The atom-scale design of surfaces holds enormous potential for applications such as catalysis or superlubricating interfaces: Approximately 24% of the global energy consumption is lost to friction, while the chemical industry consumes around 29% of the energy in the manufacturing sector.
This project will engineer defective graphene surfaces to facilitate single-atom catalysis and to design ultra-low friction at the nanoscale. Defective graphene augments the remarkable properties of graphene with tailor-made defects that change the interaction of graphene with its environment.
The project will perform large-scale density functional theory calculations and construct a machine-learned interatomic potential for defective graphene/metal superstructures. This will allow it to characterise the stability, energetics, and x-ray spectroscopic fingerprints of various defects in metal-adsorbed graphene superstructures and it will enable large-scale structure exploration and molecular-dynamics simulations of friction at the nanoscale.
The simulation results will directly inform experiments and support interpretation and analysis of spectroscopic measurements for defects and adatom adsorption. The calculations will provide insight into mechanistic predictions and controllable superlubricity at graphitic interfaces and the role of interstitial atoms on mechanical properties.