Abstract: A complementary metal oxide semiconductor (CMOS) transistor includes a first transistor with a first gate dielectric layer above a first channel, where the first gate dielectric layer includes Hf1-xZxO2, where 0.33<x<0.5. The first transistor further includes a first gate electrode on the first gate dielectric layer and a first source region and a first drain region on opposite sides of the first gate electrode. The CMOS transistor further includes a second transistor adjacent to the first transistor. The second transistor includes a second gate dielectric layer above a second channel, where the second gate dielectric layer includes Hf1-xZxO2, where 0.5<x<0.99, a second gate electrode on the second gate dielectric layer and a second source region and a second drain region on opposite sides of the second gate electrode.

Abstract: A memory device structure includes a transistor structure including a gate electrode over a top surface of a fin and adjacent to a sidewall of the fin, a source structure coupled to a first region of the fin and a drain structure coupled to a second region of the fin, where the gate electrode is between the first and the second region. A gate dielectric layer is between the fin and the gate electrode. The memory device structure further includes a capacitor coupled with the transistor structure, the capacitor includes the gate electrode, a ferroelectric layer on a substantially planar uppermost surface of the gate electrode and a word line on the ferroelectric layer.

Abstract: Transistor structures with monocrystalline metal chalcogenide channel materials are formed from a plurality of template regions patterned over a substrate. A crystal of metal chalcogenide may be preferentially grown from a template region and the metal chalcogenide crystals then patterned into the channel region of a transistor. The template regions may be formed by nanometer-dimensioned patterning of a metal precursor, a growth promoter, a growth inhibitor, or a defected region. A metal precursor may be a metal oxide suitable, which is chalcogenated when exposed to a chalcogen precursor at elevated temperature, for example in a chemical vapor deposition process.

Abstract: Thin film transistors having boron nitride integrated with two-dimensional (2D) channel materials are described. In an example, an integrated circuit structure includes a first gate stack above a substrate. A 2D channel material layer is above the first gate stack. A second gate stack is above the 2D channel material layer, the second gate stack having a first side opposite a second side. A first conductive contact is adjacent the first side of the second gate stack and in contact with the 2D channel material layer. A second conductive contact is adjacent the second side of the second gate stack and in contact with the 2D channel material layer. A hexagonal boron nitride (hBN) layer is included between the first gate stack and the 2D channel material layer, between the second gate stack and the 2D channel material layer, or both.

Abstract: A computer-implemented method of determining an agent data attribution and selection to perform a collaborative data-related task includes computing an agent data attribution score for each agent of the plurality of agents associated with the collaborative data-related task. A subset of the plurality of agents that participate in the collaborative data-related task is selected based on the agent data attribution score. An instruction is transmitted to the selected subset of the plurality of agents for each agent to conduct a respective portion of the collaborative data-related task.

Abstract: Disclosed herein are capacitors including built-in electric fields, as well as related devices and assemblies. In some embodiments, a capacitor may include a top electrode region, a bottom electrode region, and a dielectric region between and in contact with the top electrode region and the bottom electrode region, wherein the dielectric region includes a perovskite material, and the top electrode region has a different material structure than the bottom electrode region.

Abstract: A system, computer program product, and method are presented for performing multi-objective automated machine learning, and, more specifically, to identifying a plurality of machine learning pipelines as Pareto-optimal solutions to optimize a plurality of objectives. The method includes receiving input data directed toward one or more subjects of interest and determining a plurality of objectives to be optimized. The method also includes ingesting at least a portion of the input data through one or more machine learning (ML) models. The method further includes aggregating the plurality of objectives into one or more aggregated single objectives. The method also includes determining a plurality of Pareto-optimal solutions, thereby defining a plurality of ML pipelines that optimize the one or more aggregated single objectives. The method further includes selecting one ML pipeline from the plurality of ML pipelines.

Abstract: Thin film transistors having electrostatic double gates are described. In an example, an integrated circuit structure includes an insulator layer above a substrate. A first gate stack is on the insulator layer. A 2D channel material layer is on the first gate stack. A second gate stack is on a first portion of the 2D channel material layer, the second gate stack having a first side opposite a second side. A first conductive contact is adjacent the first side of the second gate stack, the first conductive contact on a second portion of the 2D channel material layer. A second conductive contact is adjacent the second side of the second gate stack, the second conductive contact on a third portion of the 2D channel material layer. A gate electrode of the first gate stack extends beneath a portion of the first conductive contact and beneath a portion of the second conductive contact.

Abstract: A capacitor device includes a first electrode having a first metal alloy or a metal oxide, a relaxor ferroelectric layer adjacent to the first electrode, where the ferroelectric layer includes oxygen and two or more of lead, barium, manganese, zirconium, titanium, iron, bismuth, strontium, neodymium, potassium, or niobium and a second electrode coupled with the relaxor ferroelectric layer, where the second electrode includes a second metal alloy or a second metal oxide.

Abstract: Disclosed herein are transistors including two-dimensional materials, as well as related methods and devices. In some embodiments, a transistor may include a first two-dimensional channel material and a second two-dimensional source/drain (S/D) material in a source/drain (S/D), and the first two-dimensional material and the second two-dimensional material may have different compositions or thicknesses. In some embodiments, a transistor may include a first two-dimensional material in a channel and a second two-dimensional material in a source/drain (S/D), wherein the first two-dimensional material is a single-crystal material, and the second two-dimensional material is a single-crystal material.

