Co基尖晶石纳米片整体式催化剂用于催化消除VOCs的研究

肖婕妤, 白文才, 杨幸川, 于毅, 徐丽, 刘国际, 曹春梅

现代化工 ›› 2023, Vol. 43 ›› Issue (12) : 74 -82.

PDF (8428KB)
现代化工 ›› 2023, Vol. 43 ›› Issue (12) : 74-82. DOI: 10.16606/j.cnki.issn0253-4320.2023.12.016
科研与开发

Co基尖晶石纳米片整体式催化剂用于催化消除VOCs的研究

    肖婕妤, 白文才, 杨幸川, 于毅, 徐丽, 刘国际, 曹春梅
作者信息 +

Co-based spinel nanosheet monolithic catalysts for catalytic elimination of VOCs

Author information +
文章历史 +
PDF (8630K)

摘要

用不同的过渡金属(Mn、Ni和Fe)取代Co3O4中A位Co合成MCo2O4纳米片整体式催化剂(MCo-NS),并以甲苯为单芳烃模型测试深度氧化挥发性有机化合物(VOCs)性能。氢气程序升温还原(H2-TPR)、X射线光电子能谱学(XPS)分析及性能测试结果表明,Mn和Ni取代Co3O4中的A位Co,不仅有助于提高催化剂的氧化还原能力,而且有利于表面氧空位的生成和表面吸附氧的活化,从而表现出比参考催化剂Co-NS更高的催化甲苯氧化性能。其中,MnCo2O4纳米片催化剂因具有较高的氧化还原能力及丰富的表面吸附氧物种而展示出最高的催化甲苯氧化活性,其T90为254℃,优于NiCo-NS和FeCo-NS;同时,MnCo2O4纳米片催化剂具有良好的稳定性。

Abstract

Different transition metals (Mn3+, Ni3+and Fe3+) are used to replace Co at A position in Co3O4 to synthesize MCo2O4 nanosheet monolithic catalyst (MCo-NS), and their performance in deeply oxidizing volatile organic compounds (VOCs) is evaluated through using toluene as a model.Through hydrogen temperature-programmed reduction (H2-TPR), X-ray photoelectron spectroscopy (XPS) and performance tests, it is shown that the substitution of Mn and Ni for Co at the position A in Co3O4 is helpful to improve the redox ability of the catalyst, and also conducive to the generation of surface oxygen vacancies and the activation of surface adsorbed oxygen, thus contributing to the catalyst with a higher catalytic performance for toluene oxidation than Co-NS, the reference catalyst.Among them, MnCo2O4 nano sheet catalyst shows the highest catalytic activity for toluene oxidation due to its high redox ability and rich surface adsorbed oxygen species.Its T90 is 254℃, superior to that of NiCo-NS and FeCo-NS.Meanwhile, MnCo2O4 nanosheet catalyst presents good stability.

关键词

钴基尖晶石 / 催化消除 / VOCs / 纳米片

Key words

Co-based spinel / catalytic elimination / VOCs / nanosheets

Author summay

肖婕妤(1998-),女,硕士生,研究方向为环境催化,202012232014491@gs.zzu.edu.cn。

引用本文

引用格式 ▾
Co基尖晶石纳米片整体式催化剂用于催化消除VOCs的研究[J]. , 2023, 43(12): 74-82 DOI:10.16606/j.cnki.issn0253-4320.2023.12.016

登录浏览全文

4963

注册一个新账户 忘记密码

参考文献

AI Summary AI Mindmap
PDF (8428KB)

193

访问

0

被引

导航
相关文章

AI思维导图

/