Quantum Monte Carlo Benchmarking of Molecular Adsorption on Graphene-Supported Single Pt Atom

Jeonghwan Ahn, Iuegyun Hong, Gwangyoung Lee, Hyeondeok Shin, Anouar Benali, Yongkyung Kwon

公開日: 2025/8/29

Abstract

The precise understanding of adsorption energetics and molecular geometry at catalytic sites is fundamental for advancing catalysis, particularly under the constraints of resource efficiency and environmental sustainability. This study benchmarks the performance of density functional theory (DFT) calculations against diffusion Monte Carlo (DMC) calculations for adsorption properties of small gas molecules relevant to CO oxidation -- namely O$_2$, CO, CO$_2$, and atomic oxygen -- on a single Pt atom supported by pristine graphene. Our findings reveal that DMC calculations provide a significantly different landscape of adsorption energetics compared to DFT results. Notably, DFT predicts different lowest-energy configurations and spin states, particularly for O$_2$, which suggests potential discrepancies in predicting the catalytic behavior. Furthermore, this study identifies the critical issue of CO poisoning, highlighted by the large disparity between the DMC adsorption energies of O$_2$ ($-1.23(2)$ eV) and CO ($-3.37(1)$ eV), which can inhibit the catalytic process. These results emphasize the necessity for more sophisticated computational approaches in catalysis research, aiming to refine the prediction accuracy of reaction mechanisms and to enhance the design of more effective catalysts.

Quantum Monte Carlo Benchmarking of Molecular Adsorption on Graphene-Supported Single Pt Atom | SummarXiv | SummarXiv