scholarly journals Magnetic Elements for Neuromorphic Computing

Molecules ◽  
2020 ◽  
Vol 25 (11) ◽  
pp. 2550 ◽  
Author(s):  
Tomasz Blachowicz ◽  
Andrea Ehrmann
Keyword(s):  
Magnetic Materials ◽  
Data Storage ◽  
Energy Efficient ◽  
Domain Walls ◽  
Magnetic Nanostructures ◽  
Data Transport ◽  
Neuromorphic Computing ◽  
Von Neumann ◽  
Spintronic Devices ◽  
Magnetic Elements

Neuromorphic computing is assumed to be significantly more energy efficient than, and at the same time expected to outperform, conventional computers in several applications, such as data classification, since it overcomes the so-called von Neumann bottleneck. Artificial synapses and neurons can be implemented into conventional hardware using new software, but also be created by diverse spintronic devices and other elements to completely avoid the disadvantages of recent hardware architecture. Here, we report on diverse approaches to implement neuromorphic functionalities in novel hardware using magnetic elements, published during the last years. Magnetic elements play an important role in neuromorphic computing. While other approaches, such as optical and conductive elements, are also under investigation in many groups, magnetic nanostructures and generally magnetic materials offer large advantages, especially in terms of data storage, but they can also unambiguously be used for data transport, e.g., by propagation of skyrmions or domain walls. This review underlines the possible applications of magnetic materials and nanostructures in neuromorphic systems.

scholarly journals Neuro-Inspired Signal Processing in Ferromagnetic Nanofibers

Biomimetics ◽  
2021 ◽  
Vol 6 (2) ◽  
pp. 32
Author(s):  
Tomasz Blachowicz ◽  
Jacek Grzybowski ◽  
Pawel Steblinski ◽  
Andrea Ehrmann
Keyword(s):  
Data Processing ◽  
Data Storage ◽  
Domain Walls ◽  
Data Transfer ◽  
Synaptic Activity ◽  
Neuromorphic Computing ◽  
Rotating Magnetic Fields ◽  
Micromagnetic Simulations ◽  
Energy Consuming ◽  
Stochastic Data

Computers nowadays have different components for data storage and data processing, making data transfer between these units a bottleneck for computing speed. Therefore, so-called cognitive (or neuromorphic) computing approaches try combining both these tasks, as is done in the human brain, to make computing faster and less energy-consuming. One possible method to prepare new hardware solutions for neuromorphic computing is given by nanofiber networks as they can be prepared by diverse methods, from lithography to electrospinning. Here, we show results of micromagnetic simulations of three coupled semicircle fibers in which domain walls are excited by rotating magnetic fields (inputs), leading to different output signals that can be used for stochastic data processing, mimicking biological synaptic activity and thus being suitable as artificial synapses in artificial neural networks.

scholarly journals Магнитостатическая энергия доменных стенок в одноосных пленках конечных размеров

2019 ◽  
Vol 61 (10) ◽  
pp. 1767
Author(s):  
П.М. Ветошко ◽  
Ф.П. Ветошко ◽  
В.Г. Шавров ◽  
В.И. Щеглов
Keyword(s):  
Domain Walls ◽  
Magnetic Sensors ◽  
Magnetization Distribution ◽  
Magnetic Memory ◽  
Spintronic Devices ◽  
Domain Structures ◽  
Magnetic Elements ◽  
Uniform Magnetization ◽  
Equilibrium Configurations ◽  
Equivalent Currents

AbstractThe solution to the problem of calculating the magnetostatic interaction energy of domain walls in uniaxial magnetics with a uniform magnetization distribution inside the domains is given. In carrying out the calculations, the principle of equivalent currents is used, assuming a uniform distribution of magnetization and its representation by equivalent currents flowing along the domain walls and along the surface. Analytical expressions for the mutual induction of two rectangular conductors with an arbitrary aspect ratio have been obtained. Results may be helpful in determining equilibrium configurations of domain structures in magnetic elements of spintronic devices, magnetic sensors and magnetic memory.

