Abstract: Embodiments may relate to a structure to be used in a neural network. A first column and a second column, both of which are to couple with a substrate. A capacitor structure may be electrically coupled with the first column. An insulator-metal transition (IMT) structure may be coupled with the first column such that the capacitor structure is electrically positioned between the IMT structure and the first column. A resistor structure may further be electrically coupled with the IMT structure and the second column such that the resistor structure is electrically positioned between the second column and the IMT structure. Other embodiments may be described or claimed.

Abstract: An apparatus is provided which comprises: a magnetic junction having a magnet with a first magnetization; an interconnect adjacent to the magnetic junction, wherein the interconnect comprises an antiferromagnetic (AFM) material which is doped with a doping material (Pt, Ni, Co, or Cr) and a structure adjacent to the interconnect such that the magnetic junction and the structure are on opposite surfaces of the interconnect, wherein the structure comprises a magnet with a second magnetization substantially different from the first magnetization.

Abstract: Embodiments of the present disclosure are directed toward probabilistic in-memory computing configurations and arrangements, and configurations of probabilistic bit devices (p-bits) for probabilistic in-memory computing. concept with emerging. A probabilistic in-memory computing device includes an array of p-bits, where each p-bit is disposed at or near horizontal and vertical wires. Each p-bit is a time-varying resistor that has a time-varying resistance, which follows a desired probability distribution. The time-varying resistance of each p-bit represents a weight in a weight matrix of a stochastic neural network. During operation, an input voltage is applied to the horizontal wires to control the current through each p-bit. The currents are accumulated in the vertical wires thereby performing respective multiply-and-accumulative (MAC) operations. Other embodiments may be described and/or claimed.

Abstract: An apparatus is provided which comprises: a stack comprising a magnetoelectric (ME such as BiFeO3, (LaBi)FeO3, LuFeO3, PMN-PT, PZT, AlN, SmBiFeO3, Cr2O3, etc.) material and a transition metal dichalcogenide (TMD such as MoS2, MoSe2, WS2, WSe2, PtS2, PtSe2, WTe2, MoTe2, graphene, etc.); a magnet adjacent to a first portion of the TMD of the stack; a first interconnect adjacent to the magnet; a second interconnect adjacent to the ME material of the stack; and a third interconnect adjacent to a second portion of the TMD of the stack.

Abstract: Described is an apparatus which comprises: a first layer comprising a semiconductor; a second layer comprising an insulating material, the second layer adjacent to the first layer; a third layer comprising a high-k insulating material, the third layer adjacent to the second layer; a fourth layer comprising a ferroelectric material, the fourth layer adjacent to the third layer; and a fifth layer comprising a high-k insulating material, the fifth layer adjacent to the fourth layer.

Abstract: One embodiment provides an apparatus. The apparatus includes a first inverter comprising a first pull up transistor and a first pull down transistor; a second inverter cross coupled to the first inverter, the second inverter comprising a second pull up transistor and a second pull down transistor; a first access transistor coupled to the first inverter; and a second access transistor coupled to the second inverter. A gate electrode of one transistor of each inverter comprises a polarization layer.

Abstract: An apparatus is described. The apparatus includes a compute-in-memory (CIM) circuit for implementing a neural network disposed on a semiconductor chip. The CIM circuit includes a mathematical computation circuit coupled to a memory array. The memory array includes an embedded dynamic random access memory (eDRAM) memory array. Another apparatus is described. The apparatus includes a compute-in-memory (CIM) circuit for implementing a neural network disposed on a semiconductor chip. The CIM circuit includes a mathematical computation circuit coupled to a memory array. The mathematical computation circuit includes a switched capacitor circuit. The switched capacitor circuit includes a back-end-of-line (BEOL) capacitor coupled to a thin film transistor within the metal/dielectric layers of the semiconductor chip. Another apparatus is described. The apparatus includes a compute-in-memory (CIM) circuit for implementing a neural network disposed on a semiconductor chip.

Abstract: Embodiments of the invention include a resonant sensing system comprising driving circuitry to generate a drive signal during excitation time periods, a first switch coupled to the driving circuitry, and a sensing device coupled to the driving circuitry via the first switch during the excitation time periods. The sensing device includes beams to receive the drive signal during a first excitation time period that causes the beams to mechanically oscillate and generate a first induced electromotive force (emf) in response to the drive signal. The first switch decouples the sensing device and the driving circuitry during measurement time periods for measurement of the induced emf.

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 herein describe techniques for an integrated circuit (IC). The IC may include a capacitor. The capacitor may include a first electrode, a second electrode, and a paraelectric layer between the first electrode and the second electrode. A first interface with a first work function exists between the paraelectric layer and the first electrode. A second interface with a second work function exists between the paraelectric layer and the second electrode. The paraelectric layer may include a ferroelectric material or an anti-ferroelectric material. A built-in electric field associated with the first work function and the second work function may exist between the first electrode and the second electrode. The built-in electric field may be at a voltage value where the capacitor may operate at a center of a memory window of a polarization-voltage hysteresis loop of the capacitor. Other embodiments may be described and/or claimed.

