Development of machine learning interatomic potentials for titanium binary alloy systems.

Atomic simulations critically depend on the choice of the interatomic potential. The role of the potential is to accurately describe interactions between atoms such that their collective behaviour give rise to the phenomena later observed in Nature.

The potentials based on high level quantum theories provide accurate description but lacks required efficiency for large scale problems. On the other end of the spectrum are empirical models which are computationally cheap but not accurate enough.


The goal of this project is to develop an interatomic potential for titanium binary alloy systems to allow large scale atomic simulations with unprecedented precision. The project will utilize a number of novel machine learning tools which aim to bridge the gap between classical and quantum methods. The potential would allow us to study the formation of polycrystals in titanium alloys which are of interest for both physicists and engineers.