Abstract: The present disclosure relates to semiconductor structures and, more particularly, to a transistor with a thermal plug and methods of manufacture. The structure includes: a semiconductor substrate; a gate structure over the semiconductor substrate; a source region on a first side of the gate structure; a drain region on a second side of the gate structure; and a thermal plug extending from a top side of the semiconductor substrate into an active region of the semiconductor substrate.

Abstract: Systems, methods, and computer program products are provided for dynamically processing model inference or training requests. A system may include at least one processor to receive a plurality of requests from a plurality of requesting systems, create a plurality of instantiations of at least one machine-learning model based on the plurality of requests and service data associated with each requesting system of the plurality of requesting systems, stream data associated with at least one request of the plurality of requests to each instantiation of the plurality of instantiations, adjust a rate limit for each instantiation of the plurality of instantiations based on the service data associated with at least one requesting system related to a respective instantiation, resulting in an adjusted rate limit, and process at least one request of the plurality of requests with an instantiation of the plurality of instantiations based on the adjusted rate limit.

Abstract: Disclosed are a transistor and a method for forming the transistor. The method includes concurrently forming gate and source/drain openings through an uppermost layer (i.e., a dielectric layer) in a stack of layers. The method can further include: depositing and patterning gate conductor material so that a first gate section is in the gate opening and a second gate section is above the gate opening and so that the source/drain openings are exposed; extending the depth of the source/drain openings; and depositing and patterning source/drain conductor material so that a first source/drain section is in each source/drain opening and a second source/drain section is above each source/drain opening. Alternatively, the method can include: forming a plug in the gate opening and sidewall spacers in the source/drain openings; extending the depth of source/drain openings; depositing and patterning the source/drain conductor material; and subsequently depositing and patterning the gate conductor material.

Abstract: A device controls opening and closing of window blinds connected to a headrail. A clamping module for securing the device to the headrail includes an upper clamp member for engaging an upper surface of the headrail and a lower clamp member for engaging a lower surface of the headrail. The upper clamp member and the lower clamp member are movably coupled to each other so as to enable clamping of the headrail by the upper clamp member and the lower clamp member. A drive module is coupled to the clamping module and includes an actuator for connecting to a tilting mechanism configured to open and close the window blinds. A drive mechanism is operatively coupled to the actuator and is configured to drive movement of the actuator such that the tilting mechanism is operated when connected to the actuator.

Abstract: The present disclosure relates to semiconductor structures and, more particularly, to high-electron-mobility transistors and methods of manufacture. A structure includes: a semiconductor layer on a semiconductor material; a gate structure on the semiconductor layer; a drain region comprising the semiconductor layer and which is adjacent to the gate structure; an ohmic contact which includes at least one terminal connection connecting to the semiconductor material, the ohmic contact being adjacent to the drain region and spaced away from the gate structure; and a capacitance reducing structure adjacent to the drain region.

Abstract: Systems and methods of reconfiguring machine learning models are disclosed. A method includes receiving, by a server computer, external data and determining, by the server computer, a machine learning model from a plurality of machine learning models, based on the external data. The plurality of machine learning models are in standby mode. The server computer configures an AI engine with the machine learning model. The method also includes receiving, by the server computer, a prediction request from a client computer, processing the prediction request with the AI engine to form a prediction response, and sending the prediction response to the client computer.

Abstract: Disclosed are embodiments of a transistor (e.g., a III-V high electron mobility transistor (HEMT), a III-V metal-insulator-semiconductor HEMT (MISHEMT), or the like) that has multiple self-aligned terminals. The self-aligned terminals include a self-aligned gate, a self-aligned source terminal and, optionally, a self-aligned drain terminal. By forming self-aligned terminals during processing, the separation distances between the terminals (e.g., between the gate and source terminal and, optionally, between the gate and drain terminal) can be reduced in order to reduce device size and to improve performance (e.g., to reduce on resistance and increase switching speeds). Also disclosed herein are method embodiments for forming such a transistor.

Abstract: The present disclosure relates to semiconductor structures and, more particularly, to a bipolar transistor with a stepped emitter and methods of manufacture. The structure includes: a collector; a base over the collector; and an emitter over the base, the emitter comprising at least one stepped feature over the base.

Abstract: Disclosed are a transistor and a method for forming the transistor. The method includes concurrently forming gate and source/drain openings through an uppermost layer (i.e., a dielectric layer) in a stack of layers. The method can further include: depositing and patterning gate conductor material so that a first gate section is in the gate opening and a second gate section is above the gate opening and so that the source/drain openings are exposed; extending the depth of the source/drain openings; and depositing and patterning source/drain conductor material so that a first source/drain section is in each source/drain opening and a second source/drain section is above each source/drain opening. Alternatively, the method can include: forming a plug in the gate opening and sidewall spacers in the source/drain openings; extending the depth of source/drain openings; depositing and patterning the source/drain conductor material; and subsequently depositing and patterning the gate conductor material.

