公开(公告)号：US20170336713A1

公开(公告)日：2017-11-23

申请号：US15533309

申请日：2015-11-13

Applicant: ASML Netherlands B.V.

Inventor： Scott Anderson MIDDLEBROOKS ,  Markus Gerardus Martinus Maria VAN KRAAJI ,  Adrianus Cornelis Matheus KOOPMAN ,  Stefan HUNSCHE ,  Willem Marie Julia Marcel COENE

IPC: G03F7/20 ,  G06T7/12 ,  G06T7/60

CPC classification number: G03F7/705 ,  G03F7/70625 ,  G03F7/70633 ,  G03F7/7065 ,  G06T7/12 ,  G06T7/149 ,  G06T7/60 ,  G06T2207/10061 ,  G06T2207/20161 ,  G06T2207/30148

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.

公开(公告)号：US20210374936A1

公开(公告)日：2021-12-02

申请号：US16968966

申请日：2019-02-15

Applicant: ASML NETHERLANDS B.V.

Inventor： Adrianus Cornelis Matheus KOOPMAN ,  Scott Anderson MIDDLEBROOKS ,  Antoine Gaston Marie KIERS ,  Mark John MASLOW

IPC: G06T7/00 ,  G06K9/62 ,  G06T7/11 ,  G03F7/20 ,  G06N3/08

Abstract: A method for training a deep learning model of a patterning process. The method includes obtaining (i) training data including an input image of at least a part of a substrate having a plurality of features and including a truth image, (ii) a set of classes, each class corresponding to a feature of the plurality of features of the substrate within the input image, and (iii) a deep learning model configured to receive the training data and the set of classes, generating a predicted image, by modeling and/or simulation with the deep learning model using the input image, assigning a class of the set of classes to a feature within the predicted image based on matching of the feature with a corresponding feature within the truth image, and generating, by modeling and/or simulation, a trained deep learning model by iteratively assigning weights using a loss function.

公开(公告)号：US20210174491A1

公开(公告)日：2021-06-10

申请号：US17145033

申请日：2021-01-08

Applicant: ASML Netherlands B.V.

Inventor： Maxim PISARENCO ,  Scott Anderson MIDDLEBROOKS ,  Markus Gerardus Martinus Maria VAN KRAAIJ ,  Adrianus Cornelis Matheus KOOPMAN

IPC: G06T7/00 ,  G06T7/70 ,  G06T5/50 ,  H01J37/28 ,  H01J37/22 ,  G03F7/20

Abstract: A method for determining the existence of a defect in a printed pattern may include obtaining a) a captured image of a printed pattern from an image capture device, and b) a simulated image of the printed pattern generated by a process model. The method may include generating a combined image as a weighted combination of portions of the captured image and the simulated image. The method may include determining whether a defect exists in the printed pattern based on the combined image.

公开(公告)号：US20200257208A1

公开(公告)日：2020-08-13

申请号：US16851477

申请日：2020-04-17

Applicant: ASML Netherlands B.V.

Inventor： Scott Anderson MIDDLEBROOKS ,  Willem Maria Julia Marcel COENE ,  Frank Arnoldus Johannes Maria DRIESSEN ,  Adrianus Cornelis Matheus KOOPMAN ,  Markus Gerardus Martinus Maria VAN KRAAIJ

IPC: G03F7/20 ,  G06N7/00 ,  G06N20/00 ,  G06F30/367

Abstract: A defect prediction method for a device manufacturing process involving production substrates processed by a lithographic apparatus, the method including training a classification model using a training set including measured or determined values of a process parameter associated with the production substrates processed by the device manufacturing process and an indication regarding existence of defects associated with the production substrates processed in the device manufacturing process under the values of the process parameter, and producing an output from the classification model that indicates a prediction of a defect for a substrate.

公开(公告)号：US20200072761A1

公开(公告)日：2020-03-05

申请号：US16490091

申请日：2018-03-02

Applicant: ASML NETHERLANDS B.V.

Inventor： Adrianus Cornelis Matheus KOOPMAN ,  Scott Anderson MIDDLEBROOKS ,  Willem Marie Julia Marcel COENE

IPC: G01N21/956 ,  G03F7/20 ,  G06F17/50

Abstract: A method including selecting a shaped feature from a set of shaped features, each shaped feature of the set of shaped features having a set of points on a perimeter of the shape of the shaped feature, creating a plurality of shape context descriptors for the selected shaped feature, wherein each shape context descriptor provides an indication of a location in a shape context descriptor framework of a first focus point of the set of points in relation to a second point of the set of points, and identifying a shaped feature from the set of shaped features having a same or similar shape as the selected shaped feature based on data from the plurality of shape context descriptors.

公开(公告)号：US20160313651A1

公开(公告)日：2016-10-27

申请号：US15104517

申请日：2014-11-14

Applicant: ASML NETHERLANDS B.V.

Inventor： Scott Anderson MIDDLEBROOKS ,  Willem Maria Julia Marcel COENE ,  Frank Arnoldus Johannes Maria DRIESSEN ,  Adrianus Cornelis Matheus KOOPMAN ,  Markus Gerardus Martinus Maria VAN KRAAIJ

IPC: G03F7/20 ,  G06N7/00 ,  G06N99/00 ,  G06F17/50

Abstract: A defect prediction method for a device manufacturing process involving production substrates processed by a lithographic apparatus, the method including training a classification model using a training set including measured or determined values of a process parameter associated with the production substrates processed by the device manufacturing process and an indication regarding existence of defects associated with the production substrates processed in the device manufacturing process under the values of the process parameter, and producing an output from the classification model that indicates a prediction of a defect for a substrate.

Abstract translation: 一种涉及由光刻设备处理的生产基板的装置制造过程的缺陷预测方法，该方法包括使用包括与通过装置制造过程处理的生产基板相关联的处理参数的测量值或确定值的训练集来训练分类模型;以及 关于在处理参数的值下在器件制造过程中处理的生产基板的相关缺陷的存在的指示，以及产生指示预测基板的缺陷的分类模型的输出。