Repeater Defect Detection
    11.
    发明申请

    公开(公告)号:US20180348147A1

    公开(公告)日:2018-12-06

    申请号:US15828632

    申请日:2017-12-01

    Abstract: Defects from a hot scan can be saved, such as on persistent storage, random access memory, or a split database. The persistent storage can be patch-based virtual inspector virtual analyzer (VIVA) or local storage. Repeater defect detection jobs can determined and the wafer can be inspected based on the repeater defect detection jobs. Repeater defects can be analyzed and corresponding defect records to the repeater defects can be read from the persistent storage. These results may be returned to the high level defect detection controller.

    Dynamic Care Areas for Defect Detection
    13.
    发明申请

    公开(公告)号:US20180276808A1

    公开(公告)日:2018-09-27

    申请号:US15858264

    申请日:2017-12-29

    Abstract: Systems and methods of a two-pass inspection methodology that dynamically creates micro care areas for inspection of repeater defects. Micro care areas can be formed around each location of a repeater defect. After inspection, additional repeater defects in the micro care areas can be identified. Attributes of the repeater defects can be compared and any repeater defects with attributes that deviate from an expected group attribute distribution can be classified as nuisance.

    Optical-mode selection for multi-mode semiconductor inspection

    公开(公告)号:US11010885B2

    公开(公告)日:2021-05-18

    申请号:US16406374

    申请日:2019-05-08

    Abstract: One or more semiconductor wafers or portions thereof are scanned using a primary optical mode, to identify defects. A plurality of the identified defects, including defects of a first class and defects of a second class, are selected and reviewed using an electron microscope. Based on this review, respective defects of the plurality are classified as defects of either the first class or the second class. The plurality of the identified defects is imaged using a plurality of secondary optical modes. One or more of the secondary optical modes are selected for use in conjunction with the primary optical mode, based on results of the scanning using the primary optical mode and the imaging using the plurality of secondary optical modes. Production semiconductor wafers are scanned for defects using the primary optical mode and the one or more selected secondary optical modes.

    Combining simulation and optical microscopy to determine inspection mode

    公开(公告)号:US10964016B2

    公开(公告)日:2021-03-30

    申请号:US16295715

    申请日:2019-03-07

    Inventor: Bjorn Brauer

    Abstract: A best optical inspection mode to detect defects can be determined when no defect examples or only a limited number of defect examples are available. A signal for a defect of interest at the plurality of sites and for the plurality of modes can be determined using electromagnetic simulation. A ratio of the signal for the defect of interest to the noise at each combination of the plurality of sites and the plurality of modes can be determined. A mode with optimized signal-to-noise characteristics can be determined based on the ratios.

    Algorithm selector based on image frames

    公开(公告)号:US10801968B2

    公开(公告)日:2020-10-13

    申请号:US16389442

    申请日:2019-04-19

    Inventor: Bjorn Brauer

    Abstract: Based on job dumps for defects of interest and nuisance events for multiple optical modes, detection algorithms, and attributes, the best combination of the aforementioned is identified. Combinations of each of the modes with each of the detection algorithms can be compared for all the defects of interest detected at an offset of zero. Capture rate versus nuisance rate can be determined for one of the attributes in each of the combinations.

    Training a learning based defect classifier

    公开(公告)号:US10713534B2

    公开(公告)日:2020-07-14

    申请号:US16109631

    申请日:2018-08-22

    Inventor: Bjorn Brauer

    Abstract: Methods and systems for training a learning based defect classifier are provided. One method includes training a learning based defect classifier with a training set of defects that includes identified defects of interest (DOIs) and identified nuisances. The DOIs and nuisances in the training set include DOIs and nuisances identified on at least one training wafer and at least one inspection wafer. The at least one training wafer is known to have an abnormally high defectivity and the at least one inspection wafer is expected to have normal defectivity.

    ALGORITHM SELECTOR BASED ON IMAGE FRAMES
    19.
    发明申请

    公开(公告)号:US20200132610A1

    公开(公告)日:2020-04-30

    申请号:US16389442

    申请日:2019-04-19

    Inventor: Bjorn Brauer

    Abstract: Based on job dumps for defects of interest and nuisance events for multiple optical modes, detection algorithms, and attributes, the best combination of the aforementioned is identified. Combinations of each of the modes with each of the detection algorithms can be compared for all the defects of interest detected at an offset of zero. Capture rate versus nuisance rate can be determined for one of the attributes in each of the combinations.

    PERFORMANCE MONITORING OF DESIGN-BASED ALIGNMENT

    公开(公告)号:US20190361363A1

    公开(公告)日:2019-11-28

    申请号:US16400756

    申请日:2019-05-01

    Inventor: Bjorn Brauer

    Abstract: Alignment can be monitored by positioning at least one alignment verification location per alignment frame. The alignment verification location is a coordinate within the alignment frame. A distance between each of the alignment verification locations and a closest instance of an alignment target is determined. An alignment score can be determined based on the distance. The alignment score can include a number of the alignment frames between the alignment verification location and the alignment target. If the alignment score is below a threshold, then alignment setup can be performed.

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