材料科学
阳极
锂(药物)
同轴
纳米-
复合材料
离子
锂离子电池
电极
电池(电)
机械工程
医学
功率(物理)
化学
物理
物理化学
量子力学
工程类
内分泌学
作者
Jiao Jiao Li,Haoran Liang,Shichao Li,Jie Sun,Yifan Zhang,Shuxing Mei,Shasha Wang,Yong Zheng
出处
期刊:Rare Metals
[Springer Science+Business Media]
日期:2025-08-03
卷期号:44 (10): 7118-7135
被引量:8
标识
DOI:10.1007/s12598-025-03437-1
摘要
Abstract Tin dioxide (SnO 2 ) with a high theoretical specific capacity of 1494 mAh g –1 is a promising candidate anode material for lithium storage. However, the shortcomings of serious volume expansion and low conductivity limit its wide application. Herein, coaxial nano‐multilayered C/SnO 2 /TiO 2 composites were fabricated via layer‐by‐layer self‐assembly of TiO 2 and SnO 2 ‐gel layers on the natural cellulose filter paper, followed by thermal treatment under a nitrogen atmosphere. Through engineering design of the assembly process, the optimal C/SnO 2 /TiO 2 composite features five alternating SnO 2 and TiO 2 nanolayers, with TiO 2 as the outside shell (denoted as C/TSTST). This unique structure endows the C/TSTST with excellent structural stability and electrochemical kinetics, making it a high‐performance anode for lithium‐ion batteries (LIBs). The C/TSTST composite delivers a high reversible capacity of 676 mAh g −1 at 0.1 A g −1 after 200 cycles and retains a capacity of 504 mAh g −1 at 1.0 A g −1 , which can be recovered to 781 mAh g −1 at 0.1 A g −1 . The significantly enhanced electrochemical performance is attributed to the hierarchical hybrid structure, where the carbon core combined with coaxial TiO 2 nanolayers serves as a structural scaffold, ameliorating volume change of SnO 2 while creating abundant interfacial defects for enhanced lithium storage and rapid charge transport. These findings are further demonstrated by the density functional theory (DFT) calculations. This work provides an efficient strategy for designing coaxial nano‐multilayered transition metal oxide‐related electrode materials, offering new insights into high‐performance LIBs anodes.
科研通智能强力驱动
Strongly Powered by AbleSci AI