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公开(公告)号：US12024791B2
公开(公告)日：2024-07-02
申请号：US17760964
申请日：2021-02-08
发明人： Hongji Qi , Duanyang Chen , Qinglin Sai
摘要： A high resistance gallium oxide quality prediction method based on deep learning and an edge-defined film-fed crystal growth method, a preparation method and a system; the quality prediction method includes the following steps: obtaining preparation data of a high resistance gallium oxide single crystal prepared by the edge-defined film-fed crystal growth method, the preparation data including seed crystal data, environment data and control data, and the control data including doping element concentration and doping element type; preprocessing the preparation data to obtain preprocessed preparation data; inputting the preprocessing preparation data into a trained neural network model, acquiring the predicted quality data corresponding to the high resistance gallium oxide single crystal through the trained neural network model, the predicted quality data including predicted resistivity.
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公开(公告)号：US12024790B2
公开(公告)日：2024-07-02
申请号：US17761042
申请日：2021-02-05
发明人： Hongji Qi , Duanyang Chen , Qinglin Sai
摘要： A quality prediction method, a preparation method and a system of conductive gallium oxide based on deep learning and Czochralski method. The quality prediction method includes the steps of obtaining preparation data of conductive gallium oxide single crystal prepared by Czochralski method. The preparation data includes a seed crystal data, an environmental data, and a control data. The environmental data includes doping element concentration and doping element type; preprocessing the preparation data to obtain a preprocessed preparation data; preparing the preprocessed data is input to a trained neural network model, and a predicted quality data corresponding to the conductive gallium oxide single crystal is obtained through the trained neural network model, and the predicted quality data includes a predicted carrier concentration.
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13.发明公开公开(公告)号：US20240020521A1
公开(公告)日：2024-01-18
申请号：US18251775
申请日：2021-02-07
发明人： Hongji QI , Duanyang CHEN
摘要： A preparation method of high resistance gallium oxide based on deep learning and heat exchange method. The prediction method includes: obtaining a preparation data of the high resistance gallium oxide single crystal, the preparation data including a seed crystal data, an environmental data, a control data, and a raw material data, the control data including a seed crystal coolant flow rate, and the raw material data including 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. Therefore, the high resistance gallium oxide with a preset resistivity is obtained.
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14.发明公开公开(公告)号：US20230160097A1
公开(公告)日：2023-05-25
申请号：US17761042
申请日：2021-02-05
发明人： Hongji QI , Duanyang CHEN , Qinglin SAI
摘要： A quality prediction method, a preparation method and a system of conductive gallium oxide based on deep learning and Czochralski method. The quality prediction method includes the steps of obtaining preparation data of conductive gallium oxide single crystal prepared by Czochralski method. The preparation data includes a seed crystal data, an environmental data, and a control data. The environmental data includes doping element concentration and doping element type; preprocessing the preparation data to obtain a preprocessed preparation data; preparing the preprocessed data is input to a trained neural network model, and a predicted quality data corresponding to the conductive gallium oxide single crystal is obtained through the trained neural network model, and the predicted quality data includes a predicted carrier concentration.
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