scholarly journals Spintronic devices for energy-efficient data storage and energy harvesting

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Jorge Puebla ◽  
Junyeon Kim ◽  
Kouta Kondou ◽  
Yoshichika Otani
Keyword(s):  
Energy Harvesting ◽  
Data Storage ◽  
Energy Efficient ◽  
Spintronic Devices ◽  
Efficient Data

Motion of Skyrmions in Well-Separated Two-Lane Racetracks

SPIN ◽  
2017 ◽  
Vol 07 (01) ◽  
pp. 1740006 ◽  
Author(s):  
P. Lai ◽  
G. P. Zhao ◽  
F. J. Morvan ◽  
S. Q. Wu ◽  
N. Ran
Keyword(s):  
Data Storage ◽  
Energy Efficient ◽  
Binary Data ◽  
Domain Walls ◽  
Magnetocrystalline Anisotropy ◽  
Magnetic Domain ◽  
Lane Width ◽  
Magnetic Domain Walls ◽  
Magnetic Skyrmions ◽  
Transport Device

Magnetic skyrmions are topological structures which can be used to store information as data bits in metallic racetrack memories. Their good properties, such as their stability, small size and low currents needed to drive them make them better candidates than traditional magnetic domain walls for the building of the next generation data storage. A skyrmion racetrack memory has been suggested, with the binary data encoded in the distance between skyrmions when the racetrack is a single lane. Here, we propose a new skyrmion-based two-lane racetrack structure separated by a high-[Formula: see text] (high magnetocrystalline anisotropy) middle lane, which confines the skyrmions in their respective lanes. This design gives a new data presentation for the skyrmions on the racetrack. Phase diagrams for the skyrmion motion on the proposed racetrack as functions of the current density, middle lane anisotropy, middle lane width and DMI constant have been calculated and given, demonstrating that skyrmions can be driven in different lanes of the racetrack. This design offers the possibility of building an ultrafast and energy-efficient skyrmion transport device.

scholarly journals Micromagnetic Simulations of Fe and Ni Nanodot Arrays Surrounded by Magnetic or Non-Magnetic Matrices

Nanomaterials ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 349
Author(s):  
Devika Sudsom ◽  
Andrea Ehrmann
Keyword(s):  
Magnetic Materials ◽  
Data Storage ◽  
Magnetization Reversal ◽  
Hysteresis Loops ◽  
Object Oriented ◽  
Basic Research ◽  
Memory Systems ◽  
The Other ◽  
Micromagnetic Simulations ◽  
Nanodot Arrays

Combining clusters of magnetic materials with a matrix of other magnetic materials is very interesting for basic research because new, possibly technologically applicable magnetic properties or magnetization reversal processes may be found. Here we report on different arrays combining iron and nickel, for example, by surrounding circular nanodots of one material with a matrix of the other or by combining iron and nickel nanodots in air. Micromagnetic simulations were performed using the OOMMF (Object Oriented MicroMagnetic Framework). Our results show that magnetization reversal processes are strongly influenced by neighboring nanodots and the magnetic matrix by which the nanodots are surrounded, respectively, which becomes macroscopically visible by several steps along the slopes of the hysteresis loops. Such material combinations allow for preparing quaternary memory systems, and are thus highly relevant for applications in data storage and processing.

Wearable energy efficient fitness tracker for sports person health monitoring application

2021 ◽  
pp. 1-10
Author(s):  
Yongyue Huang ◽  
Min Hu ◽  
BalaAnand Muthu ◽  
R. Gayathri
Keyword(s):  
Energy Consumption ◽  
Data Storage ◽  
Energy Efficient ◽  
Consumer Satisfaction ◽  
Form Factors ◽  
Recognition System ◽  
Energy Utilization ◽  
Biologically Inspired Algorithms ◽  
Enhance Efficiency ◽  
Fitness Tracker

