4.8 Article

Tunable Cationic Vacancies of Cobalt Oxides for Efficient Electrocatalysis in Li-O2Batteries

期刊

ADVANCED ENERGY MATERIALS
卷 10, 期 40, 页码 -

出版社

WILEY-V C H VERLAG GMBH
DOI: 10.1002/aenm.202001415

关键词

cationic vacancies; density functional theory; electrocatalysis; Li-O(2)batteries; spinel Co3O4

资金

  1. Taishan Scholars Program of Shandong Province [tsqn20161004]
  2. Program for Scientific Research Innovation Team of Young Scholar in Colleges and Universities of Shandong Province [2019KJC025]
  3. Young Scholars Program of Shandong University [2019WLJH21]

向作者/读者索取更多资源

Vacancy engineering is one of the most effective strategies to introduce defects for improving electrocatalytic activities of cobalt oxides. Recent intensive research has been conducted to introduce oxygen vacancies for boosting Li-O(2)battery performance. However, it is difficult to examine the efficiency of cationic vacancies due to their complicated preparation. Herein, a feasible method is demonstrated to introduce cationic vacancies into cobalt oxides via the thermal treatment of glycerolatocobalt (GlyCo) nanostructure. The formation of GlyCo composed of the repeating Co-O-Co-O units provides the possibility to regulate the ratio between cobalt and oxygen, thus cobalt vacancies in cobalt oxides can be easily created by the thermal treatment. The presence of cobalt vacancies enables the regulation of electronic structure and charge-transport properties of cobalt oxides with abundant defects on the basis of the experimental results and theoretical calculations, thus improving electrocatalytic activities. Therefore, the Li-O(2)battery delivers superior electrochemical performance with large specific capacities of 13 331/12 040 mAh g(-1), low overpotentials for the oxygen evolution reaction/oxygen reduction reaction of 1.15/0.23 V and good cycling stability. This work provides a favorable method to create metal vacancies for improving catalytic efficiency of advanced energy materials.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据