公开(公告)号：US10725386B2

公开(公告)日：2020-07-28

申请号：US16421697

申请日：2019-05-24

Applicant: ASML Netherlands B.V.

Inventor： Scott Anderson Middlebrooks ,  Niels Geypen ,  Hendrik Jan Hidde Smilde ,  Alexander Straaijer ,  Maurits Van Der Schaar ,  Markus Gerardus Martinus Maria Van Kraaij

IPC: G03F7/20

Abstract: Disclosed is a method of measuring a parameter of a lithographic process, and associated inspection apparatus. The method comprises measuring at least two target structures on a substrate using a plurality of different illumination conditions, the target structures having deliberate overlay biases; to obtain for each target structure an asymmetry measurement representing an overall asymmetry that includes contributions due to (i) the deliberate overlay biases, (ii) an overlay error during forming of the target structure and (iii) any feature asymmetry. A regression analysis is performed on the asymmetry measurement data by fitting a linear regression model to a planar representation of asymmetry measurements for one target structure against asymmetry measurements for another target structure, the linear regression model not necessarily being fitted through an origin of the planar representation. The overlay error can then be determined from a gradient described by the linear regression model.

公开(公告)号：US10274834B2

公开(公告)日：2019-04-30

申请号：US15915674

申请日：2018-03-08

Applicant: ASML Netherlands B.V.

Inventor： Alexander Ypma ,  Jasper Menger ,  David Deckers ,  David Han ,  Adrianus Cornelis Matheus Koopman ,  Irina Lyulina ,  Scott Anderson Middlebrooks ,  Richard Johannes Franciscus Van Haren ,  Jochem Sebastiaan Wildenberg

IPC: G03F7/20 ,  G06F16/26 ,  G03F9/00

Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in said multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.

公开(公告)号：US09910366B2

公开(公告)日：2018-03-06

申请号：US14906896

申请日：2014-07-18

Applicant: ASML Netherlands B.V.

Inventor： Scott Anderson Middlebrooks ,  Niels Geypen ,  Hendrik Jan Hidde Smilde ,  Alexander Straaijer ,  Maurits Van Der Schaar ,  Markus Gerardus Martinus Maria Van Kraaij

IPC: G03F7/20

CPC classification number: G03F7/70633

Abstract: Disclosed is a method of measuring a parameter of a lithographic process, and associated inspection apparatus. The method comprises measuring at least two target structures on a substrate using a plurality of different illumination conditions, the target structures having deliberate overlay biases; to obtain for each target structure an asymmetry measurement representing an overall asymmetry that includes contributions due to (i) the deliberate overlay biases, (ii) an overlay error during forming of the target structure and (iii) any feature asymmetry. A regression analysis is performed on the asymmetry measurement data by fitting a linear regression model to a planar representation of asymmetry measurements for one target structure against asymmetry measurements for another target structure, the linear regression model not necessarily being fitted through an origin of the planar representation. The overlay error can then be determined from a gradient described by the linear regression model.

公开(公告)号：US20240019788A1

公开(公告)日：2024-01-18

申请号：US18232570

申请日：2023-08-10

Applicant: ASML Netherlands B.V.

Inventor： Alexander Ypma ,  Jasper Menger ,  David Deckers ,  David Han ,  Adrianus Cornelis Matheus Koopman ,  Irina Lyulina ,  Scott Anderson Middlebrooks ,  Richard Johannes Franciscus Van Haren ,  Jochem Sebastiaan Wildenberg

IPC: G03F7/00

CPC classification number: G03F7/706837 ,  G03F7/70525 ,  G03F7/70616 ,  G06F16/26

Abstract: In a lithographic process, product units such as semiconductor wafers are subjected to lithographic patterning operations and chemical and physical processing operations. Alignment data or other measurements are made at stages during the performance of the process to obtain object data representing positional deviation or other parameters measured at points spatially distributed across each unit. This object data is used to obtain diagnostic information by performing a multivariate analysis to decompose a set of vectors representing the units in the multidimensional space into one or more component vectors. Diagnostic information about the industrial process is extracted using the component vectors. The performance of the industrial process for subsequent product units can be controlled based on the extracted diagnostic information.

公开(公告)号：US11847570B2

公开(公告)日：2023-12-19

申请号：US17837096

申请日：2022-06-10

Applicant: ASML NETHERLANDS B.V.

Inventor： Adrianus Cornelis Matheus Koopman ,  Scott Anderson Middlebrooks ,  Antoine Gaston Marie Kiers ,  Mark John Maslow

IPC: G06N3/08 ,  G06N3/084 ,  G06T7/11 ,  G03F7/00 ,  G06T7/00 ,  G06F18/214 ,  G06F18/2431 ,  G06F18/2413 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06N3/084 ,  G03F7/705 ,  G06F18/214 ,  G06F18/2431 ,  G06F18/24133 ,  G06N3/08 ,  G06T7/0004 ,  G06T7/11 ,  G06V10/764 ,  G06V10/82 ,  G06T2207/30148

Abstract: A method for training a deep learning model of a patterning process. The method includes obtaining (i) training data comprising an input image of at least a part of a substrate having a plurality of features and 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 of 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：US11625520B2

公开(公告)日：2023-04-11

申请号：US16763376

申请日：2018-11-29

Applicant: ASML NETHERLANDS B.V.

Inventor： Chrysostomos Batistakis ,  Scott Anderson Middlebrooks ,  Sander Frederik Wuister

IPC: G06F7/50 ,  G06F30/28 ,  G03F7/20 ,  G06F119/14

Abstract: A method involving obtaining a resist deformation model for simulating a deformation process of a pattern in resist, the resist deformation model being a fluid dynamics model configured to simulate an intrafluid force acting on the resist, performing, using the resist deformation model, a computer simulation of the deformation process to obtain a deformation of the developed resist pattern for an input pattern to the resist deformation model, and producing electronic data representing the deformation of the developed resist pattern for the input pattern.

公开(公告)号：US11379970B2

公开(公告)日：2022-07-05

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 ,  G06T7/11 ,  G03F7/20 ,  G06K9/62 ,  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：US20210405545A1

公开(公告)日：2021-12-30

申请号：US17471363

申请日：2021-09-10

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 ,  G06N20/00 ,  G06F30/367 ,  G06N7/00

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：US10890540B2

公开(公告)日：2021-01-12

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: G06F30/398 ,  G01N21/956 ,  G03F7/20

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：US10607334B2

公开(公告)日：2020-03-31

申请号：US15533614

申请日：2015-11-13

Applicant: ASML Netherlands B.V.

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

IPC: G06T7/00 ,  G03F7/20

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.