The 2020 skyrmionics roadmap

The notion of non-trivial topological winding in condensed matter systems represents a major area of present-day theoretical and experimental research. Magnetic materials offer a versatile platform that is particularly amenable for the exploration of topological spin solitons in real space such as skyrmions. First identified in non-centrosymmetric bulk materials, the rapidly growing zoology of materials systems hosting skyrmions and related topological spin solitons includes bulk compounds, surfaces, thin films, heterostructures, nano-wires and nano-dots. This underscores an exceptional potential for major breakthroughs ranging from fundamental questions to applications as driven by an interdisciplinary exchange of ideas between areas in magnetism which traditionally have been pursued rather independently. The skyrmionics Roadmap provides a review of the present state of the art and the wide range of research directions and strategies currently under way. These are, for instance, motivated by the identification of the fundamental structural properties of skyrmions and related textures, processes of nucleation and annihilation in the presence of non-trivial topological winding, an exceptionally efficient coupling to spin currents generating spin transfer torques at tiny current densities, as well as the capability to purpose-design broad-band spin dynamic and logic devices

Readout of a antiferromagnetic spintronics systems by strong exchange coupling of Mn2Au and Permalloy

In antiferromagnetic spintronics, the read-out of the staggered magnetization or Neel vector is the key obstacle to harnessing the ultra-fast dynamics and stability of antiferromagnets for novel devices. Here, we demonstrate strong exchange coupling of Mn2Au, a unique metallic antiferromagnet that exhibits Neel spin-orbit torques, with thin ferromagnetic Permalloy layers. This allows us to benefit from the well-estabished read-out methods of ferromagnets, while the essential advantages of antiferromagnetic spintronics are retained. We show one-to-one imprinting of the antiferromagnetic on the ferromagnetic domain pattern. Conversely, alignment of the Permalloy magnetization reorients the Mn2Au Neel vector, an effect, which can be restricted to large magnetic fields by tuning the ferromagnetic layer thickness. To understand the origin of the strong coupling, we carry out high resolution electron microscopy imaging and we find that our growth yields an interface with a well-defined morphology that leads to the strong exchange coupling.Comment: 9 pages, 5 figure

A deeper look into natural sciences with physics-based and data-driven measures

With the development of machine learning in recent years, it is possible to glean much more information from an experimental data set to study matter. In this perspective, we discuss some state-of-the-art data-driven tools to analyze latent effects in data and explain their applicability in natural science, focusing on two recently introduced, physics-motivated computationally cheap tools—latent entropy and latent dimension. We exemplify their capabilities by applying them on several examples in the natural sciences and show that they reveal so far unobserved features such as, for example, a gradient in a magnetic measurement and a latent network of glymphatic channels from the mouse brain microscopy data. What sets these techniques apart is the relaxation of restrictive assumptions typical of many machine learning models and instead incorporating aspects that best fit the dynamical systems at hand

Perspective: Magnetic skyrmions-Overview of recent progress in an active research field

Within a decade, the field of magnetic skyrmionics has developed from a niche prediction to a huge and active research field. Not only do magnetic skyrmions magnetic whirls with a unique topology reveal fundamentally new physics, but they have also risen to prominence as up-and-coming candidates for next-generation high-density efficient information encoding. Within a few years, it has been possible to efficiently create, manipulate, and destroy nanometer-size skyrmions in device compatible materials at room-temperature by all electrical means. Despite the incredibly rapid progress, several challenges still remain to obtain fully functional and competitive skyrmion devices, as discussed in this perspective article with a focus on recent results. Published by AIP Publishing

Spin-transfer torque driven motion, deformation, and instabilities of magnetic skyrmions at high currents

In chiral magnets, localized topological magnetic whirls, magnetic skyrmions, can be moved by spin polarized electric currents. Upon increasing the current strength, with prospects for high-speed skyrmion motion for spintronics applications in mind, isolated skyrmions deform away from their typical circular shape. We analyze the influence of spin-transfer torques on the shape of a single skyrmion, including its stability upon adiabatically increasing the strength of the applied electric current. For rather compact skyrmions at uniaxial anisotropies well above the critical anisotropy for domain wall formation, we find for high current densities that the skyrmion assumes a noncircular shape with a tail, reminiscent of a shooting star. For larger and hence softer skyrmions close to the critical anisotropy, in turn, we observe a critical current density above which skyrmions become unstable. We show that above a second critical current density the shooting star solution can be recovered also for these skyrmions

Neuromorphic spintronics

Neuromorphic computing uses basic principles inspired by the brain to design circuits that perform artificial intelligence tasks with superior energy efficiency. Traditional approaches have been limited by the energy area of artificial neurons and synapses realized with conventional electronic devices. In recent years, multiple groups have demonstrated that spintronic nanodevices, which exploit the magnetic as well as electrical properties of electrons, can increase the energy efficiency and decrease the area of these circuits. Among the variety of spintronic devices that have been used, magnetic tunnel junctions play a prominent role because of their established compatibility with standard integrated circuits and their multifunctionality. Magnetic tunnel junctions can serve as synapses, storing connection weights, functioning as local, nonvolatile digital memory or as continuously varying resistances. As nano-oscillators, they can serve as neurons, emulating the oscillatory behavior of sets of biological neurons. As superparamagnets, they can do so by emulating the random spiking of biological neurons. Magnetic textures like domain walls or skyrmions can be configured to function as neurons through their non-linear dynamics. Several implementations of neuromorphic computing with spintronic devices demonstrate their promise in this context. Used as variable resistance synapses, magnetic tunnel junctions perform pattern recognition in an associative memory. As oscillators, they perform spoken digit recognition in reservoir computing and when coupled together, classification of signals. As superparamagnets, they perform population coding and probabilistic computing. Simulations demonstrate that arrays of nanomagnets and films of skyrmions can operate as components of neuromorphic computers. While these examples show the unique promise of spintronics in this field, there are several challenges to scaling up, including the efficiency of coupling between devices and the relatively low ratio of maximum to minimum resistances in the individual devices