[Case Study] Optimization of Gas Nozzle Design for GaN Manufacturing Equipment

Significantly reduce calculation time! Introducing case studies of process informatics!

"GaN (gallium nitride)" is a power semiconductor that is expected to be adopted as a power source for 5G base stations. It is commonly used as a thin sliced disk wafer, but the initial manufacturing state is cylindrical. The GaN cylinder emits gas, which serves as the raw material for GaN, from holes at the bottom, allowing the crystals to grow. In reality, there are over 100 holes, leading to infinite combinations. When simulating this, it takes an astonishing 6 hours for just one condition. If you run 1000 variations, it consumes 6000 hours, which equals 250 days, taking a significant amount of time. This is where "Process Informatics" from AICrystal comes into play. By training AI with the results of 1000 randomly generated simulations, the calculation time is drastically reduced. The time required is just 1 second per condition. Thanks to the significant reduction in calculation time enabled by AI, it is now possible to compute 10,000 conditions in just about 3 hours. This optimization allows for the gas conditions and hole arrangements to be fine-tuned, successfully tripling the growth rate. *For more details, please refer to the PDF document or feel free to contact us.*

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