Enhanced reversible capacity and cycling stability of Li<sub>1.2</sub>Ni<sub>0.13</sub>Fe<sub>0.13</sub>Mn<sub>0.54</sub>O<sub>2</sub> via Mo-doped induced low Li/Ni site disorder

Chinese Physics(2024)

引用 0|浏览4
暂无评分
摘要
Li-ion batteries (LIBs) are widely used in mobile devices and electric vehicles, but the traditional layered transition metal cathode material, LiTMO2(TM=Ni, Co, Mn, or Al), has a low energy density that cannot satisfy the demand of commercial applications. The Li-rich Mn-based layered oxides (LRLOs) are a strong competitor to the traditional layered cathode materials for their specific capacity of more than 200 mAh/g. Due to the high energy density and low cost, Li-rich Mn-based layered oxides (LRLO) have been a promising candidate cathode for next-generation Li-ion batteries. The anionic redox reaction (ARR) in LRLO destabilizes the lattice oxygen, leading to voltage degradation and capacity loss. Although iron-substituted cobalt-free Li-rich materials can achieve less voltage decay, they suffer severe cation disorder and poor kinetics. Here, we develop a simple and feasible high-valent ion doping strategy by doping Mo into Li1.2Ni0.13Fe0.13Mn0.54O2(LNFMO), which expands the Li layer spacing and provides a broader channel for Li+ transport, thereby improving the diffusion kinetics of Li+, effectively suppressing the cation disorder, and further stabilizing the layered structure. As a result, the Mo-doped LRLO exhibits significantly enhanced electrochemical performance, with an initial reversible capacity of 209.48 mAh/g at 0.2 C, and the initial specific capacity increasing from 137.02 mAh/g to 165.15 mAh/g at 1 C. After 300 cycles, specific capacity remains 117.49 mAh/g for the Mo-doped cathode, and the voltage decay decreases from 2.09 mV/cycle to 1.66 mV/cycle. The Mo-doped LRLO is systematically characterized, and the mechanism of cycle stabilization is revealed, which provides an important reference for designing high performance Li-rich cathode.
更多
查看译文
关键词
low cycling,reversible capacity,cycling stability,mo-doped
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要