Intelligent identification optimization method and system for interface defect characteristics of third-generation semiconductor material

By collecting and analyzing cross-sectional image data of third-generation semiconductor materials, combined with heterogeneous graph attention networks and temperature gradient control, the problem of low efficiency in defect identification and control in traditional methods is solved, accurate identification and efficient control of interface defects are achieved, and material performance is improved.

CN120689300AInactive Publication Date: 2025-09-23ZHONGKE (HEFEI) MICROELECTRONICS RESEARCH INSTITUTE CO LTD
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Patent Information

Application Number
CN202510777019.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-11
Publication Date
2025-09-23
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Traditional methods have difficulty in extracting high-precision three-dimensional defect morphology and stress field distribution information, and are unable to quantitatively evaluate the loss effects of different types of defects on material properties, resulting in low defect control efficiency and difficulty in optimizing material properties.

Method used

Cross-sectional images of third-generation semiconductor materials are collected to obtain electron mobility distribution data and carrier concentration data. By constructing high-resolution morphology and local stress distribution feature extraction channels, multi-dimensional feature vectors are generated and input into the heterogeneous graph attention network. Combined with the material performance loss evaluation model and the hierarchical progressive defect control strategy, a temperature gradient assisted control mechanism is introduced to monitor and optimize the defect control parameters in real time.

Benefits of technology

It has achieved accurate identification and classification of interface defects, quantified the impact of defects on material properties, and improved the electrical properties and stability of third-generation semiconductor materials.

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Abstract

The invention provides a third-generation semiconductor material interface defect feature intelligent identification optimization method and system, and relates to the technical field of semiconductor defect identification, and the method comprises the steps: collecting a semiconductor material cross section image and electrical data; constructing a morphology and stress distribution feature extraction channel, extracting interface defect multi-dimensional features, inputting the extracted interface defect multi-dimensional features into a heterogeneous graph attention network, identifying defect types, density and distribution, constructing a performance loss evaluation model, determining an optimal migration path by adopting a layered progressive defect regulation and control strategy in combination with a temperature gradient auxiliary mechanism, and optimizing defect regulation and control parameters in real time. Accurate identification and intelligent regulation and control of interface defects are realized, and the electrical performance of the semiconductor material is improved.
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