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    Method of measuring variation, inspection system, computer program, and computer system
    1.
    发明授权
    Method of measuring variation, inspection system, computer program, and computer system 有权

    公开(公告)号：US11131936B2

    公开(公告)日：2021-09-28

    申请号：US16486169

    申请日：2018-02-07

    申请人： ASML NETHERLANDS B.V.

    发明人： Antoine Gaston Marie Kiers ,  Scott Anderson Middlebrooks ,  Jan-Willem Gemmink

    IPC分类号： G03F7/00 ,  G03F7/20 ,  G01N21/95 ,  G01N21/956 ,  G06K9/32

    摘要： Methods of measuring variation across multiple instances of a pattern on a substrate or substrates after a step in a device manufacturing process are disclosed. In one arrangement, data representing a set of images is received. Each image represents a different instance of the pattern, wherein the pattern includes a plurality of pattern elements. The set of images are registered relative to each other to superimpose the instances of the pattern. The registration includes applying different weightings to two or more of the plurality of pattern elements, wherein the weightings control the extent to which each pattern element contributes to the registration of the set of images and each weighting is based on an expected variation of the pattern element to which the weighting is applied. Variation in the pattern is measured using the registered set of images.

    METHOD TO DETERMINE THE USEFULNESS OF ALIGNMENT MARKS TO CORRECT OVERLAY, AND A COMBINATION OF A LITHOGRAPHIC APPARATUS AND AN OVERLAY MEASUREMENT SYSTEM
    6.
    发明申请
    METHOD TO DETERMINE THE USEFULNESS OF ALIGNMENT MARKS TO CORRECT OVERLAY, AND A COMBINATION OF A LITHOGRAPHIC APPARATUS AND AN OVERLAY MEASUREMENT SYSTEM 有权
    确定对准标记的有效性以纠正重叠的方法，以及一个平面设备和叠加测量系统的组合

    公开(公告)号：US20150146188A1

    公开(公告)日：2015-05-28

    申请号：US14403577

    申请日：2013-04-23

    申请人： ASML NETHERLANDS B.V.

    发明人： Irina Lyulina ,  Franciscus Godefridus Casper Bijnen ,  Remi Daniel Marie Edart ,  Antoine Gaston Marie Kiers ,  Michael Kubis

    IPC分类号： G03F7/20 ,  G01B11/14

    CPC分类号： G03F7/70141 ,  G01B11/14 ,  G03F7/70633 ,  G03F9/7046

    摘要： A method to determine the usefulness of an alignment mark of a first pattern in transferring a second pattern to a substrate relative to the first pattern already present on the substrate includes measuring the position of the alignment mark, modeling the position of the alignment mark, determining the model error between measured and modeled position, measuring a corresponding overlay error between first and second pattern and comparing the model error with the overlay error to determine the usefulness of the alignment mark. Subsequently this information can be used when processing next substrates thereby improving the overlay for these substrates. A lithographic apparatus and/or overlay measurement system may be operated in accordance with the method.

    摘要翻译： 确定第一图案的对准标记在基板上相对于已经存在于基板上的第一图案的第二图案的有用性的方法包括测量对准标记的位置，对对准标记的位置进行建模，确定 测量和建模位置之间的模型误差，测量第一和第二模式之间的对应覆盖误差，并将模型误差与覆盖误差进行比较，以确定对准标记的有用性。 随后，当处理下一个基板时，可以使用该信息，从而改善这些基板的覆盖层。 可以根据该方法操作光刻设备和/或覆盖测量系统。

    DEEP LEARNING FOR SEMANTIC SEGMENTATION OF PATTERN
    8.
    发明申请
    DEEP LEARNING FOR SEMANTIC SEGMENTATION OF PATTERN 有权

    公开(公告)号：US20220327686A1

    公开(公告)日：2022-10-13

    申请号：US17837096

    申请日：2022-06-10

    申请人： ASML NETHERLANDS B.V..

    发明人： Adrianus Cornelis Matheus KOOPMAN ,  Scott Anderson Middlebrooks ,  Antoine Gaston Marie Kiers ,  Mark John Maslow

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

    摘要： 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.

    Method to determine the usefulness of alignment marks to correct overlay, and a combination of a lithographic apparatus and an overlay measurement system
    9.
    发明授权
    Method to determine the usefulness of alignment marks to correct overlay, and a combination of a lithographic apparatus and an overlay measurement system 有权
    确定对准标记用于校正覆盖层的有用性的方法以及光刻设备和覆盖测量系统的组合

    公开(公告)号：US09454084B2

    公开(公告)日：2016-09-27

    申请号：US14403577

    申请日：2013-04-23

    申请人： ASML NETHERLANDS B.V.

    发明人： Irina Lyulina ,  Franciscus Godefridus Casper Bijnen ,  Remi Daniel Marie Edart ,  Antoine Gaston Marie Kiers ,  Michael Kubis

    IPC分类号： G03B27/42 ,  G03F7/20 ,  G03F9/00 ,  G01B11/14

    CPC分类号： G03F7/70141 ,  G01B11/14 ,  G03F7/70633 ,  G03F9/7046

    摘要： A method to determine the usefulness of an alignment mark of a first pattern in transferring a second pattern to a substrate relative to the first pattern already present on the substrate includes measuring the position of the alignment mark, modeling the position of the alignment mark, determining the model error between measured and modeled position, measuring a corresponding overlay error between first and second pattern and comparing the model error with the overlay error to determine the usefulness of the alignment mark. Subsequently this information can be used when processing next substrates thereby improving the overlay for these substrates. A lithographic apparatus and/or overlay measurement system may be operated in accordance with the method.

    摘要翻译： 确定第一图案的对准标记在基板上相对于已经存在于基板上的第一图案的第二图案的有用性的方法包括测量对准标记的位置，对对准标记的位置进行建模，确定 测量和建模位置之间的模型误差，测量第一和第二模式之间的对应覆盖误差，并将模型误差与覆盖误差进行比较，以确定对准标记的有用性。 随后，当处理下一个基板时，可以使用该信息，从而改善这些基板的覆盖层。 可以根据该方法操作光刻设备和/或覆盖测量系统。