一种基于深度学习和提拉法的高阻型氧化镓的质量预测方法、制备方法及系统
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HANGZHOU FUJIA GALLIUM TECH CO LTD
- Filing Date
- 2020-12-31
- Publication Date
- 2026-07-17
AI Technical Summary
In the existing Czochralski method for preparing high-resistivity gallium oxide single crystals, parameter control relies on operator experience, resulting in poor repeatability and an inability to stably produce high-resistivity gallium oxide single crystals with the predetermined resistivity.
By combining deep learning and the Czochralski method, the seed crystal, environment, and control data for preparing high-resistivity gallium oxide single crystals are obtained, preprocessed, and then input into a trained neural network model to predict the quality data of high-resistivity gallium oxide single crystals and adjust the preparation parameters to achieve the predetermined resistivity.
This method enables precise prediction and stable control of the quality of high-resistivity gallium oxide single crystals, allowing the fabrication of high-resistivity gallium oxide single crystals with predetermined resistivity, thus improving the repeatability and stability of the fabrication process.
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Figure CN112820360B_ABST