English
Related papers

Related papers: Evaluating Spintronic Devices Using The Modular Ap…

200 papers

One of the big challenges of current electronics is the design and implementation of hardware neural networks that perform fast and energy-efficient machine learning. Spintronics is a promising catalyst for this field with the capabilities…

Mesoscale and Nanoscale Physics · Physics 2022-01-17 Jan Kaiser , William A. Borders , Kerem Y. Camsari , Shunsuke Fukami , Hideo Ohno , Supriyo Datta

Accelerometers have widespread applications and are an essential component in many areas such as automotive, consumer electronics and industrial applications. Most commercial accelerometers are based on micro-electromechanical system (MEMS)…

The demand for computing power has been growing exponentially with the rise of artificial intelligence (AI), machine learning, and the Internet of Things (IoT). This growth requires unconventional computing primitives that prioritize energy…

Networked systems are systems of interconnected components, in which the dynamics of each component are influenced by the behavior of neighboring components. Examples of networked systems include biological networks, critical…

Systems and Control · Computer Science 2016-06-01 Andrew Clark , Basel Alomair , Linda Bushnell , Radha Poovendran

We present cmtj - a comprehensive simulation package that allows large-scale macrospin simulations for a variety of multilayer spintronics devices. Apart from conventional static simulations, such as magnetoresistance and magnetisation…

Spintronics is an approach to electronics in which the spin of the electrons is exploited to control the electric resistance R of devices. One basic building block is the spin-valve, which is formed if two ferromagnetic electrodes are…

Mesoscale and Nanoscale Physics · Physics 2016-08-16 Sangeeta Sahoo , Takis Kontos , Jürg Furer , Christian Hoffmann , Matthias Gräber , Audrey Cottet , Christian Schönenberger

The miniaturisation of transistors is approaching its limits due to challenges in heat management and information transfer speed. To overcome these obstacles, emerging technologies such as spintronics are being developed, which leverage the…

Due to the massive parallel computing capability and outstanding image and signal processing performance, cellular neural network (CNN) is one promising type of non-Boolean computing system that can outperform the traditional digital logic…

Emerging Technologies · Computer Science 2016-09-21 Chenyun Pan , Azad Naeemi

Spintronics is expected as the next-generation technology based on the novel notch of spin degree of freedom of electrons. Half metals, a class of materials which behave as a metal in one spin direction and an insulator in the opposite spin…

Materials Science · Physics 2011-08-19 Xiao HU

Atomtronics is a relatively new subfield of atomic physics that aims to realize the device behavior of electronic components in ultracold atom-optical systems. The fact that these systems are coherent makes them particularly interesting…

Quantum Physics · Physics 2021-04-28 R. A. Pepino

Modern hardware environments are becoming increasingly heterogeneous, leading to the emergence of applications specifically designed to exploit this heterogeneity. Efficiently adopting locks in these applications poses distinct challenges.…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-08-12 Hanze Zhang , Rong Chen , Haibo Chen

Functional aspects as well as the influence of integration technology on the system behavior have to be considered in the 3D integration design process of micro systems. Therefore, information from different physical domains has to be…

Other Computer Science · Computer Science 2008-02-22 P. Schneider , S. Reitz , A. Wilde , G. Elst , P. Schwarz

Extending Moore's law by augmenting complementary-metal-oxide semiconductor (CMOS) transistors with emerging nanotechnologies (X) has become increasingly important. One important class of problems involve sampling-based Monte Carlo…

The use of nuclear spins as physical sensing systems is disadvantaged by their low signal responsivity, particularly when compared to sensing techniques based on electron spins. This primarily results from the small nuclear gyromagnetic…

This paper addresses the question: Can spintronic circuits based on Magnetic Tunnel Junction (MTJ) transducers outperform their state-of-the-art CMOS counterparts? To this end, we use the EPFL combinational benchmark sets, synthesize them…

High-fidelity numerical methods that model the physical layout of a device are essential for the design of many technologies. For methods that characterize electromagnetic effects, these numerical methods are referred to as computational…

Within the paradigm of metamaterials and metasurfaces, electromagnetic properties of composite materials can be engineered by shaping or modulating their constituents, so-called meta-atoms. Synthesis and analysis of complex-shape meta-atoms…

Optics · Physics 2019-09-04 Viktar Asadchy , Sergei Tretyakov

Over the recent years, crossroads of magnetism and superconductivity led to the emerging field of superconducting spintronics. A cornerstone of this venture is the generation of equal-spin triplet Cooper pairs in superconductor-ferromagnet…

Superconductivity · Physics 2025-12-22 Pablo Tuero , César González-Ruano , Igor Žutić , Yuan Lu , Coriolan Tiusan , Farkhad G. Aliev

Orbitronics explores the control and manipulation of electronic orbital angular momentum in solid-state systems, opening new pathways for information processing and storage. One significant advantage of orbitronics over spintronics is that…

Mesoscale and Nanoscale Physics · Physics 2025-10-07 Tarik P. Cysne , Luis M. Canonico , Marcio Costa , R. B. Muniz , Tatiana G. Rappoport

Molecular simulations provide a powerful means to unravel the complex relationships between network architecture and the mechanical response of polymer networks, with a particular emphasis on rupture and fracture phenomena. Although…

Soft Condensed Matter · Physics 2026-02-02 Yuichi Masubuchi , Takato Ishida , Yusuke Koide , Takashi Uneyama