公开(公告)号：US20160109230A1

公开(公告)日：2016-04-21

申请号：US14879534

申请日：2015-10-09

Applicant: KLA-Tencor Corporation

Inventor： Stilian Ivanov Pandev ,  Dzmitry Sanko ,  Alexander Kuznetsov

IPC: G01B11/27 ,  G01B11/14

CPC classification number: G01B11/272 ,  G01B11/14 ,  G01B11/24 ,  G01B2210/56

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 primary, multiple patterned target is measured and a value of a parameter of interest is directly determined from the measured data by a Signal Response Metrology (SRM) measurement model. In some other examples, a primary, multiple patterned target and an assist target are measured and a value of a parameter of interest is directly determined from the measured data by a Signal Response Metrology (SRM) measurement model. In some other examples, a primary, multiple patterned target is measured at different process steps and a value of a parameter of interest is directly determined from the measured data by a Signal Response Metrology (SRM) measurement model.

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，测量主要的多个图案化靶，并且通过信号响应计量（SRM）测量模型从测量数据直接确定感兴趣的参数的值。 在一些其他示例中，测量主要，多重图案化目标和辅助目标，并且通过信号响应计量（SRM）测量模型从所测量的数据直接确定感兴趣参数的值。 在一些其他示例中，在不同的工艺步骤测量主要的多重图案化靶，并且通过信号响应计量（SRM）测量模型从所测量的数据直接确定感兴趣的参数的值。

公开(公告)号：US20150046118A1

公开(公告)日：2015-02-12

申请号：US14453440

申请日：2014-08-06

Applicant: KLA-Tencor Corporation

Inventor： Stilian Ivanov Pandev ,  Andrei V. Shchegrov

IPC: G01N21/95 ,  G01B11/02 ,  G01B11/24

CPC classification number: G03F7/70641 ,  G01N21/956 ,  G03F7/70625 ,  H01L22/12 ,  H01L22/30

Abstract: Disclosed are apparatus and methods for determining process or structure parameters for semiconductor structures. A plurality of optical signals is acquired from one or more targets located in a plurality of fields on a semiconductor wafer. The fields are associated with different process parameters for fabricating the one or more targets, and the acquired optical signals contain information regarding a parameter of interest (POI) for a top structure and information regarding one or more underlayer parameters for one or more underlayers formed below such top structure. A feature extraction model is generated to extract a plurality of feature signals from such acquired optical signals so that the feature signals contain information for the POI and exclude information for the underlayer parameters. A POI value for each top structure of each field is determined based on the feature signals extracted by the feature extraction model.

Abstract translation: 公开了用于确定半导体结构的工艺或结构参数的装置和方法。 从位于半导体晶片上的多个场中的一个或多个靶获取多个光信号。 这些场与用于制造一个或多个目标的不同过程参数相关联，并且所获取的光学信号包含关于顶部结构的关注参数（POI）的信息以及关于下面形成的一个或多个底层的一个或多个底层参数的信息 这样的顶级结构。 生成特征提取模型以从所获取的光信号中提取多个特征信号，使得特征信号包含POI的信息，并且排除下层参数的信息。 基于由特征提取模型提取的特征信号来确定每个场的每个顶部结构的POI值。

公开(公告)号：US20140379281A1

公开(公告)日：2014-12-25

申请号：US14478746

申请日：2014-09-05

Applicant: KLA-Tencor Corporation

Inventor： Stilian Ivanov Pandev

IPC: G06F17/50

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.

Abstract translation: 基于半导体晶片上的参数变化的模型来确定优化的测量模型。 全球的跨晶圆模型将结构参数表征为晶片上位置的函数。 通过使用工艺变化的跨晶圆模型约束测量模型来优化测量模型。 在一些示例中，跨晶片模型本身是参数化模型。 然而，跨晶圆模型将晶片上任何位置的结构参数的值表示为具有比在每个位置处理结构参数为未知的测量模型少的参数的参数。 在一些示例中，跨晶片模型基于晶片上的位置引起未知结构参数值中的约束。 在一个示例中，跨晶片模型基于它们在晶片上的位置来关联与测量位置组相关联的结构参数的值。

