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公开(公告)号：US10928335B2
公开(公告)日：2021-02-23
申请号：US16516837
申请日：2019-07-19
Applicant: FEI Company
Inventor： Pavel Potocek
IPC: G01N23/2251 , H01J37/26 , H01J37/28
Abstract: Techniques for adapting an adaptive specimen image acquisition system using an artificial neural network (ANN) are disclosed. An adaptive specimen image acquisition system is configurable to scan a specimen to produce images of varying qualities. An adaptive specimen image acquisition system first scans a specimen to produce a low-quality image. An ANN identifies objects of interest within the specimen image. A scan mask indicates regions of the image corresponding to the objects of interest. The adaptive specimen image acquisition system scans only the regions of the image corresponding to the objects of interest, as indicated by the scan mask, to produce a high-quality image. The low-quality image and the high-quality image are merged in a final image. The final image shows the objects of interest at a higher quality, and the rest of the specimen at a lower quality.
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102.发明授权公开(公告)号：US10903043B2
公开(公告)日：2021-01-26
申请号：US16219986
申请日：2018-12-14
Applicant: FEI Company
Inventor： Remco Schoenmakers , Maurice Peemen , Faysal Boughorbel , Pavel Potocek
Abstract: The present invention relates to a method of training a network for reconstructing and/or segmenting microscopic images comprising the step of training the network in the cloud. Further, for training the network in the cloud training data comprising microscopic images can be uploaded into the cloud and a network is trained by the microscopic images. Moreover, for training the network the network can be benchmarked after the reconstructing and/or segmenting of the microscopic images. Wherein for benchmarking the network the quality of the image(s) having undergone the reconstructing and/or segmenting by the network can be compared with the quality of the image(s) having undergone reconstructing and/or segmenting by already known algorithm and/or a second network.
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公开(公告)号：US10832901B2
公开(公告)日：2020-11-10
申请号：US16424206
申请日：2019-05-28
Applicant: FEI Company
Inventor： Bert Henning Freitag , Sorin Lazar , Stephan Kujawa , Maarten Kuijper , Gerard Nicolaas Anne van Veen , Peter Christiaan Tiemeijer , Jamie McCormack
Abstract: A method of performing Electron Energy-Loss Spectroscopy (EELS) in an electron microscope, comprising: Producing a beam of electrons from a source; Using an illuminator to direct said beam so as to irradiate the specimen; Using an imaging system to receive a flux of electrons transmitted through the specimen and direct it onto a spectroscopic apparatus comprising: A dispersion device, for dispersing said flux in a dispersion direction so as to form an EELS spectrum; and A detector, comprising a detection surface that is sub-divided into a plurality of detection zones, specifically comprising: Using at least a first detection zone, a second detection zone and a third detection zone to register a plurality of EELS spectral entities; and Reading out said first and said second detection zones whilst said third detection zone is registering one of said plurality of EELS spectral entities.
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公开(公告)号：US20200349713A1
公开(公告)日：2020-11-05
申请号：US16929709
申请日：2020-07-15
Applicant: FEI Company
Inventor： Umesh Adiga
Abstract: Smart metrology methods and apparatuses disclosed herein process images for automatic metrology of desired features. An example method at least includes extracting a region of interest from an image, the region including one or more boundaries between different sections, enhancing at least the extracted region of interest based on one or more filters, generating a multi-scale data set of the region of interest based on the enhanced region of interest, initializing a model of the region of interest; optimizing a plurality of active contours within the enhanced region of interest based on the model of the region of interest and further based on the multi-scale data set, the optimized plurality of active contours identifying the one or more boundaries within the region of interest, and performing metrology on the region of interest based on the identified boundaries.
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公开(公告)号：US10825647B2
公开(公告)日：2020-11-03
申请号：US16255210
申请日：2019-01-23
Applicant: FEI Company
Inventor： Bart Jozef Janssen , Lingbo Yu , Erik Michiel Franken
Abstract: A method of using a Transmission Charged Particle Microscope, comprising: Providing a specimen on a specimen holder; Using an illumination system to direct a beam of charged particles from a source onto said specimen; Using an imaging system to direct charged particles that are transmitted through the specimen onto a detector, further comprising the following actions: In an acquisition step, lasting a time interval T, using said detector in particle counting mode to register spatiotemporal data relating to individual particle detection incidences, and to output said spatiotemporal data in raw form, without assembly into an image frame; In a subsequent rendering step, assembling a final image from said spatiotemporal data, while performing a mathematical correction operation.