Abstract: Described is a ferroelectric-based capacitor that improves reliability of a ferroelectric memory by providing tensile stress along a plane (e.g., x-axis) of a ferroelectric or anti-ferroelectric material of the ferroelectric/anti-ferroelectric based capacitor. Tensile stress is provided by a spacer comprising metal, semimetal, or oxide (e.g., metal or oxide of one or more of: Al, Ti, Hf, Si, Ir, or N). The tensile stress provides polar orthorhombic phase to the ferroelectric material and tetragonal phase to the anti-ferroelectric material. As such, memory window and reliability of the ferroelectric/anti-ferroelectric oxide thin film improves.

Abstract: The present disclosure is directed to systems and methods of implementing a neural network using in-memory mathematical operations performed by pipelined SRAM architecture (PISA) circuitry disposed in on-chip processor memory circuitry. A high-level compiler may be provided to compile data representative of a multi-layer neural network model and one or more neural network data inputs from a first high-level programming language to an intermediate domain-specific language (DSL). A low-level compiler may be provided to compile the representative data from the intermediate DSL to multiple instruction sets in accordance with an instruction set architecture (ISA), such that each of the multiple instruction sets corresponds to a single respective layer of the multi-layer neural network model. Each of the multiple instruction sets may be assigned to a respective SRAM array of the PISA circuitry for in-memory execution.

Abstract: An apparatus is described. The apparatus includes a compute-in-memory (CIM) circuit for implementing a neural network disposed on a semiconductor chip. The CIM circuit includes a mathematical computation circuit coupled to a memory array. The memory array includes an embedded dynamic random access memory (eDRAM) memory array. Another apparatus is described. The apparatus includes a compute-in-memory (CIM) circuit for implementing a neural network disposed on a semiconductor chip. The CIM circuit includes a mathematical computation circuit coupled to a memory array. The mathematical computation circuit includes a switched capacitor circuit. The switched capacitor circuit includes a back-end-of-line (BEOL) capacitor coupled to a thin film transistor within the metal/dielectric layers of the semiconductor chip. Another apparatus is described. The apparatus includes a compute-in-memory (CIM) circuit for implementing a neural network disposed on a semiconductor chip.

Abstract: Described is an apparatus, for spin state element device, which comprises: a variable resistive magnetic (VRM) device to receive a magnetic control signal to adjust resistance of the VRM device; and a magnetic logic gating (MLG) device, coupled to the VRM device, to receive a magnetic logic input and perform logic operation on the magnetic logic input and to drive an output magnetic signal based on the resistance of the VRM device. Described is a magnetic de-multiplexer which comprises: a first VRM device to receive a magnetic control signal to adjust resistance of the first VRM; a second VRM device to receive the magnetic control signal to adjust resistance of the second VRM device; and an MLG device, coupled to the first and second VRM devices, the MLG device having at least two output magnets to output magnetic signals based on the resistances of the first and second VRM devices.

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: A three dimensional (3D) array of magnetic random access memory (MRAM) bit-cells is described, wherein the array includes a mesh of: a first interconnect extending along a first axis; a second interconnect extending along a second axis; and a third interconnect extending along a third axis, wherein the first, second and third axes are orthogonal to one another, and wherein a bit-cell of the MRAM bit-cells includes: a magnetic junction device including a first electrode coupled to the first interconnect; a piezoelectric (PZe) layer adjacent to a second electrode, wherein the second electrode is coupled to the second interconnect; and a first layer adjacent to the PZe layer and the magnetic junction, wherein the first layer is coupled the third interconnect.

Abstract: An apparatus is provided which comprises: a first paramagnet; a stack of layers, a portion of which is adjacent to the first paramagnet, wherein the stack of layers is to provide an inverse Rashba-Edelstein effect; a second paramagnet; a magnetoelectric layer adjacent to the second paramagnet; and a conductor coupled to at least a portion of the stack of layers and the magnetoelectric layer.

Abstract: Embodiments herein describe techniques for a semi-conductor device comprising a channel having a first semiconductor material; a source contact coupled to the channel, comprising a first Heusler alloy; and a drain contact coupled to the channel, comprising a second Heusler alloy. The first Heusler alloy is lattice-matched to the first semiconductor material within a first predetermined threshold. A first Schottky barrier between the channel and the source contact, and a second Schottky barrier between the channel and the drain contact are negative, or smaller than another predetermined threshold. The source contact and the drain contact can be applied to a strained silicon transistor, an III-V transistor, a tunnel field-effect transistor, a dichalcogenide (MX2) transistor, and a junctionless nanowire transistor.

Abstract: Techniques are disclosed for forming vias for integrated circuit structures. During an additive via formation process, a dielectric material is deposited, an etch stop layer is deposited, a checkerboard pattern is deposited on the etch stop layer, regions in the checkerboard pattern are removed where it is desired to have vias, openings are etched in the dielectric material through the removed regions, and the openings are filled with a first via material. This is then repeated for a second via material. During the subtractive via formation process, a first via material is deposited, an etch stop layer is deposited, a checkerboard pattern is deposited on the etch stop layer, regions in the checkerboard pattern are removed where it is not desired to have vias, openings are etched in the first via material through the removed regions. This is then repeated for a second via material.

Abstract: A perpendicular spin orbit torque memory device includes a first electrode having tungsten and at least one of nitrogen or oxygen and a material layer stack on a portion of the first electrode. The material layer stack includes a free magnet, a fixed magnet above the first magnet, a tunnel barrier between the free magnet and the fixed magnet and a second electrode coupled with the fixed magnet.