Effect of reduction pretreatment on the structure and catalytic performance of Ir-In2O3 catalysts for CO2 hydrogenation to methanol

催化作用 甲醇 解吸 吸附 X射线光电子能谱 化学 氧气 红外光谱学 产量(工程) 拉曼光谱 甲醛 无机化学 材料科学 化学工程 物理化学 有机化学 冶金 光学 工程类 物理
作者
Changyu Ding,Feifei Yang,Xue Ye,Chongya Yang,Xiaoyan Liu,Yuanlong Tan,Zheng Shen,Hongmin Duan,Xiong Su,Yanqiang Huang
出处
期刊:Journal of Environmental Sciences-china [Elsevier BV]
卷期号:140: 2-11 被引量:5
标识
DOI:10.1016/j.jes.2023.01.018
摘要

In2O3 has been found a promising application in CO2 hydrogenation to methanol, which is beneficial to the utilization of CO2. The oxygen vacancy (Ov) site is identified as the catalytic active center of this reaction. However, there remains a great challenge to understand the relations between the state of oxygen species in In2O3 and the catalytic performance for CO2 hydrogenation to methanol. In the present work, we compare the properties of multiple In2O3 and Ir-promoted In2O3 (Ir-In2O3) catalysts with different Ir loadings and after being pretreated under different reduction temperatures. The CO2 conversion rate of Ir-In2O3 is more promoted than that of pure In2O3. With only a small amount of Ir loading, the highly dispersed Ir species on In2O3 increase the concentration of Ov sites and enhance the activity. By finely tuning the catalyst structure, Ir-In2O3 with an Ir loading of 0.16 wt.% and pre-reduction treatment under 300°C exhibits the highest methanol yield of 146 mgCH3OH/(gcat·h). Characterizations of Raman, electron paramagnetic resonance, X-ray photoelectron spectroscopy, CO2-temperature programmed desorption and CO2-pulse adsorption for the catalysts confirm that more Ov sites can be generated under higher reduction temperature, which will induce a facile CO2 adsorption and desorption cycle. Higher performance for methanol production requires an adequate dynamic balance among the surface oxygen atoms and vacancies, which guides us to find more suitable conditions for catalyst pretreatment and reaction.
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
杨杨得亿发布了新的文献求助10
1秒前
本色小杆子完成签到 ,获得积分10
1秒前
Tommy完成签到,获得积分10
2秒前
CQMZY_2025完成签到,获得积分10
2秒前
科研通AI6.3应助LBJBowen23采纳,获得10
3秒前
花開完成签到,获得积分10
4秒前
郭自同完成签到,获得积分10
4秒前
4秒前
贪玩哈密瓜关注了科研通微信公众号
5秒前
独特鸽子完成签到 ,获得积分10
5秒前
花開发布了新的文献求助10
6秒前
薯片完成签到,获得积分10
7秒前
赘婿应助复杂曼梅采纳,获得10
7秒前
zcx发布了新的文献求助10
10秒前
杨杨得亿完成签到,获得积分10
11秒前
顾矜应助uj采纳,获得10
12秒前
12秒前
上上签发布了新的文献求助10
13秒前
发发发应助王欣茹采纳,获得30
14秒前
du完成签到 ,获得积分10
14秒前
蓝天发布了新的文献求助30
15秒前
16秒前
三岁完成签到 ,获得积分10
19秒前
21秒前
扶光完成签到,获得积分10
22秒前
22秒前
22秒前
23秒前
逆天的矿泉水完成签到,获得积分10
23秒前
24秒前
今后应助zcx采纳,获得10
24秒前
25秒前
25秒前
36hours完成签到,获得积分10
26秒前
27秒前
px发布了新的文献求助10
27秒前
笑一下蒜了完成签到,获得积分10
29秒前
29秒前
搜集达人应助过时的访梦采纳,获得10
29秒前
alexisgood发布了新的文献求助10
30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
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
Yangtze Reminiscences. Some Notes And Recollections Of Service With The China Navigation Company Ltd., 1925-1939 500
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 6356344
求助须知:如何正确求助?哪些是违规求助? 8171234
关于积分的说明 17203500
捐赠科研通 5412276
什么是DOI,文献DOI怎么找? 2864564
邀请新用户注册赠送积分活动 1842098
关于科研通互助平台的介绍 1690360