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Related papers: A Fokker-Planck Solver to Model MTJ Stochasticity

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Event-based neuromorphic systems provide a low-power solution by using artificial neurons and synapses to process data asynchronously in the form of spikes. Ferroelectric Tunnel Junctions (FTJs) are ultra low-power memory devices and are…

Flexible electronic devices require the integration of multiple crucial components on soft substrates to achieve their functions. In particular, memory devices are the fundamental component for data storage and processing in flexible…

Materials Science · Physics 2016-03-15 Li Ming Loong , Wonho Lee , Xuepeng Qiu , Ping Yang , Hiroyo Kawai , Mark Saeys , Jong-Hyun Ahn , Hyunsoo Yang

Ferroelectric tunnel junctions (FTJs) leverage polarization-dependent tunneling through ultrathin barriers to enable two-terminal, non-volatile memory and logic. Although conceptually appealing, the practical implementation of conventional…

Emerging non-volatile memories (NVMs) have currently attracted great interest for their potential applications in advanced low-power information storage and processing technologies. Conventional NVMs, such as magnetic random access memory…

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

Magnetic tunnel junctions (MTJs) are the key building blocks of high-performance spintronic devices. While conventional MTJs rely on ferromagnetic (FM) materials, employing antiferromagnetic (AFM) compounds can significantly increase…

The large-scale fabrication of three-terminal magnetic tunnel junctions (MTJs) with high yield is becoming increasingly crucial, especially with the growing interest in spin-orbit torque (SOT) magnetic random access memory (MRAM) as the…

Superparamagnetic tunnel junctions (SMTJs) have emerged as a competitive, realistic nanotechnology to support novel forms of stochastic computation in CMOS-compatible platforms. One of their applications is to generate random bitstreams…

Emerging Technologies · Computer Science 2020-03-09 Matthew W. Daniels , Advait Madhavan , Philippe Talatchian , Alice Mizrahi , Mark D. Stiles

We develop a fast Magnetic Josephson Junction (MJJ) - a superconducting ferromagnetic device for a scalable high-density cryogenic memory compatible in speed and fabrication with energy-efficient Single Flux Quantum (SFQ) circuits. We…

Straintronic magneto-tunneling junction (s-MTJ) switches, whose resistances are controlled with voltage-generated strain in the magnetostrictive free layer of the MTJ, are extremely energy-efficient switches that would dissipate a few aJ of…

Emerging Technologies · Computer Science 2017-07-18 S. Dey Manasi , M. M. Al Rashid , J. Atulasimha , S. Bandyopadhyay , A. R. Trivedi

Synaptic memory is considered to be the main element responsible for learning and cognition in humans. Although traditionally non-volatile long-term plasticity changes have been implemented in nanoelectronic synapses for neuromorphic…

Emerging Technologies · Computer Science 2017-12-20 Abhronil Sengupta , Kaushik Roy

Smart material implication (SIMPLY) logic has been recently proposed for the design of energy-efficient Logic-in-Memory (LIM) architectures based on non-volatile resistive memory devices. The SIMPLY logic is enabled by adding a comparator…

Emerging Technologies · Computer Science 2022-06-01 Raffaele De Rose , Tommaso Zanotti , Francesco Maria Puglisi , Felice Crupi , Paolo Pavan , Marco Lanuzza

Superparamagnetic tunnel junctions (sMTJs) are emerging as promising components for stochastic units in neuromorphic computing, owing to their tunable random switching behavior. Conventional MTJ control methods, such as spin-transfer torque…

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…

Materials Science · Physics 2016-08-03 Adrien Le Goff , Vladimir Nikitin , Thibaut Devolder

Combinatorial optimization problems are foundational challenges in fields such as artificial intelligence, logistics, and network design. Traditional algorithms, including greedy methods and dynamic programming, often struggle to balance…

Two promising strategies for achieving efficient control of magnetization in future magnetic memory and non-volatile spin logic devices are spin transfer torque from spin polarized currents and voltage-controlled magnetic anisotropy (VCMA).…

Materials Science · Physics 2012-09-06 Luqiao Liu , Chi-Feng Pai , D. C. Ralph , R. A. Buhrman

The electrically readable complex dynamics of robust and scalable magnetic tunnel junctions (MTJs) offer promising opportunities for advancing neuromorphic computing. In this work, we present an MTJ design with a free layer and two…

Multiferroic tunnel junctions (MFTJs) have already been proved to be promising candidates for application in spintronics devices. The coupling between tunnel magnetoresistance (TMR) and tunnel electroresistance (TER) in MFTJs can provide…

Materials Science · Physics 2019-06-25 Q. Liu , J. Miao , Z. D. Xu , P. F. Liu , Q. H. Zhang , L. Gu , K. K. Meng , X. G. Xu , J. K. Chen , Y. Wu , Y. Jiang

We propose spin transfer torque--magnetoresistive random access memory (STT-MRAM) based on magneto-resistance and spin transfer torque physics of band-pass spin filtering. Utilizing the electronic analogs of optical phenomena such as…

Mesoscale and Nanoscale Physics · Physics 2019-08-20 Abhishek Sharma , Ashwin Tulapurkar , Bhaskaran Muralidharan

We investigate fast-pulse switching of in-plane-magnetized magnetic tunnel junctions (MTJs) within 3-terminal devices in which spin-transfer torque is applied to the MTJ by the giant spin Hall effect. We measure reliable switching, with…

Mesoscale and Nanoscale Physics · Physics 2016-06-22 Sriharsha V. Aradhya , Graham E. Rowlands , Junseok Oh , Daniel C. Ralph , Robert A. Buhrman