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Patent Agency Ranking
公开(公告)号：US10825644B1
公开(公告)日：2020-11-03
申请号：US16522415
申请日：2019-07-25
Applicant: FEI Company
Inventor： Alexander Henstra
IPC: H01J37/153 , H01J37/28 , H01J37/20 , H01J37/141 , H01J37/26
Abstract: Charged particle microscopes having an optimized performance across multiple modes of operation are disclosed herein. More specifically, the disclosure includes improved charged particle microscopes that increase and/or optimize the performance of the microscope in both a standard mode of operation and a Lorentz mode of operation. The charged particle microscopes include an extra transfer lens between a corrector and the traditional transfer lens which allows for the flexibility to optimize performance in both the standard mode of operation and the Lorentz mode of operation. For example, in a Lorentz mode of operation, improved charged particle microscope according to the present disclosure can be used to tune the C5 aberration, while hardly affecting defocus and/or CS aberrations. Additionally, the inclusion of the extra transfer lens provides the charged particle microscopes disclosed herein with an extra degree of freedom with which to zero defocus and total CS and C5.
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公开(公告)号：US20200312608A1
公开(公告)日：2020-10-01
申请号：US16370066
申请日：2019-03-29
Applicant: FEI Company
Inventor： Qinsong Steve WANG , Jim MCGINN , Peter TVAROZEK , Amir WEISS
IPC: H01J37/244 , H01J37/21
Abstract: Systems and devices for improving the efficiency of secondary electron detection in charged particle beam systems include a charged particle detector, a first elongate member coupled with the charged particle detector, and a second elongate member coupled with the charged particle detector. The first elongate member and the second elongate member each extend away from the charged particle detector. The system also includes at least one drawing member that is coupled with the first elongate member. Additionally, at least one electrical connection point is arranged to supply at least one bias voltage to the first elongate member, the second elongate member, and the drawing member. The drawing member is configured to generate an electromagnetic field that applies a drawing force that draws charged particles away from the charged particle source, and/or reduces the amount of charged particles from the charged particle source that strike the charged particle tool.
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公开(公告)号：US20200294759A1
公开(公告)日：2020-09-17
申请号：US16299948
申请日：2019-03-12
Applicant: FEI Company
Inventor： Zhenxin Zhong
Abstract: Various methods and systems are provided for aligning zone axis of a sample with an incident beam. As one example, the alignment may be based on a zone axis tilt. The zone axis tilt may be determined based on locations of a direct beam and a zero order Laue zone in the diffraction pattern. The direct beam location may be determined based on diffraction patterns acquired with different incident angles.
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公开(公告)号：US20200279362A1
公开(公告)日：2020-09-03
申请号：US16409477
申请日：2019-05-10
Applicant: FEI Company
Inventor： Thomas Gary Miller , John F. Flanagan, IV , Brian Routh, JR. , Richard Young , Brad Larson , Aditee Shrotre
IPC: G06T7/00 , G06K9/62 , H01L21/66 , H01L21/263 , H01L21/268
Abstract: Methods and systems for implementing artificial intelligence enabled preparation end-pointing are disclosed. An example method at least includes obtaining an image of a surface of a sample, the sample including a plurality of features, analyzing the image to determine whether an end point has been reached, the end point based on a feature of interest out of the plurality of features observable in the image, and based on the end point not being reached, removing a layer of material from the surface of the sample.
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公开(公告)号：US10685759B2
公开(公告)日：2020-06-16
申请号：US15407098
申请日：2017-01-16
Applicant: FEI Company
Inventor： Wilfred Kelsham Fullagar , Andrew Maurice Kingston , Glenn Robert Myers , Mahsa Paziresh , Trond Karsten Varslot
IPC: G01N23/00 , G21K7/00 , G01N23/046 , G01N23/2252
Abstract: A method of analyzing a specimen using X-rays, comprising the steps of: Irradiating the specimen with input X-rays; Using a detector to detect a flux of output X-rays emanating from the specimen in response to said irradiation, which method further comprises the following steps: Using the detector to intercept at least a portion of said flux so as to produce a set {Ij} of pixeled images Ij of at least part of the specimen, whereby the cardinality of the set {Ij} is M>1. For each pixel pi in each image Ij, determining the accumulated signal strength Sij, thus producing an associated set of signal strengths {Sij}. Using the set {Sij} to calculate the following values: A mean signal strength S per pixel position i; A variance σ2S in S per pixel position i. Using these values S and σ2S to produce a map of mean X-ray photon energy E per pixel.
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