Quality prediction method, preparation method and system of high resistance gallium oxide based on deep learning and edge-defined film-fed growth method
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United States of America Patent
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Jul 2, 2024
Grant Date -
May 25, 2023
app pub date -
Feb 8, 2021
filing date -
Dec 31, 2020
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Abstract
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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