(13g) Surface Diffusion of Large Molecules: A Computational Study

Kutay B. Sezginel and Christopher E. Wilmer

Department of Chemical and Petroleum Engineering, University of Pittsburgh, 3700 O’Hara Street, Pittsburgh, Pennsylvania 15261, United States

Controlling molecular motion on surfaces is one of the first steps towards bottom-up construction of nanoscale machines. This process is commonly utilized in cells to transport molecular cargo: enzyme molecules are moved along protein filament tracks converting chemical energy into mechanical work. Careful design of the molecular structure and selection of the appropriate surface can enable precise manipulation of the molecular diffusion. Several strategies have been shown to greatly influence diffusion such as molecular functionalization and adjusting the orientation of the molecule with respect to the substrate lattice. Although these strategies are useful, to achieve a nanoscale understanding and control over the dynamics of molecular motion on surfaces it is crucial to develop theoretical models and utilize modern computational tools. Developing a robust computational method is crucial to get further insights and deeper understanding of the molecular surface diffusion which then can be used to design molecules to tailor diffusion properties such as speed and directionality.

In this work, we investigated the diffusion of 9 large organic molecules on a Cu (110) surface. The molecules were selected from available experimental diffusion data in the literature. First, we reviewed different modeling strategies to qualitatively reproduce experimental diffusion results using molecular dynamics (MD) simulations. After developing a robust method, we then calculated the speed and the directionality of the motion of these molecules. Analyzing the MD trajectories, we studied the effect of long jumps (random jumps between nearest neighbor sites) and calculated hopping rate for each molecule. By comparing the nature of diffusion of each molecule we present insights on how to optimize directionality and speed of the motion.