Jump rates for surface diffusion of large molecules from first principles.

Area of Science:

• Surface science
• Physical chemistry
• Computational materials science

Background:

• Understanding molecular diffusion on surfaces is crucial for catalysis and materials design.
• Accurate prediction of diffusion requires sophisticated theoretical models.
• Previous methods like transition state theory often lack precision for complex systems.

Purpose of the Study:

• To apply a novel stochastic model for calculating surface diffusion jump rates.
• To investigate the diffusion of 9,10-dithioanthracene on a Copper(111) surface.
• To compare model predictions with experimental data and transition state theory.

Main Methods:

• Utilized a recently developed stochastic model for surface diffusion.
• Employed density functional theory (DFT) with van der Waals corrections to compute model parameters.
• Calculated jump rates for 9,10-dithioanthracene on Cu(111).

Main Results:

• Inclusion of van der Waals corrections was critical for accurate adsorption geometry and diffusion energy barriers.
• The stochastic model predictions for jump rates showed excellent agreement with experimental values.
• A significant reduction in the jump rate prefactor compared to transition state theory was observed.

Conclusions:

• The developed stochastic model provides a more accurate approach to predicting molecular diffusion on surfaces.
• Frictional damping from surface phonons and molecular rotation significantly impact diffusion rates.
• This work highlights the importance of accurate electronic structure calculations and advanced modeling for surface dynamics.