Dr. Alireza Tabarraei

Graphene, a monolayer of carbon atoms packed together in a honeycomb lattice structure, displays fantastic thermal, electronic, optical, and mechanical properties. Its fantastic properties have made graphene an attractive material for a wide range of applications including field-effect transistors, supercapacitors advanced nanocomposites and sensors. The wide range of applications of graphene exposes it to different environmental and mechanical loading conditions. To ensure the structural integrity of graphene-based materials, it is essential to understand the fracture and mechanical properties of graphene.

Molecular dynamic simulations are used to study the fracture and mechanical properties of graphene under different loading conditions when polycrystalline graphene sheets are exposed to environmental molecules. Our results show that the presence of environmental molecules such as oxygen or hydrogen molecules can lead to subcritical crack growth in graphene. Using molecular dynamics simulations we have extracted the traction-separation laws for graphene grain boundaries and have shown that the adsorption of hydrogen atoms at graphene grain boundaries can lead to the embrittlement of grain boundaries. Using the molecular dynamic results, a machine learning model is trained to predict the fracture of polycrystalline graphene at a significantly lower computational cost than molecular dynamics.

Dr. Tabarraei has received his Ph.D. from the University of California at Davis. After working as a postdoctoral fellow at Northwestern University for two years, he joined the University of North Carolina at Charlotte in 2012. His research focus is on using computational methods such as finite elements, molecular dynamics, and machine learning for studying the mechanical and fracture properties of materials.