  The ability of type-II superconductors to carry large amounts of current at
high magnetic fields is a key requirement for future design innovations in
high-field magnets for accelerators and compact fusion reactors and largely
depends on the vortex pinning landscape comprised of material defects. The
complex interaction of vortices with defects that can be grown chemically,
e.g., self-assembled nanoparticles and nanorods, or introduced by
post-synthesis particle irradiation precludes a priori prediction of the
critical current and can result in highly non-trivial effects on the critical
current. Here, we borrow concepts from biological evolution to create a genetic
algorithm evolving pinning landscapes to accommodate vortex pinning and
determine the best possible configuration of inclusions for two different
scenarios: an evolution process starting from a pristine system and one with
pre-existing defects to demonstrate the potential for a post-processing
approach to enhance critical currents. Furthermore, the presented approach is
even more general and can be adapted to address various other targeted material
optimization problems.