公开(公告)号：US20140316730A1

公开(公告)日：2014-10-23

申请号：US14252323

申请日：2014-04-14

Applicant: KLA-Tencor Corporation

Inventor： Andrei V. Shchegrov ,  Jonathan M. Madsen ,  Stilian Ivanov Pandev ,  Ady Levy ,  Daniel Kandel ,  Michael E. Adel ,  Ori Tadmor

IPC: H01L21/66

CPC classification number: H01L22/12 ,  H01L22/20 ,  H01L22/30 ,  H01L2924/0002 ,  H01L2924/00

Abstract: Methods and systems for performing semiconductor metrology directly on device structures are presented. A measurement model is created based on measured training data collected from at least one device structure. The trained measurement model is used to calculate process parameter values, structure parameter values, or both, directly from measurement data collected from device structures of other wafers. In some examples, 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.

Abstract translation: 提出了直接在器件结构上执行半导体测量的方法和系统。 基于从至少一个设备结构收集的测量训练数据创建测量模型。 训练后的测量模型用于直接从其他晶圆的器件结构收集的测量数据中计算过程参数值，结构参数值或两者。 在一些示例中，收集来自多个目标的测量数据用于模型构建，训练和测量。 在一些示例中，使用与多个目标相关联的测量数据消除或显着降低测量结果中下层的影响，并且能够进行更精确的测量。 用于模型建立，训练和测量收集的测量数据可以通过多种不同测量技术的组合进行的测量得出。

公开(公告)号：US20130305206A1

公开(公告)日：2013-11-14

申请号：US13887357

申请日：2013-05-05

Applicant: KLA-TENCOR CORPORATION

Inventor： Stilian Ivanov Pandev

IPC: G06F17/50

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.

Abstract translation: 基于半导体晶片上的参数变化的模型来确定优化的测量模型。 全球的跨晶圆模型将结构参数表征为晶片上位置的函数。 通过使用工艺变化的跨晶圆模型约束测量模型来优化测量模型。 在一些示例中，跨晶片模型本身是参数化模型。 然而，跨晶圆模型将晶片上任何位置的结构参数的值表示为具有比在每个位置处理结构参数为未知的测量模型少的参数的参数。 在一些示例中，跨晶片模型基于晶片上的位置引起未知结构参数值中的约束。 在一个示例中，跨晶片模型基于它们在晶片上的位置来关联与测量位置组相关联的结构参数的值。

公开(公告)号：US20130304408A1

公开(公告)日：2013-11-14

申请号：US13887524

申请日：2013-05-06

Applicant: KLA-TENCOR CORPORATION

Inventor： Stilian Ivanov Pandev

IPC: H01L21/66

CPC classification number: H01L22/20 ,  G01B11/24 ,  G01B2210/56 ,  H01L22/12 ,  H01L2924/0002 ,  H01L2924/00

Abstract: An optimized measurement recipe is determined by reducing the set of measurement technologies and ranges of machine parameters required to achieve a satisfactory measurement result. The reduction in the set of measurement technologies and ranges of machine parameters is based on available process variation information and spectral sensitivity information associated with an initial measurement model. The process variation information and spectral sensitivity information are used to determine a second measurement model having fewer floating parameters and less correlation among parameters. Subsequent measurement analysis is performed using the second, constrained model and a set of measurement data corresponding to a reduced set of measurement technologies and ranges of machine parameters. The results of the subsequent measurement analysis are compared with reference measurement results to determine if a difference between the estimated parameter values and the parameter values derived from the reference measurement is within a predetermined threshold.

Abstract translation: 通过减少测量技术的集合和实现令人满意的测量结果所需的机器参数的范围来确定优化的测量配方。 测量技术和机器参数范围的减少是基于与初始测量模型相关联的可用过程变化信息和光谱灵敏度信息。 过程变化信息和光谱灵敏度信息用于确定具有较少浮动参数和参数之间相关性较小的第二测量模型。 使用第二约束模型和对应于减少的测量技术集合和机器参数范围的一组测量数据来执行随后的测量分析。 将后续测量分析的结果与参考测量结果进行比较，以确定估计参数值与从参考测量得到的参数值之间的差是否在预定阈值内。

