公开(公告)号：US09910348B2

公开(公告)日：2018-03-06

申请号：US14788296

申请日：2015-06-30

Applicant: GLOBALFOUNDRIES INC.

Inventor： Geng Han ,  Scott M. Mansfield ,  Dominique Nguyen-Ngoc ,  Donald J. Samuels ,  Ramya Viswanathan

IPC: G06F17/50 ,  G03F1/00 ,  G03F1/36 ,  H01L21/027

CPC classification number: G03F1/36 ,  G03F1/144 ,  G06F17/5068 ,  G06F17/5081 ,  G06F2217/12 ,  H01L21/0274

Abstract: A method of mask correction where two independent process models are analyzed and co-optimized simultaneously. In the method, a first lithographic process model simulation is run on a computer system that results in generating a first mask size in a first process window. Simultaneously, a second hard mask open etch process model simulation is run resulting in generating a second mask size in a second process window. Each first lithographic process model and second hard mask open etch process model simulations are analyzed in a single iterative loop and a common process window (PW) optimized between lithography and etch is obtained such that said first mask size and second mask size are centered between said common PW. Further, an etch model form is generated that accounts for differences in an etched pattern due to variation in three-dimensional photoresist profile, the model form including both optical and density terms that directly relate to an optical image.

公开(公告)号：US10120963B1

公开(公告)日：2018-11-06

申请号：US15587602

申请日：2017-05-05

Applicant: GlobalFoundries Inc.

Inventor： Pardeep Kumar ,  Alan E. Rosenbluth ,  Ramana Murthy Pusuluri ,  Ramya Viswanathan

IPC: G06F17/50

CPC classification number: G06F17/5009 ,  G06F17/5081 ,  G06F2217/10

Abstract: A method for correcting a lithographic pattern includes selecting, by a processor, first stage input factors for utilization with a first computer-implemented model. The processor measures pattern data from existing measured dimensions of a semiconductor to obtain values for the first stage input factors and the first model against the measured pattern data. The processor applies the calibrated first model to predict printed dimensions and the printed dimensions from applying the calibrated first model comprise residuals. The processor establishes, based on the residuals, second stage input factors for a second model and calibrates the second model against the measured pattern data to predict deviations of the printed dimensions from the printed dimensions from the first stage input factors by utilizing the second stage input factors. The method produces predicted printed dimensions of a lithographic pattern by using the second model to revise the printed dimensions of the first model.

公开(公告)号：US09223911B2

公开(公告)日：2015-12-29

申请号：US14168133

申请日：2014-01-30

Applicant: GLOBALFOUNDRIES INC.

Inventor： Jason E. Meiring ,  Mohamed Talbi ,  Ramya Viswanathan

IPC: G06F17/50

CPC classification number: G06F17/5009 ,  G03F1/44 ,  G03F7/70441 ,  G03F7/705 ,  G03F7/70625 ,  G06F17/5068

Abstract: Optical simulation can be performed employing a calibrated printing model, in which a unique phase transmission value is assigned to each type of sub-resolution assist features (SRAFs). The printing model can be calibrated employing a mask including multiple test patterns. Each test pattern is defined by a combination of a main feature, at least one SRAF applied to the main feature, and the geometrical relationship between the main feature and the at least one SRAF. Generation of the phase transmission values for each SRAF can be performed by fitting a printing model employing phase shift values and/or transmission values for SRAFs with measured printed feature dimensions as a function of defocus and/or with measured SRAF printing behavior on a printed photoresist layer. A properly calibrated printing model can predict the printed feature dimensions, shift in the best focus, and presence or absence of printed SRAFs.

