中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

12 records (took 0.018 seconds)

    Bandpass charged particle energy filtering detector for charged particle tools
    3.
    发明授权
    Bandpass charged particle energy filtering detector for charged particle tools 有权

    公开(公告)号：US11749495B2

    公开(公告)日：2023-09-05

    申请号：US17494784

    申请日：2021-10-05

    Applicant: KLA Corporation

    Inventor： Youfei Jiang ,  Michael Steigerwald

    IPC: H01J37/244 ,  H01J37/28 ,  H01J37/05 ,  H01J37/147

    CPC classification number: H01J37/244 ,  H01J37/05 ,  H01J37/1471 ,  H01J37/28 ,  H01J2237/0492 ,  H01J2237/2448 ,  H01J2237/24475

    Abstract: Methods and systems for detecting charged particles from a specimen are provided. One system includes a first repelling mesh configured to repel charged particles from a specimen having an energy lower than a first predetermined energy and a second repelling mesh configured to repel the charged particles that pass through the first repelling mesh and have an energy that is lower than a second predetermined energy. The system also includes a first attracting mesh configured to attract the charged particles that pass through the first repelling mesh, are repelled by the second repelling mesh, and have an energy that is higher than the first predetermined energy and lower than the second predetermined energy. The system further includes a first detector configured to generate output responsive to the charged particles that pass through the first attracting mesh.

    Systems and methods for setting up a physics-based model
    6.
    发明授权
    Systems and methods for setting up a physics-based model 有权

    公开(公告)号：US11868689B2

    公开(公告)日：2024-01-09

    申请号：US17959712

    申请日：2022-10-04

    Applicant: KLA Corporation

    Inventor： Chad Huard ,  Premkumar Panneerchelvam ,  Guy Parsey ,  Ankur Agarwal

    IPC: G06F119/18 ,  G06F30/27

    CPC classification number: G06F30/27 ,  G06F2119/18

    Abstract: Systems and methods for setting up a physics-based model are provided. One system includes one or more components that are executed by one or more computer subsystems and that include a physics-based model describing a semiconductor fabrication-related process and a set up component configured for setting up the physics-based model in multiple phases in each of which only a subset of all of the parameters of the physics-based model are set up. A configuration of the set up component is changed between at least two of the multiple phases based on the subset of all of the parameters of the physics-based model set up in the at least two of the multiple phases. The set up component may perform a Bayesian optimization technique for cascaded model set up or calibration using multiple information sources and objective functions.

    Deep generative model-based alignment for semiconductor applications
    7.
    发明授权
    Deep generative model-based alignment for semiconductor applications 有权

    公开(公告)号：US11983865B2

    公开(公告)日：2024-05-14

    申请号：US17308878

    申请日：2021-05-05

    Applicant: KLA Corporation

    Inventor： Bjorn Brauer ,  Richard Wallingford

    IPC: G06T7/00 ,  G06T7/33

    CPC classification number: G06T7/001 ,  G06T7/337 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30148

    Abstract: Methods and systems for deep learning alignment for semiconductor applications are provided. One method includes transforming first actual information for an alignment target on a specimen from either design data to a specimen image or a specimen image to design data by inputting the first actual information into a deep generative model such as a GAN. The method also includes aligning the transformed first actual information to second actual information for the alignment target, which has the same information type as the transformed first actual information. The method further includes determining an offset between the transformed first actual information and the second actual information based on results of the aligning and storing the determined offset as an align-to-design offset for use in a process performed on the specimen.

    3D structure inspection or metrology using deep learning
    9.
    发明授权
    3D structure inspection or metrology using deep learning 有权

    公开(公告)号：US11644756B2

    公开(公告)日：2023-05-09

    申请号：US17393979

    申请日：2021-08-04

    Applicant: KLA Corporation

    Inventor： Scott A. Young ,  Kris Bhaskar ,  Lena Nicolaides

    IPC: G03F7/20 ,  G06T7/00 ,  G06N3/04

    CPC classification number: G03F7/7065 ,  G03F7/70508 ,  G03F7/70666 ,  G06N3/04 ,  G06T7/0004 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30148

    Abstract: Methods and systems for determining information for a specimen are provided. Certain embodiments relate to bump height 3D inspection and metrology using deep learning artificial intelligence. For example, one embodiment includes a deep learning (DL) model configured for predicting height of one or more 3D structures formed on a specimen based on one or more images of the specimen generated by an imaging subsystem. One or more computer systems are configured for determining information for the specimen based on the predicted height. Determining the information may include, for example, determining if any of the 3D structures are defective based on the predicted height. In another example, the information determined for the specimen may include an average height metric for the one or more 3D structures.

Patent Agency Ranking