发明公开
- 专利标题: DEEP LEARNING BASED ADAPTIVE ALIGNMENT PRECISION METROLOGY FOR DIGITAL OVERLAY
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申请号: US18034903申请日: 2021-11-30
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公开(公告)号: US20230408932A1公开(公告)日: 2023-12-21
- 发明人: Tamer COSKUN , Yen-Shuo LIN , Aidyn KEMELDINOV
- 申请人: Applied Materials, Inc.
- 申请人地址: US CA Santa Clara
- 专利权人: Applied Materials, Inc.
- 当前专利权人: Applied Materials, Inc.
- 当前专利权人地址: US CA Santa Clara
- 国际申请: PCT/US2021/061088 2021.11.30
- 进入国家日期: 2023-05-02
- 主分类号: G03F7/00
- IPC分类号: G03F7/00 ; G03F9/00 ; G06V10/75 ; G06V10/764 ; G06T7/73 ; G06T7/33 ; G06T7/00
摘要:
Embodiments described herein relate to a system, methods, and non-transitory computer-readable mediums that accurately align subsequent patterned layers in a photoresist utilizing a deep learning model and utilizing device patterns to replace alignment marks in lithography processes. The deep learning model is trained to recognize unique device patterns called alignment patterns in the FOV of the camera. Cameras in the lithography system capture images of the alignment patterns. The deep learning model finds the alignment patterns in the field of view of the cameras. An ideal image generated from a design file is matched with the camera with respect to the center of the field of view of the camera. A shift model and a rotation model are output from the deep learning model to create an alignment model. The alignment model is applied to the currently printing layer.
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