Table of Contents
Fetching ...

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

TL;DR

This study benchmarks diffusion Monte Carlo (DMC) against DFT-PBE for adsorption of $O_2$, $CO$, $CO_2$, and atomic $O$ on a graphene-supported single Pt atom, revealing substantial discrepancies in energies and preferred spin geometries, particularly for $O_2$. It finds that CO binds much more strongly ($E_{ad}=-3.37(1)$ eV) than $O_2$ ($E_{ad}=-1.23(2)$ eV), implying CO poisoning on this model catalyst and challenging commonly invoked Langmuir–Hinshelwood and Eley–Rideal pathways on pristine graphene. CO2 and atomic O display distinct adsorption patterns, with CO2 favoring side-on binding ($E_{ad}=-1.21(2)$ eV) and O in the triplet state ($E_{ad}=-4.04(1)$ eV), while $E_{dissoc}$ for $O_2$ on Pt–graphene is $2.29(3)$ eV, aligning with experimental estimates for isolated $O_2$ dissociation. These results indicate that many-body effects reshape the adsorption landscape and catalytic mechanisms, suggesting alternative routes such as forming an $O$-Pt-graphene complex to enable CO oxidation; the work highlights the need for advanced computational approaches to reliably guide catalyst design.

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

TL;DR

This study benchmarks diffusion Monte Carlo (DMC) against DFT-PBE for adsorption of , , , and atomic on a graphene-supported single Pt atom, revealing substantial discrepancies in energies and preferred spin geometries, particularly for . It finds that CO binds much more strongly ( eV) than ( eV), implying CO poisoning on this model catalyst and challenging commonly invoked Langmuir–Hinshelwood and Eley–Rideal pathways on pristine graphene. CO2 and atomic O display distinct adsorption patterns, with CO2 favoring side-on binding ( eV) and O in the triplet state ( eV), while for on Pt–graphene is eV, aligning with experimental estimates for isolated dissociation. These results indicate that many-body effects reshape the adsorption landscape and catalytic mechanisms, suggesting alternative routes such as forming an -Pt-graphene complex to enable CO oxidation; the work highlights the need for advanced computational approaches to reliably guide catalyst design.

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, CO, CO, 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, 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 ( eV) and CO ( 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.

Paper Structure

This paper contains 7 sections, 5 figures.

Figures (5)

  • Figure 1: (Color online) DMC adsorption energies of an O$_{2}$ molecule adsorbed on a graphene-supported Pt atom as functions of $1/N_{c}$ for three different configurations (Z-, A- and V$'$-modes), where $N_{c}$ represents the total number of carbon atoms in the supercell. The solid lines represent the extrapolations through linear regression fits.
  • Figure 2: (Color online) (a) to (c) Three stable configurations of an O$_{2}$-adsorbed Pt-graphene complex, where black, white, and red spheres represent carbon, platinum, and oxygen atoms, respectively. Here the blue parallelograms indicate a $3 \times 3 \times 1$ graphene supercell. (d) presents DMC and DFT molecular adsorption energies for each configuration.
  • Figure 3: (Color online) One-dimensional charge density differences, projected along the vertical $z$-axis, between the O$_2$-adsorbed Pt-graphene complex in the Z-mode and the Pt-graphene system plus an isolated O$_2$ molecule. The horizontal dashed lines indicate the vertical positions of the graphene sheet, the Pt atom, and each oxygen atoms of the O$_2$ molecule, while the vertical dotted line corresponds to the zero charge density difference.
  • Figure 4: (Color online) (a) to (c) Three PBE-optimized configurations ((a) to (c)) of a CO-adsorbed Pt-graphene complex, where black, white, and red spheres represent carbon, platinum, and oxygen atoms, respectively. Here the blue parallelogram indicates a $3 \times 3 \times 1$ graphene supercell. (d) presents DMC and DFT molecular adsorption energies for each configuration.
  • Figure 5: (Color online) The most stable PBE-optimized configurations of (a) an O atom and (b) a CO$_{2}$ molecule adsorbed on the Pt-graphene complex, along with their respective adsorption energies in (c) and (d). Black, white, and red spheres represent carbon, platinum, and oxygen atoms, respectively. The blue parallelogram indicates a $3 \times 3 \times 1$ graphene supercell.