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    Scatterometry Modeling in the Presence of Undesired Diffraction Orders
    2.
    发明申请
    Scatterometry Modeling in the Presence of Undesired Diffraction Orders 审中-公开

    公开(公告)号：US20200232909A1

    公开(公告)日：2020-07-23

    申请号：US16286315

    申请日：2019-02-26

    Applicant: KLA-Tencor Corporation

    Inventor： Phillip Atkins ,  Liequan Lee ,  Shankar Krishnan ,  David C.S. Wu ,  Emily Chiu

    IPC: G01N21/25 ,  G01N21/47

    Abstract: A metrology system may receive a model for measuring one or more selected attributes of a target including features distributed in a selected pattern based on regression of spectroscopic scatterometry data from a scatterometry tool for a range of wavelengths. The metrology system may further generate a weighting function for the model to de-emphasize portions of the spectroscopic scatterometry data associated with wavelengths at which light captured by the scatterometry tool when measuring the target is predicted to include undesired diffraction orders. The metrology system may further direct the spectroscopic scatterometry tool to generate scatterometry data of one or more measurement targets including fabricated features distributed in the selected pattern. The metrology system may further measure the selected attributes for the one or more measurement targets based on regression of the scatterometry data of the one or more measurement targets to the model weighted by the weighting function.

    System, method, and computer program product for automatically determining a parameter causing an abnormal semiconductor metrology measurement
    5.
    发明授权
    System, method, and computer program product for automatically determining a parameter causing an abnormal semiconductor metrology measurement 有权

    公开(公告)号：US10393647B1

    公开(公告)日：2019-08-27

    申请号：US14578245

    申请日：2014-12-19

    Applicant: KLA-Tencor Corporation

    Inventor： Qiang Jimmy Zhao ,  Liequan Lee ,  Jonathan Ian Iloreta ,  Hong Qiu ,  Leonid Poslavsky

    IPC: G01N21/25

    Abstract: A system, method, and computer program product are provided for automatically determining a parameter causing an abnormal semiconductor metrology measurement. In use, an abnormal semiconductor metrology measurement measured from a fabricated semiconductor component is received. At least one parameter of the fabricated semiconductor component causing the abnormal semiconductor metrology measurement is then automatically determined by one or more hardware processors. In particular, the one or more hardware processors determine a subset of parameters of the fabricated semiconductor component as potential sources of the abnormal semiconductor metrology measurement, rank the parameters in the determined subset of parameters, select an Nth number of the parameters in the determined subset of parameters in accordance with the ranking, and then analyze each of the selected parameters to identify one or more of the selected parameters as the at least one parameter of the fabricated semiconductor component causing the abnormal semiconductor metrology measurement.

    LIBRARY EXPANSION SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR METROLOGY
    6.
    发明申请
    LIBRARY EXPANSION SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR METROLOGY 审中-公开
    图书馆扩展系统，方法和计算机程序产品

    公开(公告)号：US20150330770A1

    公开(公告)日：2015-11-19

    申请号：US14710462

    申请日：2015-05-12

    Applicant: KLA-Tencor Corporation

    Inventor： Leonid Poslavsky ,  Liequan Lee

    IPC: G01B11/02 ,  G01B11/00

    CPC classification number: G01B11/02 ,  G01B11/00 ,  G01B21/04 ,  G01N21/211 ,  G01N21/9501 ,  G01N21/95607 ,  G01N2021/213 ,  G01N2021/95615 ,  G03F7/70625

    Abstract: A library expansion system, method, and computer program product for metrology are provided. In use, processing within a first multi-dimensional library is performed by a metrology system. During the processing within the first multi-dimensional library, a second multi-dimensional library is identified. The processing is then transitioned to the second multi-dimensional library. Further, processing within the second multi-dimensional library is performed by the metrology system.

    Abstract translation: 提供了图书馆扩展系统，方法和计算机程序产品。 在使用中，第一多维库中的处理由计量系统执行。 在第一多维库中的处理期间，识别第二个多维库。 然后处理过渡到第二个多维库。 此外，第二多维库中的处理由计量系统执行。

    Scatterometry modeling in the presence of undesired diffraction orders
    7.
    发明授权
    Scatterometry modeling in the presence of undesired diffraction orders 有权

    公开(公告)号：US11422095B2

    公开(公告)日：2022-08-23

    申请号：US16286315

    申请日：2019-02-26

    Applicant: KLA-Tencor Corporation

    Inventor： Phillip Atkins ,  Liequan Lee ,  Shankar Krishnan ,  David C. S. Wu ,  Emily Chiu

    IPC: G01N21/956 ,  G01N21/25 ,  G01N21/47 ,  G03F7/20 ,  G01N21/95

    Abstract: A metrology system may receive a model for measuring one or more selected attributes of a target including features distributed in a selected pattern based on regression of spectroscopic scatterometry data from a scatterometry tool for a range of wavelengths. The metrology system may further generate a weighting function for the model to de-emphasize portions of the spectroscopic scatterometry data associated with wavelengths at which light captured by the scatterometry tool when measuring the target is predicted to include undesired diffraction orders. The metrology system may further direct the spectroscopic scatterometry tool to generate scatterometry data of one or more measurement targets including fabricated features distributed in the selected pattern. The metrology system may further measure the selected attributes for the one or more measurement targets based on regression of the scatterometry data of the one or more measurement targets to the model weighted by the weighting function.

