Segregation of solute elements to grain boundaries (GBs) is a key factor for production and performance of many technologically relevant materials. It influences fundamental material properties such as formability, crack propagation, grain growth, precipitation, diffusivity or electric conductivity. By controlling the segregation state, a lever for developing materials of superior properties can be obtained.
present atomistic simulations based mainly on density functional theory which
target the prediction of segregation energies and modification of cohesive
properties in transition metals. First the anisotropy of GB properties in pure
bcc and fcc metals will be discussed to identify different GB classes and to
determine which can be considered as representative GBs. Next, segregation
energies in the transition metals W, Mo and Cu will be presented and analyzed
to understand whether simple modeling (Miedema model, Friedel model) can
reproduce trends or how machine learning techniques can contribute. Then, we
will show a comparison with experiment involving tracer diffusion for Cu and
atom-probe tomography for a particular Mo-Hf alloy system. In this course also
a new model for kinetics of segregation will be discussed. I will conclude by
discussing the future challenges of segregation modeling and how databases can
be created and used for grain boundary engineering.