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Related papers: Inside the perpendicular spin-torque memristor

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Progress in the last two decades has effectively integrated spintronics and nanomagnetics into a single field, creating a new class of spin-based devices that are now being used both to Read (R) information from magnets and to Write (W)…

Mesoscale and Nanoscale Physics · Physics 2014-04-09 Supriyo Datta , Vinh Quang Diep , Behtash Behin-Aein

Dynamic reconfiguration of charge carriers in confined ion-channels under electrical stimulation produces memory effects, where the internal resistance depends on history of the electric field. Vermiculite nanofluidic devices harness this…

Recent years have witnessed growing interest in the use of Artificial Neural Networks (ANNs) for vision, classification, and inference problems. An artificial neuron sums N weighted inputs and passes the result through a non-linear transfer…

Emerging Technologies · Computer Science 2016-11-18 Deliang Fan , Yong Shim , Anand Raghunathan , Kaushik Roy

Memristors have been compared to neurons (usually specifically the synapses) since 1976 but no experimental evidence has been offered for support for this position. Here we highlight that memristors naturally form fast-response, highly…

Materials Science · Physics 2013-12-17 Ella Gale , Ben de Lacy Costello , Andrew Adamatzky

Energy-efficient methods are addressed for leveraging low energy barrier nanomagnetic devices within neuromorphic architectures. Using a Magnetoresistive Random Access Memory (MRAM) probabilistic device (p-bit) as the basis of neuronal…

Emerging Technologies · Computer Science 2020-05-06 Hossein Pourmeidani , Punyashloka Debashis , Zhihong Chen , Ronald F. DeMara , Ramtin Zand

Memristors have been suggested as a novel route to neuromorphic computing based on the similarity between them and neurons (specifically synapses and ion pumps). The d.c. action of the memristor is a current spike which imparts a short-term…

Emerging Technologies · Computer Science 2015-10-21 Ella Gale

Memristors as emergent nano-electronic devices have been successfully fabricated and used in non-conventional and neuromorphic computing systems in the last years. Several behavioral or physical based models have been developed to explain…

Technology based on memristors, resistors with memory whose resistance depends on the history of the crossing charges, has lately enhanced the classical paradigm of computation with neuromorphic architectures. However, in contrast to the…

Quantum Physics · Physics 2017-01-12 P. Pfeiffer , I. L. Egusquiza , M. Di Ventra , M. Sanz , E. Solano

We propose a method for inducing magnetization reversal using an AC spin current polarized perpendicular to the equilibrium magnetization of the free magnetic layer. We show that the critical AC spin current is significantly smaller than…

Mesoscale and Nanoscale Physics · Physics 2015-06-05 Tom Dunn , Alex Kamenev

Memristor (resistor with memory), inductor with memory (meminductor) and capacitor with memory (memcapacitor) have different roles to play in novel computing architectures. We found that a coil with a magnetic core is an inductor with…

Emerging Technologies · Computer Science 2025-12-15 Frank Zhigang Wang

This paper reports on the improvement of the differential current gain in the spin-torque transistor based on two independent innovations, viz.the use of magnetic insulators and the spin Hall effect. Since, except for a few examples, spin…

Mesoscale and Nanoscale Physics · Physics 2014-08-22 Takahiro Chiba , Gerrit E. W. Bauer , Saburo Takahashi

In many cases, the behavior of physical memristive devices can be relatively well captured by using a single internal state variable. This study investigates the low-power control of first-order memristive devices to derive the most…

Emerging Technologies · Computer Science 2026-01-14 Valeriy A. Slipko , Alon Ascoli , Fernando Corinto , Yuriy V. Pershin

Magnetization dynamics in nanomagnets has attracted broad interest since it was predicted that a dc-current flowing through a thin magnetic layer can create spin-wave excitations. These excitations are due to spin-momentum transfer, a…

Mesoscale and Nanoscale Physics · Physics 2012-06-25 F. Macià , A. D. Kent , F. C. Hoppensteadt

In this paper we discuss the potential of emerging spintorque devices for computing applications. Recent proposals for spinbased computing schemes may be differentiated as all-spin vs. hybrid, programmable vs. fixed, and, Boolean vs.…

Disordered Systems and Neural Networks · Physics 2013-08-19 Kaushik Roy , Mrigank Sharad , Deliang Fan , Karthik Yogendra

Memristive devices, whose resistance can be controlled by applying a voltage and further retained, are attractive as possible circuit elements for neuromorphic computing. This new type of devices poses a number of both technological and…

Mesoscale and Nanoscale Physics · Physics 2023-05-31 Oleg G. Kharlanov

Present day computers expend orders of magnitude more computational resources to perform various cognitive and perception related tasks that humans routinely perform everyday. This has recently resulted in a seismic shift in the field of…

Emerging Technologies · Computer Science 2017-12-22 Abhronil Sengupta , Kaushik Roy

In this paper, we build a general modelling framework for memristors, suitable for the simulation of event-based systems such as hardware spiking neural networks, and more generally, neuromorphic computing systems composed of three…

Emerging Technologies · Computer Science 2025-12-02 Waleed El-Geresy , Christos Papavassiliou , Deniz Gündüz

The recent demonstration of neuromorphic computing with spin-torque nano-oscillators has opened a path to energy efficient data processing. The success of this demonstration hinged on the intrinsic short-term memory of the oscillators. In…

We report gate-tunable memristive switching in patterned LaAlO3/SrTiO3 interfaces at cryogenic temperatures. The application of voltages in the order of a few volts to the back gate of the device allows controlling and switching-on and -off…

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…