METHOD FOR GENERATING ASSIST FEATURES USING MACHINE LEARNING MODEL

    公开(公告)号:US20240256976A1

    公开(公告)日:2024-08-01

    申请号:US18565759

    申请日:2022-06-10

    IPC分类号: G06N20/00 G03F1/36

    CPC分类号: G06N20/00 G03F1/36

    摘要: Described herein is a method of determining assist features for a mask pattern. The method includes obtaining (i) a target pattern comprising a plurality of target features, wherein each of the plurality of target features comprises a plurality of target edges, and (ii) a trained sequence-to-sequence machine leaning (ML) model (e.g., long short term memory, Gated Recurrent Units, etc.) configured to determine sub-resolution assist features (SRAFs) for the target pattern. For a target edge of the plurality of target edges, geometric information (e.g., length, width, distances between features, etc.) of a subset of target features surrounding the target edge is determined. Using the geometric information as input, the ML model generates SRAFs to be placed around the target edge.

    METHODS OF DETERMINING SCATTERING OF RADIATION BY STRUCTURES OF FINITE THICKNESSES ON A PATTERNING DEVICE

    公开(公告)号:US20200073260A1

    公开(公告)日:2020-03-05

    申请号:US16467124

    申请日:2017-12-06

    IPC分类号: G03F7/20

    摘要: A method including: obtaining a thin-mask transmission function of a patterning device and a M3D model for a lithographic process, wherein the thin-mask transmission function represents a continuous transmission mask and the M3D model at least represents a portion of M3D attributable to multiple edges of structures on the patterning device; determining a M3D mask transmission function of the patterning device by using the thin-mask transmission function and the M3D model; and determining an aerial image produced by the patterning device and the lithographic process, by using the M3D mask transmission function.

    METHODS FOR GENERATING CHARACTERISTIC PATTERN AND TRAINING MACHINE LEARNING MODEL

    公开(公告)号:US20220335333A1

    公开(公告)日:2022-10-20

    申请号:US17641159

    申请日:2020-08-21

    摘要: Methods of generating a characteristic pattern for a patterning process and training a machine learning model. A method of training a machine learning model configured to generate a characteristic pattern for a mask pattern includes obtaining (i) a reference characteristic pattern that meets a satisfactory threshold related to manufacturing of the mask pattern, and (ii) a continuous transmission mask (CTM) for use in generating the mask pattern; and training, based on the reference characteristic pattern and the CTM, the machine learning model such that a first metric between the characteristic pattern and the CTM, and a second metric between the characteristic pattern and the reference characteristic pattern is reduced.

    FAST FREEFORM SOURCE AND MASK CO-OPTIMIZATION METHOD

    公开(公告)号:US20200218850A1

    公开(公告)日:2020-07-09

    申请号:US16821048

    申请日:2020-03-17

    发明人: Luoqi CHEN Jun YE Yu CAO

    摘要: The present disclosure relates to lithographic apparatuses and processes, and more particularly to tools for optimizing illumination sources and masks for use in lithographic apparatuses and processes. According to certain aspects, the present disclosure significantly speeds up the convergence of the optimization by allowing direct computation of gradient of the cost function. According to other aspects, the present disclosure allows for simultaneous optimization of both source and mask, thereby significantly speeding the overall convergence. According to still further aspects, the present disclosure allows for free-form optimization, without the constraints required by conventional optimization techniques.

    METHODS OF DETERMINING SCATTERING OF RADIATION BY STRUCTURES OF FINITE THICKNESSES ON A PATTERNING DEVICE

    公开(公告)号:US20200012196A1

    公开(公告)日:2020-01-09

    申请号:US16483452

    申请日:2018-02-13

    IPC分类号: G03F7/20 G06N3/08 G06F17/50

    摘要: A method including: obtaining a characteristic of a portion of a design layout; determining a characteristic of M3D of a patterning device including or forming the portion; and training, by a computer, a neural network using training data including a sample whose feature vector includes the characteristic of the portion and whose supervisory signal includes the characteristic of the M3D. Also disclosed is a method including: obtaining a characteristic of a portion of a design layout; obtaining a characteristic of a lithographic process that uses a patterning device including or forming the portion; determining a characteristic of a result of the lithographic process; training, by a computer, a neural network using training data including a sample whose feature vector includes the characteristic of the portion and the characteristic of the lithographic process, and whose supervisory signal includes the characteristic of the result.

    METHODS AND SYSTEMS FOR PARAMETER-SENSITIVE AND ORTHOGONAL GAUGE DESIGN FOR LITHOGRAPHY CALIBRATION
    7.
    发明申请
    METHODS AND SYSTEMS FOR PARAMETER-SENSITIVE AND ORTHOGONAL GAUGE DESIGN FOR LITHOGRAPHY CALIBRATION 有权
    参数敏感和正交测量设计的方法和系统进行LITHOGRAPHY校准

    公开(公告)号:US20150186557A1

    公开(公告)日:2015-07-02

    申请号:US14589738

    申请日:2015-01-05

    IPC分类号: G06F17/50 G06F17/10

    摘要: Methods according to the present invention provide computationally efficient techniques for designing gauge patterns for calibrating a model for use in a simulation process. More specifically, the present invention relates to methods of designing gauge patterns that achieve complete coverage of parameter variations with minimum number of gauges and corresponding measurements in the calibration of a lithographic process utilized to image a target design having a plurality of features. According to some aspects, a method according to the invention includes transforming the space of model parametric space (based on CD sensitivity or Delta TCCs), then iteratively identifying the direction that is most orthogonal to existing gauges' CD sensitivities in this new space, and determining most sensitive line width/pitch combination with optimal assist feature placement which leads to most sensitive CD changes along that direction in model parametric space.

