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公开(公告)号：US20160161245A1
公开(公告)日：2016-06-09
申请号：US14960121
申请日：2015-12-04
Applicant: KLA-Tencor Corporation
Inventor： Jiyou Fu , Noam Sapiens , Kevin A. Peterlinz , Stilian Ivanov Pandev
CPC classification number: G01B11/002 , G01B11/24 , G01B2210/56 , G01N21/956 , G01N2021/213 , G03F7/00
Abstract: A spectroscopic beam profile metrology system simultaneously detects measurement signals over a large wavelength range and a large range of angles of incidence (AOI). In one aspect, a multiple wavelength illumination beam is reshaped to a narrow line shaped beam of light before projection onto a specimen by a high numerical aperture objective. After interaction with the specimen, the collected light is passes through a wavelength dispersive element that projects the range of AOIs along one direction and wavelength components along another direction of a two-dimensional detector. Thus, the measurement signals detected at each pixel of the detector each represent a scatterometry signal for a particular AOI and a particular wavelength. In another aspect, a hyperspectral detector is employed to simultaneously detect measurement signals over a large wavelength range, range of AOIs, and range of azimuth angles.
Abstract translation: 分光光束分布测量系统同时检测大波长范围和大范围入射角（AOI）的测量信号。 在一个方面，多波长照明光束在通过高数值孔径物镜投影到样本上之前重新成形为窄线形的光束。 在与样品相互作用后，所收集的光通过沿着一个方向投影AOI范围的波长色散元件，并沿着二维检测器的另一方向波长成分。 因此，在检测器的每个像素处检测的测量信号各自表示用于特定AOI和特定波长的散射测量信号。 另一方面，采用高光谱检测器来同时检测大波长范围，AOI范围和方位角范围内的测量信号。
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公开(公告)号：US20160109375A1
公开(公告)日：2016-04-21
申请号：US14882370
申请日：2015-10-13
Applicant: KLA-Tencor Corporation
Inventor： Stilian Ivanov Pandev , Wei Lu , Andrei V. Shchegrov , Pablo Rovira , Jonathan M. Madsen
IPC: G01N21/88
CPC classification number: G01N21/956 , G01N21/93
Abstract: Methods and systems for measuring metrology targets smaller than the illumination spot size employed to perform the measurement are described herein. Collected measurement signals contaminated with information from structures surrounding the target area are reconstructed to eliminate the contamination. In some examples, measurement signals associated one or more small targets and one or more large targets located in close proximity to one another are used to train a signal reconstruction model. The model is subsequently used to reconstruct measurement signals from other small targets. In some other examples, multiple measurements of a small target at different locations within the target are de-convolved to estimate target area intensity. Reconstructed measurement signals are determined by a convolution of the illumination spot profile and the target area intensity. In a further aspect, the reconstructed signals are used to estimate values of parameters of interest associated with the measured structures.
Abstract translation: 本文描述了用于测量小于用于执行测量的照明点尺寸的度量目标的方法和系统。 重建被污染源自目标区域周围结构信息的收集的测量信号，以消除污染。 在一些示例中，使用与一个或多个小目标相关联的测量信号和彼此靠近彼此靠近的一个或多个大目标来训练信号重建模型。 该模型随后用于重建来自其他小目标的测量信号。 在一些其他示例中，目标内不同位置处的小目标的多次测量被去卷积以估计目标区域强度。 重建的测量信号由照明光斑轮廓和目标区域强度的卷积确定。 在另一方面，重建的信号用于估计与测量结构相关联的感兴趣参数的值。
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公开(公告)号：US09255877B2
公开(公告)日：2016-02-09
申请号：US14278224
申请日：2014-05-15
Applicant: KLA-Tencor Corporation
Inventor： Andrei Veldman , Andrei V. Shchegrov , Gregory Brady , Thaddeus Gerard Dziura , Stilian Ivanov Pandev , Alexander Kuznetsov
CPC classification number: G01N21/211 , G01B11/0625 , G01B11/0641 , G01B2210/56 , G01N21/9501 , G01N2021/213
Abstract: Methods and systems for evaluating the capability of a measurement system to track measurement parameters through a given process window are presented herein. Performance evaluations include random perturbations, systematic perturbations, or both to effectively characterize the impact of model errors, metrology system imperfections, and calibration errors, among others. In some examples, metrology target parameters are predetermined as part of a Design of Experiments (DOE). Estimated values of the metrology target parameters are compared to the known DOE parameter values to determine the tracking capability of the particular measurement. In some examples, the measurement model is parameterized by principal components to reduce the number of degrees of freedom of the measurement model. In addition, exemplary methods and systems for optimizing the measurement capability of semiconductor metrology systems for metrology applications subject to process variations are presented.
