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    METHODS OF DETERMINING SCATTERING OF RADIATION BY STRUCTURES OF FINITE THICKNESSES ON A PATTERNING DEVICE
    11.
    发明申请
    METHODS OF DETERMINING SCATTERING OF RADIATION BY STRUCTURES OF FINITE THICKNESSES ON A PATTERNING DEVICE 审中-公开

    公开(公告)号：US20200012196A1

    公开(公告)日：2020-01-09

    申请号：US16483452

    申请日：2018-02-13

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Peng LIU ,  Ya LUO ,  Yu CAO ,  Yen-Wen LU

    IPC: G03F7/20 ,  G06N3/08 ,  G06F17/50

    Abstract: A method including: obtaining a characteristic of a portion of a design layout; determining a characteristic of M3D of a patterning device including or forming the portion; and training, by a computer, a neural network using training data including a sample whose feature vector includes the characteristic of the portion and whose supervisory signal includes the characteristic of the M3D. Also disclosed is a method including: obtaining a characteristic of a portion of a design layout; obtaining a characteristic of a lithographic process that uses a patterning device including or forming the portion; determining a characteristic of a result of the lithographic process; training, by a computer, a neural network using training data including a sample whose feature vector includes the characteristic of the portion and the characteristic of the lithographic process, and whose supervisory signal includes the characteristic of the result.

    METHODS AND SYSTEMS FOR PARAMETER-SENSITIVE AND ORTHOGONAL GAUGE DESIGN FOR LITHOGRAPHY CALIBRATION
    12.
    发明申请
    METHODS AND SYSTEMS FOR PARAMETER-SENSITIVE AND ORTHOGONAL GAUGE DESIGN FOR LITHOGRAPHY CALIBRATION 有权
    参数敏感和正交测量设计的方法和系统进行LITHOGRAPHY校准

    公开(公告)号：US20150186557A1

    公开(公告)日：2015-07-02

    申请号：US14589738

    申请日：2015-01-05

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Jun YE ,  Yu CAO ,  Hanying FENG ,  Wenjin SHAO

    IPC: G06F17/50 ,  G06F17/10

    CPC classification number: G06F17/50 ,  G03F1/14 ,  G03F1/44 ,  G03F1/68 ,  G03F7/70433 ,  G03F7/705 ,  G06F17/10 ,  G06F17/5009

    Abstract: Methods according to the present invention provide computationally efficient techniques for designing gauge patterns for calibrating a model for use in a simulation process. More specifically, the present invention relates to methods of designing gauge patterns that achieve complete coverage of parameter variations with minimum number of gauges and corresponding measurements in the calibration of a lithographic process utilized to image a target design having a plurality of features. According to some aspects, a method according to the invention includes transforming the space of model parametric space (based on CD sensitivity or Delta TCCs), then iteratively identifying the direction that is most orthogonal to existing gauges' CD sensitivities in this new space, and determining most sensitive line width/pitch combination with optimal assist feature placement which leads to most sensitive CD changes along that direction in model parametric space.

    Abstract translation: 根据本发明的方法提供了用于设计用于校准用于模拟过程中的模型的计量模式的计算上有效的技术。 更具体地说，本发明涉及设计规格图案的方法，该图形模式可以用最小数量的量规完成覆盖参数变化，并且在用于对具有多个特征的目标设计进行成像的光刻处理的校准中的对应测量。 根据一些方面，根据本发明的方法包括改变模型参数空间的空间（基于CD灵敏度或Delta TCC），然后迭代地识别在该新空间中与现有计量器的CD灵敏度最正交的方向，以及 确定最敏感的线宽/间距组合与最佳辅助功能放置，导致在模型参数空间中沿着该方向的最敏感的CD变化。

    MODEL-BASED SCANNER TUNING SYSTEMS AND METHODS
    13.
    发明申请
    MODEL-BASED SCANNER TUNING SYSTEMS AND METHODS 审中-公开
    基于模型的扫描仪调谐系统和方法

    公开(公告)号：US20150045935A1

    公开(公告)日：2015-02-12

    申请号：US14525704

    申请日：2014-10-28

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Yu CAO ,  Wenjin SHAO ,  Ronaldus Johannes Gijsbertus GOOSSENS ,  Jun YE ,  James Patrick KOONMEN

    IPC: B29C67/00

    CPC classification number: B29C64/386 ,  G03F7/70091 ,  G03F7/70458 ,  G03F7/705 ,  G03F7/70516 ,  G03F7/70525 ,  G06F17/50 ,  G06F17/5009 ,  G06F17/5081

    Abstract: Systems and methods for tuning photolithographic processes are described. A model of a target scanner is maintained defining sensitivity of the target scanner with reference to a set of tunable parameters. A differential model represents deviations of the target scanner from the reference. The target scanner may be tuned based on the settings of the reference scanner and the differential model. Performance of a family of related scanners may be characterized relative to the performance of a reference scanner. Differential models may include information such as parametric offsets and other differences that may be used to simulate the difference in imaging behavior.

