The Materials Theory & Computation group headed by Professor David J. Srolovitz focuses on understanding material behaviour through theoretical models and computation. The principal thrust areas are:
structure, thermodynamics and properties of defects in materials (including grain boundaries, twins, heterophase interfaces, dislocations, point defects and surfaces)
the effects of these defects on mechanical deformation, electronic/optical properties, and radiation damage
new techniques for first-principles, atomistic and statistical mechanics simulations of multiphase, two-dimensional, and topological materials
application of machine learning methods (e.g. machine learning potentials) in materials science