METHOD FOR GENERATING PATTERNING DEVICE PATTERN AT PATCH BOUNDARY

    公开(公告)号:WO2020135946A1

    公开(公告)日:2020-07-02

    申请号:PCT/EP2019/081574

    申请日:2019-11-18

    Abstract: Described herein is a method for generating a mask pattern to be employed in a patterning process. The method including (P301) obtaining (i) a first feature patch (301) comprising a first polygon portion of an initial mask pattern, and (ii) a second feature patch (302) comprising a second polygon portion of the initial mask pattern; (P303) adjusting the second polygon portion at a patch boundary between the first feature patch and the second feature patch such that a difference between the first polygon portion and the second polygon portion at the patch boundary is reduced; and (P305) combining the first polygon portion and the adjusted second polygon portion at the patch boundary to form the mask pattern (330).

    METHOD FOR DETERMINING PATTERNING DEVICE PATTERN BASED ON MANUFACTURABILITY

    公开(公告)号:WO2020108902A1

    公开(公告)日:2020-06-04

    申请号:PCT/EP2019/079562

    申请日:2019-10-29

    Abstract: Described herein is a method for determining a patterning device pattern. The method includes obtaining (i) an initial patterning device pattern having at least one feature, and (ii) a desired feature size of the at least one feature, obtaining, based on a patterning process model, the initial patterning device pattern and a target pattern for a substrate, a difference value between a predicted pattern of the substrate image by the initial patterning device and the target pattern for the substrate, determining a penalty value related the manufacturability of the at least one feature, wherein the penalty value varies as a function of the size of the at least one feature, and determining the patterning device pattern based on the initial patterning device pattern and the desired feature size such that a sum of the difference value and the penalty value is reduced.

    A MACHINE LEARNING MODEL USING TARGET PATTERN AND REFERENCE LAYER PATTERN TO DETERMINE OPTICAL PROXIMITY CORRECTION FOR MASK

    公开(公告)号:WO2022179802A1

    公开(公告)日:2022-09-01

    申请号:PCT/EP2022/052213

    申请日:2022-01-31

    Abstract: Described are embodiments for generating a post-optical proximity correction (OPC) result for a mask using a target pattern and reference layer patterns. Images of the target pattern and reference layers are provided as an input to a machine learning (ML) model to generate a post-OPC image. The images may be input separately or combined into a composite image (e.g., using a linear function) and input to the ML model. The images are rendered from pattern data. For example, a target pattern image is rendered from a target pattern to be printed on a substrate, and a reference layer image such as dummy pattern image is rendered from dummy pattern. The ML model is trained to generate the post-OPC image using multiple images associated with target patterns and reference layers, and using a reference post-OPC image of the target pattern. The post-OPC image may be used to generate a post-OPC mask.

    METHOD FOR IMPROVING CONSISTENCY IN MASK PATTERN GENERATION

    公开(公告)号:WO2021115766A1

    公开(公告)日:2021-06-17

    申请号:PCT/EP2020/082995

    申请日:2020-11-21

    Abstract: Described herein is a method (400) of determining a mask pattern for a target pattern to be printed on a substrate. The method includes partitioning (P401) a portion of a design layout (401) including the target pattern into a plurality of cells (402) with reference to a given location on the target pattern; assigning (P403) a plurality of variables (403) within a particular cell of the plurality of cells, the particular cell including the target pattern or a portion thereof; and determining (P405), based on values of the plurality of variables, the mask pattern (405) for the target pattern such that a performance metric of a patterning process utilizing the mask pattern is within a desired performance range.

    METHOD FOR DETERMINING A MASK PATTERN COMPRISING OPTICAL PROXIMITY CORRECTIONS USING A TRAINED MACHINE LEARNING MODEL

    公开(公告)号:WO2021160522A1

    公开(公告)日:2021-08-19

    申请号:PCT/EP2021/052724

    申请日:2021-02-04

    Abstract: Described herein are a method for determining a mask pattern and a method for training a machine learning model. The method for determining a mask pattern includes obtaining, via executing a model using a target pattern to be printed on a substrate as an input pattern, a post optical proximity correction (post-OPC) pattern; determining, based on the post-OPC pattern, a simulated pattern that will be printed on the substrate; and determining the mask pattern based on a difference between the simulated pattern and the target pattern. The determining of the mask pattern includes modifying, based on the difference, the input pattern inputted to the model such that the difference is reduced; and executing, using the modified input pattern, the model to generate a modified post-OPC pattern from which the mask pattern can be derived.

    METHOD FOR DETERMINING CURVILINEAR PATTERNS FOR PATTERNING DEVICE

    公开(公告)号:WO2019179747A1

    公开(公告)日:2019-09-26

    申请号:PCT/EP2019/055067

    申请日:2019-02-28

    Abstract: Described herein is a method to determine a curvilinear pattern of a patterning device that includes obtaining (i) an initial image of the patterning device corresponding to a target pattern to be printed on a substrate subjected to a patterning process, and (ii) a process model configured to predict a pattern on the substrate from the initial image, generating, by a hardware computer system, an enhanced image from the initial image, generating, by the hardware computer system, a level set image using the enhanced image, and iteratively determining, by the hardware computer system, a curvilinear pattern for the patterning device based on the level set image, the process model, and a cost function, where the cost function (e.g., EPE) determines a difference between a predicted pattern and the target pattern, where the difference is iteratively reduced.

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