    Abstract translation: 描述用于调整光刻工艺的系统和方法。 保持目标扫描仪的型号，参考一组可调谐参数来定义目标扫描仪的灵敏度。 差分模型表示目标扫描器与参考值的偏差。 可以基于参考扫描仪和差分模型的设置来调整目标扫描仪。 可以相对于参考扫描仪的性能来表征相关扫描仪系列的性能。 差分模型可能包括诸如参数偏移和可能用于模拟成像行为差异的其他差异的信息。

    METHOD FOR DETERMINING A MASK PATTERN COMPRISING OPTICAL PROXIMITY CORRECTIONS USING A TRAINED MACHINE LEARNING MODEL
    15.
    发明申请
    METHOD FOR DETERMINING A MASK PATTERN COMPRISING OPTICAL PROXIMITY CORRECTIONS USING A TRAINED MACHINE LEARNING MODEL 有权

    公开(公告)号：US20230100578A1

    公开(公告)日：2023-03-30

    申请号：US17796751

    申请日：2021-02-04

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Yu CAO ,  Jun TAO ,  Quan ZHANG ,  Yongsheng SHU ,  Wei-chun FONG

    IPC: G03F1/36 ,  G06N3/0464 ,  G03F7/20

    Abstract: A method for determining a mask pattern and a method for training a machine learning model. The method for determining a mask pattern includes obtaining, via executing a model using a target pattern to be printed on a substrate as an input pattern, a post optical proximity correction (post-OPC) pattern; determining, based on the post-OPC pattern, a simulated pattern that will be printed on the substrate; and determining the mask pattern based on a difference between the simulated pattern and the target pattern. The determining of the mask pattern includes modifying, based on the difference, the input pattern inputted to the model such that the difference is reduced; and executing, using the modified input pattern, the model to generate a modified post-OPC pattern from which the mask pattern can be derived.

    THREE-DIMENSIONAL MASK MODEL FOR PHOTOLITHOGRAPHY SIMULATION
    18.
    发明申请
    THREE-DIMENSIONAL MASK MODEL FOR PHOTOLITHOGRAPHY SIMULATION 有权

    公开(公告)号：US20210064811A1

    公开(公告)日：2021-03-04

    申请号：US17097106

    申请日：2020-11-13

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Peng LIU ,  Yu CAO ,  Luoqi CHEN ,  Jun YE

    IPC: G06F30/398 ,  G03F7/20 ,  G06F30/30 ,  G03F1/76 ,  G03F1/50

    Abstract: A three-dimensional mask model that provides a more realistic approximation of the three-dimensional effects of a photolithography mask with sub-wavelength features than a thin-mask model. In one embodiment, the three-dimensional mask model includes a set of filtering kernels in the spatial domain that are configured to be convolved with thin-mask transmission functions to produce a near-field image. In another embodiment, the three-dimensional mask model includes a set of correction factors in the frequency domain that are configured to be multiplied by the Fourier transform of thin-mask transmission functions to produce a near-field image.

    METHOD FOR DETERMINING MASK PATTERN AND TRAINING MACHINE LEARNING MODEL
    20.
    发明公开
    METHOD FOR DETERMINING MASK PATTERN AND TRAINING MACHINE LEARNING MODEL 审中-公开

    公开(公告)号：US20240004305A1

    公开(公告)日：2024-01-04

    申请号：US18039697

    申请日：2021-12-02

    Applicant: ASML NETHERLANDS B.V.

    Inventor： Jun TAO ,  Yu CAO ,  Christopher Alan SPENCE

    IPC: G03F7/00 ,  G03F1/36

    CPC classification number: G03F7/70283 ,  G03F1/36

    Abstract: A method for determining a mask pattern and a method for training a machine learning model. The method for generating data for a mask pattern associated with a patterning process includes obtaining (i) a first mask image (e.g., CTM) associated with a design pattern, (ii) a contour (e.g., a resist contour) based on the first mask image, (iii) a reference contour (e.g., an ideal resist contour) based on the design pattern; and (iv) a contour difference between the contour and the reference contour. The contour difference and the first mask image are inputted to a model to generate mask image modification data. Based on the first mask image and the mask image modification data, a second mask image is generated for determining a mask pattern to be employed in the patterning process.

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