-
11.发明申请公开(公告)号：US20220373892A1
公开(公告)日：2022-11-24
申请号：US17882389
申请日：2022-08-05
Applicant: ASML NETHERLANDS B.V.
Inventor： Yu CAO , Yen-Wen LU , : Peng LIU , Rafael C. HOWELL , Roshni BISWAS
IPC: G03F7/20
Abstract: A method including: obtaining a thin-mask transmission function of a patterning device and a M3D model for a lithographic process, wherein the thin-mask transmission function is a continuous transmission mask (CTM) and the M3D model at least represents a portion of M3D attributable to multiple edges of structures on the patterning device; determining a M3D mask transmission function of the patterning device by using the thin-mask transmission function and the M3D model; and determining an aerial image produced by the patterning device and the lithographic process, by using the M3D mask transmission function.
-
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
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
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
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：US20140351772A1
公开(公告)日：2014-11-27
申请号：US14456462
申请日：2014-08-11
Applicant: ASML NETHERLANDS B.V.
Inventor： Taihui LIU , Been-Der CHEN , Yen-Wen LU
IPC: G06F17/50
CPC classification number: G06F17/5081 , G03F1/70 , G06F17/50
Abstract: Described herein is a method of processing a pattern layout for a lithographic process, the method comprising: identifying a feature from a plurality of features of the layout, the feature violating a pattern layout requirement; and reconfiguring the feature, wherein the reconfigured feature still violates the pattern layout requirement, the reconfiguring including evaluating a cost function that measures a lithographic metric affected by a change to the feature and a parameter characteristic of relaxation of the pattern layout requirement.
Abstract translation: 这里描述了一种处理光刻处理的图案布局的方法，该方法包括：从布局的多个特征中识别特征，所述特征违反图案布局要求; 并且重新配置所述特征，其中所述重新配置的特征仍然违反所述图案布局要求，所述重新配置包括评估测量受所述特征的改变影响的光刻度量的成本函数以及所述图案布局要求的松弛的参数特征。
-
公开(公告)号：US20220404712A1
公开(公告)日：2022-12-22
申请号：US17772529
申请日：2020-10-01
Applicant: ASML NETHERLANDS B.V.
Inventor： Qiang ZHANG , Yunbo GUO , Yu CAO , Jen-Shiang WANG , Yen-Wen LU , Danwu CHEN , Pengcheng YANG , Haoyi LIANG , Zhichao CHEN , Lingling PU
IPC: G03F7/20 , G06V10/774 , G06V10/82 , G06T7/32 , G06T7/33
Abstract: A method for training a machine learning model to generate a predicted measured image, the method including obtaining (a) an input target image associated with a reference design pattern, and (b) a reference measured image associated with a specified design pattern printed on a substrate, wherein the input target image and the reference measured image are non-aligned images; and training, by a hardware computer system and using the input target image, the machine learning model to generate a predicted measured image.
-
17.发明申请
公开(公告)号：US20210271173A1
公开(公告)日：2021-09-02
申请号：US17326481
申请日：2021-05-21
Applicant: ASML NETHERLANDS B.V.
Inventor： Yu CAO , Yen-Wen LU , Peng LIU , Rafael C. HOWELL , Roshni BISWAS
IPC: G03F7/20
Abstract: A method including: obtaining a thin-mask transmission function of a patterning device and a M3D model for a lithographic process, wherein the thin-mask transmission function is a continuous transmission mask (CTM) and the M3D model at least represents a portion of M3D attributable to multiple edges of structures on the patterning device; determining a M3D mask transmission function of the patterning device by using the thin-mask transmission function and the M3D model; and determining an aerial image produced by the patterning device and the lithographic process, by using the M3D mask transmission function.
-
公开(公告)号：US20210208510A1
公开(公告)日：2021-07-08
申请号：US16463430
申请日：2017-11-24
Applicant: ASML NETHERLANDS B.V.
Inventor： Yen-Wen LU , Xiaorui CHEN , Yang LIN
IPC: G03F7/20 , G05B19/418
Abstract: A method of controlling a computer process for designing or verifying a photolithographic component includes building a source tree including nodes of the process, including dependency relationships among the nodes, defining, for some nodes, at least two different process conditions, expanding the source tree to form an expanded tree, including generating a separate node for each different defined process condition, and duplicating dependent nodes having an input relationship to each generated separate node, determining respective computing hardware requirements for processing the node, selecting computer hardware constraints based on capabilities of the host computing system, determining, based on the requirements and constraints and on dependency relations in the expanded tree, an execution sequence for the computer process, and performing the computer process on the computing system.
-
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.
-
公开(公告)号：US20180089359A1
公开(公告)日：2018-03-29
申请号：US15821051
申请日：2017-11-22
Applicant: ASML NETHERLANDS B.V.
Inventor： Frank Gang CHEN , Joseph Werner DE VOCHT , Yuelin DU , Wanyu LI , Yen-Wen LU
Abstract: Disclosed herein is a computer-implemented method for determining an overlapping process window (OPW) of an area of interest on a portion of a design layout for a device manufacturing process for imaging the portion onto a substrate, the method including: obtaining a plurality of features in the area of interest; obtaining a plurality of values of one or more processing parameters of the device manufacturing process; determining existence of defects, probability of the existence of defects, or both in imaging the plurality of features by the device manufacturing process under each of the plurality of values; and determining the OPW of the area of interest from the existence of defects, the probability of the existence of defects, or both.
