We developed a targeted evolution genetic algorithm to create a vortex-pinning genome that can be used to enhance the current carrying capability of high temperature superconductors.
Significance and Impact
The novel simulation tool advances the materials-by-design paradigm using evolution-based processes and can be adapted to improve the functional properties of advanced materials.
- Use of leadership class computing and genetic algorithm based artificial intelligence
- Numerical targeted selection used to automatically recognize defect configurations for better vortex pinning
- Selected configuration is used as seed for a new population generation of defects and the system topology evolves to a defect landscape with the highest critical current
Work was performed at Argonne LCF, Oak Ridge LCF, and Computing Facility at Northern Illinois University.
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