Related papers: Voltage Gated Domain Wall Magnetic Tunnel Junction…
We have developed and optimized two categories of spin transfer torque magnetic tunnel junctions (STT-MTJs) that exhibit a high tunnel magnetoresistance (TMR) ratio, low critical current, high outputpower in the micro watt range, and…
Lateral inhibition is an important functionality in neuromorphic computing, modeled after the biological neuron behavior that a firing neuron deactivates its neighbors belonging to the same layer and prevents them from firing. In most…
Neuromorphic computing (NC) is gaining wide acceptance as a potential technology to achieve low-power intelligent devices. To realize NC, researchers investigate various types of synthetic neurons and synaptic devices such as memristors and…
Machine learning implements backpropagation via abundant training samples. We demonstrate a multi-stage learning system realized by a promising non-volatile memory device, the domain-wall magnetic tunnel junction (DW-MTJ). The system…
Neuromorphic computing (NC) is a promising candidate for artificial intelligence applications. To realize NC, electronic analogues of brain components, such as synapses and neurons, must be designed. In spintronics, domain wall (DW) based…
Current-induced spin-transfer torques (STT) and spin-orbit torques (SOT) enable the electrical switching of magnetic tunnel junctions (MTJs) in nonvolatile magnetic random access memories. In order to develop faster memory devices, an…
Current-induced spin-orbit torques (SOTs) enable fast and efficient manipulation of the magnetic state of magnetic tunnel junctions (MTJs), making it attractive for memory, in-memory computing, and logic applications. However, the…
We theoretically investigate influences of electronic circuit delay, noise and temperature on write-error-rate (WER) in voltage-controlled magnetization switching operation of a magnetic-topological-insulator-based (MTI) device by means of…
Stochastic spiking neural networks based on nanoelectronic spin devices can be a possible pathway to achieving "brainlike" compact and energy-effcient cognitive intelligence. The computational model attempt to exploit the intrinsic device…
Spin-transfer torque magnetic random-access memory (STT-MRAM) relies on nanoscale magnetic tunnel junctions (MTJs) as its fundamental building blocks. Next-generation STT-MRAM requires strategies that simultaneously improve switching energy…
In this work, we simulate the functionality of artificial neuron and synapse using spin-orbit torque-based spintronic devices and implemented a fully connected artificial neural netwrok (ANN). These neuro-synaptic devices are emulated using…
In this work, we introduce an optoelectronic spiking artificial neuron capable of operating at ultrafast rates ($\approx$ 100 ps/optical spike) and with low energy consumption ($<$ pJ/spike). The proposed system combines an excitable…
Domain-wall memory (DWM) has SRAM class access performance, low energy, high endurance, high density, and CMOS compatibility. Recently, shift reliability and processing-using-memory (PuM) proposals developed a need to count the number of…
We present a design-scheme for ultra-low power neuromorphic hardware using emerging spin-devices. We propose device models for 'neuron', based on lateral spin valves and domain wall magnets that can operate at ultra-low terminal voltage of…
In this paper, we study the domain wall motion induced by vertical current flow in asymmetric magnetic tunnel junctions. The domain wall motion in the free layer is mainly dictated by the current-induced field-like torque acting on it. We…
A new spin based logic device is proposed. It is comprised of a common free ferromagnetic layer separated by a tunnel junction from three inputs and one output with separate fixed layers. It has the functionality of a majority gate and is…
True random number generators (TRNGs) are fundamental building blocks for many applications, such as cryptography, Monte Carlo simulations, neuromorphic computing, and probabilistic computing. While perpendicular magnetic tunnel junctions…
A promising branch of neuromorphic computing aims to perform cognitive operations in hardware leveraging the physics of efficient and well-established nano-devices. In this work, we present a reconfigurable classifier based on a network of…
The effect of damping-like spin-orbit torque (DL SOT) on magnetic domain walls (DWs) in in-plane magnetised soft tracks is studied analytically and with micromagnetic simulations. We find that DL SOT drives vortex DWs, whereas transverse…
We study whether a direct measurement of the absolute temperature of a Magnetic Tunnel Junction (MTJ) can be performed using the high frequency electrical noise that it delivers under a finite voltage bias. Our method includes quasi-static…