-
公开(公告)号:US12105048B2
公开(公告)日:2024-10-01
申请号:US18154235
申请日:2023-01-13
申请人: Lyten, Inc.
发明人: Bruce Lanning , Michael W. Stowell , Carlos Montalvo , Daniel Cook , Sung H. Lim , Shreeyukta Singh , John Chmiola
IPC分类号: G01N27/414 , B01J20/28 , B33Y80/00 , C01B32/182 , C23C20/00 , G01N27/12 , G01N27/404 , G01N29/036 , G01N33/00 , H01M4/62 , H01M4/66 , H01M4/80 , H01M4/96 , H01M10/0525 , H01M12/08
CPC分类号: G01N27/4141 , B01J20/28066 , C01B32/182 , C23C20/00 , H01M4/62 , H01M4/625 , H01M4/663 , H01M4/667 , H01M4/801 , H01M4/96 , H01M10/0525 , H01M12/08 , B33Y80/00 , C01B2204/04 , C01B2204/22 , C01B2204/32 , G01N27/127 , G01N27/4045 , G01N29/036 , G01N33/0037 , G01N33/0039 , G01N33/004 , G01N33/0044 , G01N2291/014
摘要: A battery-powered analyte sensing system includes a printed battery and an analyte sensor. The printed battery includes an anode composed of a non-toxic biocompatible metal, a first carbon-based current collector in electrical contact with the anode, a three-dimensional hierarchical mesoporous carbon-based cathode, a second carbon-based current collector, and an electrolyte layer disposed between the anode and the cathode, the electrolyte layer configured to activate the printed battery when the electrolyte is released into one or both the anode and the cathode. The analyte sensor includes a sensing material and a reactive chemistry additive in the sensing material.
-
公开(公告)号:US20240288381A1
公开(公告)日:2024-08-29
申请号:US18440753
申请日:2024-02-13
申请人: Lyten, Inc.
发明人: Michael Stowell , Daniel Cook , Carlos Montalvo , George Clayton Gibbs , Jacques Nicole , Karel Vanheusden , Kyle Matthys , Bruce Lanning , Sung Lim , John Chmiola
摘要: Methods and system to learn precise sensing fingerprints based on machine learning integration are disclosed herein. In use, the system receives at least one first parameter associated with at least one sensor and associates the first parameter with a pre-identified first digital signature in a signature database. A machine learning system is trained based on the first parameter and the pre-identified digital signature. The system then receives at least one second parameter from the at least one sensor and determines that the second parameter is independent of a digital signature in the signature database. Using the machine learning system, a second digital signature for the second parameter is identified and saved in the signature database.
-
公开(公告)号:US11555799B2
公开(公告)日:2023-01-17
申请号:US16740381
申请日:2020-01-10
申请人: Lyten, Inc.
发明人: Bruce Lanning , Michael W. Stowell , Carlos Montalvo , Daniel Cook , Sung H. Lim , Shriyukta Singh , John Chmiola
IPC分类号: C01B32/182 , B01J20/28 , C23C20/00 , H01M4/62 , H01M10/0525 , H01M12/08 , H01M4/66 , H01M4/80 , H01M4/96 , B33Y80/00 , G01N27/414 , G01N33/00 , G01N27/404 , G01N27/12 , G01N29/036
摘要: A battery system comprising: an anode composed of a non-toxic biocompatible metal; a first printable carbon-based current collector comprising biocompatible multiple few layer graphene (FLG) sheets in electrical contact with and extending from the anode; a three-dimensional (3D) hierarchical mesoporous carbon-based cathode including an open porous structure configured to catalyze an active material via gas diffusion; a polymer-based barrier film deposited on the 3D hierarchical mesoporous carbon-based cathode, the polymer-based barrier film configured to prevent oxygen from entering the open porous structure while deposited on the 3D hierarchical mesoporous carbon-based cathode; a second printable carbon-based current collector comprising biocompatible multiple few layer graphene (FLG) sheets in electrical contact with and extending from the cathode; and an electrolyte layer disposed between the anode and the cathode, the electrolyte layer configured to activate the battery system when released into one or both of the anode and the cathode.
-
公开(公告)号:US20210181146A1
公开(公告)日:2021-06-17
申请号:US17182045
申请日:2021-02-22
申请人: Lyten, Inc.
发明人: Michael W. Stowell , Bruce Lanning , Sung H. Lim , John Chmiola , Karel Vanheusden , Daniel Cook , George Clayton Gibbs
IPC分类号: G01N27/414 , C01B32/182 , B01J20/28
摘要: A sensing device for detecting analytes within a package or container is disclosed. In various implementations, the sensing device may include a substrate, one or more electrodes, and a sensor array. The sensor array may be disposed on the substrate, and may include a plurality of carbon-based sensors coupled to the one or more electrodes. The carbon-based sensors may be configured to react with unique groups of analytes in response to an electromagnetic signal received from an external device. In some instances, a first sensor may be configured to detect a presence of each analyte of a group of analytes, and a second sensor may be configured to confirm the presence of each analyte of a subset of the group of analytes.
-
公开(公告)号:US20210181145A1
公开(公告)日:2021-06-17
申请号:US17182006
申请日:2021-02-22
申请人: Lyten, Inc.
