Patents by Inventor Zhaxylyk A. Kudyshev

Zhaxylyk A. Kudyshev has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 12159369
    Abstract: A method of providing super-resolved images of a photon emitting particle is disclosed, which includes providing a machine-learning (ML) platform, wherein the ML platform is configured to receive pixel-based sparse autocorrelation data and generate a predicted super-resolved image of a photon emitting particle, receiving photons from the photon emitting particle by two or more photon detectors, each generating an electrical pulse associated with receiving an incident photon thereon, generating sparse autocorrelation data from the two or more photon detectors for each pixel within an image area, and inputting the pixel-based sparse autocorrelation data to the ML platform, thereby generating a predicted super-resolved image of the imaging area, wherein the resolution of the super-resolved image is improved by ?n as compared to a classical optical microscope limited by Abbe diffraction limit.
    Type: Grant
    Filed: July 6, 2022
    Date of Patent: December 3, 2024
    Assignee: Purdue Research Foundation
    Inventors: Zhaxylyk A. Kudyshev, Demid Sychev, Zachariah Olson Martin, Simeon I. Bogdanov, Xiaohui Xu, Alexander Kildishev, Alexandra Boltasseva, Vladimir Shalaev
  • Publication number: 20230177642
    Abstract: A method of providing super-resolved images of a photon emitting particle is disclosed, which includes providing a machine-learning (ML) platform, wherein the ML platform is configured to receive pixel-based sparse autocorrelation data and generate a predicted super-resolved image of a photon emitting particle, receiving photons from the photon emitting particle by two or more photon detectors, each generating an electrical pulse associated with receiving an incident photon thereon, generating sparse autocorrelation data from the two or more photon detectors for each pixel within an image area, and inputting the pixel-based sparse autocorrelation data to the ML platform, thereby generating a predicted super-resolved image of the imaging area, wherein the resolution of the super-resolved image is improved by ?n as compared to a classical optical microscope limited by Abbe diffraction limit.
    Type: Application
    Filed: July 6, 2022
    Publication date: June 8, 2023
    Applicant: Purdue Research Foundation
    Inventors: Zhaxylyk A. Kudyshev, Demid Sychev, Zachariah Olson Martin, Simeon I. Bogdanov, Xiaohui Xu, Alexander Kildishev, Alexandra Boltasseva, Vladimir Shalaev
  • Patent number: 11656386
    Abstract: A plasmonic system is disclosed. The system includes at least one polarizer that is configured to provide at least one linearly polarized broadband light beam, an anisotropic plasmonic metasurface (APM) assembly having a plurality of nanoantennae each having a predetermined orientation with respect to a global axis representing encoded digital data, the APM assembly configured to receive the at least one linearly polarized broadband light beam and by applying localized surface plasmon resonance reflect light with selectable wavelengths associated with the predetermined orientations of the nanoantennae, and at least one analyzer that is configured to receive the reflected light with selectable wavelength, wherein the relative angles between each of the at least one analyzers and each of the at least one polarizers are selectable with respect to the global axis, thereby allowing decoding of the digital data.
    Type: Grant
    Filed: April 7, 2021
    Date of Patent: May 23, 2023
    Assignee: Purdue Research Foundation
    Inventors: Alexander V. Kildishev, Di Wang, Zhaxylyk A. Kudyshev, Maowen Song, Alexandra Boltasseva, Vladimir M. Shalaev
  • Publication number: 20210325577
    Abstract: A plasmonic system is disclosed. The system includes at least one polarizer that is configured to provide at least one linearly polarized broadband light beam, an anisotropic plasmonic metasurface (APM) assembly having a plurality of nanoantennae each having a predetermined orientation with respect to a global axis representing encoded digital data, the APM assembly configured to receive the at least one linearly polarized broadband light beam and by applying localized surface plasmon resonance reflect light with selectable wavelengths associated with the predetermined orientations of the nanoantennae, and at least one analyzer that is configured to receive the reflected light with selectable wavelength, wherein the relative angles between each of the at least one analyzers and each of the at least one polarizers are selectable with respect to the global axis, thereby allowing decoding of the digital data.
    Type: Application
    Filed: April 7, 2021
    Publication date: October 21, 2021
    Applicant: Purdue Research Foundation
    Inventors: Alexander V. Kildishev, Di Wang, Zhaxylyk A. Kudyshev, Maowen Song, Alexandra Boltasseva, Vladimir M. Shalaev
  • Publication number: 20190353830
    Abstract: A plasmonic system is disclosed. The system includes at least one polarizer that is configured to provide at least one linearly polarized broadband light beam, an anisotropic plasmonic metasurface (APM) assembly having a plurality of nanoantennae each having a predetermined orientation with respect to a global axis representing encoded digital data, the APM assembly configured to receive the at least one linearly polarized broadband light beam and by applying localized surface plasmon resonance reflect light with selectable wavelengths associated with the predetermined orientations of the nano antennae, and at least one analyzer that is configured to receive the reflected light with selectable wavelength, wherein the relative angles between each of the at least one analyzers and each of the at least one polarizers are selectable with respect to the global axis, thereby allowing decoding of the digital data.
    Type: Application
    Filed: May 13, 2019
    Publication date: November 21, 2019
    Applicant: Purdue Research Foundation
    Inventors: Alexander V. Kildishev, Di Wang, Zhaxylyk A. Kudyshev, Maowen Song, Alexandra Boltasseva, Vladimir M. Shalaev