High‐Content Analysis of Energy Materials Using Facile and Versatile Cross‐Sectional Preparation

Optimizing the internal morphology of cathode materials is essential for enhancing lithium‐ion battery performance by improving ion diffusion, electrical conductivity, and structural stability. This study introduces a novel high‐content analysis approach to optimize cathode materials for lithium‐ion batteries, focusing on internal morphology's role in performance. By combining resin‐embedding cross‐sectional preparation with high‐throughput imaging, this method enables efficient, large‐scale analysis of particle morphology, overcoming limitations in the representativeness of the observational domain. This approach allows for the rapid extraction of key features like pore size, 2D porosity, and particle uniformity, providing statistically robust insights into how synthesis conditions affect material properties. The versatility of the advanced approach for multimodal analysis, such as X‐ray diffraction, atomic force microscopy, and energy‐dispersive X‐ray spectroscopy, highlights its potential for broad applications. This work demonstrates a significant advance in the systematic characterization and optimization of energy materials, offering a pathway for improving battery performance through tailored material design.