The growing demand for lithium-ion batteries requires improved performance and productivity. The formation of electronic conduction paths by carbon nanotubes (CNTs) is an important factor influencing electrode performance. However, only a few methods have been reported to allow direct and quantitative evaluation of CNT dispersion. Conventional ion milling for cross-sectional preparation exposes only CNTs in the interstices of active materials, limiting accurate assessment. In this study, we applied a fracturing method to prepare electrode cross sections, thereby exposing more CNTs in the observation area and enabling clear visualization of CNT networks. Furthermore, low-accelerating-voltage SEM enhanced the contrast between binders and CNTs, facilitating their separation and enabling quantitative evaluation of CNT linear density when combined with machine-learning-based image analysis. This study demonstrates a direct and quantitative method for assessing CNT distribution in lithium-ion battery electrodes.
Akimoto et al. (Fri,) studied this question.