氧化还原
催化作用
X射线光电子能谱
化学
氮氧化物
选择性催化还原
吸附
活化能
无机化学
物理化学
化学工程
有机化学
工程类
燃烧
作者
Fengyuan Liu,Junqi Li,Hong Yong Sohn,Chaoyi Chen,Jian Yang,Xudong Liu,Yuanpei Lan,Wei Zhang,Qin Wang,Li Liu
出处
期刊:Fuel
[Elsevier BV]
日期:2023-06-01
卷期号:350: 128806-128806
被引量:26
标识
DOI:10.1016/j.fuel.2023.128806
摘要
The objective of this work was to clearly elucidate the interactions on Mn-Ce interface and understand how they affect low temperature selective catalytic reduction (SCR) for NOx removal. In this work, three Mn-Ce catalysts in similar particle size and morphology with different Mn-Ce interface areas were prepared. MnO2@CeO2-F had the tightest and largest amount of Mn-Ce interfaces compared with MnO2@CeO2-P and MnO2-CeO2-M, and also exhibited the highest NO conversion degree at 100–150 °C as well as the strongest activity of Mn species and lowest generation of N2O. The TG-DTG, XPS and electrochemical impedance spectroscopy results proved the redox of Ce4+ + Mn3+ ↔ Ce3+ + Mn4+ on the Mn-Ce interface, and MnO2@CeO2-F had the highest Mn4+, Ce3+, Oα concentrations. The results of the study on the redox reactions during the NH3-SCR process provided powerful evidence of the Mn4+/Mn3+ and Ce3+/Ce4+ recycles that are important for low temperature NH3-SCR process. Moreover, the Mn-Ce interface was directly proved to benefit the surface acid sites, redox ability, and activity of the adsorbed intermediates. Both the Eley-Rideal (E-R) and Langmuir-Hinshelwood (L-H) reaction mechanisms were observed in the SCR reaction with prepared Mn-Ce materials, where "fast SCR" can be observed with MnO2@CeO2-F. Moreover, the Mn-Ce interface also lowers the activation energy of the low-temperature SCR process, with MnO2@CeO2-F having the lowest activation energy. The results from this work offered powerful evidences for the interactions of Mn/Ce redox at the Mn-Ce interface and elucidated clear understanding of the effects of Mn-Ce redox on low-temperature SCR process, which is expected to promote the NOx removal process.
科研通智能强力驱动
Strongly Powered by AbleSci AI