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The Tunneling Anisotropic Magneto-Thermopower (TAMT) and the Tunneling Anisotropic Spin-Seebeck (TASS) effects are studied for a magnetic tunnel junction (MTJ) composed of a ferromagnetic electrode, a zinc-blende semiconductor and a normal…

Mesoscale and Nanoscale Physics · Physics 2014-11-25 Carlos López-Monís , Alex Matos-Abiague , Jaroslav Fabian

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

We theoretically investigate the spin--wave spin current induced by the spin Seebeck effect in magnonic spin tunneling junctions (MSTJs) for arbitrary magnetization directions. We show that the MSTJ functions as a \textit{tunable} spin…

Mesoscale and Nanoscale Physics · Physics 2018-11-16 Diasuke Miura , Akimasa Sakuma

Neuromorphic computing uses brain-inspired principles to design circuits that can perform computational tasks with superior power efficiency to conventional computers. Approaches that use traditional electronic devices to create artificial…

Applied Physics · Physics 2020-07-14 J. Grollier , D. Querlioz , K. Y. Camsari , K. Everschor-Sitte , S. Fukami , M. D. Stiles

Spin-polarized charge-currents induce magnetic tunnel junction (MTJ) switching by virtue of spin-transfer-torque (STT). Recently, by taking advantage of the spin dependent thermoelectric properties of magnetic materials, novel means of…

Mesoscale and Nanoscale Physics · Physics 2015-06-15 Aakash Pushp , Timothy Phung , Charles Rettner , Brian P. Hughes , See-Hun Yang , Stuart S. P. Parkin

Perpendicular magnetic tunnel junctions (MTJ) with a bottom pinned reference layer and a composite free layer (FL) are investigated. Different thicknesses of the FL were tested to obtain an optimal balance between tunneling…

Brain-inspired learning in physical hardware has enormous potential to learn fast at minimal energy expenditure. One of the characteristics of biological learning systems is their ability to learn in the presence of various noise sources.…

Magnetic tunnel junctions (MTJs), that consist of two ferromagnetic electrodes separated by an insulating barrier layer, have non-trivial fundamental properties associated with spin-dependent tunneling. Especially interesting are fully…

Materials Science · Physics 2024-09-12 Kartik Samanta , Evgeny Y. Tsymbal

We present the design and numerical simulation of a spiking neuron capable of on-chip machine learning. Built within the CMOS+X framework, the spiking neuron consists of an NMOS transistor combined with a magnetic tunnel junction (MTJ).…

HfO2-based ferroelectric tunnel junctions (FTJs) exhibit attractive properties for adoption in neuromorphic applications. The combination of ultra-low-power multi-level switching capability together with the low on-current density suggests…

Applied Physics · Physics 2022-11-02 Suzanne Lancaster , Quang T. Duong , Erika Covi , Thomas Mikolajick , Stefan Slesazeck

The ever-increasing amount of data from ubiquitous smart devices fosters data-centric and cognitive algorithms. Traditional digital computer systems have separate logic and memory units, resulting in a huge delay and energy cost for…

Applied Physics · Physics 2025-03-17 Qiming Shao , Zhongrui Wang , Yan Zhou , Shunsuke Fukami , Damien Querlioz , Leon O. Chua

The magnetic tunnel junctions (MTJ) based on van der Waals (vdW) materials possess atomically smooth interfaces with minimal element intermixing. This characteristic ensures that spin polarization is well maintained during transport,…

Applied Physics · Physics 2024-02-23 Shouguo Zhu , Hailong Lin , Wenkai Zhu , Weihao Li , Jing Zhang , Kaiyou Wang

Magnetic Tunnel Junctions (MTJs) are of great interest for non-conventional computing applications. The Toffoli gate is a universal reversible logic gate, enabling the construction of arbitrary boolean circuits. Here, we present a…

We theoretically investigate the chaotic behavior of spin-torque ferromagnetic resonance in magnetic tunnel junctions (MTJs) with perpendicular magnetic anisotropy under thermal fluctuations. By calculating the Lyapunov exponent based on…

Mesoscale and Nanoscale Physics · Physics 2026-03-04 Ryo Tatsumi , Shinji Miwa , Hiroaki Matsueda , Takahiro Chiba

Magnetic materials play a key role in the contemporary industry, providing unique features with a wide application potential. To study physical phenomena and design new materials, it is important to possess an appropriate tool, a model…

Materials Science · Physics 2026-01-13 Jakub Šebesta , Dominik Legut

Spin-torque memristors were proposed in 2009, which could provide fast, low-power and infinite memristive behavior for large-density non-volatile memory and neuromorphic computing. However, the strict requirements of combining high…

Magnetization dynamics described by the Landau-Lifshitz-Gilbert-Slonczewski (LLGS) equation can be formulated to have the form of the well-known two-level-system (TLS) equations. Recently, we showed that a DC spin-transfer torque (STT) term…

Strongly Correlated Electrons · Physics 2022-11-14 Benjamin Assouline , Amir Capua

Magnetic tunnel junction-based molecular spintronics devices (MTJMSDs) are designed by covalently connecting the paramagnetic molecules across two ferromagnets (FM) electrodes of a magnetic tunnel junction (MTJ). MTJMSD provides…

We present a complete theory of the spin torque phenomena in a ultrasmall nanomagnet coupled to non-collinear ferromagnetic electrodes through tunnelling junctions. This model system can be described by a simple microscopic model which…

Mesoscale and Nanoscale Physics · Physics 2008-02-22 O. Parcollet , X. Waintal

The development of machine learning interatomic potentials has immensely contributed to the accuracy of simulations of molecules and crystals. However, creating interatomic potentials for magnetic systems that account for both magnetic…

Computational Physics · Physics 2024-04-30 Hongyu Yu , Yang Zhong , Liangliang Hong , Changsong Xu , Wei Ren , Xingao Gong , Hongjun Xiang