基于分子动力学仿真的缺陷消除方法及装置、设备
By combining molecular dynamics simulation and machine learning with big data technology, surface defects in atomic crystal materials can be predicted and eliminated, solving the problem of low detection and repair efficiency in existing technologies and achieving efficient and low-cost surface defect repair.
CN118155732BActive Publication Date: 2026-07-17XIDIAN UNIV
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- XIDIAN UNIV
- Filing Date
- 2024-03-11
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
In existing technologies, the detection and repair of surface defects in atomic crystal materials during processing is inefficient, has a low success rate, is costly, and has poor repair results.
Method used
By employing a molecular dynamics simulation-based approach combined with machine learning and big data technologies, a pre-trained wafer defect estimation model is used to obtain the location and characteristic parameters of surface defects, determine the target processing parameters, and perform precise processing to eliminate surface defects.
Benefits of technology
It improved the success rate of surface defect elimination, shortened the repair time, reduced costs, improved repair efficiency, and reduced manpower consumption.
✦ Generated by Eureka AI based on patent content.
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Figure CN118155732B_ABST
Abstract
本公开提供了一种基于分子动力学仿真的缺陷消除方法及装置、设备，涉及晶片加工技术领域，融合大数据技术和机器学习技术。该基于分子动力学仿真的缺陷消除方法包括：可以将待处理晶片的分子结构数据输入到晶片缺陷估计模型中，得到表面缺陷估计位置以及相应的表面缺陷特征参数；根据表面缺陷特征参数确定表面缺陷估计位置处的目标加工参数；通过目标加工参数对相应的表面缺陷估计位置处的区域进行加工处理，得到表面缺陷消除后的待处理晶片。本公开实施例的技术方案能够从根源上对晶片表面缺陷进行消除，提高晶片表面消除的成功率，有效降低晶片的表面损伤，保证加工得到的晶片的质量。
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