Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 116, Issue 21, Pages 10291-10296Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1817417116
Keywords
genetic algorithms; targeted selection; superconductivity; vortex pinning; critical current
Categories
Funding
- Scientific Discovery through Advanced Computing program
- US Department of Energy (DOE), Office of Science, Advanced Scientific Computing Research and Basic Energy Science, Division of Materials Science and Engineering
- Center for Emergent Superconductivity, an Energy Frontier Research Center - US DOE, Office of Basic Energy Sciences
- DOE [DE-AC05-00OR22725]
- Argonne LCF (DOE) [DE-AC02-06CH11357]
- Computing Facility at Northern Illinois University
Ask authors/readers for more resources
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 postsynthesis particle irradiation precludes a priori prediction of the critical current and can result in highly nontrivial effects on the critical current. Here, we borrow concepts from biological evolution to create a vortex pinning genome based on a genetic algorithm, naturally evolving the pinning landscape to accommodate vortex pinning and determine the best possible configuration of inclusions for two different scenarios: a natural evolution process initiating from a pristine system and one starting with preexisting defects to demonstrate the potential for a postprocessing 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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available