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    PROCESS WINDOW OPTIMIZER
    12.
    发明申请
    PROCESS WINDOW OPTIMIZER 有权

    公开(公告)号：US20220147665A1

    公开(公告)日：2022-05-12

    申请号：US17586856

    申请日：2022-01-28

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Stefan Hunsche ,  Venugopal Vellanki

    IPC: G06F30/20 ,  H01L21/66 ,  G03F7/20

    Abstract: A defect prediction method for a device manufacturing process involving processing a pattern onto a substrate, the method comprising: identifying a processing window limiting pattern (PWLP) from the pattern; determining a processing parameter under which the PWLP is processed; and determining or predicting, using the processing parameter, existence, probability of existence, a characteristic, or a combination thereof, of a defect produced from the PWLP with the device manufacturing process.

    Process window based on defect probability
    13.
    发明授权
    Process window based on defect probability 有权

    公开(公告)号：US11079687B2

    公开(公告)日：2021-08-03

    申请号：US16955483

    申请日：2018-12-17

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Abraham Slachter ,  Stefan Hunsche ,  Wim Tjibbo Tel ,  Anton Bernhard Van Oosten ,  Koenraad Van Ingen Schenau ,  Gijsbert Rispens ,  Brennan Peterson

    IPC: G03F7/20

    Abstract: A method including obtaining (i) measurements of a parameter of the feature, (ii) data related to a process variable of a patterning process, (iii) a functional behavior of the parameter defined as a function of the process variable based on the measurements of the parameter and the data related to the process variable, (iv) measurements of a failure rate of the feature, and (v) a probability density function of the process variable for a setting of the process variable, converting the probability density function of the process variable to a probability density function of the parameter based on a conversion function, where the conversion function is determined based on the function of the process variable, and determining a parameter limit of the parameter based on the probability density function of the parameter and the measurements of the failure rate.

    Method and apparatus for image analysis
    14.
    发明授权
    Method and apparatus for image analysis 有权

    公开(公告)号：US10732513B2

    公开(公告)日：2020-08-04

    申请号：US16561096

    申请日：2019-09-05

    Applicant: ASML Netherlands B.V.

    Inventor： Scott Anderson Middlebrooks ,  Markus Gerardus Martinus Maria Van Kraaij ,  Adrianus Cornelis Matheus Koopman ,  Stefan Hunsche ,  Willem Marie Julia Marcel Coene

    IPC: G03B27/32 ,  G03F7/20 ,  G06T7/12 ,  G06T7/149 ,  G06T7/60

    Abstract: A method and apparatus of detection, registration and quantification of an image. The method may include obtaining an image of a lithographically created structure, and applying a level set method to an object, representing the structure, of the image to create a mathematical representation of the structure. The method may include obtaining a first dataset representative of a reference image object of a structure at a nominal condition of a parameter, and obtaining second dataset representative of a template image object of the structure at a non-nominal condition of the parameter. The method may further include obtaining a deformation field representative of changes between the first dataset and the second dataset. The deformation field may be generated by transforming the second dataset to project the template image object onto the reference image object. A dependence relationship between the deformation field and change in the parameter may be obtained.

    Inspection Apparatus and Methods, Substrates Having Metrology Targets, Lithographic System and Device Manufacturing Method
    15.
    发明申请
    Inspection Apparatus and Methods, Substrates Having Metrology Targets, Lithographic System and Device Manufacturing Method 审中-公开

    公开(公告)号：US20180239263A1

    公开(公告)日：2018-08-23

    申请号：US15961377

    申请日：2018-04-24

    Applicant: ASML Netherlands B.V.

    Inventor： Simon Gijsbert Josephus Mathijssen ,  Stefan Hunsche ,  Markus Gerardus Martinus Maria Van Kraaij

    IPC: G03F7/20 ,  G03F7/213 ,  G03F7/22

    Abstract: Disclosed is an inspection apparatus for use in lithography. It comprises a support for a substrate carrying a plurality of metrology targets; an optical system for illuminating the targets under predetermined illumination conditions and for detecting predetermined portions of radiation diffracted by the targets under the illumination conditions; a processor arranged to calculate from said detected portions of diffracted radiation a measurement of asymmetry for a specific target; and a controller for causing the optical system and processor to measure asymmetry in at least two of said targets which have different known components of positional offset between structures and smaller sub-structures within a layer on the substrate and calculate from the results of said asymmetry measurements a measurement of a performance parameter of the lithographic process for structures of said smaller size. Also disclosed are substrates provided with a plurality of novel metrology targets formed by a lithographic process.

    METHOD FOR PROCESS WINDOW OPTIMIZED OPTICAL PROXIMITY CORRECTION
    17.
    发明申请
    METHOD FOR PROCESS WINDOW OPTIMIZED OPTICAL PROXIMITY CORRECTION 有权
    用于处理窗口优化光学近似校正的方法

    公开(公告)号：US20130219348A1

    公开(公告)日：2013-08-22

    申请号：US13854872

    申请日：2013-04-01

    Applicant: ASML Netherlands B.V.

    Inventor： Jun YE ,  Jiangwei Li ,  Stefan Hunsche

    IPC: G06F17/50

    CPC classification number: G06F17/50 ,  G03F1/144 ,  G03F1/36

    Abstract: One embodiment of a method for process window optimized optical proximity correction includes applying optical proximity corrections to a design layout, simulating a lithography process using the post-OPC layout and models of the lithography process at a plurality of process conditions to produce a plurality of simulated resist images. A weighted average error in the critical dimension or other contour metric for each edge segment of each feature in the design layout is determined, wherein the weighted average error is an offset between the contour metric at each process condition and the contour metric at nominal condition averaged over the plurality of process conditions. A retarget value for the contour metric for each edge segment is determined using the weighted average error and applied to the design layout prior to applying further optical proximity corrections.

    Abstract translation: 用于处理窗口优化的光学邻近校正的方法的一个实施例包括将光学邻近校正应用于设计布局，使用后OPC布局模拟光刻处理和在多个工艺条件下的光刻工艺的模型，以产生多个模拟 抵抗图像。 确定设计布局中每个特征的每个边缘段的临界尺寸或其他轮廓度量的加权平均误差，其中加权平均误差是在每个处理条件下的轮廓度量与标称条件下的轮廓度量之间的偏移平均 在多个工艺条件下。 使用加权平均误差确定每个边缘段的轮廓度量的重定向值，并在应用进一步的光学邻近校正之前应用于设计布局。

    Identification of hot spots or defects by machine learning
    20.
    发明授权
    Identification of hot spots or defects by machine learning 有权

    公开(公告)号：US11443083B2

    公开(公告)日：2022-09-13

    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: G06T7/00 ,  G06F30/20 ,  G03F7/20 ,  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.

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