Magnetic Texture Research Articles

Probing intrinsic magnetic domain in bare CrI3 bulk with a magnetic force microscope

Two-dimensional magnetism in CrI3 links to its stacking structural order. In bulk CrI3, coexistence of monoclinic and rhombohedral phases has been observed across wide temperature range. Direct characterization of the magnetic textures on the exposed surface of bulk CrI3 has been challenging but meaningful. Here, we have employed a custom glovebox-assisted magnetic force microscope to observe the evolution of magnetic domains on the bare CrI3 surface under variable temperatures and magnetic fields for the first time. Below the Curie temperature, robust parallel stripe magnetic domains spontaneously emerge. The root mean square values of the localized weak pinning domain images at various temperatures indicate a critical transition behavior consistent with 3D Ising model with Tc ∼ 59 K. Images obtained by varying the magnetic field at low temperatures, showing magnetization saturation-reentry cycles, reveal larger hysteresis and stronger disorder compared to the VSM measurement, indicating local structural phase inhomogeneity. ​Two in-plane stripe magnetic domains oriented locally at an angle of 51-degrees compete under an out-of-plane magnetic field, presumably due to different sliding orientations induced by the magnetic field during the transition from a monoclinic to a rhombohedral phase. This study provides an experimental reference for future spin density wave manipulation in CrI3.

Structure, control, and dynamics of altermagnetic textures

We present a phenomenological theory of altermagnets, that captures their unique magnetization dynamics and allows modeling magnetic textures in this new magnetic phase. Focusing on the prototypical d-wave altermagnets, e.g., RuO2, we can explain intuitively the characteristic lifted degeneracy of their magnon spectra, by the emergence of an effective sublattice-dependent anisotropic spin stiffness arising naturally from the phenomenological theory. We show that as a consequence the altermagnetic domain walls, in contrast to antiferromagnets, have a finite gradient of the magnetization, with its strength and gradient direction connected to the altermagnetic anisotropy, even for 180° domain walls. This gradient generates a ponderomotive force in the domain wall in the presence of a strongly inhomogeneous external magnetic field, which may be achieved through magnetic force microscopy techniques. The motion of these altermagentic domain walls is also characterized by an anisotropic Walker breakdown, with much higher speed limits of propagation than ferromagnets but lower than antiferromagnets.

Polarity-controllable magnetic skyrmion filter

Abstract The skyrmion generator is one of the indispensable components for the future functional skyrmion devices, but the process of generating skyrmion cannot avoid mixing with other magnetic textures, such as skyrmionium and nested skyrmion bags. These mixed magnetic textures will inevitably lead to the blockage of skyrmion transport and even the distortion of data information. Therefore, the design of an efficient skyrmion filter is of great significance for the development of skyrmion-based spintronic devices. In this work, a skyrmion filter scheme is proposed, and the high-efficiency filtering function is demonstrated by micromagnetic simulations. The results show that the filtering effect of the scheme depends on the structure geometry and the spin current density that drives the skyrmion. Based on this scheme, the polarity of the filtered skyrmion can be controlled by switching the magnetization state at the output end, and the “cloning” of the skyrmion can be realized by geometric optimization of the structure. We believe that in the near future, the skyrmion filter will become one of the important components of skyrmion-based spintronic devices in the future.

Decoupling the influences of chiral damping and Dzyaloshinskii-Moriya interaction in chiral magnetic domain walls

We revisit the nature and impact of both the chiral damping (CD) and Dzyaloshinskii-Moriya interaction (DMI) in uniaxial chiral ferromagnetic nanowires with broken inversion symmetry. We propose that CD, akin to its chiral energy counterpart (DMI), can be described in terms of the Lifshitz invariants permissible by the underlying symmetry of the system. This representation offers a clearer foundation for integrating CD into the dynamics of various chiral magnetic textures. We theoretically investigate the current-induced motion of chiral domain walls (DWs), driven by both spin-transfer torque and the spin Hall effect in the presence of CD. We demonstrate that it is possible to unambiguously separate the influence of CD from that of DMI by analyzing the current-induced dynamics. In particular, below the Walker breakdown (WB), the DMI does not affect the DW velocity, whereas increases in the strength of CD result in a decrease in the DW velocity. Moreover, for the spin-orbit torque driven motion, while the DMI enhances both the WB current density and the maximum attainable velocity below the WB, the CD only enhances the WB without affecting the maximum attainable velocity below the WB. Our findings open up intriguing opportunities for exploitation in exotic magnetic textures. Published by the American Physical Society 2024

