公开(公告)号：US10401740B2

公开(公告)日：2019-09-03

申请号：US15154051

申请日：2016-05-13

Applicant: KLA-Tencor Corporation

Inventor： Walter Dean Mieher

IPC: G03F1/44 ,  G03F7/20

Abstract: A lithography mask is disclosed. The lithography mask includes at least one asymmetric segmented pattern element. A particular asymmetric segmented pattern element includes at least two segments with a separation distance between consecutive segments smaller than a resolution of a set of projection optics for generating an image of the particular asymmetric segmented pattern element on a sample such that the image of the particular asymmetric segmented pattern element is an unsegmented pattern image. A position of the unsegmented pattern image on the sample is indicative of a location of the sample along an optical axis of the set of projection optics.

公开(公告)号：US20160334716A1

公开(公告)日：2016-11-17

申请号：US15154051

申请日：2016-05-13

Applicant: KLA-Tencor Corporation

Inventor： Walter Dean Mieher

IPC: G03F7/20 ,  G03F1/50 ,  H04N5/225

CPC classification number: G03F7/70641 ,  G03F1/44 ,  G03F7/70683

Abstract: A lithography mask is disclosed. The lithography mask includes at least one asymmetric segmented pattern element. A particular asymmetric segmented pattern element includes at least two segments with a separation distance between consecutive segments smaller than a resolution of a set of projection optics for generating an image of the particular asymmetric segmented pattern element on a sample such that the image of the particular asymmetric segmented pattern element is an unsegmented pattern image. A position of the unsegmented pattern image on the sample is indicative of a location of the sample along an optical axis of the set of projection optics.

Abstract translation: 公开了一种光刻掩模。 光刻掩模包括至少一个不对称的分段图案元件。 特定的非对称分段图案元件包括至少两个段，其间连续段之间的间隔距离小于一组投影光学元件的分辨率，用于在样本上产生特定非对称分割图案元素的图像，使得特定不对称分割图案的图像 分段图案元素是未分割的图案图像。 样品上的未分段图案图像的位置指示样品沿着该组投影光学器件的光轴的位置。

公开(公告)号：US10352876B2

公开(公告)日：2019-07-16

申请号：US14704840

申请日：2015-05-05

Applicant: KLA—Tencor Corporation

Inventor： Andrei V. Shchegrov ,  Stilian Ivanov Pandev ,  Jonathan M. Madsen ,  Alexander Kuznetsov ,  Walter Dean Mieher

IPC: G06N20/00 ,  G01N21/95 ,  G01B11/27

Abstract: Methods and systems for creating a measurement model based only on measured training data are presented. The trained measurement model is then used to calculate overlay values directly from measured scatterometry data. The measurement models receive scatterometry signals directly as input and provide overlay values as output. In some embodiments, overlay error is determined from measurements of design rule structures. In some other embodiments, overlay error is determined from measurements of specialized target structures. In a further aspect, the measurement model is trained and employed to measure additional parameters of interest, in addition to overlay, based on the same or different metrology targets. In some embodiments, measurement data from multiple targets, measurement data collected by multiple metrologies, or both, is used for model building, training, and measurement. In some embodiments, an optimization algorithm automates the measurement model building and training process.

公开(公告)号：US20150323316A1

公开(公告)日：2015-11-12

申请号：US14704840

申请日：2015-05-05

Applicant: KLA-Tencor Corporation

Inventor： Andrei V. Shchegrov ,  Stilian Ivanov Pandev ,  Jonathan M. Madsen ,  Alexander Kuznetsov ,  Walter Dean Mieher

IPC: G01B11/27 ,  G06N99/00

CPC classification number: G01N21/9501 ,  G01B11/27 ,  G06N20/00

Abstract: Methods and systems for creating a measurement model based only on measured training data are presented. The trained measurement model is then used to calculate overlay values directly from measured scatterometry data. The measurement models receive scatterometry signals directly as input and provide overlay values as output. In some embodiments, overlay error is determined from measurements of design rule structures. In some other embodiments, overlay error is determined from measurements of specialized target structures. In a further aspect, the measurement model is trained and employed to measure additional parameters of interest, in addition to overlay, based on the same or different metrology targets. In some embodiments, measurement data from multiple targets, measurement data collected by multiple metrologies, or both, is used for model building, training, and measurement. In some embodiments, an optimization algorithm automates the measurement model building and training process.

Abstract translation: 提出了仅基于测量训练数据创建测量模型的方法和系统。 然后使用经过训练的测量模型直接从测量的散射测量数据计算覆盖值。 测量模型直接接收散射信号作为输入，并提供重叠值作为输出。 在一些实施例中，根据设计规则结构的测量确定覆盖误差。 在一些其它实施例中，通过专门的目标结构的测量来确定覆盖误差。 在另一方面，测量模型被训练并用于基于相同或不同的度量目标来测量除叠加之外的附加参数。 在一些实施例中，来自多个目标的测量数据，由多个计量学收集的测量数据或两者都用于建模，训练和测量。 在一些实施例中，优化算法使测量模型构建和训练过程自动化。