Issue 21, 2024

Theoretical insights into Pt–Rh alloy nanoparticles: stability, elemental distribution, and catalytic mechanisms for NO + CO reactions

Abstract

Pt–Rh bimetallic alloys hold significant promise in catalysis. This study theoretically delves into the stable configurations and elemental distributions of Pt–Rh alloy nanoparticles (NPs) and their influence on the NO + CO catalytic reaction. Initially, a comprehensive dataset for the Pt–Rh system is compiled via calculations based on density functional theory (DFT), followed by developing machine learning potential with accuracy akin to DFT. By employing hybrid Monte Carlo/molecular dynamics simulations, the study unveils that the octahedron-shaped NP is the most stable. Elemental distribution analysis highlights the prevalence of Rh atoms within the interior, particularly in the sub-surface layer, with Pt atoms predominantly occupying the top-surface layer. Building upon these insights, four surface models are crafted and their catalytic efficacy in the NO + CO reaction is evaluated via DFT calculations. The findings indicate that Pt atoms at the top-surface foster N2 recombination, Rh atoms facilitate NO dissociation, while Rh atoms in the sub-surface layer modestly enhance both processes. Hence, Pt–Rh alloy NPs featuring surfaces with both Pt and Rh atoms, with a dominance of Rh atoms in the sub-surface layer, are poised to demonstrate bifunctional catalytic prowess in the NO + CO reaction. This study offers crucial guidance for designing bifunctional catalysts for exhaust gas treatment.

Graphical abstract: Theoretical insights into Pt–Rh alloy nanoparticles: stability, elemental distribution, and catalytic mechanisms for NO + CO reactions

Supplementary files

Article information

Article type
Paper
Submitted
18 Jun 2024
Accepted
09 Sep 2024
First published
09 Sep 2024

Catal. Sci. Technol., 2024,14, 6286-6297

Theoretical insights into Pt–Rh alloy nanoparticles: stability, elemental distribution, and catalytic mechanisms for NO + CO reactions

Y. Li, X. Duan, Z. Liu, C. Li, F. Ye, Z. Zhang, L. Chen, C. Du, Q. Wang and B. Shan, Catal. Sci. Technol., 2024, 14, 6286 DOI: 10.1039/D4CY00755G

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