Multi-objective optimization of Magnetic Czochralski crystal growth process using surrogate modeling and evolutionary algorithm

Key Points

• Optimized crystal growth improves the yield and quality of magnetic czochralski crystals, paving the way for better materials.
• The process uses specific modeling techniques, achieving optimal results without exhaustive resource use or time.
• Surrogate modeling combined with an evolutionary algorithm streamlines the optimization process, enhancing overall efficiency.
• Findings suggest that this approach may enable advancements in manufacturing techniques for high-performance crystal materials.