Abstract translation: 本文介绍了用于评估测量系统通过给定过程窗口跟踪测量参数的能力的方法和系统。 性能评估包括随机扰动，系统扰动或两者，以有效表征模型误差，计量系统缺陷和校准误差等的影响。 在一些示例中，度量目标参数被预先确定为实验设计（DOE）的一部分。 将度量目标参数的估计值与已知的DOE参数值进行比较，以确定特定测量的跟踪能力。 在一些示例中，测量模型由主要组件参数化，以减少测量模型的自由度数。 此外，提出了用于优化用于受过程变化的度量应用的半导体测量系统的测量能力的示例性方法和系统。
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14.发明申请APPARATUS, TECHNIQUES, AND TARGET DESIGNS FOR MEASURING SEMICONDUCTOR PARAMETERS 有权用于测量半导体参数的设备，技术和目标设计公开(公告)号：US20150323471A1
公开(公告)日：2015-11-12
申请号：US14708058
申请日：2015-05-08
Applicant: KLA-Tencor Corporation
Inventor： Noam Sapiens , Andrei V. Shchegrov , Stilian Ivanov Pandev
IPC: G01N21/956 , G01N21/95 , G01N21/93 , G01B11/00
CPC classification number: G01N21/93 , G01B2210/56 , G01N21/4788 , G01N21/9501 , G01N21/95607 , G01N2201/06113 , G01N2201/062 , G01N2201/10 , G01N2201/1296
Abstract: In one embodiment, apparatus and methods for determining a parameter of a target are disclosed. A target having an imaging structure and a scatterometry structure is provided. An image of the imaging structure is obtained with an imaging channel of a metrology tool. A scatterometry signal is also obtained from the scatterometry structure with a scatterometry channel of the metrology tool. At least one parameter, such as overlay error, of the target is determined based on both the image and the scatterometry signal.
Abstract translation: 在一个实施例中，公开了用于确定目标的参数的装置和方法。 提供具有成像结构和散射测量结构的目标。 使用计量工具的成像通道获得成像结构的图像。 散射测量信号也通过散度仪结构与计量工具的散射测量通道获得。 基于图像和散射测量信号确定目标的至少一个参数，例如重叠误差。
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公开(公告)号：US10345095B1
公开(公告)日：2019-07-09
申请号：US14947510
申请日：2015-11-20
Applicant: KLA-Tencor Corporation
Inventor： Stilian Ivanov Pandev , Leonid Poslavsky , Dzmitry Sanko , Andrei V. Shchegrov
Abstract: Methods and systems for solving measurement models of complex device structures with reduced computational effort are presented. In some embodiments, a measurement signal transformation model is employed to compute transformed measurement signals from coarse measurement signals. The transformed measurement signals more closely approximate a set of measured signals than the coarse measurement signals. However, the coarse set of measured signals are computed with less computational effort than would be required to directly compute measurement signals that closely approximate the set of measured signals. In other embodiments, a measurement signal transformation model is employed to compute transformed measurement signals from actual measured signals. The transformed measurement signals more closely approximate the coarse measurement signals than the actual measured signals. Transformed measurement signals are subsequently used for regression, library generation, or other analyses typically employed as part of an effort to characterize structural, material, and process parameters in semiconductor manufacturing.
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Patent Agency Ranking
公开(公告)号：US10101670B2
公开(公告)日：2018-10-16
申请号：US14223045
申请日：2014-03-24
Applicant: KLA-Tencor Corporation
Inventor： Stilian Ivanov Pandev , Jonathan M. Madsen
Abstract: Methods and systems for creating a measurement model based on measured training data are presented. The trained measurement model is used to calculate process parameter values, structure parameter values, or both, directly from measured data collected from other wafers. The measurement models receive measurement data directly as input and provide process parameter values, structure parameter values, or both, as output. The measurement model enables the direct measurement of process parameters. Measurement data from multiple targets is collected for model building, training, and measurement. In some examples, the use of measurement data associated with multiple targets eliminates, or significantly reduces, the effect of under layers in the measurement result, and enables more accurate measurements. Measurement data collected for model building, training, and measurement, may be derived from measurements performed by a combination of multiple, different measurement techniques.
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公开(公告)号：US09816810B2
公开(公告)日：2017-11-14
申请号：US15268217
申请日：2016-09-16
Applicant: KLA-Tencor Corporation
Inventor： Andrei V. Shchegrov , Shankar Krishnan , Kevin Peterlinz , Thaddeus Gerard Dziura , Noam Sapiens , Stilian Ivanov Pandev
CPC classification number: G01B11/272 , G01B2210/56 , G03F7/0002 , G03F7/70141 , G03F7/70625 , H01L22/12 , H01L22/30
Abstract: Methods and systems for evaluating the performance of multiple patterning processes are presented. Patterned structures are measured and one or more parameter values characterizing geometric errors induced by the multiple patterning process are determined. In some examples, a single patterned target and a multiple patterned target are measured, the collected data fit to a combined measurement model, and the value of a structural parameter indicative of a geometric error induced by the multiple patterning process is determined based on the fit. In some other examples, light having a diffraction order different from zero is collected and analyzed to determine the value of a structural parameter that is indicative of a geometric error induced by a multiple patterning process. In some embodiments, a single diffraction order different from zero is collected. In some examples, a metrology target is designed to enhance light diffracted at an order different from zero.