Observation of the sliding phason mode of the incommensurate magnetic texture in Fe/Ir(111)

The nanoscopic magnetic texture forming in a monolayer of iron on the (111) surface of iridium, Fe/Ir(111), is spatially modulated and uniaxially incommensurate with respect to the crystallographic periodicities. As a consequence, a low-energy magnetic excitation is expected that corresponds to the sliding of the texture along the incommensurate direction, i.e., a phason mode, which we explicitly confirm with atomistic spin simulations. Using scanning tunneling microscopy (STM), we succeed to observe this phason mode experimentally. It can be excited by the STM tip, which leads to a random telegraph noise in the tunneling current that we attribute to the presence of two minima in the phason potential due to the presence of disorder in our sample. This provides the prospect of a floating phase in cleaner samples and, potentially, a commensurate-incommensurate transition as a function of external control parameters.

Theory of Moiré Magnetism and Multidomain Spin Textures in Twisted Mott Insulator-Semimetal Heterobilayers.

Motivated by the recent experimental developments in van der Waals heterostructures, we investigate the emergent magnetism in Mott insulator-semimetal moiré superlattices by deriving effective spin models and exploring their phase diagram by Monte Carlo simulations. Our analysis indicates that the stacking-dependent interlayer Kondo interaction can give rise to different types of magnetic order, forming domains within the moiré unit cell. In particular, we find that the AB (AA) stacking regions tend to order (anti)ferromagnetically for an extended range of parameters. The remaining parts of the moiré unit cell form ferromagnetic chains that are coupled antiferromagnetically. We show that the decay length of the Kondo interaction can control the extent of these phases. Our results highlight the importance of stacking-dependent interlayer exchange and the rich magnetic spin textures that can be obtained in van der Waals heterostructures.

Influence of Magnetic Sublattice Ordering on Skyrmion Bubble Stability in 2D Magnet Fe5GeTe2.

The realization of above room-temperature ferromagnetism in the two-dimensional (2D) magnet Fe5GeTe2 represents a major advance for the use of van der Waals (vdW) materials in practical spintronic applications. In particular, observations of magnetic skyrmions and related states within exfoliated flakes of this material provide a pathway to the fine-tuning of topological spin textures via 2D material heterostructure engineering. However, there are conflicting reports as to the nature of the magnetic structures in Fe5GeTe2. The matter is further complicated by the study of two types of Fe5GeTe2 crystals with markedly different structural and magnetic properties, distinguished by their specific fabrication procedure: whether they are slowly cooled or rapidly quenched from the growth temperature. In this work, we combine X-ray and electron microscopy to observe the formation of magnetic stripe domains, skyrmion-like type-I, and topologically trivial type-II bubbles, within exfoliated flakes of Fe5GeTe2. The results reveal the influence of the magnetic ordering of the Fe1 sublattice below 150 K, which dramatically alters the magnetocrystalline anisotropy and leads to a complex magnetic phase diagram and a sudden change of the stability of the magnetic textures. In addition, we highlight the significant differences in the magnetic structures intrinsic to slow-cooled and quenched Fe5GeTe2 flakes.

Evolution of magnetization textures in Mn1.4PtSn under magnetic field

We have used Lorentz transmission electron microscopy (LTEM) and the transport of intensity equation (TIE) method to investigate the spin structures in the Mn1.4PtSn magnet, which exhibits D2d symmetry. The evolution of the spin structures under the external magnetic field was observed. In particular, a perpendicular field is able to modulate the striped domain widths and to induce the formation of anti-skyrmions and bubbles. While an in-plane magnetic field can control the state of these structures, the coexistence of different types of skyrmions suggests that the hysteresis properties of the magnet may affect the effectiveness of the field control.

