METHOD OF FORMING OPTICAL PROXIMITY CORRECTION MODEL AND METHOD OF FABRICATING SEMICONDUCTOR DEVICE USING THE SAME

    公开(公告)号:US20230062677A1

    公开(公告)日:2023-03-02

    申请号:US17735593

    申请日:2022-05-03

    Abstract: Disclosed are a method of forming an optical proximity correction (OPC) model and/or a method of fabricating a semiconductor device using the same. The method of forming the OPC model may include obtaining a scanning electron microscope (SEM) image, which is an average image of a plurality of images taken using one or more scanning electron microscopes, and a graphic data system (GDS) image, which is obtained by imaging a designed layout, aligning the SEM image and the GDS image, performing an image filtering process on the SEM image, extracting a contour from the SEM image, and verifying the contour. The verifying of the contour may be performed using a genetic algorithm. Variables in the genetic algorithm may include first parameters related to the image alignment process, second parameters related to the image filtering process, and third parameters related to a critical dimension (CD) measurement process.

    PROCESS PROXIMITY CORRECTION METHOD AND THE COMPUTING DEVICE FOR THE SAME

    公开(公告)号:US20220035237A1

    公开(公告)日:2022-02-03

    申请号:US17245947

    申请日:2021-04-30

    Abstract: A process proximity correction method is performed by a process proximity correction computing device which performs a process proximity correction (PPC) through at least one of a plurality of processors. The process proximity correction method includes: converting a target layout including a plurality of patterns into an image, zooming-in or zooming-out the image at a plurality of magnifications to generate a plurality of input channels, receiving the plurality of input channels and performing machine learning to predict an after-cleaning image (ACI), comparing the predicted after-cleaning image with a target value to generate an after-cleaning image error, and adjusting the target layout on the basis of the after-cleaning image error.

    ELECTRONIC DEVICE SUPPORTING MANUFACTURE OF SEMICONDUCTOR DEVICE AND OPERATING METHOD OF ELECTRONIC DEVICE

    公开(公告)号:US20240386635A1

    公开(公告)日:2024-11-21

    申请号:US18528275

    申请日:2023-12-04

    Abstract: Disclosed is an operating method of an electronic device which includes a processor and supports manufacture of a semiconductor device. The operating method includes receiving, at the processor, a layout image for the manufacture of the semiconductor device and a captured image generated by capturing the semiconductor device actually manufactured, aligning, at the processor, the layout image and the captured image based on a result of emphasizing edges and corners of the layout image and the captured image, and performing, at the processor, learning based on the aligned layout image and the aligned captured image such that a first modified layout image is generated from the layout image, and the semiconductor device is manufactured based on a second modified layout image generated from the layout image.

    DEVICE AND METHOD FOR DETECTING DEFECTS ON WAFER

    公开(公告)号:US20220108436A1

    公开(公告)日:2022-04-07

    申请号:US17465179

    申请日:2021-09-02

    Abstract: Disclosed is a wafer defect inference system, which includes a test equipment that receives a first image obtained by imaging circuit patterns formed on a semiconductor wafer by using a scanning electron microscope and a second image obtained by imaging a layout image of a mask for implementing the circuit pattern on the semiconductor wafer and combines the first image and the second image to generate a combination image, and at least one computing device that is capable of communicating with the test equipment and infers a defect associated with the circuit pattern formed on the semiconductor wafer. The computing device receives the combination image, performs machine learning for inferring the defect based on the combination image, and generates an output image including information about the defect based on the machine learning.

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