METHOD FOR CONVERTING METROLOGY DATA

    公开(公告)号:US20240377343A1

    公开(公告)日:2024-11-14

    申请号:US18684558

    申请日:2022-08-22

    Abstract: Described herein is a metrology system and a method for converting metrology data via a trained machine learning (ML) model. The method includes accessing a first (MD1) SEM data set (e.g., images, contours, etc.) acquired by a first scanning electron metrology (SEM) system (TS1) and a second (MD2) SEM data set acquired by a second SEM system (TS2), where the first SEM data set and the second SEM data set being associated with a patterned substrate. Using the first SEM data set and the second SEM data set as training data, a machine learning (ML) model is trained (P303) such that the trained ML model is configured to convert (P307) a metrology data set (310) acquired (P305) by the second SEM system to a converted data set (311) having characteristics comparable to metrology data being acquired by the first SEM system. Furthermore, measurements may be determined based on the converted SEM data.

    PATTERN SELECTION SYSTEMS AND METHODS

    公开(公告)号:US20240370621A1

    公开(公告)日:2024-11-07

    申请号:US18686994

    申请日:2022-08-22

    Abstract: Selecting an optimized, geometrically diverse subset of clips for a design layout for a semiconductor wafer is described. A complete representation of the design layout is received. A set of representative clips of the design layout is determined such that individual representative clips comprise different combinations of one or more unique patterns of the design layout. A subset of the representative clips is selected based on the one or more unique patterns. The subset of the representative clips is configured to include: (1) each geometrically unique pattern in a minimum number of representative clips; or (2) as many geometrically unique patterns of the design layout as possible in a maximum number of representative clips. The subset of representative clips is provided as training data for training an optical proximity correction or source mask optimization semiconductor process machine learning model, for example.

    INSPECTION APPARATUS AND METHOD
    54.
    发明申请

    公开(公告)号:US20240369356A1

    公开(公告)日:2024-11-07

    申请号:US18776207

    申请日:2024-07-17

    Abstract: An inspection apparatus for adjusting a working height for a substrate for multiple target heights is disclosed. The inspection apparatus includes a radiation source configured to provide a radiation beam and a beam splitter configured to split the radiation beam into multiple beamlets that each reflect off a substrate. Each beamlet contains light of multiple wavelengths. The inspection apparatus includes multiple light reflecting components, wherein each light reflecting component is associated with one of the beamlets reflecting off the substrate and is configured to support a different target height for the substrate by detecting a height or a levelness of the substrate based on the beamlet reflecting off the substrate.

    Overlay measurement system using lock-in amplifier technique

    公开(公告)号:US12124177B2

    公开(公告)日:2024-10-22

    申请号:US17782622

    申请日:2020-11-18

    Abstract: A detection system (200) includes an illumination system (210), a first optical system (232), a phase modulator (220), a lock-in detector (255), and a function generator (230). The illumination system is configured to transmit an illumination beam (218) along an illumination path. The first optical system is configured to transmit the illumination beam toward a diffraction target (204) on a substrate (202). The first optical system is further configured to transmit a signal beam including diffraction order sub-beams (222, 224, 226) that are diffracted by the diffraction target. The phase modulator is configured to modulate the illumination beam or the signal beam based on a reference signal. The lock-in detector is configured to collect the signal beam and to measure a characteristic of the diffraction target based on the signal beam and the reference signal. The function generator is configured to generate the reference signal for the phase modulator and the lock-in detector.

    METHOD OF EVALUATING SELECTED SET OF PATTERNS

    公开(公告)号:US20240345487A1

    公开(公告)日:2024-10-17

    申请号:US18681613

    申请日:2022-08-02

    CPC classification number: G03F7/705 G03F7/70441

    Abstract: Systems and methods for evaluating selected set of patterns of a design layout. A method herein includes obtaining (i) a first pattern set resulting from a pattern selection process, (ii) first pattern data associated with the first pattern set, (iii) characteristic data associated with the first pattern data, and (iv) second pattern data associated with a second pattern set. A machine learning model is trained based on the characteristic data, where the machine learning model being configured to predict pattern data for an input pattern. The second pattern set is input to the trained machine learning model to predict second pattern data of the second pattern set. The first pattern set is evaluated by comparing the second pattern data and the predicted second pattern data. If the evaluation indicates insufficient pattern coverage, additional patterns can be included to improve the pattern coverage.

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