Print check repeater defect detection

    公开(公告)号:US11328411B2

    公开(公告)日:2022-05-10

    申请号:US17246034

    申请日:2021-04-30

    Abstract: Systems and methods for detecting defects on a reticle are provided. One system includes computer subsystem(s) configured for performing at least one repeater defect detection step in front-end processing during an inspection process performed on a wafer having features printed in a lithography process using a reticle. The at least one repeater defect detection step performed in the front-end processing includes identifying any defects detected at corresponding locations in two or more test images by double detection and any defects detected by stacked defect detection as first repeater defect candidates. One or more additional repeater defect detections may be performed on the first repeater defect candidates to generate final repeater defect candidates and identify defects on the reticle from the final repeater defect candidates.

    Print check repeater defect detection

    公开(公告)号:US12190498B2

    公开(公告)日:2025-01-07

    申请号:US18072605

    申请日:2022-11-30

    Abstract: Systems and methods for detecting defects on a reticle are provided. One system is configured for generating different stacked difference images for multiple instances of first patterned areas in different rows on a wafer based on images generated for the first patterned areas in the different rows. The system is also configured for performing double detection based on the different stacked difference images. The system then identifies defects on the reticle based on the defects detected by the double detection. As described further herein, the systems and methods detect defects from multiple reticle rows printed on a wafer, which can reduce noise and enable detection of substantially small repeater defects. The embodiments are particularly useful for high sensitivity repeater defect detection for extreme ultraviolet (EUV) reticles and multi-die reticles (MDR).

    PRINT CHECK REPEATER DEFECT DETECTION
    3.
    发明公开

    公开(公告)号:US20240177294A1

    公开(公告)日:2024-05-30

    申请号:US18072605

    申请日:2022-11-30

    Abstract: Systems and methods for detecting defects on a reticle are provided. One system is configured for generating different stacked difference images for multiple instances of first patterned areas in different rows on a wafer based on images generated for the first patterned areas in the different rows. The system is also configured for performing double detection based on the different stacked difference images. The system then identifies defects on the reticle based on the defects detected by the double detection. As described further herein, the systems and methods detect defects from multiple reticle rows printed on a wafer, which can reduce noise and enable detection of substantially small repeater defects. The embodiments are particularly useful for high sensitivity repeater defect detection for extreme ultraviolet (EUV) reticles and multi-die reticles (MDR).

    Unsupervised Learning-Based Reference Selection for Enhanced Defect Inspection Sensitivity

    公开(公告)号:US20210090229A1

    公开(公告)日:2021-03-25

    申请号:US17013264

    申请日:2020-09-04

    Abstract: An optical characterization system and a method of using the same are disclosed. The system comprises a controller configured to be communicatively coupled with one or more detectors configured to receive illumination from a sample and generate image data. One or more processors may be configured to receive images of dies on the sample, calculate dissimilarity values for all combinations of the images, perform a cluster analysis to partition the combinations of the images into two or more clusters, generate a reference image for a cluster of the two or more clusters using two or more of the combinations of the images in the cluster; and detect one or more defects on the sample by comparing a test image in the cluster to the reference image for the cluster.

    System and method for inspection using tensor decomposition and singular value decomposition

    公开(公告)号:US11431976B2

    公开(公告)日:2022-08-30

    申请号:US16744301

    申请日:2020-01-16

    Abstract: A sample characterization system is disclosed. In embodiments, the sample characterization system includes a controller communicatively coupled to an inspection sub-system, the controller including one or more processors configured to execute a set of program instructions stored in memory, the set of program instructions configured to cause the one or more processors to: acquire one or more target image frames of a sample; generate a target tensor with the one or more acquired target image frames; perform a first set of one or more decomposition processes on the target tensor to generate one or more reference tensors including one or more reference image frames; identify one or more differences between the one or more target image frames and the one or more reference image frames; and determine one or more characteristics of the sample based on the one or more identified differences.

    PRINT CHECK REPEATER DEFECT DETECTION

    公开(公告)号:US20210342992A1

    公开(公告)日:2021-11-04

    申请号:US17246034

    申请日:2021-04-30

    Abstract: Systems and methods for detecting defects on a reticle are provided. One system includes computer subsystem(s) configured for performing at least one repeater defect detection step in front-end processing during an inspection process performed on a wafer having features printed in a lithography process using a reticle. The at least one repeater defect detection step performed in the front-end processing includes identifying any defects detected at corresponding locations in two or more test images by double detection and any defects detected by stacked defect detection as first repeater defect candidates. One or more additional repeater defect detections may be performed on the first repeater defect candidates to generate final repeater defect candidates and identify defects on the reticle from the final repeater defect candidates.

    Unsupervised learning-based reference selection for enhanced defect inspection sensitivity

    公开(公告)号:US11120546B2

    公开(公告)日:2021-09-14

    申请号:US17013264

    申请日:2020-09-04

    Abstract: An optical characterization system and a method of using the same are disclosed. The system comprises a controller configured to be communicatively coupled with one or more detectors configured to receive illumination from a sample and generate image data. One or more processors may be configured to receive images of dies on the sample, calculate dissimilarity values for all combinations of the images, perform a cluster analysis to partition the combinations of the images into two or more clusters, generate a reference image for a cluster of the two or more clusters using two or more of the combinations of the images in the cluster; and detect one or more defects on the sample by comparing a test image in the cluster to the reference image for the cluster.

    System and Method for Inspection Using Tensor Decomposition and Singular Value Decomposition

    公开(公告)号:US20200244963A1

    公开(公告)日:2020-07-30

    申请号:US16744301

    申请日:2020-01-16

    Abstract: A sample characterization system is disclosed. In embodiments, the sample characterization system includes a controller communicatively coupled to an inspection sub-system, the controller including one or more processors configured to execute a set of program instructions stored in memory, the set of program instructions configured to cause the one or more processors to: acquire one or more target image frames of a sample; generate a target tensor with the one or more acquired target image frames; perform a first set of one or more decomposition processes on the target tensor to form generate one or more reference tensors including one or more reference image frames; identify one or more differences between the one or more target image frames and the one or more reference image frames; and determine one or more characteristics of the sample based on the one or more identified differences.

Patent Agency Ranking