发明人: Michael W. Stowell , Bruce Lanning , Sung H. Lim , John Chmiola , Karel Vanheusden , Daniel Cook , George Clayton Gibbs
IPC分类号: G01N27/414 , C01B32/182 , B01J20/28
摘要: Sensors for detecting analytes are disclosed. In various implementations, the sensing device may include a substrate and a sensor array. The sensor array may be arranged on the substrate, and may include a plurality of sensors. In some implementations, at least two of the sensors may include a first carbon-based sensing material disposed between a first pair of electrodes, and a second carbon-based sensing material disposed between a second pair of electrodes. The first carbon-based sensing material may be configured to detect a presence of each analyte of a group of analytes, and the second carbon-based sensing material may be configured to confirm the presence of each analyte of a subset of the group of analytes. In some instances, the group of analytes includes at least twice as many different analytes as the subset of analytes.
-
公开(公告)号:US20240272103A1
公开(公告)日:2024-08-15
申请号:US18440806
申请日:2024-02-13
申请人: Lyten, Inc.
发明人: Daniel Cook , Michael Stowell , Karel Vanheusden , George Clayton Gibbs , Jacques Nicole , Carlos Montalvo , Kyle Matthys , Bruce Lanning , Sung Lim , John Chmiola
摘要: Methods and system to learn precise sensing fingerprints based on machine learning integration are disclosed herein. In use, the system receives at least one first parameter associated with at least one sensor and associates the first parameter with a pre-identified first digital signature in a signature database. A machine learning system is trained based on the first parameter and the pre-identified digital signature. The system then receives at least one second parameter from the at least one sensor and determines that the second parameter is independent of a digital signature in the signature database. Using the machine learning system, a second digital signature for the second parameter is identified and saved in the signature database.
-
公开(公告)号:US11988628B2
公开(公告)日:2024-05-21
申请号:US17182069
申请日:2021-02-22
申请人: Lyten, Inc.
IPC分类号: G01N27/414 , B01J20/28 , C01B32/182 , G01N27/12 , G01N27/404 , G01N29/036 , G01N33/00
CPC分类号: G01N27/4141 , B01J20/28066 , C01B32/182 , C01B2204/04 , C01B2204/22 , C01B2204/32 , G01N27/127 , G01N27/4045 , G01N29/036 , G01N33/0037 , G01N33/0039 , G01N33/004 , G01N33/0044 , G01N2291/014
摘要: A container for storing one or more items is disclosed. The container may include a surface defining a volume of the container and a label printed on the container. In various implementations, the label includes a substrate, a plurality of carbon-based sensors printed on the substrate, and one or more electrodes printed on the substrate. The sensors may be collectively configured to detect a presence of one or more analytes within the container. Each sensor may be configured to react with a unique group of analytes in response to an electromagnetic signal received from an external device. The electrodes may be configured to provide one or more output signals indicating the presence or absence of the one or more analytes within the container.
-
公开(公告)号:US10955378B2
公开(公告)日:2021-03-23
申请号:US16706542
申请日:2019-12-06
申请人: Lyten, Inc.
IPC分类号: G01N27/414 , C01B32/182 , B01J20/28 , G01N33/00 , G01N27/404 , G01N29/036 , G01N27/12
摘要: A method for detecting an analyte comprises providing a first carbon-based material comprising reactive chemistry additives, providing conductive electrodes connected to the first carbon-based material, exposing the first carbon-based material to an analyte, applying a plurality of alternating currents having a range of frequencies across the conductive electrodes, and measuring the complex impedance of the first carbon-based material using the plurality of alternating currents.
-
公开(公告)号:US20190204265A1
公开(公告)日:2019-07-04
申请号:US16239423
申请日:2019-01-03
申请人: Lyten, Inc.
IPC分类号: G01N27/414 , B01J20/28 , C01B32/182
CPC分类号: G01N27/4141 , B01J20/28066 , C01B32/182 , G01N2291/014
摘要: A method for detecting an analyte comprises providing a first carbon-based material comprising reactive chemistry additives, providing conductive electrodes connected to the first carbon-based material, exposing the first carbon-based material to an analyte, applying a plurality of alternating currents having a range of frequencies across the conductive electrodes, and measuring the complex impedance of the first carbon-based material using the plurality of alternating currents.
-
10.
公开(公告)号:US20240280526A1
公开(公告)日:2024-08-22
申请号:US18440741
申请日:2024-02-13
申请人: Lyten, Inc.
发明人: Daniel Cook , Michael Stowell , Karel Vanheusden , George Clayton Gibbs , Jacques Nicole , Carlos Montalvo , Kyle Matthys , Bruce Lanning , Sung Lim , John Chmiola
IPC分类号: G01N27/22 , G01N27/414 , G01N27/447
CPC分类号: G01N27/221 , G01N27/4145 , G01N27/447 , G01N2027/222
摘要: Methods and system to learn precise sensing fingerprints based on machine learning integration are disclosed herein. In use, the system receives at least one first parameter associated with at least one sensor and associates the first parameter with a pre-identified first digital signature in a signature database. A machine learning system is trained based on the first parameter and the pre-identified digital signature. The system then receives at least one second parameter from the at least one sensor and determines that the second parameter is independent of a digital signature in the signature database. Using the machine learning system, a second digital signature for the second parameter is identified and saved in the signature database.
-
-
-
-
-
-
-
-
-