Interpretation of surface diffusion data with Langevin simulations: a quantitative assessment

Area of Science:

• Surface science
• Computational physics
• Physical chemistry

Background:

• Surface diffusion is crucial for understanding chemical reactions and material properties.
• Two-dimensional Langevin simulations offer a computationally efficient method for studying surface diffusion.
• These simulations simplify complex substrate-adsorbate interactions by neglecting correlated motion.

Purpose of the Study:

• To quantify the impact of neglecting correlations in Langevin simulations on surface diffusion observables.
• To compare the accuracy of Langevin simulations with explicit molecular dynamics simulations.
• To assess the validity of using simplified Langevin models for experimental data interpretation.

Main Methods:

• Performed 2D Langevin simulations of adsorbate diffusion.
• Conducted explicit molecular dynamics (MD) simulations for comparison.
• Calculated experimentally accessible observables from both simulation types.
• Analyzed the influence of temperature-dependent friction on simulation results.

Main Results:

• Langevin simulations provide a valid alternative for calculating surface diffusion processes within the explored parameter range.
• The effect of neglecting correlations was found to be negligible within the numerical accuracy of the study.
• Temperature-dependent friction significantly influences calculated observables, underscoring its importance.

Conclusions:

• Simplified 2D Langevin simulations are suitable for analyzing adsorbate surface diffusion and interpreting experimental data.
• The impact of correlated motion is minimal and does not significantly affect the interpretation of experimental results.
• Accurate interpretation of experimental surface diffusion data requires accounting for temperature-dependent friction.