Continuous evaluation of biological and physiological metrics of sports personalities, evaluating general health status, and alerting for life-saving treatments, is supposed to enhance efficiency and healthy performance. Wearable devices with acceptable form factors compact, flexibility, minimal power consumption, etc., are needed for continuous monitoring to avoid affecting everyday operations, thereby retaining functional effectiveness and consumer satisfaction. This research focuses on the acceleration tracker for particularizing the work. Acceleration data is typically collected on battery-powered sensors for activity detection, referring to an exchange between high-precision detection and energy-efficient processing. From a feature selection perspective, the paper explores this trade-off. It suggests an Energy-Efficient Behavior Recognition System with a comprehensive energy utilization model and the Multi-objective Algorithm of Particle Swarm Optimization (EEBRS-MPSO). Therefore, using Random Forest (RF) classifiers, the model and algorithm are tested to measure the precision of identification and obtain the task’s best performance with the lowest energy consumption, among other biologically-inspired algorithms. The findings indicate that energy consumption for data storage and data processing is minimized with magnitude relative to the raw data method by choosing suitable groups of attributes. Thus, the platform allows a scalable range of feature clusters that require the authors to provide an adequate power adjustment for given target use.

Discovery of intrinsic two-dimensional antiferromagnets from transition-metal borides

Nanoscale ◽  
2021 ◽  
Author(s):  
Shiyao Wang ◽  
Nanxi Miao ◽  
Kehe Su ◽  
Vladislav A. Blatov ◽  
Junjie Wang
Keyword(s):  
Transition Metal ◽  
Magnetic Materials ◽  
Van Der Waals ◽  
Two Dimensional ◽  
Spintronic Devices ◽  
Metal Borides

Intrinsic two-dimensional (2-D) magnets are promising materials for developing advanced spintronic devices. Few have already been synthesized from the exfoliation of the van der Waals magnetic materials. In this work,...

Hypercoordinate Two-dimensional Transition-metal Borides for Spintronics and Catalyst Applications

2021 ◽  
Author(s):  
Shiyao Wang ◽  
Mohammad Khazaei ◽  
Junjie Wang ◽  
Hideo Hosono
Keyword(s):  
Transition Metal ◽  
Magnetic Materials ◽  
Two Dimensional ◽  
Spintronic Devices ◽  
Metal Borides

Two-dimensional (2-D) magnetic materials are promising to be ideal platforms for constructing novel spintronic devices. Until to now, most 2-D magnetic materials have mainly been achieved by the exfoliation of...

scholarly journals Probing nanoscale behavior of magnetic materials with soft X-ray spectromicroscopy

2012 ◽  
Vol 1 (1) ◽  
pp. 5-15 ◽  
Author(s):  
Peter Fischer ◽  
Charles S. Fadley
Keyword(s):  
Magnetic Properties ◽  
Magnetic Materials ◽  
Spin Dynamics ◽  
Magnetic Nanostructures ◽  
Magnetic Behavior ◽  
Research Area ◽  
X Ray ◽  
Spatially Resolved ◽  
Buried Interfaces ◽  
Analytical Tools

AbstractThe magnetic properties of matter continue to be a vibrant research area driven both by scientific curiosity to unravel the basic physical processes which govern magnetism and the vast and diverse utilization of magnetic materials in current and future devices, e.g., in information and sensor technologies. Relevant length and time scales approach fundamental limits of magnetism and with state-of-the-art synthesis approaches we are able to create and tailor unprecedented properties. Novel analytical tools are required to match these advances and soft X-ray probes are among the most promising ones. Strong and element-specific magnetic X-ray dichroism effects as well as the nanometer wavelength of photons and the availability of fsec short and intense X-ray pulses at upcoming X-ray sources enable unique experimental opportunities for the study of magnetic behavior. This article provides an overview of recent achievements and future perspectives in magnetic soft X-ray spectromicroscopies which permit us to gain spatially resolved insight into the ultrafast spin dynamics and the magnetic properties of buried interfaces of advanced magnetic nanostructures.

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