    摘要翻译: 根据本发明的方法提供了用于设计用于校准用于模拟过程中的模型的计量模式的计算上有效的技术。 更具体地说,本发明涉及设计规格图案的方法,该图形模式可以用最小数量的量规完成覆盖参数变化,并且在用于对具有多个特征的目标设计进行成像的光刻处理的校准中的对应测量。 根据一些方面,根据本发明的方法包括改变模型参数空间的空间(基于CD灵敏度或Delta TCC),然后迭代地识别在该新空间中与现有计量器的CD灵敏度最正交的方向,以及 确定最敏感的线宽/间距组合与最佳辅助功能放置,导致在模型参数空间中沿着该方向的最敏感的CD变化。

    MODEL-BASED SCANNER TUNING SYSTEMS AND METHODS
    8.
    发明申请
    MODEL-BASED SCANNER TUNING SYSTEMS AND METHODS 审中-公开
    基于模型的扫描仪调谐系统和方法

    公开(公告)号:US20150045935A1

    公开(公告)日:2015-02-12

    申请号:US14525704

    申请日:2014-10-28

    IPC分类号: B29C67/00

    摘要: Systems and methods for tuning photolithographic processes are described. A model of a target scanner is maintained defining sensitivity of the target scanner with reference to a set of tunable parameters. A differential model represents deviations of the target scanner from the reference. The target scanner may be tuned based on the settings of the reference scanner and the differential model. Performance of a family of related scanners may be characterized relative to the performance of a reference scanner. Differential models may include information such as parametric offsets and other differences that may be used to simulate the difference in imaging behavior.

    摘要翻译: 描述用于调整光刻工艺的系统和方法。 保持目标扫描仪的型号,参考一组可调谐参数来定义目标扫描仪的灵敏度。 差分模型表示目标扫描器与参考值的偏差。 可以基于参考扫描仪和差分模型的设置来调整目标扫描仪。 可以相对于参考扫描仪的性能来表征相关扫描仪系列的性能。 差分模型可能包括诸如参数偏移和可能用于模拟成像行为差异的其他差异的信息。

    MACHINE LEARNING BASED INVERSE OPTICAL PROXIMITY CORRECTION AND PROCESS MODEL CALIBRATION

    公开(公告)号:US20210216697A1

    公开(公告)日:2021-07-15

    申请号:US15734141

    申请日:2019-05-23

    IPC分类号: G06F30/398 G06F30/392

    摘要: A method for calibrating a process model and training an inverse process model of a patterning process. The training method includes obtaining a first patterning device pattern from simulation of an inverse lithographic process that predicts a patterning device pattern based on a wafer target layout, receiving wafer data corresponding to a wafer exposed using the first patterning device pattern, and training an inverse process model configured to predict a second patterning device pattern using the wafer data related to the exposed wafer and the first patterning device pattern.

    COMPUTATIONAL PROCESS CONTROL
    10.
    发明申请
    COMPUTATIONAL PROCESS CONTROL 有权
    计算过程控制

    公开(公告)号:US20150025668A1

    公开(公告)日:2015-01-22

    申请号:US14507553

    申请日:2014-10-06

    IPC分类号: G03F9/00 B29C67/00

    摘要: The present invention provides a number of innovations in the area of computational process control (CPC). CPC offers unique diagnostic capability during chip manufacturing cycle by analyzing temporal drift of a lithography apparatus/ process, and provides a solution towards achieving performance stability of the lithography apparatus/process. Embodiments of the present invention enable optimized process windows and higher yields by keeping performance of a lithography apparatus and/or parameters of a lithography process substantially close to a pre-defined baseline condition. This is done by comparing the measured temporal drift to a baseline performance using a lithography process simulation model. Once in manufacturing, CPC optimizes a scanner for specific patterns or reticles by leveraging wafer metrology techniques and feedback loop, and monitors and controls, among other things, overlay and/or CD uniformity (CDU) performance over time to continuously maintain the system close to the baseline condition.

    摘要翻译: 本发明提供了计算过程控制(CPC)领域的许多创新。 CPC通过分析光刻设备/工艺的时间漂移​​,在芯片制造周期中提供独特的诊断功能,并为实现光刻设备/工艺的性能稳定性提供了解决方案。 本发明的实施例通过保持光刻设备的性能和/或基本上接近预定义基线条件的光刻工艺的参数来实现优化的工艺窗口和更高的产量。 这通过使用光刻过程模拟模型将测量的时间漂移​​与基线性能进行比较来完成。 一旦制造,CPC通过利用晶片计量技术和反馈回路来优化扫描仪的特定图案或掩模版,并监控和控制其他方面的重叠和/或CD均匀性(CDU)性能,以持续保持系统接近 基线条件。