Publications / SAND Report

Predicting growth of graphene nanostructures using high-fidelity atomistic simulations

Bartelt, Norman C.; McCarty, Keven F.; Foster, Michael E.; Schultz, Peter A.; Zhou, Xiaowang Z.; Ward, Donald K.

In this project we developed t he atomistic models needed to predict how graphene grows when carbon is deposited on metal and semiconductor surfaces. We first calculated energies of many carbon configurations using first principles electronic structure calculations and then used these energies to construct an empirical bond order potentials that enable s comprehensive molecular dynamics simulation of growth. We validated our approach by comparing our predictions to experiments of graphene growth on Ir, Cu and Ge. The robustness of ou r understanding of graphene growth will enable high quality graphene to be grown on novel substrates which will expand the number of potential types of graphene electronic devices.