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In power semiconductors like GaN, even the smallest roughness at the nanometer level (one-millionth of a millimeter) can affect performance, making crystal processing after creating a cylinder essential in traditional methods. To find appropriate experimental conditions, it is necessary to conduct experiments with at least two different conditions for each factor, meaning that for five factors, a minimum of 32 experiments is required. Based on those trends, we try dozens of experimental conditions to find the combination of factors that leads to the desired results. Therefore, traditional optimization methods centered around experiments required a significant number of trials. In contrast, the approach taken by Aicrystal, which learns from results, explores, and suggests conditions, was able to reduce the number of experiments to just 19. Moreover, this approach achieved a level of processing precision that allowed for the omission of later processes, and the benefits of not needing additional capital investment are significant. The conditions deemed appropriate here were combinations that had never been tried by engineers, showcasing the value of collaboration between AI and humans. *For more details, please refer to the PDF document or feel free to contact us.*

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"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 disc 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, providing infinite combinations. Simulating this takes an astonishing 6 hours for just one condition. If you run 1000 variations, it consumes 6000 hours, which is equivalent to 250 days. This is where "Process Informatics" from AICrystal comes into play. By training AI on the results of 1000 randomly generated simulations, the calculation time is significantly reduced. The time required is just 1 second per condition. Thanks to the substantial reduction in calculation time enabled by AI, it is now possible to calculate 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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