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We demonstrate a magnetic tunnel junction injected with spin Hall current to exhibit linear rotation of magnetization of the free-ferromagnet using only the spin current. Using the linear resistance change of the MTJ, we devise a circuit…

Mesoscale and Nanoscale Physics · Physics 2023-07-26 Venkatesh Vadde , Bhaskaran Muralidharan , Abhishek Sharma

We present spintronic devices based hardware implementation of UNet for segmentation tasks. Our approach involves designing hardware for convolution, deconvolution, rectified activation function (ReLU), and max pooling layers of the UNet…

Emerging Technologies · Computer Science 2024-07-12 Venkatesh Vadde , Bhaskaran Muralidharan , Abhishek Sharma

We propose a new network architecture for standard spin-Hall magnetic tunnel junction-based spintronic neurons that allows them to compute multiple critical convolutional neural network functionalities simultaneously and in parallel, saving…

Emerging Technologies · Computer Science 2019-05-13 Andrew W. Stephan , Steven J. Koester

We propose the use of resonant tunneling as a route to enhance the spin-transfer torque switching characteristics of magnetic tunnel junctions. The proposed device structure is a resonant tunneling magnetic tunnel junction based on a…

Mesoscale and Nanoscale Physics · Physics 2014-12-16 Niladri Chatterji , Ashwin A Tulapurkar , Bhaskaran Muralidharan

In this paper, a 3-terminal spin-transfer torque nano-oscillator (STNO) is studied using the concurrent spin injection of a spin-polarized tunneling current and a spin Hall current exciting the free layer into dynamic regimes beyond what is…

Using the Keldysh formalism the tunneling current through a hybrid structure where a confined magnetic insulator (I) is sandwiched between two non-magnetic leads is calculated. The leads can be either normal metals (M) or superconductors…

Strongly Correlated Electrons · Physics 2009-11-13 N. Sandschneider , W. Nolting

Recent research has indicated that introducing impurities that increase the resistivity of Pt can enhance the efficiency of the spin Hall torque it generates. Here we directly demonstrate the usefulness of this strategy by fabricating…

Spin-orbitronics, based on both spin and orbital angular momentum, presents a promising pathway for energy-efficient memory and logic devices. Recent studies have demonstrated the emergence of orbital currents in light transition metals…

Ising spin model is considered as an efficient computing method to solve combinatorial optimization problems based on its natural tendency of convergence towards low energy state. The underlying basic functions facilitating the Ising model…

Emerging Technologies · Computer Science 2016-09-27 Yong Shim , Akhilesh Jaiswal , Kaushik Roy

We present a unified transport theory of hybrid structures, in which a confined normal state ($N$) sample is sandwiched between two leads each of which can be either a ferromagnet ($F$) or a superconductor ($S$) via tunnel barriers. By…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 Z. Y. Zeng , Baowen Li , F. Claro

Significant scientific and technological progress in the field of spintronics is based on trilayer magnetic tunnel junction devices which principally rely on the physics of single barrier tunneling. While technologically relevant devices…

Mesoscale and Nanoscale Physics · Physics 2019-11-14 Abhishek Sharma , Ashwin. A. Tulapurkar , Bhaskaran Muralidharan

There exists a significant challenge in developing efficient magnetic tunnel junctions with low write currents for non-volatile memory devices. With the aim of analysing potential materials for efficient current-operated magnetic junctions…

Mesoscale and Nanoscale Physics · Physics 2017-12-13 Matthew O. A. Ellis , Maria Stamenova , Stefano Sanvito

The figures-of-merit for reservoir computing (RC), using spintronics devices called magnetic tunnel junctions (MTJs), are evaluated. RC is a type of recurrent neural network. The input information is stored in certain parts of the…

Perpendicular magnetic tunnel junctions are one of the building blocks for spintronic memories, which allow fast nonvolatile data access, offering substantial potentials to revolutionize the mainstream computing architecture. However,…

Recently, multiferroic tunnel junctions (MFTJs) have gained significant spotlight in the literature due to its high tunneling electro-resistance together with its non-volatility. In order to analyze such devices and to have insightful…

Computational Physics · Physics 2019-07-02 Robert Andrawis , Kaushik Roy

We present a computationally efficient strategy that allows to simulate magnetization switching driven by spin-transfer torque in magnetic tunnel junctions within a micromagnetic model coupled with a matrix-based non-equilibrium Green's…

Computational Physics · Physics 2025-02-28 Peter Flauger , Claas Abert , Dieter Suess

The dynamics of a single spin embedded in the tunnel junction (quantum point contact) between ferromagnets is addressed. Using the Keldysh technique, we derive a quantum Langevin equation. As a consequence of the spin-polarization in the…

Mesoscale and Nanoscale Physics · Physics 2011-11-09 J. Fransson , Jian-Xin Zhu

The possibility of quantum oscillations of the tunnel conductance and magnetoresistance induced by spin-wave excitations in a ferromagnet-ferromagnet-ferromagnet double barrier tunnel junction, when the magnetizations of the two side…

Mesoscale and Nanoscale Physics · Physics 2008-01-23 Xi Chen , Qing-Rong Zheng , Gang Su

Magnetic tunnel junctions (MTJs) are key elements in practical spintronics, enabling not only conventional tasks such as data storage, transmission, and processing but also the implementation of compute-in-memory processing elements,…

Other Condensed Matter · Physics 2025-12-09 Maksim Stebliy , Alex Jenkins , Luana Benetti , Ricardo Ferreira

This paper proposes a novel spiking artificial neuron design based on a combined spin valve/magnetic tunnel junction (SV/MTJ). Traditional hardware used in artificial intelligence and machine learning faces significant challenges related to…

Applied Physics · Physics 2025-06-10 Steven Louis , Hannah Bradley , Cody Trevillian , Andrei Slavin , Vasyl Tyberkevych
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