公开(公告)号：US11313809B1

公开(公告)日：2022-04-26

申请号：US15587297

申请日：2017-05-04

Applicant: KLA-Tencor Corporation

Inventor： Stilian Ivanov Pandev ,  Wei Lu

IPC: G01N21/95 ,  H01L21/66 ,  H01L21/67

Abstract: Methods and systems for estimating values of process parameters based on measurements of structures fabricated on a product wafer are presented herein. Exemplary process parameters include lithography dosage and exposure and lithography scanner aberrations. A measurement model is employed to estimate process parameter values from measurements of structures fabricated on a wafer by a particular fabrication process. The measurement model includes process parameters and geometric parameters of structures under measurement. In some embodiments, a model based regression of both a process model and a metrology model is employed to arrive at estimates of at least one process parameter value based on measurements of a fabricated structure. In some embodiments, a trained measurement model is employed to directly estimate process parameter values based on measurements of structures. The measurement model is trained based on simulated measurement signals associated with measurements of shape profiles generated by different sets of process parameter values.

公开(公告)号：US10801953B2

公开(公告)日：2020-10-13

申请号：US16245695

申请日：2019-01-11

Applicant: KLA-Tencor Corporation

Inventor： David Y. Wang ,  Alexander Buettner ,  Stilian Ivanov Pandev ,  Emanuel Saerchen ,  Andrei V. Shchegrov ,  Barry Blasenheim

IPC: G01J3/28 ,  G01N21/3563 ,  H01L21/66 ,  G01N21/21

Abstract: Methods and systems for performing semiconductor measurements based on hyperspectral imaging are presented herein. A hyperspectral imaging system images a wafer over a large field of view with high pixel density over a broad range of wavelengths. Image signals collected from a measurement area are detected at a number of pixels. The detected image signals from each pixel are spectrally analyzed separately. In some embodiments, the illumination and collection optics of a hyperspectral imaging system include fiber optical elements to direct illumination light from the illumination source to the measurement area on the surface of the specimen under measurement and fiber optical elements to image the measurement area. In another aspect, a fiber optics collector includes an image pixel mapper that couples a two dimensional array of collection fiber optical elements into a one dimensional array of pixels at the spectrometer and the hyperspectral detector.

公开(公告)号：US20200225151A1

公开(公告)日：2020-07-16

申请号：US16245695

申请日：2019-01-11

Applicant: KLA-Tencor Corporation

Inventor： David Y. Wang ,  Alexander Buettner ,  Stilian Ivanov Pandev ,  Emanuel Saerchen ,  Andrei V. Shchegrov ,  Barry Blasenheim

IPC: G01N21/3563 ,  G01J3/28 ,  H01L21/66 ,  G01N21/21

Abstract: Methods and systems for performing semiconductor measurements based on hyperspectral imaging are presented herein. A hyperspectral imaging system images a wafer over a large field of view with high pixel density over a broad range of wavelengths. Image signals collected from a measurement area are detected at a number of pixels. The detected image signals from each pixel are spectrally analyzed separately. In some embodiments, the illumination and collection optics of a hyperspectral imaging system include fiber optical elements to direct illumination light from the illumination source to the measurement area on the surface of the specimen under measurement and fiber optical elements to image the measurement area. In another aspect, a fiber optics collector includes an image pixel mapper that couples a two dimensional array of collection fiber optical elements into a one dimensional array of pixels at the spectrometer and the hyperspectral detector.

公开(公告)号：US10386729B2

公开(公告)日：2019-08-20

申请号：US14293221

申请日：2014-06-02

Applicant: KLA-Tencor Corporation

Inventor： Lie-Quan Lee ,  Leonid Poslavsky ,  Stilian Ivanov Pandev

IPC: G03F1/44 ,  G01N21/25 ,  G03F7/20

Abstract: Dynamic removal of correlation of highly-correlated parameters for optical metrology is described. An embodiment of a method includes determining a model of a structure, the model including a set of parameters; performing optical metrology measurement of the structure, including collecting spectra data on a hardware element; during the measurement of the structure, dynamically removing correlation of two or more parameters of the set of parameters, an iteration of the dynamic removal of correlation including: generating a Jacobian matrix of the set of parameters, applying a singular value decomposition of the Jacobian matrix, selecting a subset of the set of parameters, and computing a direction of the parameter search based on the subset of parameters. If the model does not converge, performing one or more additional iterations of the dynamic removal of correlation until the model converges; and if the model does converge, reporting the results of the measurement.