npj Spintronics最新文献

Ultrafast heating of FeRh by a femtosecond laser pulse launches a magneto-structural phase transition from an antiferromagnetic to a ferromagnetic state. Aiming to reveal the ultrafast kinetics of this transition, we studied magnetization dynamics with the help of the magneto-optical Kerr effect in a broad range of temperatures (from 4 K to 400 K) and magnetic fields (up to 25 T). Three different types of ultrafast magnetization dynamics were observed and, using a numerically calculated H-T phase diagram, the differences were explained by different initial states of FeRh corresponding to a (i) collinear antiferromagnetic, (ii) canted antiferromagnetic and (iii) ferromagnetic alignment of spins. We argue that ultrafast heating of FeRh in the canted antiferromagnetic phase launches practically the fastest possible emergence of ferromagnetism in this material. The magnetization emerges on a time scale of 2 ps, which corresponds to the earlier reported time scale of the structural changes during the phase transition.

The inverse design approach in magnonics exploits the wave nature of magnons and machine learning to develop logical devices with functionalities that exceed the capabilities of analytical methods. While promising for analog, Boolean, and neuromorphic computing, current implementations face memory limitations that hinder the design of complex systems. This study presents a level-set parameterization method for topology optimization, combined with an adjoint-state approach for memory-efficient simulation of magnetization dynamics. The framework is implemented in NeuralMag, a GPU-accelerated micromagnetic solver featuring a nodal finite-difference scheme and automatic differentiation tools. To validate the method, we optimized the shape of a magnetic nanoparticle by applying constraints to the objective function, and designed a 300 nm-wide yttrium iron garnet demultiplexer achieving frequency-selective spin-wave separation. These results highlight the algorithm's efficiency in exploring local minima across various initial configurations, establishing its utility as a versatile tool for the inverse design of magnonic logic devices.

Chiral crystals, due to the lack of inversion and mirror symmetries, exhibit unique spin responses to external fields, enabling physical effects rarely observed in high-symmetry systems. Here, we show that materials from the chiral dichalcogenide family TM₃X₆ (T = 3d, M = 4d/5d, X = S) exhibit persistent spin texture (PST) - unidirectional spin polarization of states across large regions of the reciprocal space - in their nonmagnetic metallic phase. Using the example of NiTa₃S₆ and NiNb₃S₆, we show that PSTs cover the full Fermi surface, a rare and desirable feature that enables efficient charge-to-spin conversion and suggests long spin lifetimes and coherent spin transport above magnetic ordering temperatures. At low temperatures, the materials that order antiferromagnetically become chiral altermagnets, where spin textures originating from spin-orbit coupling and altermagnetism combine in a way that sensitively depends on the orientation of the Néel vector. Using symmetry analysis and first-principles calculations, we classify magnetic ground states across the family, identify cases with weak ferromagnetism, and track the evolution of spin textures and charge-to-spin conversion across magnetic phases and different Néel vector orientations, revealing spin transport signatures that allow one to distinguish Néel vector directions. These findings establish TM₃X₆ as a tunable platform for efficient charge-to-spin conversion and spin transport, combining structural chirality, persistent spin textures, and altermagnetism.

Topological defects play a crucial role across various fields, mediating phase transitions and macroscopic behaviors as they propagate through space. Their role as robust information carriers has also generated much attention. However, controlling their motion remains challenging, especially towards achieving motion along well-defined paths, which typically require predefined structural patterning. Here, we demonstrate the tunable, unidirectional motion of topological defects in a laterally unconfined thin film. The motion of these defects-specifically magnetic dislocations-is shown to mediate the overall continuous rotation of the stripe pattern in which they are embedded. We determine the connection between the unidirectional motion of dislocations and the underlying three-dimensional (3D) magnetic structure by performing 3D magnetic vectorial imaging with in situ magnetic fields. A minimal model for dislocations in stripe patterns that encodes the symmetry breaking induced by the external magnetic field reproduces the motion of dislocations that facilitate the 2D rotation of the stripes, highlighting the universality of the phenomenon. This work establishes a framework for studying the field-driven behavior of topological textures and designing materials that enable well-defined, controlled motion of defects in unconfined systems, paving the way to manipulate information carriers in higher-dimensional systems.

The interplay of electronic charge, spin, and orbital currents, coherently driven by picosecond long oscillations of light fields in spin-orbit coupled systems, is the foundation of emerging terahertz lightwave spintronics and orbitronics. The essential rules for how terahertz fields interact with these systems in a nonlinear way are still not understood. In this work, we demonstrate a universally applicable electronic nonlinearity originating from spin-orbit interactions in conducting materials, wherein the interplay of light-induced spin and orbital textures manifests. We utilized terahertz harmonic generation spectroscopy to investigate the nonlinear dynamics over picosecond timescales in various transition metal films. We found that the terahertz harmonic generation efficiency scales with the spin Hall conductivity in the studied films, while the phase takes two possible values (shifted by π), depending on the d-shell filling. These findings elucidate the fundamental mechanisms governing non-equilibrium spin and orbital polarization dynamics at terahertz frequencies, which is relevant for potential applications of terahertz spin- and orbital-based devices.

In materials science, we have been increasing the number of constituent elements in an alloy and compounds to improve their properties. For example, in magnetism and spintronics, ternary alloys, such as NdFeB and CoFeB have been developed and widely used in permanent magnets and memories/sensors, respectively. It has now been considered to be a time to add more elements to further explore their horizon. For such a complicated development, a manual systematic study is no longer practical, leading to the utilisation of machine learning to predict a candidate. These candidates can then be additionally screened by ab initio calculations before experimental confirmation, which can be performed routinely. Additional use of quantum annealing may also broaden the adoptability of machine learning on the materials development. In this perspective, we plan to offer a standardised process for such a development with some requirements for improvement.