Abstract: Disclosed are a transistor and a method for forming the transistor. The method includes concurrently forming gate and source/drain openings through an uppermost layer (i.e., a dielectric layer) in a stack of layers. The method can further include: depositing and patterning gate conductor material so that a first gate section is in the gate opening and a second gate section is above the gate opening and so that the source/drain openings are exposed; extending the depth of the source/drain openings; and depositing and patterning source/drain conductor material so that a first source/drain section is in each source/drain opening and a second source/drain section is above each source/drain opening. Alternatively, the method can include: forming a plug in the gate opening and sidewall spacers in the source/drain openings; extending the depth of source/drain openings; depositing and patterning the source/drain conductor material; and subsequently depositing and patterning the gate conductor material.

Abstract: Disclosed are embodiments of a transistor (e.g., a III-V high electron mobility transistor (HEMT), a III-V metal-insulator-semiconductor HEMT (MISHEMT), or the like) that has multiple self-aligned terminals. The self-aligned terminals include a self-aligned gate, a self-aligned source terminal and, optionally, a self-aligned drain terminal. By forming self-aligned terminals during processing, the separation distances between the terminals (e.g., between the gate and source terminal and, optionally, between the gate and drain terminal) can be reduced in order to reduce device size and to improve performance (e.g., to reduce on resistance and increase switching speeds). Also disclosed herein are method embodiments for forming such a transistor.

Abstract: The present disclosure relates to integrated circuits, and more particularly, to an anti-tamper x-ray blocking package for secure integrated circuits and methods of manufacture and operation. In particular, the present disclosure relates to a structure including: one or more devices on a front side of a semiconductor material; a plurality of patterned metal layers under the one or more devices, located and structured to protect the one or more devices from an active intrusion; an insulator layer between the plurality of patterned metal layers; and at least one contact providing an electrical connection through the semiconductor material to a front side of the plurality of metals.

Abstract: Disclosed are a transistor and a method for forming the transistor. The method includes concurrently forming gate and source/drain openings through an uppermost layer (i.e., a dielectric layer) in a stack of layers. The method can further include: depositing and patterning gate conductor material so that a first gate section is in the gate opening and a second gate section is above the gate opening and so that the source/drain openings are exposed; extending the depth of the source/drain openings; and depositing and patterning source/drain conductor material so that a first source/drain section is in each source/drain opening and a second source/drain section is above each source/drain opening. Alternatively, the method can include: forming a plug in the gate opening and sidewall spacers in the source/drain openings; extending the depth of source/drain openings; depositing and patterning the source/drain conductor material; and subsequently depositing and patterning the gate conductor material.

Abstract: The present disclosure relates to integrated circuits, and more particularly, to an anti-tamper x-ray blocking package for secure integrated circuits and methods of manufacture and operation. In particular, the present disclosure relates to a structure including: one or more devices on a front side of a semiconductor material; a plurality of patterned metal layers under the one or more devices, located and structured to protect the one or more devices from an active intrusion; an insulator layer between the plurality of patterned metal layers; and at least one contact providing an electrical connection through the semiconductor material to a front side of the plurality of metals.

Abstract: Systems and methods of reconfiguring machine learning models are disclosed. A method includes receiving, by a server computer, external data and determining, by the server computer, a machine learning model from a plurality of machine learning models, based on the external data. The plurality of machine learning models are in standby mode. The server computer configures an AI engine with the machine learning model. The method also includes receiving, by the server computer, a prediction request from a client computer, processing the prediction request with the AI engine to form a prediction response, and sending the prediction response to the client computer.

Abstract: The present disclosure relates to an active x-ray attack prevention structure for secure integrated circuits. In particular, the present disclosure relates to a structure including a functional circuit, and at least one latchup sensitive diode circuit configured to induce a latchup condition in the functional circuit, placed in proximity of the functional circuit.

Abstract: The present disclosure relates to an active x-ray attack prevention structure for secure integrated circuits. In particular, the present disclosure relates to a structure including a functional circuit, and at least one latchup sensitive diode circuit configured to induce a latchup condition in the functional circuit, placed in proximity of the functional circuit.

Abstract: Systems and methods of reconfiguring machine learning models are disclosed. A method includes receiving, by a server computer, external data and determining, by the server computer, a machine learning model from a plurality of machine learning models, based on the external data. The plurality of machine learning models are in standby mode. The server computer configures an AI engine with the machine learning model. The method also includes receiving, by the server computer, a prediction request from a client computer, processing the prediction request with the AI engine to form a prediction response, and sending the prediction response to the client computer.

Abstract: The present disclosure relates to a metal layer for an active x-ray attack prevention device for securing integrated circuits. In particular, the present disclosure relates to a structure including a semiconductor material, one or more devices on a front side of the semiconductor material, a backside patterned metal layer under the one or more devices, located and structured to protect the one or more devices from an active intrusion, and at least one contact providing an electrical connection through the semiconductor material to a front side of the backside patterned metal layer. The backside patterned metal layer is between a wafer and one of the semiconductor material and an insulator layer.

Abstract: Systems and methods of reconfiguring machine learning models are disclosed. A method includes receiving, by a server computer, external data and determining, by the server computer, a machine learning model from a plurality of machine learning models, based on the external data. The plurality of machine learning models are in standby mode. The server computer configures an AI engine with the machine learning model. The method also includes receiving, by the server computer, a prediction request from a client computer, processing the prediction request with the AI engine to form a prediction response, and sending the prediction response to the client computer.