As the demand for high-performance batteries accelerates, so does the pace of innovation from researchers and engineers. The ability to analyze battery materials across multiple scales—from macro to nano—is essential to understanding performance, failure mechanisms, and opportunities for optimization. Scanning Electron Microscopy (SEM) has emerged as a pivotal tool for this purpose, offering unparalleled insights into the structural and chemical properties of battery materials. This blog explores how SEM and related techniques can revolutionize battery research, drawing on a detailed case study of lithium intercalation in silicon particles from solid state battery systems.
Why SEM Matters in Battery Research
SEM enables high-resolution imaging and compositional analysis of materials, making it invaluable for battery research. Its versatility spans a range of applications, including:
- Electrode Morphology Analysis: Understanding the structure of active materials and binders.
- Failure Mechanism Investigation: Identifying cracks, voids, and dendrite formation.
- Chemical State Mapping: Examining the distribution of key elements and insights into their bonding states within a sample.
By coupling SEM with advanced detectors and preparation workflows, researchers can address critical challenges in battery development, such as energy density, cycle life, and safety.
Advanced Sample Preparation: The Role of Cross-Section Polishers
Proper sample preparation is a cornerstone of reliable SEM analysis. For battery materials, maintaining the integrity of sensitive components like lithium and the electrolyte is crucial. Cross-section polishers (CPs) are particularly effective for this purpose. CPs use an argon ion beam to create clean, artifact-free cross-sections, preserving the microstructure for accurate imaging and analysis.
For air-sensitive materials, maintaining the pristine state of these samples is equally critical. Specialized air-isolation workflows allow for seamless transfer from glove box to CPs to the SEM chamber, ensuring that reactive materials remain unaltered.
Key SEM Detectors for Battery Analysis
Imaging and X-ray detectors play a pivotal role in SEM-based battery research:
- Backscatter Electron (BSE) Detectors:
- BSE detectors provide contrast based on atomic number, highlighting compositional variations within the sample.
- BSE detectors provide contrast based on atomic number, highlighting compositional variations within the sample.
- Energy-Dispersive X-ray Spectroscopy (EDS)
- EDS maps elemental composition, offering a detailed view of how elements are distributed across electrode materials. Advanced Windowless EDS detectors like JEOL’s Gather-X are particularly useful in identifying lithium distribution in electrodes when in the right chemical state.
- EDS maps elemental composition, offering a detailed view of how elements are distributed across electrode materials. Advanced Windowless EDS detectors like JEOL’s Gather-X are particularly useful in identifying lithium distribution in electrodes when in the right chemical state.
- Soft X-ray Emission Spectrometer (SXES):
- Detects low energy X-rays in the soft X-ray region with ultra-high spatial resolution and sensitivity. This detector provides not only elemental information but also insight into chemical bonding states. SXES has proven itself invaluable in the study of Li intercalation in solid state battery systems.
Case Study: Lithium Intercalation in Silicon Particles
Experiment Overview
A critical aspect of battery performance is how lithium intercalates into active materials. In this case study, SEM, EDS, and SXES were used to analyze silicon particles in-situ, during charging and discharging cycles. Silicon’s high theoretical capacity makes it an attractive candidate for next-generation anodes, but its large volume changes during lithiation pose significant challenges.
Observations at Various Charge States
- Initial State (0% Charge):
- At the outset, BSE imaging revealed uniform contrast across the silicon particles, indicating minimal lithium presence. EDS and SXES confirmed the absence of lithium peaks in the spectrum.
- At the outset, BSE imaging revealed uniform contrast across the silicon particles, indicating minimal lithium presence. EDS and SXES confirmed the absence of lithium peaks in the spectrum.
- 10% Charge:
- Lithium began to intercalate, as evidenced by a slight increase in lithium signal intensity in the EDS maps and SXES spectrum. Changes in the BSE image contrast corroborated this observation.
- Lithium began to intercalate, as evidenced by a slight increase in lithium signal intensity in the EDS maps and SXES spectrum. Changes in the BSE image contrast corroborated this observation.
- 20% Charge:
- The lithium peak intensity grew more pronounced, and subtle shifts in the silicon peak shape in the SXES spectrum suggested the onset of alloying.
- The lithium peak intensity grew more pronounced, and subtle shifts in the silicon peak shape in the SXES spectrum suggested the onset of alloying.
- 40% Charge:
- A dramatic increase in lithium concentration was observed. The lithium peak shifted further, indicating significant alloying with silicon. BSE images and EDS maps highlighted the spatial distribution of lithium within the particles.
- A dramatic increase in lithium concentration was observed. The lithium peak shifted further, indicating significant alloying with silicon. BSE images and EDS maps highlighted the spatial distribution of lithium within the particles.
- Fully Discharged State:
- Even after full discharge, residual lithium was detected in the silicon particles. The peak shape changes in the SXES spectrum suggested a transition from crystalline to amorphous silicon, highlighting structural changes induced by cycling.
Key Insights
- Intercalation Dynamics: Lithium intercalates more readily in silicon particles near the electrolyte interface, emphasizing the importance of optimizing particle contact.
- Residual Lithium: The presence of lithium post-discharge points to inefficiencies in the cycling process, which could impact capacity retention.
- Structural Changes: The shift from crystalline to amorphous silicon highlights the need for materials engineering to mitigate volume changes and enhance cycle life.
For a concise demonstration of the workflow showing lithium-ion movement, click here.
Beyond SEM: Integrating Complementary Techniques
While SEM provides valuable structural and compositional data, integrating it with complementary techniques enhances the depth of analysis:
- Soft X-ray Emission Spectroscopy (SXES): Offers insights into the chemical state of elements, providing additional context for alloying and phase transitions.
- Focused Ion Beam (FIB): Enables site-specific sample preparation and 3D tomography for more detailed analysis.
Implications for Battery Research
The insights gained from SEM analysis can inform multiple aspects of battery development:
- Material Design: Optimizing particle size, morphology, and coatings to enhance performance.
- Manufacturing Processes: Improving electrode fabrication to ensure uniformity and minimize defects.
- Diagnostics: Developing strategies to mitigate degradation and extend cycle life.
Conclusion
SEM’s ability to analyze battery materials from the macro to the nanoscale makes it an indispensable tool in the quest for better batteries. By leveraging advanced detectors, preparation workflows, and complementary techniques, researchers can uncover critical insights that drive innovation. As this case study demonstrates, understanding lithium intercalation dynamics is just one of many ways SEM contributes to the advancement of energy storage technology.
To learn more, check out this program on YouTube: How To Look Inside Your LIB with SEM
Insights written by Donna Gosselin, SEM Product Manager @ JEOL USA and Nella Chapell, Product Marketing Specialist at JEOL USA.
This work highlights the collaborative efforts of academic and industry researchers. Special thanks to Professor Matsuda at Toyohashi University of Technology for providing the silicon anode and to the dedicated teams at Toyohashi University of Technology, JEOL in Japan and the USA who collaborated and conducted the experiments.
