材料科学
阴极
氟化物
金红石
化学工程
介孔材料
催化作用
镍
无机化学
物理化学
化学
有机化学
冶金
工程类
作者
Tao Wu,Yanhua Cui,Kaiyuan Wei,Chuanzhong Lai,Yu Zhao,Shuang Ni,Yongjin Chen,Xiang Gao,Yixiu Cui,Chilin Li
出处
期刊:Nano Energy
[Elsevier]
日期:2022-09-22
卷期号:103: 107843-107843
被引量:7
标识
DOI:10.1016/j.nanoen.2022.107843
摘要
Transition metal fluoride is being considered as one of the most promising cathode materials due to its feasibility of high-voltage conversion reaction and high theoretical capacity. But the low solubility of LiF in fluoride is prone to degrade the electrode conductivity and Li-resource supply from fluoride cathode side, therefore limiting the reversibility of conversion reaction and its practical use in Li-ion batteries. Here, we propose a catalysis effect of Ni nanodomains to activate the Li-F splitting with much lower dissociation energy and to enable the LiF/Fe/Ni ternary cathode with superior conversion reaction capacity (600 mAh g−1) and rate performance (306 mAh g−1 at 3.8 A g−1). The crowded effect between LiF and dual-metal phases suppresses the growth of crystal grains and promotes the enrichment and penetration of LiF-Fe-Ni triple-phase interfaces. This compact interface contact endows the lithiated fluoride with an ultrahigh initial charge capacity exceeding 600 mAh g−1 and lowered charge plateau below 3.5 V. The preservation of interconnectivity and catalytic activity of electron conductive network enables the high reversibility of LiF splitting/recombination under high energy efficiency of 76%, as well as the electrochemical synthesis of rutile-like NixFe1−xF2 solid-solution phase. This fluoride cathode enables a release of high energy density (1414 Wh kg−1) under a power density of 849 W kg−1 and the energy density can still be preserved at 629 Wh kg−1 under an extremely high power densities of 3374 W kg−1. This work paves the way to develop the high-energy-density fluoride cathodes with the prior delithiation ability, which can lessen and even eliminate the use of Li metal at anode side.
科研通智能强力驱动
Strongly Powered by AbleSci AI