CPC C30B 15/20 (2013.01) [C30B 15/14 (2013.01); C30B 29/16 (2013.01); G16C 20/30 (2019.02); G16C 20/70 (2019.02)] | 10 Claims |
1. A quality prediction and preparation method of high resistance gallium oxide based on deep learning and Czochralski method, comprising:
preparing a seed crystal in a crucible by the Czochralski method;
determining preparation data of a high resistance gallium oxide single crystal prepared by the Czochralski method, the preparation data comprising seed crystal data measured from the seed crystal, an environmental data, and a control data, and the environmental data comprises a doping element concentration and a doping element type;
preprocessing the preparation data to obtain a preprocessed preparation data and training data;
training a neural network model using the training data;
inputting the preprocessed preparation data into the trained neural network model;
determining, by the trained neural network model, a targeted quality data corresponding to the high resistance gallium oxide single crystal through the trained neural network model, and the targeted quality data comprises a predicted resistivity; and
preparing a targeted high resistance gallium oxide crystal according to the targeted quality data.
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