Abstract: Disclosed herein are transistors including two-dimensional materials, as well as related methods and devices. In some embodiments, a transistor may include a first two-dimensional channel material and a second two-dimensional source/drain (S/D) material in a source/drain (S/D), and the first two-dimensional material and the second two-dimensional material may have different compositions or thicknesses. In some embodiments, a transistor may include a first two-dimensional material in a channel and a second two-dimensional material in a source/drain (S/D), wherein the first two-dimensional material is a single-crystal material, and the second two-dimensional material is a single-crystal material.

Abstract: One or more computer processors decompose a weight matrix associated with a neural network utilizing a permutation dependent decomposition. The one or more computer processors regenerate a recovered matrix utilizing the decomposed weight matrix. The one or more computer processors reduce an error between the decomposed weight matrix and regenerated recovered matrix.

Abstract: Methods, systems, and computer program products for determining optimal compute resources for distributed batch based optimization applications are provided herein. A method includes obtaining a size of an input dataset, a size of a model, and a set of batch sizes corresponding to a job to be processed using a distributed computing system; computing, based at least in part on the set of batch sizes, one or more node counts corresponding to a number of nodes that can be used for processing said job; estimating, for each given one of the node counts, an execution time to process the job based on an average computation time for a batch of said input dataset and an average communication time for said batch of said input dataset; and selecting, based at least in part on said estimating, at least one of said node counts for processing the job.

Abstract: Embodiments disclosed herein comprise semiconductor devices with two dimensional (2D) semiconductor channels and methods of forming such devices. In an embodiment, the semiconductor device comprises a source contact and a drain contact. In an embodiment, a 2D semiconductor channel is between the source contact and the drain contact. In an embodiment, the 2D semiconductor channel is a shell.

Abstract: A transistor includes a channel including a first layer including a first monocrystalline transition metal dichalcogenide (TMD) material, where the first layer is stoichiometric and includes a first transition metal. The channel further includes a second layer above the first layer, the second layer including a second monocrystalline TMD material, where the second monocrystalline TMD material includes a second transition metal and oxygen, and where the second layer is sub-stoichiometric. The transistor further includes a gate electrode above a first portion of the channel layer, a gate dielectric layer between the channel layer and the gate electrode, a source contact on a second portion of the channel layer and a drain contact on a third portion of the channel layer, where the gate electrode is between drain contact and the source contact.

Abstract: A transistor structure includes a first channel layer over a second channel layer, where the first and the second channel layers include a monocrystalline transition metal dichalcogenide (TMD). The transistor structure further includes a source material coupled to a first end of the first and second channel layers, a drain material coupled to a second end of the first and second channel layers, a gate electrode between the source material and the drain material, and between the first channel layer and the second channel layer and a gate dielectric between the gate electrode and each of the first channel layer and the second channel layer.

Abstract: Described herein are ferroelectric (FE) memory cells that include transistors having gate stacks separate from FE capacitors of these cells. An example memory cell may be implemented as an IC device that includes a support structure (e.g., a substrate) and a transistor provided over the support structure and including a gate stack. The IC device also includes a FE capacitor having a first capacitor electrode, a second capacitor electrode, and a capacitor insulator of a FE material between the first capacitor electrode and the second capacitor electrode, where the FE capacitor is separate from the gate stack (i.e., is not integrated within the gate stack and does not have any layers that are part of the gate stack). The IC device further includes an interconnect structure, configured to electrically couple the gate stack and the first capacitor electrode.

Abstract: Embodiments include two-dimensional (2D) semiconductor sheet transistors and methods of forming such devices. In an embodiment, a semiconductor device comprises a stack of 2D semiconductor sheets, where individual ones of the 2D semiconductor sheets have a first end and a second end opposite from the first end. In an embodiment, a first spacer is over the first end of the 2D semiconductor sheets, and a second spacer is over the second end of the 2D semiconductor sheets. Embodiments further comprise a gate electrode between the first spacer and the second spacer, a source contact adjacent to the first end of the 2D semiconductor sheets, and a drain contact adjacent to the second end of the 2D semiconductor sheets.

Abstract: Systems, methods and apparatus for wireless charging are disclosed. A charging device has a resonant circuit comprising one or more transmitting coils, a driver circuit configured to provide a charging current to the resonant circuit, a zero-crossing detector configured to provide a zero-crossing signal that includes edges corresponding to transitions of a voltage measured across the resonant circuit through a zero volt level or corresponding to transitions of a current in the resonant circuit through a zero ampere level and a controller. The controller may be configured to cause the driver circuit to provide the charging current to the resonant circuit when a receiving device is present on a surface of the charging device, and control a level of power that is wirelessly transferred to the receiving device by phase-aligning the charging current with a phase-modulation signal generated from the zero-crossing signal.

Abstract: Methods, systems, and computer program products for cognitive disambiguation of problem-solving tasks involving a power grid are provided herein. A computer-implemented method includes capturing user feedback pertaining to relevance of remote terminal unit measurements related to a grid event through user interface interactions carried out by the user, wherein the user interface is communicatively linked to at least one computing device; automatically inferring rules related to the grid event to curate remote terminal unit measurements across iterations of analysis by recognizing irrelevant data and/or distractions in a visual display associated with the user interface, wherein said automatically inferring comprises implementing machine learning via the at least one computing device based on the user feedback; and outputting candidate solutions to a problem-solving task involving the grid based on the inferred rules, wherein said outputting is carried out by the at least one computing device.