Automated ultra-high-resolution SEM imaging enables fast, quantitative insights into particle size, shape, and surface morphology — all critical to optimizing lithium-ion battery manufacturing.
In lithium-ion battery manufacturing, the size and morphology of active powder particles significantly impact the electrode's packing density, electrical conductivity, and electrochemical performance. Even small variations in size can influence calendering, coating uniformity, and overall battery stability.
This app note demonstrates how Tescan CLARA UHR SEM, combined with automated Essence™ Image Snapper software, provides fast, reliable particle size analysis in Ni-based battery powders. With high-resolution SEM imaging and automated image analysis, researchers can optimize the trade-off between energy performance and long-term battery stability — accelerating quality assurance and design cycles.
Tescan CLARA provides high-resolution imaging without magnetic interference, making it ideal for sensitive battery materials. Its automated workflows and contrast flexibility allow precise analysis of powder morphology, particle distribution, and surface texture.
Tescan Essence™ simplifies complex SEM workflows with its intuitive interface and automation modules. In this application, Essence™ Image Snapper was used to acquire aligned, contrast-optimized SEM images from multiple regions of interest in a fully automated process — without requiring operator input.
Measure electrode porosity, pore connectivity, and accessibility in 3D using high-volume FIB-SEM tomography.
Tescan CLARA delivers non-destructive, nanometer-scale insights into separator porosity — enhancing safety and quality control in lithium-ion battery production.
Non-destructive micro-CT imaging uncovers structural voids and packing uniformity — key factors for optimizing battery performance and electrolyte flow.
High-resolution X-ray tomography uncovers subtle but critical anode overhang variations — helping battery developers align performance with safety standards.
X-ray microtomography provides a non-destructive view into internal cell architecture — supporting performance validation, design optimization, and safety-critical QA.
