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    • 4. 发明授权
    • Information matrix creation and calibration test pattern selection based on computational lithography model parameters
    • 基于计算光刻模型参数的信息矩阵创建和校准测试模式选择
    • US09588439B1
    • 2017-03-07
    • US13332303
    • 2011-12-20
    • Antoine Jean BruguierYu CaoJun YeWenjin Shao
    • Antoine Jean BruguierYu CaoJun YeWenjin Shao
    • G06F17/10G06F7/60G03F7/20G06F17/50
    • G03F7/705G03F7/70516G03F7/70625G06F17/5009
    • Embodiments of the present invention describe methods of selecting a subset of test patterns from an initial larger set of test patterns for calibrating a computational lithography model. An example method comprises: generating an information matrix for the initial larger set of test patterns, wherein the terms of the information matrix comprise one or more identified model parameters that represent a lithographic process response; and, executing a selection algorithm using terms of the information matrix to select the subset of test patterns that effectively determines values of the identified model parameters that contribute significantly in the lithographic process response, wherein the subset of test patterns characteristically represents the initial larger set of test patterns. The selection algorithm explores coverage relationships existing in the initial larger set of test patterns.
    • 本发明的实施例描述了从用于校准计算光刻模型的初始较大组测试图案中选择测试图案子集的方法。 示例性方法包括:生成用于初始较大组的测试模式的信息矩阵,其中信息矩阵的项包括表示光刻过程响应的一个或多个识别的模型参数; 以及使用所述信息矩阵的项来执行选择算法,以选择有效地确定在所述光刻过程响应中有显着贡献的所识别的模型参数的值的测试模式子集,其中,所述测试模式的子集特征性地表示所述初始较大集合 测试模式。 选择算法探讨了初始较大的一组测试模式中存在的覆盖关系。
    • 5. 发明授权
    • Calibration pattern selection based on noise sensitivity
    • 基于噪声敏感度的校准模式选择
    • US08887105B1
    • 2014-11-11
    • US13662239
    • 2012-10-26
    • Antoine Jean BruguierWenjin ShaoSong Lan
    • Antoine Jean BruguierWenjin ShaoSong Lan
    • G06F17/50
    • G03F1/70G03F1/36
    • The preset invention provides methods, systems and computer program product for selection of an optimum set of patterns to calibrate a lithography model so that the model can predict imaging performance of a lithography apparatus/system more accurately and reliably without being prohibitively expensive in terms of using computational and metrology resources and time. The method is based on modeling sensitivity of the calibration patterns to measurement noise. In one aspect of the present invention, a method is disclosed, comprising: identifying a model of at least a portion of a lithographic process; identifying a set of patterns for calibrating the model; and, estimating measurement noise associated with the set of patterns.
    • 本发明提供了用于选择用于校准光刻模型的最佳图案集合的方法,系统和计算机程序产品,使得该模型可以更准确和可靠地预测光刻设备/系统的成像性能,而不会在使用方面过于昂贵 计算和计量资源和时间。 该方法基于校准模式对测量噪声的建模灵敏度。 在本发明的一个方面,公开了一种方法,包括:识别光刻工艺的至少一部分的模型; 识别用于校准模型的一组模式; 并且估计与该组模式相关联的测量噪声。
    • 10. 发明授权
    • Pattern selection for lithographic model calibration
    • 光刻模型校准的图案选择
    • US08694928B2
    • 2014-04-08
    • US12613244
    • 2009-11-05
    • Yu CaoWenjin ShaoJun YeRonaldus Johannes Gljsbertus Goossens
    • Yu CaoWenjin ShaoJun YeRonaldus Johannes Gljsbertus Goossens
    • G06F17/50
    • G06F17/50G03F1/14G03F1/44G03F1/68G03F7/70433G03F7/705G06F17/10G06F17/5009
    • The present invention relates generally to methods and apparatuses for test pattern selection for computational lithography model calibration. According to some aspects, the pattern selection algorithms of the present invention can be applied to any existing pool of candidate test patterns. According to some aspects, the present invention automatically selects those test patterns that are most effective in determining the optimal model parameter values from an existing pool of candidate test patterns, as opposed to designing optimal patterns. According to additional aspects, the selected set of test patterns according to the invention is able to excite all the known physics and chemistry in the model formulation, making sure that the wafer data for the test patterns can drive the model calibration to the optimal parameter values that realize the upper bound of prediction accuracy imposed by the model formulation.
    • 本发明一般涉及用于计算光刻模型校准的测试图案选择的方法和装置。 根据一些方面,本发明的模式选择算法可以应用于任何现有的候选测试模式池。 根据一些方面,与设计最佳图案相反,本发明自动选择从现有的候选测试图案池中确定最佳模型参数值最有效的测试图案。 根据另外的方面,根据本发明的所选择的一组测试图案能够激发模型配方中的所有已知物理和化学,确保用于测试图案的晶片数据可以将模型校准驱动到最佳参数值 实现了模型公式对预测精度的上限。