公开(公告)号：US20220335333A1

公开(公告)日：2022-10-20

申请号：US17641159

申请日：2020-08-21

Applicant: ASML NETHERLANDS B.V.

Inventor： Yu CAO ,  Greggory SCRANTON ,  Jing SU ,  Yi ZOU

IPC: G06N20/00 ,  G03F1/36 ,  G03F7/20 ,  G06N3/04

Abstract: Methods of generating a characteristic pattern for a patterning process and training a machine learning model. A method of training a machine learning model configured to generate a characteristic pattern for a mask pattern includes obtaining (i) a reference characteristic pattern that meets a satisfactory threshold related to manufacturing of the mask pattern, and (ii) a continuous transmission mask (CTM) for use in generating the mask pattern; and training, based on the reference characteristic pattern and the CTM, the machine learning model such that a first metric between the characteristic pattern and the CTM, and a second metric between the characteristic pattern and the reference characteristic pattern is reduced.

公开(公告)号：US20250044710A1

公开(公告)日：2025-02-06

申请号：US18714547

申请日：2022-12-13

Applicant: ASML NETHERLANDS B.V.

Inventor： Jiyou FU ,  Jing SU ,  Chenxi LIN ,  Jiao LIANG ,  Guangqing CHEN ,  Yi ZOU

IPC: G03F7/00 ,  G03F9/00 ,  G06T7/00 ,  G06T7/33 ,  H01L21/66

Abstract: A method of image template matching for multiple process layers of, for example, semiconductor substrate with an adaptive weight map is described. An image template is provided with a weight map, which is adaptively updated based during template matching based on the position of the image template on the image. A method of template matching a grouped pattern or artifacts in a composed template is described, wherein the pattern comprises deemphasized areas weighted less than the image templates. A method of generating an image template based on a synthetic image is described. The synthetic image can be generated based on process and image modeling. A method of selecting a grouped pattern or artifacts and generating a composed template is described. A method of per layer image template matching is described.

公开(公告)号：US20220291590A1

公开(公告)日：2022-09-15

申请号：US17634309

申请日：2020-07-09

Applicant: ASML NETHERLANDS B.V.

Inventor： Jing SU ,  Yana CHENG ,  Zchenxi LIN ,  Yi ZOU ,  Ddavit HARUTYUNYAN ,  Emil Peter SCHMITT-WEAVER ,  Kaustuve BHATTACHARYYA ,  Cornelis Johannes Henricus LAMBREGTS ,  Hadi YAGUBIZADE

IPC: G03F7/20

Abstract: A method for determining a model to predict overlay data associated with a current substrate being patterned. The method involves obtaining (i) a first data set associated with one or more prior layers and/or current layer of the current substrate, (ii) a second data set including overlay metrology data associated with one or more prior substrates, and (iii) de-corrected measured overlay data associated with the current layer of the current substrate; and determining, based on (i) the first data set, (ii) the second data set, and (iii) the de-corrected measured overlay data, values of a set of model parameters associated with the model such that the model predicts overlay data for the current substrate, wherein the values are determined such that a cost function is minimized, the cost function comprising a difference between the predicted data and the de-corrected measured overlay data.

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

IPC: G03F1/36 ,  G06T7/00 ,  G06T7/60

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.

公开(公告)号：US20210048753A1

公开(公告)日：2021-02-18

申请号：US16976492

申请日：2019-02-28

Applicant: ASML NETHERLANDS B.V.

Inventor： Quan ZHANG ,  Been-Der CHENG ,  Rafael C. HOWELL ,  Jing SU ,  Yi ZOU ,  Yen-Wen LU

IPC: G03F7/20 ,  G03F1/36 ,  G03F1/70

Abstract: A method to determine a curvilinear pattern of a patterning device that includes obtaining (i) an initial image of the patterning device corresponding to a target pattern to be printed on a substrate subjected to a patterning process, and (ii) a process model configured to predict a pattern on the substrate from the initial image, generating, by a hardware computer system, an enhanced image from the initial image, generating, by the hardware computer system, a level set image using the enhanced image, and iteratively determining, by the hardware computer system, a curvilinear pattern for the patterning device based on the level set image, the process model, and a cost function, where the cost function (e.g., EPE) determines a difference between a predicted pattern and the target pattern, where the difference is iteratively reduced.

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

IPC: G03F1/36 ,  G06F17/50 ,  G06N20/10 ,  G05B19/4097 ,  G06K9/46 ,  G06T7/60 ,  G06T7/00

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.

公开(公告)号：US20190147127A1

公开(公告)日：2019-05-16

申请号：US16300380

申请日：2017-04-20

Applicant: ASML NETHERLANDS B.V.

Inventor： Jing SU ,  Yi ZOU ,  Chenxi LIN ,  Stefan HUNSCHE ,  Marinus JOCHEMSEN ,  Yen-Wen LU ,  Lin Lee CHEONG

IPC: G06F17/50 ,  G03F7/20 ,  G06N20/00 ,  G06T7/00

Abstract: Methods of identifying a hot spot from a design layout or of predicting whether a pattern in a design layout is defective, using a machine learning model. An example method disclosed herein includes obtaining sets of one or more characteristics of performance of hot spots, respectively, under a plurality of process conditions, respectively, in a device manufacturing process; determining, for each of the process conditions, for each of the hot spots, based on the one or more characteristics under that process condition, whether that hot spot is defective; obtaining a characteristic of each of the process conditions; obtaining a characteristic of each of the hot spots; and training a machine learning model using a training set including the characteristic of one of the process conditions, the characteristic of one of the hot spots, and whether that hot spot is defective under that process condition.

公开(公告)号：US20220277116A1

公开(公告)日：2022-09-01

申请号：US17744091

申请日：2022-05-13

Applicant: ASML NETHERLANDS B.V.

Inventor： Jing SU ,  Yi Zou ,  Chenxi Lin ,  Stefan Hunsche ,  Marinus Jochemsen ,  Yen-Wen Lu ,  Lin Lee Cheong

IPC: G06F30/20 ,  G03F7/20 ,  G06T7/00 ,  G06K9/62 ,  G06F30/398 ,  G06N20/00

Abstract: Methods of identifying a hot spot from a design layout or of predicting whether a pattern in a design layout is defective, using a machine learning model. An example method disclosed herein includes obtaining sets of one or more characteristics of performance of hot spots, respectively, under a plurality of process conditions, respectively, in a device manufacturing process; determining, for each of the process conditions, for each of the hot spots, based on the one or more characteristics under that process condition, whether that hot spot is defective; obtaining a characteristic of each of the process conditions; obtaining a characteristic of each of the hot spots; and training a machine learning model using a training set including the characteristic of one of the process conditions, the characteristic of one of the hot spots, and whether that hot spot is defective under that process condition.

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

IPC: G06N3/08 ,  G06N3/04

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.