Stochastic models for surface diffusion of molecules.

Area of Science:

• Physical Chemistry
• Surface Science
• Computational Chemistry

Background:

• Understanding molecule diffusion on surfaces is key to catalysis and materials science.
• Classical models often simplify molecular dynamics, potentially missing crucial vibrational effects.

Purpose of the Study:

• To derive a stochastic model for molecular surface diffusion from fundamental equations of motion.
• To investigate the influence of molecular vibrations on the diffusion of molecules on surfaces.

Main Methods:

• Derived a generalized Langevin equation for molecular center of mass motion.
• Analyzed the friction kernel, including non-Markovian effects and the Markov approximation.
• Investigated the dependence of effective friction on the diffusion path curvature.

Main Results:

• Molecular vibrations increase the effective friction for center of mass motion.
• Effective friction is simply related to the curvature of the lowest energy diffusion path.
• The Markov approximation is valid when intramolecular forces are strong, simplifying the model.

Conclusions:

• A simplified one-dimensional model can effectively describe molecular diffusion, incorporating vibrational dynamics.
• The derived model provides insights into friction and memory effects in surface diffusion.
• This work offers a more accurate theoretical framework for surface diffusion phenomena.