Abstract translation: 可以使用校准的打印模型来执行光学仿真，其中将唯一的相位传输值分配给每种类型的分解辅助特征（SRAF）。 可以使用包括多个测试图案的蒙版来校准印刷模型。 每个测试图案由主要特征，应用于主要特征的至少一个SRAF以及主要特征与至少一个SRAF之间的几何关系的组合来定义。 可以通过对具有测量的印刷特征尺寸的SRAF的相移值和/或透射值拟合作为散焦的函数和/或在印刷的光致抗蚀剂上测量的SRAF印刷行为来拟合针对每个SRAF的相位透射值的生成 层。 正确校准的打印模型可以预测打印的特征尺寸，最佳焦点位移以及印刷的SRAF的存在或不存在。

公开(公告)号：US20170004233A1

公开(公告)日：2017-01-05

申请号：US14788296

申请日：2015-06-30

Applicant: GLOBALFOUNDRIES INC.

Inventor： Geng Han ,  Scott M. Mansfield ,  Dominique Nguyen-Ngoc ,  Donald J. Samuels ,  Ramya Viswanathan

IPC: G06F17/50 ,  G03F1/36

CPC classification number: G03F1/36 ,  G03F1/144 ,  G06F17/5068 ,  G06F17/5081 ,  G06F2217/12 ,  H01L21/0274

Abstract: A method of mask correction where two independent process models are analyzed and co-optimized simultaneously. In the method, a first lithographic process model simulation is run on a computer system that results in generating a first mask size in a first process window. Simultaneously, a second hard mask open etch process model simulation is run resulting in generating a second mask size in a second process window. Each first lithographic process model and second hard mask open etch process model simulations are analyzed in a single iterative loop and a common process window (PW) optimized between lithography and etch is obtained such that said first mask size and second mask size are centered between said common PW. Further, an etch model form is generated that accounts for differences in an etched pattern due to variation in three-dimensional photoresist profile, the model form including both optical and density terms that directly relate to an optical image.

Abstract translation: 一种掩模校正方法，其中两个独立的过程模型被同时分析和共同优化。 在该方法中，在计算机系统上运行第一光刻过程模型模拟，其导致在第一处理窗口中产生第一掩模尺寸。 同时，运行第二硬掩模开放蚀刻工艺模型模拟，导致在第二处理窗口中产生第二掩模尺寸。 在单个迭代循环中分析每个第一光刻处理模型和第二硬掩模开放蚀刻工艺模拟模拟，并且获得在光刻和蚀刻之间优化的公共工艺窗口（PW），使得所述第一掩模尺寸和第二掩模尺寸在所述 普通PW。 此外，产生蚀刻模型形式，其考虑由于三维光致抗蚀剂轮廓的变化而导致的蚀刻图案的差异，该模型形式包括与光学图像直接相关的光学和密度项。

公开(公告)号：US20160246167A1

公开(公告)日：2016-08-25

申请号：US14628446

申请日：2015-02-23

Applicant: GLOBALFOUNDRIES INC.

Inventor： Amr Y. Abdo ,  Nathalie Casati ,  Maria Gabrani ,  James M. Oberschmidt ,  Ramya Viswanathan ,  Josef S. Watts

IPC: G03F1/36 ,  G06F17/50

CPC classification number: G03F1/36 ,  G06F17/5081

Abstract: Methods, program products, and systems for improving optical proximity correction (OPC) calibration, and automatically determining a minimal number of clips, are disclosed. The method can include using a computing device to perform actions including: calculating a total relevancy score for a projected sample plan including a candidate clip, and wherein the relevancy score is derived from at least one relevancy criterion and a relevancy weight; calculating a relevancy score for the candidate clip, the relevancy score for the candidate clip being a contribution from the candidate clip to the total relevancy score; and adding the candidate clip to a sample plan for the IC layout and removing the candidate clip from the plurality of clips in response a difference in relevancy score between the projected sample plan and one or more previous sample plans substantially fitting a non-linear relevancy score function.

