Date of Award

Spring 2019

Document Type

Open Access Thesis



First Advisor

Yi Sun


Through the assembly of procedural information about physical processes, the kinetic Monte Carlo method offers a simple and efficient stochastic approach to model the temporal evolution of a system. While suitable for a variety of systems, the approach has found widespread use in the simulation of epitaxial growth. Motivated by chem- ically reacting systems, we discuss the developments and elaborations of the kinetic Monte Carlo method, highlighting the computational cost associated with realizing a given algorithm. We then formulate a solid-on-solid bond counting model of epitax- ial growth which permits surface atoms to advance the state of the system through three events: hopping, evaporation, and condensation. Finally, we institute the ki- netic Monte Carlo method to describe the evolution of a crystalline structure and to examine how temperature influences the mobility of surface atoms.

Included in

Mathematics Commons