相关论文: Energy-efficient magnetoelastic non-volatile memor…

In this work, we propose valley-coupled spin-hall memories (VSH-MRAMs) based on monolayer WSe2. The key features of the proposed memories are (a) the ability to switch magnets with perpendicular magnetic anisotropy (PMA) via VSH effect and…

We propose a novel topological photonic memory that encodes information through dynamically controllable Chern numbers in a two-band topological photonic system. Utilizing a honeycomb lattice photonic crystal, the memory leverages…

Battery-less technology evolved to replace battery technology. Non-volatile memory (NVM) based processors were explored to store the program state during a power failure. The energy stored in a capacitor is used for a backup during a power…

Taking advantage of the Magnetoelectric (ME) and its inverse effect, this article demonstrates strain-mediated magnetoelectric write and read operations simultaneously in Co60Fe20B20/ Pb(Mg1/3Nb2/3)0.7Ti0.3O3 heterostructures without using…

The demand for high-density storage is urgent in the current era of data explosion. Recently, several single-molecule (-atom) magnets/ferroelectrics have been reported to be promising candidates for high-density storage. As another…

We show that the established physics of spin valves together with the recently discovered giant spin-Hall effect could be used to construct Read and Write units that can be integrated into a single spin switch with input-output isolation,…

Progress in artificial intelligence and machine learning over the past decade has been driven by the ability to train larger deep neural networks (DNNs), leading to a compute demand that far exceeds the growth in hardware performance…

We demonstrate non-volatile optical functionality by embedding multi-layer $HfO_2/Al_2O_3$ memristors with III-V/Si photonics. The wafer-bonded III-V/Si memristor facilitates non-volatile optical functionality for a variety of devices such…

One of the most exciting applications of Spin Torque Magnetoresistive Random Access Memory (ST-MRAM) is the in-memory implementation of deep neural networks, which could allow improving the energy efficiency of Artificial Intelligence by…

Antiferromagnetic Tunnel Junctions (AFMTJs) enable picosecond switching and femtojoule writes through ultrafast sublattice dynamics. We present the first end-to-end AFMTJ simulation framework integrating multi-sublattice…

Nanomagnetic implementations of Boolean logic [1,2] have garnered attention because of their non-volatility and the potential for unprecedented energy-efficiency. Unfortunately, the large dissipative losses that take place when nanomagnets…

Refresh is an important operation to prevent loss of data in dynamic random-access memory (DRAM). However, frequent refresh operations incur considerable power consumption and degrade system performance. Refresh power cost is especially…

We numerically study the thermal stability properties of computer memory storage realized by a magnetic ellipse. In the case of practical magnetic random-access memory devices, the bit can form a spin texture during switching events. To…

We report a novel field-sensitive tunneling barrier by embedding C60 in SiO2 for nonvolatile memory applications. C60 is a better choice than ultra-small nanocrystals due to its monodispersion. Moreover, C60 provides accessible energy…

Recent progresses in magnetoionics offer exciting potentials to leverage its non-linearity, short-term memory, and energy-efficiency to uniquely advance the field of physical reservoir computing. In this work, we experimentally demonstrate…

Applications of Binary Neural Networks (BNNs) are promising for embedded systems with hard constraints on computing power. Contrary to conventional neural networks with the floating-point datatype, BNNs use binarized weights and activations…

Spin-torque memristors were proposed in 2009, which could provide fast, low-power and infinite memristive behavior for large-density non-volatile memory and neuromorphic computing. However, the strict requirements of combining high…

This paper proposes a spintronic neuron structure composed of a heterostructure of magnets and a piezoelectric with a magnetic tunnel junction (MTJ). The operation of the device is simulated using SPICE models. Simulation results illustrate…

AI chips commonly employ SRAM memory as buffers for their reliability and speed, which contribute to high performance. However, SRAM is expensive and demands significant area and energy consumption. Previous studies have explored replacing…

Demonstration of ultra-low energy switching mechanisms is an imperative for continued improvements in computing devices. Ferroelectric (FE) and multiferroic (MF) orders and their manipulation promises an ideal combination of state variables…