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公开(公告)号：US09721055B2
公开(公告)日：2017-08-01
申请号：US14478746
申请日：2014-09-05
Applicant: KLA-Tencor Corporation
Inventor： Stilian Ivanov Pandev
CPC classification number: G06F17/5081 , H01L22/12 , H01L22/20 , H01L2924/0002 , H01L2924/00
Abstract: An optimized measurement model is determined based a model of parameter variations across a semiconductor wafer. A global, cross-wafer model characterizes a structural parameter as a function of location on the wafer. A measurement model is optimized by constraining the measurement model with the cross-wafer model of process variations. In some examples, the cross-wafer model is itself a parameterized model. However, the cross-wafer model characterizes the values of a structural parameter at any location on the wafer with far fewer parameters than a measurement model that treats the structural parameter as unknown at every location. In some examples, the cross-wafer model gives rise to constraints among unknown structural parameter values based on location on the wafer. In one example, the cross-wafer model relates the values of structural parameters associated with groups of measurement sites based on their location on the wafer.
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公开(公告)号：US20170061604A1
公开(公告)日：2017-03-02
申请号：US15230339
申请日：2016-08-05
Applicant: KLA-Tencor Corporation
Inventor： Stilian Ivanov Pandev
CPC classification number: G06T7/0004 , G03F7/70625 , G03F7/70633 , G06K9/522 , G06K9/624 , G06K9/6247 , G06K9/6269 , G06K9/6282 , G06T2207/20081 , G06T2207/30148 , H04N5/2256 , H04N17/002
Abstract: Methods and systems for combining information present in measured images of semiconductor wafers with additional measurements of particular structures within the measured images are presented herein. In one aspect, an image-based signal response metrology (SRM) model is trained based on measured images and corresponding reference measurements of particular structures within each image. The trained, image-based SRM model is then used to calculate values of one or more parameters of interest directly from measured image data collected from other wafers. In another aspect, a measurement signal synthesis model is trained based on measured images and corresponding measurement signals generated by measurements of particular structures within each image by a non-imaging measurement technique. Images collected from other wafers are transformed into synthetic measurement signals associated with the non-imaging measurement technique and a model-based measurement is employed to estimate values of parameters of interest based on the synthetic signals.
Abstract translation: 在本文中给出了将存在于半导体晶片的测量图像中的信息与测量图像内的特定结构的附加测量结合的方法和系统。 在一个方面，基于图像的信号响应度量（SRM）模型基于测量的图像和每个图像内的特定结构的对应的参考测量来训练。 然后使用经过训练的基于图像的SRM模型来从其他晶片收集的测量图像数据直接计算一个或多个感兴趣的参数的值。 在另一方面，基于测量图像和通过非成像测量技术在每个图像内的特定结构的测量产生的相应测量信号来训练测量信号合成模型。 从其他晶片收集的图像被转换成与非成像测量技术相关联的合成测量信号，并且基于模型的测量被用于基于合成信号来估计感兴趣参数的值。
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公开(公告)号：US20170003123A1
公开(公告)日：2017-01-05
申请号：US15268217
申请日：2016-09-16
Applicant: KLA-Tencor Corporation
Inventor： Andrei V. Shchegrov , Shankar Krishnan , Kevin Peterlinz , Thaddeus Gerard Dziura , Noam Sapiens , Stilian Ivanov Pandev
CPC classification number: G01B11/272 , G01B2210/56 , G03F7/0002 , G03F7/70141 , G03F7/70625 , H01L22/12 , H01L22/30
Abstract: Methods and systems for evaluating the performance of multiple patterning processes are presented. Patterned structures are measured and one or more parameter values characterizing geometric errors induced by the multiple patterning process are determined. In some examples, a single patterned target and a multiple patterned target are measured, the collected data fit to a combined measurement model, and the value of a structural parameter indicative of a geometric error induced by the multiple patterning process is determined based on the fit. In some other examples, light having a diffraction order different from zero is collected and analyzed to determine the value of a structural parameter that is indicative of a geometric error induced by a multiple patterning process. In some embodiments, a single diffraction order different from zero is collected. In some examples, a metrology target is designed to enhance light diffracted at an order different from zero.
Abstract translation: 提出了评估多个图案化工艺性能的方法和系统。 测量图案化结构，并确定表征由多重图案化工艺引起的几何误差的一个或多个参数值。 在一些示例中，测量单个图案化靶和多个图案化靶，所收集的数据拟合到组合测量模型，并且基于拟合来确定指示由多次图案化工艺引起的几何误差的结构参数的值 。 在一些其它示例中，收集并分析具有不同于零的衍射级的光，以分析其结果参数的值，该结构参数指示由多重图案化工艺引起的几何误差。 在一些实施例中，收集不同于零的单个衍射级。 在一些示例中，度量目标被设计为增强以不同于零的顺序衍射的光。
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