兴奋剂
电化学
价(化学)
分析化学(期刊)
化学
阴极
电解质
切断
锂(药物)
材料科学
物理化学
电极
光电子学
物理
医学
内分泌学
量子力学
有机化学
色谱法
作者
Minmin Chen,Enyue Zhao,Dongfeng Chen,Meimei Wu,Songbai Han,Q. Huang,Limei Yang,Xiaoling Xiao,Zhongbo Hu
出处
期刊:Inorganic Chemistry
[American Chemical Society]
日期:2017-06-26
卷期号:56 (14): 8355-8362
被引量:164
标识
DOI:10.1021/acs.inorgchem.7b01035
摘要
Decreasing Li/Ni disorder has been a challenging problem for layered oxide materials, where disorder seriously restricts their electrochemical performances for lithium-ion batteries (LIBs). Element doping is a great strategy that has been widely used to stabilize the structure of the cathode material of an LIB and improve its electrochemical performance. On the basis of the results of previous studies, we hypothesized that the element of Ca, which has a lower valence state and larger radius compared to Ni2+, would be an ideal doping element to decrease the Li/Ni disorder of LiMO2 materials and enhance their electrochemical performances. A Ni-rich LiNi0.8Mn0.1Co0.1O2 cathode material was selected as the bare material, which usually shows severe Li/Ni disorder and serious capacity attenuation at a high cutoff voltage. So, a series of Ca-doped LiNi0.8(1-x)Co0.1Mn0.1Ca0.8xO2 (x = 0-8%) samples were synthesized by a traditional solid-state method. As hypothesized, neutron diffraction showed that Ca-doped LiNi0.8Co0.1Mn0.1O2 possessed a lower degree of Li/Ni disorder, and potentiostatic intermittent titration results showed a faster diffusion coefficient of Li+ compared with that of LiNi0.8Mn0.1Co0.1O2. The Ca-doped LiNi0.8Mn0.1Co0.1O2 samples exhibited higher discharge capacities and better cycle stabilities and rate capabilities, especially under a high cutoff voltage with 4.5 V. In addition, the problems of polarization and voltage reduction of LiNi0.8Mn0.1Co0.1O2 were also alleviated by doping with Ca. More importantly, we infer that it is crucial to choose an appropriate doping element and our findings will help in the research of other layered oxide materials.
科研通智能强力驱动
Strongly Powered by AbleSci AI