Reduction or elimination of pattern placement error in metrology measurements

    公开(公告)号:US11537043B2

    公开(公告)日:2022-12-27

    申请号:US17161645

    申请日:2021-01-28

    Abstract: Metrology methods and targets are provided for reducing or eliminating a difference between a device pattern position and a target pattern position while maintaining target printability, process compatibility and optical contrast—in both imaging and scatterometry metrology. Pattern placement discrepancies may be reduced by using sub-resolved assist features in the mask design which have a same periodicity (fine pitch) as the periodic structure and/or by calibrating the measurement results using PPE (pattern placement error) correction factors derived by applying learning procedures to specific calibration terms, in measurements and/or simulations. Metrology targets are disclosed with multiple periodic structures at the same layer (in addition to regular target structures), e.g., in one or two layers, which are used to calibrate and remove PPE, especially when related to asymmetric effects such as scanner aberrations, off-axis illumination and other error sources.

    Determining the impacts of stochastic behavior on overlay metrology data

    公开(公告)号:US10901325B2

    公开(公告)日:2021-01-26

    申请号:US15763662

    申请日:2018-02-27

    Abstract: Methods are provided for designing metrology targets and estimating the uncertainty error of metrology metric values with respect to stochastic noise such as line properties (e.g., line edge roughness, LER). Minimal required dimensions of target elements may be derived from analysis of the line properties and uncertainty error of metrology measurements, by either CDSEM (critical dimension scanning electron microscopy) or optical systems, with corresponding targets. The importance of this analysis is emphasized in view of the finding that stochastic noise may have increased importance with when using more localized models such as CPE (correctables per exposure). The uncertainty error estimation may be used for target design, enhancement of overlay estimation and evaluation of measurement reliability in multiple contexts.

    REDUCTION OR ELIMINATION OF PATTERN PLACEMENT ERROR IN METROLOGY MEASUREMENTS

    公开(公告)号:US20230099105A1

    公开(公告)日:2023-03-30

    申请号:US18076375

    申请日:2022-12-06

    Abstract: Metrology methods and targets are provided for reducing or eliminating a difference between a device pattern position and a target pattern position while maintaining target printability, process compatibility and optical contrast—in both imaging and scatterometry metrology. Pattern placement discrepancies may be reduced by using sub-resolved assist features in the mask design which have a same periodicity (fine pitch) as the periodic structure and/or by calibrating the measurement results using PPE (pattern placement error) correction factors derived by applying learning procedures to specific calibration terms, in measurements and/or simulations. Metrology targets are disclosed with multiple periodic structures at the same layer (in addition to regular target structures), e.g., in one or two layers, which are used to calibrate and remove PPE, especially when related to asymmetric effects such as scanner aberrations, off-axis illumination and other error sources.

    REDUCTION OR ELIMINATION OF PATTERN PLACEMENT ERROR IN METROLOGY MEASUREMENTS

    公开(公告)号:US20210149296A1

    公开(公告)日:2021-05-20

    申请号:US17161645

    申请日:2021-01-28

    Abstract: Metrology methods and targets are provided for reducing or eliminating a difference between a device pattern position and a target pattern position while maintaining target printability, process compatibility and optical contrast—in both imaging and scatterometry metrology. Pattern placement discrepancies may be reduced by using sub-resolved assist features in the mask design which have a same periodicity (fine pitch) as the periodic structure and/or by calibrating the measurement results using PPE (pattern placement error) correction factors derived by applying learning procedures to specific calibration terms, in measurements and/or simulations. Metrology targets are disclosed with multiple periodic structures at the same layer (in addition to regular target structures), e.g., in one or two layers, which are used to calibrate and remove PPE, especially when related to asymmetric effects such as scanner aberrations, off-axis illumination and other error sources.

    METHODS OF ANALYZING AND UTILIZING LANDSCAPES TO REDUCE OR ELIMINATE INACCURACY IN OVERLAY OPTICAL METROLOGY
    10.
    发明申请
    METHODS OF ANALYZING AND UTILIZING LANDSCAPES TO REDUCE OR ELIMINATE INACCURACY IN OVERLAY OPTICAL METROLOGY 审中-公开
    分析和利用景观以减少或消除在重叠光学计量学中不精确的方法

    公开(公告)号:US20160313658A1

    公开(公告)日:2016-10-27

    申请号:US15198902

    申请日:2016-06-30

    Abstract: Methods are provided for deriving a partially continuous dependency of metrology metric(s) on recipe parameter(s), analyzing the derived dependency, determining a metrology recipe according to the analysis, and conducting metrology measurement(s) according to the determined recipe. The dependency may be analyzed in form of a landscape such as a sensitivity landscape in which regions of low sensitivity and/or points or contours of low or zero inaccuracy are detected, analytically, numerically or experimentally, and used to configure parameters of measurement, hardware and targets to achieve high measurement accuracy. Process variation is analyzed in terms of its effects on the sensitivity landscape, and these effects are used to characterize the process variation further, to optimize the measurements and make the metrology both more robust to inaccuracy sources and more flexible with respect to different targets on the wafer and available measurement conditions.

    Abstract translation: 提供了用于导出计量度量对配方参数的部分连续依赖性的方法,分析衍生依赖性,根据分析确定计量配方,并根据确定的配方进行计量测量。 依赖性可以以景观的形式进行分析,例如灵敏度景观,其中检测到低分辨率或零误差的低灵敏度和/或点或等值线的区域,分析,数字或实验,并用于配置测量参数,硬件 并达到高测量精度。 根据其对灵敏度景观的影响分析过程变化,并且这些效应用于进一步表征过程变化,优化测量结果,使计量学对于不准确性来源更加鲁棒,并且对于不同的目标更灵活 晶圆和可用的测量条件。

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