Similarly, electron backscatter diffraction (EBSD) in SEM provides crystallographic orientation maps, which can be overlaid with TEM-based high-resolution strain analysis to understand mechanical degradation mechanisms in electrodes during cycling.

The workflow for correlative microscopy typically begins with non-destructive SEM imaging to identify regions of interest, followed by FIB-SEM tomography for 3D structural analysis. Selected sub-volumes are then extracted as lamellae for TEM investigation, ensuring that the same features are examined across multiple techniques. Advanced software tools enable the alignment and overlay of datasets from different instruments, accounting for differences in resolution, field of view, and dimensionality. This integrated approach is particularly valuable for studying degradation mechanisms in batteries, where phenomena like crack propagation, phase separation, or interfacial reactions span multiple length scales.

Practical considerations for successful correlative microscopy include minimizing sample preparation artifacts, optimizing beam parameters to reduce damage, and ensuring accurate spatial registration between datasets. For battery materials, which are often beam-sensitive or reactive, cryogenic sample preparation and transfer systems can preserve their native state during analysis. Additionally, low-voltage SEM imaging and gentle FIB milling conditions help maintain the integrity of delicate structures like SEI layers or polymer electrolytes.

The application of these techniques has led to significant insights in battery research. For example, correlative FIB-SEM and TEM studies have revealed the heterogeneous nature of lithium plating and stripping in anode materials, explaining the origins of capacity fade and short-circuiting. In cathode materials, the combination of EBSD and TEM has uncovered the role of crystallographic orientation in crack initiation during cycling. Similarly, 3D reconstructions from FIB-SEM tomography have provided quantitative metrics for electrode optimization, such as the relationship between porosity gradients and rate performance.

In summary, correlative microscopy combining SEM, FIB, and TEM offers a powerful toolkit for 3D analysis of battery materials. By bridging the gap between microstructural and atomic-scale characterization, these techniques enable a deeper understanding of structure-property relationships, guiding the design of next-generation energy storage systems. The integration of multi-modal data further enhances the value of these approaches, providing a comprehensive picture of complex phenomena in battery materials. As instrumentation and computational methods continue to advance, correlative microscopy will play an increasingly vital role in accelerating battery research and development.