Understanding Dislocations Networks in Metals

Almost all the things we interact with daily contain metal components, and most of them have been manufactured into their final shape by plastic deformation. Industrial forming for the production of these objects is largely based on empirical values, such as how much stress is required to form a product from certain components and to a certain thickness. Almost 100 years ago, researcherse realized that the theoretical stress required for this purpose – i.e. force per surface area – was 100 to 1,000 times greater than the actual stress required. This is due to defects in the crystal lattice of the metals that occur in lines, so-called dislocations.

These dislocations are already well understood at the atomistic scale. On a larger scale, however, they interact in a complex way. For example, the interaction between dislocations is partly to blame for the fact that a metal becomes increasingly difficult to deform further with increasing deformation – an effect known as work hardening. Previous models that attempt to describe this behavior don’t work very well yet. Basically, the dislocation behavior underlying these effects is not really understood yet.

He wants to use his ERC grant “DISCO-DATA: Hard work, plastic flow: a data-centric approach to dislocation-based plasticity” to investigate the interaction of dislocations for the first time by simulating them and explicitly representing them as networks using mathematical methods from graph theory. Using many simulations of different networks, he plans to create abstract networks and analyze their behavior during deformation. In the final step, he will then go back to the physical model.