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公开(公告)号：US20220284344A1
公开(公告)日：2022-09-08
申请号：US17631557
申请日：2020-07-30
Applicant: ASML NETHERLANDS B.V.
Inventor： Ziyang MA , Jin CHENG , Ya LUO , Leiwu ZHENG , Xin GUO , Jen-Shiang WANG
IPC: G06N20/00
Abstract: A method for training a machine learning model configured to predict values of a physical characteristic associated with a substrate and for use in adjusting a patterning process. The method involves obtaining a reference image; determining a first set of model parameter values of the machine learning model such that a first cost function is reduced from an initial value of the cost function obtained using an initial set of model parameter values, where the first cost function is a difference between the reference image and an image generated via the machine learning model; and training, using the first set of model parameter values, the machine learning model such that a combination of the first cost function and a second cost function is iteratively reduced, the second cost function representing a difference between measured values and predicted values.
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2.发明申请公开(公告)号：US20200012196A1
公开(公告)日：2020-01-09
申请号：US16483452
申请日：2018-02-13
Applicant: ASML NETHERLANDS B.V.
Inventor： Peng LIU , Ya LUO , Yu CAO , Yen-Wen LU
Abstract: A method including: obtaining a characteristic of a portion of a design layout; determining a characteristic of M3D of a patterning device including or forming the portion; and training, by a computer, a neural network using training data including a sample whose feature vector includes the characteristic of the portion and whose supervisory signal includes the characteristic of the M3D. Also disclosed is a method including: obtaining a characteristic of a portion of a design layout; obtaining a characteristic of a lithographic process that uses a patterning device including or forming the portion; determining a characteristic of a result of the lithographic process; training, by a computer, a neural network using training data including a sample whose feature vector includes the characteristic of the portion and the characteristic of the lithographic process, and whose supervisory signal includes the characteristic of the result.
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公开(公告)号：US20220299881A1
公开(公告)日：2022-09-22
申请号：US17636103
申请日：2020-08-01
Applicant: ASML NETHERLANDS B.V.
Inventor： Yunan ZHENG , Yongfa FAN , Mu FENG , Leiwu ZHENG , Jen-Shiang WANG , Ya LUO , Chenji ZHANG , Jun CHEN , Zhenyu HOU , Jinze WANG , Feng CHEN , Ziyang MA , Xin GUO , Jin CHENG
IPC: G03F7/20
Abstract: A method for generating modified contours and/or generating metrology gauges based on the modified contours. A method of generating metrology gauges for measuring a physical characteristic of a structure on a substrate includes obtaining (i) measured data associated with the physical characteristic of the structure printed on the substrate, and (ii) at least portion of a simulated contour of the structure, the at least a portion of the simulated contour being associated with the measured data; modifying, based on the measured data, the at least a portion of the simulated contour of the structure; and generating the metrology gauges on or adjacent to the modified at least a portion of the simulated contour, the metrology gauges being placed to measure the physical characteristic of the simulated contour of the structure.
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Patent Agency Ranking
公开(公告)号：US20220327364A1
公开(公告)日：2022-10-13
申请号：US17638472
申请日：2020-07-31
Applicant: ASML NETHERLANDS B.V.
Inventor： Stefan HUNSCHE , Fuming WANG , Ya LUO , Pioter NIKOLSKI
Abstract: Systems and methods for predicting substrate geometry associated with a patterning process are described. Input information including geometry information and/or process information for a pattern is received and, using a machine learning prediction model, multi-dimensional output substrate geometry is predicted. The multi-dimensional output information may include pattern probability images. A stochastic edge placement error band and/or a stochastic failure rate may be predicted. The input information can include simulated aerial images, simulated resist images, target substrate dimensions, and/or data from a lithography apparatus associated with device manufacturing. Different aerial images may correspond to different heights in resist layers associated with the patterning process, for example.
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公开(公告)号：US20220179321A1
公开(公告)日：2022-06-09
申请号：US17442662
申请日：2020-03-05
Applicant: ASML NETHERLANDS B.V.
Inventor： Ziyang MA , Jin CHENG , Ya LUO , Leiwu ZHENG , Xin GUO , Jen-Shiang WANG , Yongfa FAN , Feng CHEN , Yi-Yin CHEN , Chenji ZHANG , Yen- Wen LU
Abstract: A method for training a patterning process model, the patterning process model configured to predict a pattern that will be formed by a patterning process. The method involves obtaining an image data associated with a desired pattern, a measured pattern of the substrate, a first model including a first set of parameters, and a machine learning model including a second set of parameters; and iteratively determining values of the first set of parameters and the second set of parameters to train the patterning process model. An iteration involves executing, using the image data, the first model and the machine learning model to cooperatively predict a printed pattern of the substrate; and modifying the values of the first set of parameters and the second set of parameters such that a difference between the measured pattern and the predicted pattern is reduced.
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公开(公告)号：US20200380362A1
公开(公告)日：2020-12-03
申请号：US16970648
申请日：2019-02-20
Applicant: ASML NETHERLANDS B.V.
Inventor： Yu CAO , Ya LUO , Yen-Wen LU , Been-Der CHEN , Rafael C. HOWELL , Yi ZOU , Jing SU , Dezheng SUN
Abstract: Methods of training machine learning models related to a patterning process, including 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 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.
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7.发明申请公开(公告)号：US20220137503A1
公开(公告)日：2022-05-05
申请号：US17429770
申请日：2020-01-24
Applicant: ASML NETHERLANDS B.V.
Inventor： Jun TAO , Stanislas Hugo Louis BARON , Jing SU , Ya LUO , Yu CAO
Abstract: Training methods and a mask correction method. One of the methods is for training a machine learning model configured to predict a post optical proximity correction (OPC) image for a mask. The method involves obtaining (i) a pre-OPC image associated with a design layout to be printed on a substrate, (ii) an image of one or more assist features for the mask associated with the design layout, and (iii) a reference post-OPC image of the design layout; and training the machine learning model using the pre-OPC image and the image of the one or more assist features as input such that a difference between the reference image and a predicted post-OPC image of the machine learning model is reduced.
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公开(公告)号：US20200050099A1
公开(公告)日：2020-02-13
申请号：US16606791
申请日：2018-05-04
Applicant: ASML NETHERLANDS B.V.
Inventor： Jing SU , Yi ZOU , Chenxi LIN , Yu CAO , Yen-Wen LU , Been-Der CHEN , Quan ZHANG , Stanislas Hugo Louis BARON , Ya LUO
Abstract: A method including: obtaining a portion of a design layout; determining characteristics of assist features based on the portion or characteristics of the portion; and training a machine learning model using training data including a sample whose feature vector includes the characteristics of the portion and whose label includes the characteristics of the assist features. The machine learning model may be used to determine characteristics of assist features of any portion of a design layout, even if that portion is not part of the training data.
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