Related papers: Antiferromagnetic Skyrmion based Energy-Efficient …
We introduce a novel integrated hybrid plasmonic-photonic device for all-optical switching and reading of nanoscale ferrimagnet bits. The racetrack memory made of synthetic ferrimagnetic material with a perpendicular magnetic anisotropy is…
Topologically protected spin textures, such as magnetic skyrmions, have the potential for dense data storage as well as energy-efficient computing due to their small size and a low driving current. The evaluation of the writing and reading…
Flexible electronics and neuromorphic computing face key challenges in material integration and function retention. In particular, freestanding membranes suffer from slow sacrificial layer removal and interfacial strain, while neuromorphic…
Skyrmion racetrack memory has a lots of potential in future non-volatile solid state devices. In general such devices require current to nucleate skyrmions via spin transfer torque (STT) effect. Further the current is also required to drive…
Due to the limitations of realizing artificial neural networks on prevalent von Neumann architectures, recent studies have presented neuromorphic systems based on spiking neural networks (SNNs) to reduce power and computational cost.…
The dynamical properties of skyrmions can be exploited to build devices with new functionalities. Here, we first investigate a skyrmion-based ring-shaped device by means of micromagnetic simulations and Thiele equation. We subsequently show…
Magnetic skyrmions are topologically stable spin swirling particle like entities which are appealing for next generation spintronic devices. The expected low critical current density for the motion of skyrmions makes them potential…
Spiking Neural Networks (SNNs) are valued for their ability to process spatio-temporal information efficiently, offering biological plausibility, low energy consumption, and compatibility with neuromorphic hardware. However, the commonly…
Nanoelectromangetomechanical systems (NEMMS) open up a new path for the development of high speed autonomous nanoresonators and signal generators that could be used as actuators, for information processing, as elements of quantum computers…
Skyrmion-based spin torque nano-oscillators are potential next-generation microwave signal generators. However, ferromagnetic skyrmion-based spin torque nano-oscillators cannot reach high oscillation frequencies. In this work, we propose to…
We employ a self-consistent simulation approach based on quantum physics here to study the magnetism of antiferromagnetic skyrmions formed on manolayer nanodisk planes. We find that if the disk is small and the Dzyaloshinsky-Moriya (DM)…
Neuromorphic computing offers an energy-efficient alternative to conventional deep learning accelerators for real-time time-series processing. However, many edge applications, such as wireless sensing and audio recognition, generate…
Magnetic skyrmion holds promise as information carriers in the next-generation memory and logic devices, owing to the topological stability, small size and extremely low current needed to drive it. One of the most potential applications of…
Magnetic skyrmions have been in the spotlight since their observation in technologically relevant systems at room temperature. More recently, there has been increasing interest in additional quasiparticles that may exist as…
SNNs are an active research domain towards energy efficient machine intelligence. Compared to conventional ANNs, SNNs use temporal spike data and bio-plausible neuronal activation functions such as Leaky-Integrate Fire/Integrate Fire…
Magnetic skyrmions are promising for building next-generation magnetic memories and spintronic devices due to their stability, small size and the extremely low currents needed to move them. In particular, skyrmion-based racetrack memory is…
Controlled movement of nano-scale stable magnetic objects has been proposed as the foundation for a new generation of magnetic storage devices. Magnetic skyrmions, vortex-like spin textures stabilized by their topology are particularly…
Magnetic random access memory schemes employing magnetoelectric coupling to write binary information promise outstanding energy efficiency. We propose and demonstrate a purely antiferromagnetic magnetoelectric random access memory…
Ferroelectric materials with switchable electric polarization hold great promise for a plethora of emergent applications, such as post-Moore's law nanoelectronics, beyond-Boltzmann transistors, non-volatile memories, and above-bandgap…
Deep learning has driven significant technological advancements, but its high energy consumption limits its use on battery-operated edge devices. Spiking Neural Networks (SNNs) offer promising reductions in inference-time energy…