Predicting growth of graphene nanostructures using high-fidelity atomistic simulations

Technical Report · 01 September 2015

DOI:https://doi.org/10.2172/1221517· OSTI ID:1221517

McCarty, Kevin F. ^[1]; Zhou, Xiaowang ^[1]; Ward, Donald K. ^[1]; Schultz, Peter A. ^[1]; Foster, Michael E. ^[1]; Bartelt, Norman Charles ^[1]

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1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)

In this project we developed the 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 enables 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 our 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.

• Research Organization: Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Sandia National Laboratories, Albuquerque, NM (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA); USDOE Laboratory Directed Research and Development (LDRD) Program
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 1221517
• Report Number(s): SAND2015-7944; 603848
• Country of Publication: United States
• Language: English

Related Subjects

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY