Multiscale Imaging Techniques for Real‐Time, Noninvasive Diagnosis of Li‐Ion Battery Failures

电池(电) 可靠性(半导体) 计算机科学 可视化 材料科学 可靠性工程 纳米技术 人工智能 工程类 功率(物理) 量子力学 物理
作者
Mingyu Lee,Jiwon Lee,Yewon Shin,Hongkyung Lee
出处
期刊:Small science [Wiley]
卷期号:3 (11): 2300063-2300063 被引量:10
标识
DOI:10.1002/smsc.202300063
摘要

With the increasing popularity of battery-powered mobility, ensuring the safety and reliability of Li-ion batteries (LIBs) has become critical for manufacturers. Despite advanced manufacturing processes for large-scale Li-ion cells, "latent defects" still unintentionally appear, due to imbalanced battery design, invisible faults, and extreme operating conditions. These defects cause performance degradation and can even lead to battery fires. Hence, early detection of latent defects, along with understanding the influence of cell parameters and operating conditions on battery failure scenarios, is crucial. For straightforward investigations and interpretations, noninvasive and in operando battery imaging techniques and methods have been proposed using X-rays, neutrons, and ultrasound, as these can penetrate active and component materials and cell packaging. Moreover, magnetic-field-guided visualization of the current distribution pattern in cells under a current load has been proposed to identify invisible defects. This review thoroughly examines various imaging techniques for internal batteries, from the atomic and molecular levels in electrode materials and interfaces to macroscale battery systems. By assessing qualitative case studies and newly discovered phenomena, this review provides valuable insights into state-of-the-art noninvasive battery imaging and its potential to improve the safety and reliability of LIB technology.
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