English
Related papers

Related papers: Skyrmion-mediated Nonvolatile Ternary Memory

200 papers

Multiferroic tunnel junctions (MFTJs), integrating ferroelectric and ferromagnetic functionalities within a single nanoscale device, hold significant promise for non-volatile, multi-state memory and innovative computing paradigms. In…

Mesoscale and Nanoscale Physics · Physics 2026-05-25 Wei Yang , Yibo Xu , Shen Li , Jiangchao Han , Jiayou Chen , Juan-Carlos Rojas-Sánchez , Stéphane Mangin , Xiaoyang Lin , Weisheng Zhao

Today's high-performance architectures are increasingly constrained by data movement latency and energy overhead, as the slowdown of single-core performance scaling coincides with the rise of highly data-intensive workloads. In-memory…

Emerging Technologies · Computer Science 2026-05-06 Farzad Razi , Mehran Moghadam , Sercan Aygun , M. Hassan Najafi , Marc Riedel

Reservoir Computing is a type of recursive neural network commonly used for recognizing and predicting spatio-temporal events relying on a complex hierarchy of nested feedback loops to generate a memory functionality. The Reservoir…

Mesoscale and Nanoscale Physics · Physics 2018-02-05 George Bourianoff , Daniele Pinna , Matthias Sitte , Karin Everschor-Sitte

Recently, an associative memory operation by a virtual oscillator network, consisting of a single spintronic oscillator, was examined to solve issues in conventional, real oscillators-based neural networks such as inhomogeneities between…

Mesoscale and Nanoscale Physics · Physics 2024-04-10 Tomohiro Taniguchi , Yusuke Imai

In recent years, the energy consumption of computing systems has increased and a large fraction of this energy is consumed in main memory. Towards this, researchers have proposed use of non-volatile memory, such as phase change memory…

Hardware Architecture · Computer Science 2013-09-17 Sparsh Mittal

Spin-orbit torque and spin-transfer torque are leading the pathway to the future of spintronic memories. However, both of the mechanisms are suffering from intrinsic limitations. In particular, an external magnetic field is required for…

We report on non-volatile memory devices based on multifunctional manganites. The electric field induced resistive switching of Ti/$La_{1/3}$$Ca_{2/3}$Mn$O_3$/n-Si devices is explored using different measurement protocols. We show that…

Materials Science · Physics 2016-06-20 W. Román Acevedo , D. Rubi , J. Lecourt , U. Lüders , F. Gomez-Marlasca , P. Granell , F. Golmar , P. Levy

The ferroelectric material is an important platform to realize non-volatile memories. So far, existing ferroelectric memory devices utilize out-of-plane polarization in ferroelectric thin films. In this paper, we propose a new type of…

Applied Physics · Physics 2019-02-26 Huitao Shen , Junwei Liu , Kai Chang , Liang Fu

Skyrmions, which are topologically stable magnetic structures, have manifested promising features to be used as an information carrier in new-age, non-volatile data storage devices. In this article, Co/Pt square nano-structure with Co-free…

Materials Science · Physics 2025-01-23 Tamali Mukherjee , V Satya Narayana Murthy

By integrating the local voltage-controlled magnetic anisotropy (VCMA) effect, Dzyaloshinskii-Moriya interaction (DMI) effect, and spin-orbit torque (SOT) effect, we propose a novel device structure for field-free magnetic tunnel junction…

Signal Processing · Electrical Eng. & Systems 2023-12-27 Rui Zhou , Haiyang Zhang , Hao Wang , Jin He , Qijun Huang , Sheng Chang

The topologically non-trivial nano-whirls, called magnetic skyrmions, are often considered attractive for spintronic applications like the racetrack data storage device. However, skyrmions do not move parallel to applied currents and…

Strongly Correlated Electrons · Physics 2021-06-30 Börge Göbel , Ingrid Mertig

Magnetic random access memory that uses magnetic tunnel junction memory cells is a high performance, non-volatile memory technology that goes beyond traditional charge-based memories. Today its speed is limited by the high magnetization of…

Spin-resolved electron symmetry filtering is a key mechanism behind giant tunneling magnetoresistance (TMR) in Fe/MgO/Fe and similar magnetic tunnel junctions (MTJs), providing room temperature functionality in modern spin electronics.…

Mesoscale and Nanoscale Physics · Physics 2021-10-12 César González-Ruano , Coriolan Tiusan , Michel Hehn , Farkhad G. Aliev

Magnetic skyrmions are topologically protected quasiparticles and have drawn much attention because of their potential applications in next-generation spintronics devices. Their inherent topological stability, nanoscale size, and efficient…

Mesoscale and Nanoscale Physics · Physics 2025-02-19 Hind Prakash , Himanshu Fulara

Valley-spin hall (VSH) effect in monolayer WSe2 has been shown to exhibit highly beneficial features for nonvolatile memory (NVM) design. Key advantages of VSH-based magnetic random-access memory (VSH-MRAM) over spin orbit torque (SOT)-MRAM…

Systems and Control · Electrical Eng. & Systems 2022-09-20 Karam Cho , Sumeet Kumar Gupta

Magnetic skyrmions are topological spin structures having immense potential for energy efficient spintronic devices. However, observations of skyrmions at room temperature are limited to patterned nanostructures. Here, we report the…

Spin transfer torque magnetic random access memory (STT-MRAM) is considered as one of the most promising candidates to build up a true universal memory thanks to its fast write/read speed, infinite endurance and non-volatility. However the…

Emerging Technologies · Computer Science 2015-06-04 Weisheng Zhao , Sumanta Chaudhuri , Celso Accoto , Jacques-Olivier Klein , Claude Chappert , Pascale Mazoyer

Multiferroic tunnel junctions (MFTJs) based on two-dimensional (2D) van der Waals heterostructures with sharp and clean interfaces at the atomic scale are crucial for applications in nanoscale multi-resistive logic memory devices. The…

Mesoscale and Nanoscale Physics · Physics 2023-08-24 Xinlong Dong , Xuemin Shen , Xiaowen Sun , Yuhao Bai , Zhi Yan , Xiaohong Xu

Ternary and binary neural networks enable multiplication-free computation and promise multiple orders of magnitude efficiency gains over full-precision networks if implemented on specialized hardware. However, since both the parameter and…

Computation and Language · Computer Science 2023-06-06 Zechun Liu , Barlas Oguz , Aasish Pappu , Yangyang Shi , Raghuraman Krishnamoorthi

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…

Hardware Architecture · Computer Science 2023-08-07 Sourjya Roy , Cheng Wang , Anand Raghunathan
‹ Prev 1 8 9 10 Next ›