Abstract translation: 公开了用于改进光学邻近校正（OPC）校准以及自动确定最小数量的片段的方法，程序产品和系统。 该方法可以包括使用计算设备来执行动作，包括：计算包括候选剪辑的投影样本计划的总相关性得分，并且其中所述相关性得分来自至少一个相关性标准和相关权重; 计算候选剪辑的相关性分数，候选剪辑的相关性分数是从候选剪辑到总相关性分数的贡献; 以及将所述候选剪辑添加到所述IC布局的样本计划并从所述多个剪辑中移除所述候选剪辑，以响应所述预测样本计划与基本拟合非线性相关性得分的一个或多个先前样本计划之间的相关性得分的差异 功能。

公开(公告)号：US09471743B1

公开(公告)日：2016-10-18

申请号：US14674571

申请日：2015-03-31

Applicant: GLOBALFOUNDRIES INC.

Inventor： Geng Han ,  Scott M. Mansfield ,  Ramya Viswanathan

IPC: G06F17/50

CPC classification number: G06F17/5081 ,  G06F17/5036 ,  G06F2217/12 ,  Y02P90/265

Abstract: In an approach for predicting a process fail limit for a semiconductor manufacturing process, a computer determines a potential working process condition for each of a plurality of process parameters varied in forming a test wafer feature. The computer determines a process sigma value for each of the plurality of process parameters in forming the test wafer feature and a measurement sigma value. The computer evaluates a set of measurements of the test wafer feature compared to an acceptable wafer feature dimension, where each measurement of the set of measurements is a pass or fail as compared to the acceptable wafer feature dimension. The computer determines whether one or more fails are evaluated compared to the acceptable wafer feature dimension. The computer produces a predicted process fail limit based, at least in part, on the evaluation of fails, the measurement sigma value, and a desired target sigma value.

Abstract translation: 在用于预测半导体制造工艺的工艺故障限制的方法中，计算机确定在形成测试晶片特征时变化的多个工艺参数中的每一个的潜在工作工艺条件。 在形成测试晶片特征和测量西格玛值时，计算机确定多个工艺参数中的每个工艺参数的工艺sigma值。 与可接受的晶片特征尺寸相比，计算机评估测试晶片特征的一组测量，其中与可接受的晶片特征尺寸相比，该组测量的每个测量是通过或失败。 与可接受的晶片特征尺寸相比，计算机确定是否评估一个或多个故障。 该计算机至少部分地基于失败的评估，测量西格玛值和期望的目标σ值产生预测的过程失败限制。

公开(公告)号：US09405186B1

公开(公告)日：2016-08-02

申请号：US14628446

申请日：2015-02-23

Applicant: GLOBALFOUNDRIES INC.

Inventor： Amr Y. Abdo ,  Nathalie Casati ,  Maria Gabrani ,  James M. Oberschmidt ,  Ramya Viswanathan ,  Josef S. Watts

IPC: G06F17/50 ,  G03F1/36

CPC classification number: G03F1/36 ,  G06F17/5081

Abstract: Methods, program products, and systems for improving optical proximity correction (OPC) calibration, and automatically determining a minimal number of clips, are disclosed. The method can include using a computing device to perform actions including: calculating a total relevancy score for a projected sample plan including a candidate clip, and wherein the relevancy score is derived from at least one relevancy criterion and a relevancy weight; calculating a relevancy score for the candidate clip, the relevancy score for the candidate clip being a contribution from the candidate clip to the total relevancy score; and adding the candidate clip to a sample plan for the IC layout and removing the candidate clip from the plurality of clips in response a difference in relevancy score between the projected sample plan and one or more previous sample plans substantially fitting a non-linear relevancy score function.

Abstract translation: 公开了用于改进光学邻近校正（OPC）校准以及自动确定最小数量的片段的方法，程序产品和系统。 该方法可以包括使用计算设备来执行动作，包括：计算包括候选剪辑的投影样本计划的总相关性得分，并且其中所述相关性得分来自至少一个相关性标准和相关权重; 计算候选剪辑的相关性分数，候选剪辑的相关性分数是从候选剪辑到总相关性分数的贡献; 以及将所述候选剪辑添加到所述IC布局的样本计划并从所述多个剪辑中移除所述候选剪辑，以响应所述预测样本计划与基本拟合非线性相关性得分的一个或多个先前样本计划之间的相关性得分的差异 功能。