阳极
材料科学
电化学
阴极
纳米技术
兴奋剂
石墨
锂离子电池的纳米结构
锂(药物)
电极
光电子学
电气工程
复合材料
化学
工程类
医学
物理化学
内分泌学
出处
期刊:The Royal Society of Chemistry eBooks
[The Royal Society of Chemistry]
日期:2023-07-12
卷期号:: 454-467
标识
DOI:10.1039/bk9781839169366-00454
摘要
Lithium-ion batteries (LIBs) have a high energy and power density, making them attractive for electric vehicles (EVs) and portable electronic devices. In commercially available LIBs, graphite and transition metal oxides (LiCoO2) are used as anode and cathode materials, respectively. Unfortunately, graphite has a safety concern related to dendrite formation at low voltage and also has low rate-capability issues, restricting its high-power demand. Li4Ti5O12 (LTO) is considered an alternative anode and a good contender for LIBs due to its high reversibility and zero structural changes during the lithiation/(de)lithiation process. Its high operating voltage (∼1.55 V vs. Li+/Li) helps avoid dendritic formations, thereby ensuring safe cycling. Despite these advantages, LTO has low electronic conductivity, relatively low capability at high current rates due to large polarization, and sluggish Li-ion diffusion. The work provides a solution to overcome these drawbacks and improve the LTO performance at high currents by modifying the crystal and electronic structure and reducing particle size. To accomplish these goals, the structural characteristics and electrochemical behavior of LTO-based materials have been systematically and intensively discussed. In this chapter, three different ways of doping in LTO are discussed that are already been synthesized by a simple solid-state method, co-doped LTO electrode exhibits outstanding cycling stability, having higher capacity retention of ∼98.79% after 300 cycles at high currents. While considering the practical advantages, this study provides two more benefits: (1) it sheds light on the doping strategy; (2) it elucidates the relations among the material composition, structure, and electrochemical performances in LIBs.
科研通智能强力驱动
Strongly Powered by AbleSci AI