Synergistic Catalysis of Rh Single‐Atom and Clusters Supported on TiO<sub>2</sub> Nanosheet Array for Highly Efficient Removal of CO and NO<sub><i>x</i></sub>

Developing an efficient catalyst is the key to selective catalytic reduction (SCR) of NO x by CO (CO‐SCR) to simultaneously address the pollution of toxic NO x and CO. Herein, a novel Rh/TiO 2 /Ti monolithic catalyst is designed and synthesized, featuring Rh species in the form of single atoms (Rh 1 ) and clusters (Rh n ). This catalyst overcomes the inhibitory effects of oxygen, achieving low‐temperature NO conversion. The investigation substantively contributes insights into the strategic manipulation of active metal components, emphasizing the potential of single‐atom/cluster catalysts to enhance efficiency. The Rh/TiO 2 /Ti catalyst has demonstrated exceptional catalytic efficacy, achieving 100% NO conversion at a low temperature of 190 °C in the presence of oxygen. Additionally, it exhibits remarkable stability and water resistance for practical applications. Moreover, comprehensive characterization confirms that Rh clusters and single‐atom sites play an important role in the selective adsorption of NO and CO molecules, promoting the formation of –N 2 O species and ultimately resulting in the complete conversion of NO and CO to N 2 and CO 2 . This study not only provides valuable guidance for designing high‐performance CO‐SCR catalysts but also underscores the potential of single atoms/clusters catalytic systems in both fundamental research and industrial catalysis.

Authors

Institutions

Publication Details

Journal
Small Structures
Published
2024-09-19
DOI
https://doi.org/10.1002/sstr.202400230
Citations
14
Primary Topic
Catalytic Processes in Materials Science
Type
article
Field-Weighted Citation Impact
1.64

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Synergistic Catalysis of Rh Single‐Atom and Clusters Supported on TiO2 Nanosheet Array for Highly Efficient Removal of CO and NOx

Baodan Liu, Junchao Wang, Xinglai Zhang, Yang Liu et al.
14 citations
Small Structures
Catalytic Processes in Materials Science
1.64
article

Synergistic Catalysis of Rh Single‐Atom and Clusters Supported on TiO2 Nanosheet Array for Highly Efficient Removal of CO and NOx

Baodan Liu, Junchao Wang, Xinglai Zhang, Yang Liu, Jing Li, Xinyu Li, Song Li, Hanze He, Tingting Liu
article en
14 citations

Abstract

Developing an efficient catalyst is the key to selective catalytic reduction (SCR) of NO x by CO (CO‐SCR) to simultaneously address the pollution of toxic NO x and CO. Herein, a novel Rh/TiO 2 /Ti monolithic catalyst is designed and synthesized, featuring Rh species in the form of single atoms (Rh 1 ) and clusters (Rh n ). This catalyst overcomes the inhibitory effects of oxygen, achieving low‐temperature NO conversion. The investigation substantively contributes insights into the strategic manipulation of active metal components, emphasizing the potential of single‐atom/cluster catalysts to enhance efficiency. The Rh/TiO 2 /Ti catalyst has demonstrated exceptional catalytic efficacy, achieving 100% NO conversion at a low temperature of 190 °C in the presence of oxygen. Additionally, it exhibits remarkable stability and water resistance for practical applications. Moreover, comprehensive characterization confirms that Rh clusters and single‐atom sites play an important role in the selective adsorption of NO and CO molecules, promoting the formation of –N 2 O species and ultimately resulting in the complete conversion of NO and CO to N 2 and CO 2 . This study not only provides valuable guidance for designing high‐performance CO‐SCR catalysts but also underscores the potential of single atoms/clusters catalytic systems in both fundamental research and industrial catalysis.

Small StructuresVol. 5(11)
University of Science and Technology of China (CN), Foshan University (CN), Chinese Academy of Sciences (CN), Northeastern University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 12%
Catalytic Processes in Materials Science
1.64
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.