Oxygen vacancy engineering for tuning the catalytic activity of LaCoO3 perovskite

钙钛矿(结构) 氧气 催化作用 无机化学 材料科学 热处理 空位缺陷 化学工程 化学 工程类 有机化学 结晶学 复合材料
作者
JeongHyun Cho,Min-Jae Kim,Inchan Yang,Kyung Tae Park,Chang Houn Rhee,Hai Woong Park,Ji Chul Jung
出处
期刊:Journal of Rare Earths [Elsevier BV]
卷期号:42 (3): 506-514 被引量:45
标识
DOI:10.1016/j.jre.2023.01.002
摘要

Herein, we attempted to engineer oxygen vacancies on the surface of LaCoO3 perovskite through simple post-treatments (acid or reductive thermal treatments). Acid treatment induces oxygen vacancies through the selective etching of the La cations, whereas thermal treatment in a reducing atmosphere generates oxygen vacancies by directly removing lattice oxygen. The characterization results confirm that the number of surface oxygen vacancies, which are crucial in various catalytic oxidation reactions, considerably increases in the LaCoO3 catalysts treated with acid or reducing gas. Acid treatment enriches the oxygen vacancies while maintaining the structure of the LaCoO3 catalysts, which can not be achieved through reductive thermal treatment. Therefore, the acid treatment is considered a promising technique for oxygen vacancy engineering of perovskite catalysts for tuning their catalytic activities. Furthermore, the catalytic activities of the posttreated LaCoO3 catalysts for CO oxidation were evaluated and are noted to be considerably better than those of the pristine LaCoO3 catalyst due to their abundant oxygen vacancies. Consequently, we conclude that the oxygen vacancies of perovskite catalysts can be effectively engineered via two simple methods and play a significant role in CO oxidation.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
1秒前
1秒前
1秒前
1秒前
1秒前
1秒前
星辰大海应助科研通管家采纳,获得10
1秒前
1秒前
xzy998应助科研通管家采纳,获得10
1秒前
1秒前
2秒前
勾真义完成签到,获得积分10
3秒前
草上飞发布了新的文献求助10
3秒前
蓝天发布了新的文献求助10
3秒前
WilliamYuan应助格子采纳,获得10
4秒前
6秒前
充电宝应助ZJM采纳,获得10
7秒前
夏天发布了新的文献求助10
7秒前
7秒前
8秒前
8秒前
科研通AI2S应助骆凤灵采纳,获得10
9秒前
充电宝应助tianxiao采纳,获得10
9秒前
MiSD完成签到,获得积分10
10秒前
10秒前
11秒前
zzcs33完成签到,获得积分10
12秒前
嘉心糖应助buddyM采纳,获得80
13秒前
共享精神应助楠楠DAYTOY采纳,获得10
13秒前
Audience发布了新的文献求助10
15秒前
wuxunxun2015发布了新的文献求助10
15秒前
Adelinelili发布了新的文献求助10
15秒前
17秒前
18秒前
19秒前
20秒前
zhaosheng发布了新的文献求助10
20秒前
21秒前
於傲松发布了新的文献求助10
22秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1000
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
信任代码:AI 时代的传播重构 450
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6357156
求助须知:如何正确求助?哪些是违规求助? 8171810
关于积分的说明 17205805
捐赠科研通 5412819
什么是DOI,文献DOI怎么找? 2864787
邀请新用户注册赠送积分活动 1842223
关于科研通互助平台的介绍 1690482