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Antiferromagnetic materials hold promising prospects in novel types of spintronics applications. Assessing the stability of antiferromagnetic nanostructures against thermal excitations is a crucial aspect of designing devices with a high…

Mesoscale and Nanoscale Physics · Physics 2019-08-28 Levente Rózsa , Severin Selzer , Tobias Birk , Unai Atxitia , Ulrich Nowak

Neuromorphic computing promises to transform the current paradigm of traditional computing towards Non-Von Neumann dynamic energy-efficient problem solving. Thus, dynamic memory devices capable of simultaneously performing nonlinear…

Magnetic skyrmions are magnetic quasi-particles with enhanced stability and different manipulation mechanisms using external fields and currents making them promising candidates for future applications for instance in neuromorphic…

Materials Science · Physics 2023-03-30 Thomas Brian Winkler , Jan Rothörl , Maarten A. Brems , Hans Fangohr , Mathias Kläui

Recent years have witnessed growing interest in the field of brain-inspired computing based on neural-network architectures. In order to translate the related algorithmic models into powerful, yet energy-efficient cognitive-computing…

Disordered Systems and Neural Networks · Physics 2015-06-17 Mrigank Sharad , D. Fan , Kaushik Roy

Exploiting both spin and charge of the electron in electronic micordevices has lead to a tremendous progress in both basic condensed-matter research and microelectronic applications, resulting in the modern field of spintronics. Current…

Materials Science · Physics 2015-06-25 X. Martí , I. Fina , T. Jungwirth

Magnetic domain walls are information tokens in both logic and memory devices, and hold particular interest in applications such as neuromorphic accelerators that combine logic in memory. Here, we show that devices based on the electrical…

Disordered Systems and Neural Networks · Physics 2020-01-03 Saima A Siddiqui , Sumit Dutta , Astera Tang , Luqiao Liu , Caroline A Ross , Marc A Baldo

2D ferromagnets offer valuable insights into the fundamentals of magnetism and stimulate the progress of ultracompact spintronics. The demand for seamless integration of the materials with the Si technology, particularly helpful to their…

Antiferromagnetic materials promise improved performance for spintronic applications, as they are robust against external magnetic field perturbations and allow for faster magnetization dynamics compared to ferromagnets. The direct…

Construction and training principles have been proposed and tested for an artificial neural network based on metal-oxide thin-film nanostructures possessing bipolar resistive switching (memristive) effect. Experimental electronic circuit of…

Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to…

Ferroelectric devices use their electric polarization ferroic order as the switching and storage physical quantity for memory applications. However, additional built-in physical quantities and memory paradigms are requested for…

Materials Science · Physics 2014-06-16 B. Kundys , V. Iurchuk , C. Meny , H. Majjad , B. Doudin

Integration of magneto-electric and spintronic sensors presents a massive potential for advancing flexible and wearable technology. Magnetic nanowires are core components for building such devices, and therefore it important to realize…

Mesoscale and Nanoscale Physics · Physics 2020-06-19 Giuseppe Muscas , Petra E. Jönsson , I. G. Serrano , Örjan Vallin , M. Venkata Kamalakar

The progress in the field of neural computation hinges on the use of hardware more efficient than the conventional microprocessors. Recent works have shown that mixed-signal integrated memristive circuits, especially their passive ('0T1R')…

Emerging Technologies · Computer Science 2017-12-05 F. Merrikh Bayat , M. Prezioso , B. Chakrabarti , I. Kataeva , D. Strukov

Significant research has focused on low-power stochastic devices built from memristive materials. These devices foster neuromorphic approaches to computational efficiency enhancement in merged biomimetic and CMOS architectures due to their…

Magnetic skyrmions are promising candidates for the next generation of spintronic devices due to their small size and topologically protected structure. One challenge for using these magnetic states in applications lies on controlling the…

Mesoscale and Nanoscale Physics · Physics 2018-10-19 J. Brandão , D. A. Dugato , R. L. Seeger , J. C. Denardin , T. J. A. Mori , J. C. Cezar

The increasing need to store large amounts of information with an ultra-dense, reliable, low power and low cost memory device is driving aggressive efforts to improve upon current perpendicular magnetic recording technology. However, the…

Mesoscale and Nanoscale Physics · Physics 2019-01-09 Ozhan Ozatay , Aisha Gokce , Thomas Hauet , Liesl Folks , Anna Giordano , Giovanni Finocchio

In 2016, the Global Burden of Disease reported that neurological disorders were the principal cause of disability-adjusted life years (DALYs) and the second leading cause of deaths. Research in the last decade has pushed neuroscience to…

Applied Physics · Physics 2019-10-08 Renata Saha , Kai Wu , Diqing Su , Jian-Ping Wang

Magnetic skyrmion-based data storage and unconventional computing devices have gained increasing attention due to their topological protection, small size, and low driving current. However, skyrmion creation, deletion, and motion are still…

Materials Science · Physics 2023-01-11 Aijaz H. Lone , Arnab Ganguly , Selma Amara , Gobind Das , H. Fariborzi

The dynamics of magnetic domain walls along ferromagnetic strips with spatially modulated perpendicular magnetic anisotropy is theoretically studied by means of micromagnetic simulations. Ferromagnetic layers with a periodic sawtooth…

Materials Science · Physics 2018-06-19 Luis Sánchez-Tejerina , Óscar Alejos , Víctor Raposo , Eduardo Martínez

Stochastic diffusion processes are pervasive in nature, from the seemingly erratic Brownian motion to the complex interactions of synaptically-coupled spiking neurons. Recently, drawing inspiration from Langevin dynamics, neuromorphic…

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