    Automatic optimization of measurement accuracy through advanced machine learning techniques
    8.
    发明授权
    Automatic optimization of measurement accuracy through advanced machine learning techniques 有权

    公开(公告)号：US11380594B2

    公开(公告)日：2022-07-05

    申请号：US15903693

    申请日：2018-02-23

    Applicant: KLA-TENCOR CORPORATION

    Inventor： Tianrong Zhan ,  Yin Xu ,  Liequan Lee

    IPC: H01L21/66 ,  G06N3/04 ,  G01N21/88 ,  G01N21/95 ,  G06N3/08

    Abstract: Machine learning techniques are used to predict values of fixed parameters when given reference values of critical parameters. For example, a neural network can be trained based on one or more critical parameters and a low-dimensional real-valued vector associated with a spectrum, such as a spectroscopic ellipsometry spectrum or a specular reflectance spectrum. Another neural network can map the low-dimensional real-valued vector. When using two neural networks, one neural network can be trained to map the spectra to the low-dimensional real-valued vector. Another neural network can be trained to predict the fixed parameter based on the critical parameters and the low-dimensional real-valued vector from the other neural network.

    Multi-model metrology
    9.
    发明授权
    Multi-model metrology 有权
    多模式计量

    公开(公告)号：US09412673B2

    公开(公告)日：2016-08-09

    申请号：US14459516

    申请日：2014-08-14

    Applicant: KLA-Tencor Corporation

    Inventor： In-Kyo Kim ,  Xin Li ,  Leonid Poslavsky ,  Liequan Lee ,  Meng Cao ,  Sungchul Yoo ,  Andrei V. Shchegrov ,  Sangbong Park

    IPC: G06F17/50 ,  H01L21/66 ,  G03F7/20

    CPC classification number: H01L22/20 ,  G03F7/70616 ,  G03F7/70625 ,  G06F17/5068 ,  H01L21/67288 ,  H01L22/12

    Abstract: Disclosed are apparatus and methods for characterizing a plurality of structures of interest on a semiconductor wafer. A plurality of models having varying combinations of floating and fixed critical parameters and corresponding simulated spectra is generated. Each model is generated to determine one or more critical parameters for unknown structures based on spectra collected from such unknown structures. It is determined which one of the models best correlates with each critical parameter based on reference data that includes a plurality of known values for each of a plurality of critical parameters and corresponding known spectra. For spectra obtained from an unknown structure using a metrology tool, different ones of the models are selected and used to determine different ones of the critical parameters of the unknown structure based on determining which one of the models best correlates with each critical parameter based on the reference data.

    Abstract translation: 公开了用于在半导体晶片上表征感兴趣的多个结构的装置和方法。 产生具有浮动和固定关键参数和对应的模拟光谱的变化组合的多个模型。 生成每个模型以基于从这样的未知结构收集的光谱来确定未知结构的一个或多个关键参数。 基于包括多个关键参数和相应的已知光谱中的每一个的多个已知值的参考数据，确定哪一个模型与每个关键参数最佳相关。 对于使用计量工具从未知结构获得的光谱，选择不同的模型并且用于基于确定哪一个模型与每个关键参数最相关的来确定未知结构的关键参数的不同的参数 参考数据。

    MULTI-MODEL METROLOGY
    10.
    发明申请
    MULTI-MODEL METROLOGY 有权
    多模式计量学

    公开(公告)号：US20150058813A1

    公开(公告)日：2015-02-26

    申请号：US14459516

    申请日：2014-08-14

    Applicant: KLA-Tencor Corporation

    Inventor： In-Kyo Kim ,  Xin Li ,  Leonid Poslavsky ,  Liequan Lee ,  Meng Cao ,  Sungchul Yoo ,  Andrei V. Shchegrov ,  Sangbong Park

    IPC: G06F17/50

    CPC classification number: H01L22/20 ,  G03F7/70616 ,  G03F7/70625 ,  G06F17/5068 ,  H01L21/67288 ,  H01L22/12

    Abstract: Disclosed are apparatus and methods for characterizing a plurality of structures of interest on a semiconductor wafer. A plurality of models having varying combinations of floating and fixed critical parameters and corresponding simulated spectra is generated. Each model is generated to determine one or more critical parameters for unknown structures based on spectra collected from such unknown structures. It is determined which one of the models best correlates with each critical parameter based on reference data that includes a plurality of known values for each of a plurality of critical parameters and corresponding known spectra. For spectra obtained from an unknown structure using a metrology tool, different ones of the models are selected and used to determine different ones of the critical parameters of the unknown structure based on determining which one of the models best correlates with each critical parameter based on the reference data.

    Abstract translation: 公开了用于在半导体晶片上表征感兴趣的多个结构的装置和方法。 产生具有浮动和固定关键参数和对应的模拟光谱的变化组合的多个模型。 生成每个模型以基于从这样的未知结构收集的光谱来确定未知结构的一个或多个关键参数。 基于包括多个关键参数和相应的已知光谱中的每一个的多个已知值的参考数据，确定哪一个模型与每个关键参数最佳相关。 对于使用计量工具从未知结构获得的光谱，选择不同的模型并且用于基于确定哪一个模型与每个关键参数最相关的来确定未知结构的关键参数的不同的参数 参考数据。

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