d-π Orbital Interaction Promoting NO<sub><i>x</i></sub> Selective Reduction on the Mn-Doped α-Fe<sub>2</sub>O<sub>3</sub>(001) Catalyst

Understanding the structure-activity relationship on a solid surface is crucial for developing an efficient low-temperature NH<sub>3</sub>-SCR catalyst. Herein, an in-depth investigation was conducted on a single-atom Mn-doped α-Fe<sub>2</sub>O<sub>3</sub> catalyst by combining experimental studies and density functional theory calculations. Mn doping not only facilitates N-H cleavage in the Eley-Rideal (E-R) pathway but also promotes the adsorption of NO and the cleavage of the N-O bond, lowering the energy barrier of the rate-determining step in the Langmuir-Hinshelwood (L-H) pathway. Thus, Mn doping facilitates the catalytic reaction along both potential pathways, which promotes the NH<sub>3</sub>-SCR reaction. Further analysis reveals that the doping of Mn introduces an unoccupied d<sub><i>xy</i></sub> orbital, which facilitates the interaction with the π orbital of NO, thereby augmenting NO adsorption. Moreover, Mn doping redistributes the electron density, enhancing the flexibility of electrons on the Fe atom and facilitating electron transfer from Fe to the π* orbital of Mn-N-O, thus promoting N-O cleavage. The present study demonstrates that the incorporation of unoccupied d orbitals with appropriate energy and symmetry facilitates a d-π interaction between the dopant and reactant, thereby significantly enhancing catalytic efficiency. These findings provide valuable new insights into the design of high-performance NH<sub>3</sub>-SCR catalysts.

Authors

Institutions

Publication Details

Journal
Environmental Science & Technology
Published
2025-02-18
DOI
https://doi.org/10.1021/acs.est.4c11442
Citations
6
Primary Topic
Catalytic Processes in Materials Science
Type
article
Field-Weighted Citation Impact
3.11
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

d-π Orbital Interaction Promoting NOx Selective Reduction on the Mn-Doped α-Fe2O3(001) Catalyst

Dezhan Chen, Fang Huang, Hao Liu, Shengnan Yuan et al.
6 citations
Environmental Science & Technology
Catalytic Processes in Materials Science
3.11
article

d-π Orbital Interaction Promoting NOx Selective Reduction on the Mn-Doped α-Fe2O3(001) Catalyst

Dezhan Chen, Fang Huang, Hao Liu, Shengnan Yuan, Chuanzhi Sun, Xueqing Liu, Lin Dong, Xuechen Zhu
article en
6 citations

Abstract

Understanding the structure-activity relationship on a solid surface is crucial for developing an efficient low-temperature NH<sub>3</sub>-SCR catalyst. Herein, an in-depth investigation was conducted on a single-atom Mn-doped α-Fe<sub>2</sub>O<sub>3</sub> catalyst by combining experimental studies and density functional theory calculations. Mn doping not only facilitates N-H cleavage in the Eley-Rideal (E-R) pathway but also promotes the adsorption of NO and the cleavage of the N-O bond, lowering the energy barrier of the rate-determining step in the Langmuir-Hinshelwood (L-H) pathway. Thus, Mn doping facilitates the catalytic reaction along both potential pathways, which promotes the NH<sub>3</sub>-SCR reaction. Further analysis reveals that the doping of Mn introduces an unoccupied d<sub><i>xy</i></sub> orbital, which facilitates the interaction with the π orbital of NO, thereby augmenting NO adsorption. Moreover, Mn doping redistributes the electron density, enhancing the flexibility of electrons on the Fe atom and facilitating electron transfer from Fe to the π* orbital of Mn-N-O, thus promoting N-O cleavage. The present study demonstrates that the incorporation of unoccupied d orbitals with appropriate energy and symmetry facilitates a d-π interaction between the dopant and reactant, thereby significantly enhancing catalytic efficiency. These findings provide valuable new insights into the design of high-performance NH<sub>3</sub>-SCR catalysts.

Environmental Science & TechnologyVol. 59(8)
Shandong Normal University (CN), Nanjing University (CN)
Openalex Percentile: Top 9%
Catalytic Processes in Materials Science
3.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.