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    Material identification through image capture of Raman scattering
    167.
    发明授权
    Material identification through image capture of Raman scattering 有权

    公开(公告)号：US12025561B2

    公开(公告)日：2024-07-02

    申请号：US17604006

    申请日：2020-04-15

    Applicant: Ohio State Innovation Foundation

    Inventor： Heather Allen ,  Juan Velez

    IPC: G01N21/65 ,  G01J3/18 ,  G01J3/28 ,  G01J3/44

    CPC classification number: G01N21/65 ,  G01J3/18 ,  G01J3/2823 ,  G01J3/4412 ,  G01N2201/06113 ,  G01N2201/1296

    Abstract: A hand-held sized imaging instrument identifies molecules with high selectivity and in complex mixtures. The instrument uses inelastic scattering and scattering intensities from with machine learning algorithms based on convolutional neural networks (CNN's) to identify the presence of a specified chemical or combination of chemicals. A laser is housed within the instrument to initiate a material response of a sample using laser light of a specified wavelength. The instrument uses an image sensor to capture visible images with inelastic scattering information. The CNN is able to classify the image to determine whether the specified chemical or combination of chemicals is present in the sample. The instrument is inexpensive, portable, easy to use by anyone (nonchemist, nonprofessional), and safe (laser is completely housed). The instrument can be used efficiently and easily for quality control, security, and other applications to reliably detect the presence of specified substances.

    A SMART TISSUE CLASSIFICATION FRAMEWORK BASED ON MULTI-CLASSIFIER SYSTEMS
    168.
    发明公开
    A SMART TISSUE CLASSIFICATION FRAMEWORK BASED ON MULTI-CLASSIFIER SYSTEMS 审中-公开

    公开(公告)号：US20240210321A1

    公开(公告)日：2024-06-27

    申请号：US18567981

    申请日：2022-06-07

    Applicant: CytoVeris Inc.

    Inventor： Rishikesh Pandey ,  Alan Kersey ,  Gary Root ,  Aditya Shirvalkar

    IPC: G01N21/64

    CPC classification number: G01N21/6486 ,  G01N21/645 ,  G01N2021/6417 ,  G01N2201/1296

    Abstract: A method and system of analyzing an ex-vivo tissue sample is provided. The method includes interrogating the tissue sample a plurality of times, each interrogation using at least one excitation light centered on a wavelength distinct from the others, at least one excitation light produces AF emissions from one or more biomolecules associated with the tissue sample, and another is produces diffuse reflectance signals from the tissue sample; b) using a photodetector to detect the AF emissions or diffuse reflectance signals from the tissue sample, producing photodetector signals representative thereof; c) processing the photodetector signals attributable to the AF emissions using a first trained classifier to determine first data sets indicative of biomolecules; d) processing the photodetector signals attributable to the diffuse reflectance signals using a second trained classifier to determine one or more second data sets; and e) determining a type of the tissue sample.

    CONTACTLESS MEASUREMENT OF ROCK WETTABILITY BY PHOTONIC TECHNIQUES
    169.
    发明公开
    CONTACTLESS MEASUREMENT OF ROCK WETTABILITY BY PHOTONIC TECHNIQUES 审中-公开

    公开(公告)号：US20240201079A1

    公开(公告)日：2024-06-20

    申请号：US18082186

    申请日：2022-12-15

    Applicant: Saudi Arabian Oil Company

    Inventor： Adrian Cesar Cavazos Sepulveda ,  Damian Pablo San Roman Alerigi ,  Ziyad K. Kaidar ,  Thamer Zahrani

    IPC: G01N21/3563 ,  G01N21/3581 ,  G01N21/552

    CPC classification number: G01N21/3563 ,  G01N21/3581 ,  G01N21/552 ,  G01N2201/1296

    Abstract: Systems and methods include a computer-implemented method for analyzing rock samples. Rock and oil electromagnetic baselines are determined for rock samples in at least a section of an electromagnetic spectrum ranging from ultraviolet to long terahertz radiation. An aging process is conducted on each rock sample, initially starting with the rock and oil electromagnetic baselines. The aging process is repeated using spectrometry on the rock sample and measured wettabilities of the rock sample until changes in spectra are less than a predetermined threshold. Aging information including the spectra and wettabilities are stored in a machine learning database. Spectra are obtained from an unknown rock sample. The spectra are mapped to clusters in the machine learning database. Wettability ranges are determined for the unknown rock sample based on a mapping of the spectra of the unknown rock sample to clusters in the machine learning database.

    FLUID QUALITY MONITORING
    170.
    发明公开
    FLUID QUALITY MONITORING 审中-公开

    公开(公告)号：US20240003808A1

    公开(公告)日：2024-01-04

    申请号：US18038111

    申请日：2021-12-10

    Applicant: UPONOR OYJ

    Inventor： Esa Hämäläinen ,  Tero Kesti ,  Teemu Heikkilä ,  Vili Hätönen ,  Oskari Lehto ,  Joel Pyykkö

    IPC: G01N21/45

    CPC classification number: G01N21/453 ,  G01N2201/1296 ,  G01N33/18

    Abstract: It is an objective to provide a fluid quality measurement device. According to an embodiment, a fluid quality measurement device is configured to: obtain a plurality of holograms, wherein each hologram in the plurality of holograms represents a microscopic object in a fluid sample; produce a latent space representation of each hologram using a trained autoencoder neural network; assign each hologram in the plurality of holograms to a class based on the latent space representation of the hologram; and produce a fluid sample fingerprint based on the assignment of the plurality of holograms into the plurality of classes.

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