Kinetic Monte Carlo Modeling of Graphene Sheet Growth During Chemical Vapor Deposition
Graphene is a material of key interest across several research fields. Bulk graphene synthesis, however, has long remained a challenge for larger-scale projects and real-world manufacturability. This work seeks an improved understanding of graphene sheet growth via computational modeling, with the objective of maximizing grain size. To this end, the kinetic Monte Carlo method is used to simulate chemical vapor deposition under various configurations of carbon flow and graphene seeding, with particular emphasis on computational efficiency. Ultimately, both quantitative and qualitative results are obtained to shed light on graphene growth mechanisms, with insights into real-world synthesis and future computational models.
