Molecular Modelling of Friction at Lubricated Surfaces
Supervisors: Professor Daniele Dini and Dr. James Ewen
Sponsor: Baker Hughes
Description
The interaction between formulated lubricants and engineered surfaces is not fully understood. This research aims to conduct molecular simulations, while using machine learning techniques, to investigate the chemical and physical interactions between surfaces in shear (and lubricants). The ultimate goal is to develop a truly multi-scale (atomistic to continuum), multi-physics tribological model in order to demonstrate how atomistic interactions influence observed macroscale behaviour.
Skills and Techniques used
- Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS)
- Reactive Force Field (ReaxFF)
- Density-functional Theory (DFT)
- Python