公开(公告)号：WO2019162346A1

公开(公告)日：2019-08-29

申请号：PCT/EP2019/054246

申请日：2019-02-20

Applicant: ASML NETHERLANDS B.V.

Inventor： CAO, Yu ,  LUO, Ya ,  LU, Yen-Wen ,  CHEN, Been-Der ,  HOWELL, Rafael C. ,  ZOU, Yi ,  SU, Jing ,  SUN, Dezheng

IPC: G06N20/00 ,  G03F1/36 ,  G06N3/04 ,  G06N3/08 ,  G06F17/50

Abstract: Described herein are different methods of training machine learning models related to a patterning process. Described herein is a method for training a machine learning model configured to predict a mask pattern. The method including obtaining (i) a process model of a patterning process configured to predict a pattern on a substrate, wherein the process model comprises one or more trained machine learning models, and (ii) a target pattern, and training, by a hardware computer system, the machine learning model configured to predict a mask pattern based on the process model and a cost function that determines a difference between the predicted pattern and the target pattern.

公开(公告)号：WO2023016752A1

公开(公告)日：2023-02-16

申请号：PCT/EP2022/069967

申请日：2022-07-15

Applicant: ASML NETHERLANDS B.V.

Inventor： HSU, Duan-Fu, Stephen ,  TANG, Jialei ,  SUN, Dezheng

IPC: G03F7/20 ,  G03F1/42 ,  G03F1/44 ,  G03F9/00

Abstract: Described are embodiments for generating a design (e.g., a metrology mark or a device pattern to be printed on a substrate) that is optimized for aberration sensitivity related to an optical system of a lithography system. A metrology mark (e.g., a transmission image sensor (TIS) mark) is optimized for a given device pattern by matching the aberration sensitivity of the metrology mark with the aberration sensitivity of the device pattern. A cost function that comprises the aberration sensitivity differences between the metrology mark and the device pattern is evaluated based on imaging characteristic response (e.g., a critical dimension (CD) response to focus) obtained from simulation models that simulate lithography. The cost function is evaluated by modifying the metrology mark until the cost function is minimized and an optimized metrology mark is output when the cost function is minimized.

公开(公告)号：WO2020182440A1

公开(公告)日：2020-09-17

申请号：PCT/EP2020/054545

申请日：2020-02-20

Applicant: ASML NETHERLANDS B.V.

Inventor： HSU, Duan-Fu, Stephen ,  SUN, Dezheng

IPC: G03F7/20

Abstract: A diffraction pattern guided source mask optimization (SMO) method is described. The method comprises configuring a lithographic apparatus. The method comprises determining a source variable region from a diffraction pattern. The source variable region corresponds to one or more areas of a diffraction pattern in a pupil for which pupil variables are to be adjusted. The source variable region in the diffraction pattern comprises a plurality of pixels in an image of a selected region of interest in the diffraction pattern. Determining the source variable region comprises binarization of the plurality of pixels in the image such that individual pixels are either included in the source variable region or excluded from the source variable region. The method comprises adjusting the pupil variables for the one or more areas of the pupil that correspond to the source variable region; and rendering a final pupil based on the adjusted pupil variables.

公开(公告)号：EP4449204A1

公开(公告)日：2024-10-23

申请号：EP22822563.7

申请日：2022-11-30

Applicant: ASML Netherlands B.V.

Inventor： HSU, Duan-Fu, Stephen ,  LIU, Gerui ,  JIN, Wenjie ,  SUN, Dezheng

IPC: G03F7/20

公开(公告)号：EP4526731A1

公开(公告)日：2025-03-26

申请号：EP23724230.0

申请日：2023-05-01

Applicant: ASML Netherlands B.V.

Inventor： HSU, Duan-Fu, Stephen ,  TANG, Jialei ,  SUN, Dezheng

IPC: G03F7/00