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公开(公告)号：US12026616B2
公开(公告)日：2024-07-02
申请号：US17761030
申请日：2021-02-05
发明人： Hongji Qi , Long Zhang , Duanyang Chen
CPC分类号： G06N3/08
摘要： The present application discloses a preparation method of high resistance gallium oxide based on deep learning and vertical Bridgman growth method. The prediction method comprises: obtaining a preparation data of the high resistance gallium oxide single crystal, the preparation data comprises a seed crystal data, an environmental data, a control data and a raw material data, and the raw material data comprises a doping type data and a doping concentration; preprocessing the preparation data to obtain a preprocessed preparation data; inputting the preprocessed preparation data into a trained neural network model, and obtaining a predicted property data corresponding to the high resistance gallium oxide single crystal through the trained neural network model, the predicted property data comprises a predicted resistivity.
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公开(公告)号：US12057199B2
公开(公告)日：2024-08-06
申请号：US17761322
申请日：2021-02-07
发明人： Hongji Qi , Long Zhang , Duanyang Chen
IPC分类号： C30B11/02 , G06N3/0464 , G06N3/08 , G16C20/10 , G16C20/70
CPC分类号： G16C20/10 , C30B11/02 , G06N3/0464 , G06N3/08 , G16C20/70
摘要： A preparation method of conductive gallium oxide based on deep learning and vertical Bridgman growth method. The prediction method includes: obtaining a preparation data of the conductive gallium oxide single crystal, the preparation data includes a seed crystal data, an environmental data, a control data and a raw material data, and the raw material data includes a doping type data and a conductive doping concentration; preprocessing the preparation data to obtain a preprocessed preparation data; inputting the preprocessed preparation data into a trained neural network model, and obtaining a predicted property data corresponding to the conductive gallium oxide single crystal through the trained neural network model, the predicted property data includes a predicted carrier concentration.
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