Emergent chiral spin textures in centrosymmetric iron garnet with spin alignment constraints

Chiral spin textures have emerged as a captivating class of topological matter. These intriguing structures harbor localized and topologically protected magnetic textures, rendering them promising candidates for novel spintronic applications. Here, the emergent chiral spin textures in an iron garnet with nanodisk configuration have been micromagnatically simulated based on the Landau-Lifshitz-Gilbert equation (LLG) of COMSOL Multiphysics. The modification of magnetic spin texture in the considered iron garnet has been controlled by introducing the interfacial Dzyaloshinskii-Moriya interaction (I-DMI) and spin alignment constraints as locally pinned spins and curvilinear defects at edges. These boundary conditions induced interesting chiral textures not commonly observed in such iron garnet due to its centrosymmetric crystal structure. The simulation results showed the presence of two distinct regions of spin texture: inside and outside the pinning boundary. By systematically varying the DMI strength (D) with the size of the pinning boundary (Rpin) and the number of defects (Ndef), the emerging chiral spin textures have been explored and reported, including the existence of ramified helical stripes, skyrmions, and skyrmions-like textures such as elongated skyrmions, chiral horseshoe domains, biskyrmions and target skyrmions (TSk) (2π-TSk and 3π-TSk). Also, it has been reported that various collapses occur in the final spin texture states, leading to the transition from one state to another when varying the values of Rpin and Ndef with D.

Machine learning and magnetic resonance image texture analysis predicts accelerated lung function decline in ex-smokers with and without chronic obstructive pulmonary disease.

Our objective was to train machine-learning algorithms on hyperpolarized magnetic resonance imaging (MRI) datasets to generate models of accelerated lung function decline in participants with and without chronic-obstructive-pulmonary-disease. We hypothesized that hyperpolarized gas MRI ventilation, machine-learning, and multivariate modeling could be combined to predict clinically-relevant changes in forced expiratory volume in 1s ( ) across 3 years. Hyperpolarized MRI was acquired using a coronal Cartesian fast gradient recalled echo sequence with a partial echo and segmented using a k-means clustering algorithm. A maximum entropy mask was used to generate a region-of-interest for texture feature extraction using a custom-developed algorithm and the PyRadiomics platform. The principal component and Boruta analyses were used for feature selection. Ensemble-based and single machine-learning classifiers were evaluated using area-under-the-receiver-operator-curve and sensitivity-specificity analysis. We evaluated 88 ex-smoker participants with months follow-up data, 57 of whom (22 females/35 males, years) had negligible changes in and 31 participants (7 females/24 males, years) with worsening . In addition, 3/88 ex-smokers reported a change in smoking status. We generated machine-learning models to predict decline using demographics, spirometry, and texture features, with the later yielding the highest classification accuracy of 81%. The combined model (trained on all available measurements) achieved the overall best classification accuracy of 82%; however, it was not significantly different from the model trained on MRI texture features alone. For the first time, we have employed hyperpolarized MRI ventilation texture features and machine-learning to identify ex-smokers with accelerated decline in with 82% accuracy.

The 68th annual conference on magnetism and magnetic materials

The 2023 Conference on Magnetism and Magnetic Materials (MMM) was held from October 30–November 3 at the Dallas Hyatt Regency, at the base of the iconic Reunion Tower. There, 703 on-site attendees from 37 different countries discussed cutting-edge research in fundamental and applied magnetism, made new connections, and met old friends and colleagues at one of the first primarily in-person conferences in our field since the major disruptions of the pandemic era. The format of the conference was primarily in-person, with supporting online content that included recordings of the most popular programs and presentations, made available after the conference (including all symposia, the tutorial, and selected other special content). All presenters had the option to contribute online content, as did 96 participants who did not travel to the venue and elected to present virtual posters. Attendees enjoyed a vibrant celebration of the magnetism research community that included a Texas-sized welcome reception, tutorials on machine learning in magnetism, seven symposia, a lively exhibit hall that hosted poster sessions and bierstuben, a full roster of special events, coffee breaks to facilitate active scientific discussions, and of course, excellent technical presentations. These technical presentations, organized into 45 oral sessions, 23 in-person poster sessions, and 17 virtual poster sessions, were selected by a Program Committee of 57 members, capably coordinated by three Program Chairs: Hendrik Ohldag (ALS-LBNL), Karin Leistner (TU Chemnitz), and Takahiro Moriyama (Nagoya University). These three Program Chairs worked seamlessly and tirelessly over many months to make the central mission of MMM a huge success. The Program Committee selected seven symposia from nominations provided by the magnetism community: “Frontier Topics in Antiferromagnetism: Altermagnetism and Topology,” “Rare Earth Spintronics,” “Recent Advances in Cavity Magnonics,” “Emerging Topics in Magnetic Tunnel Junctions: Altermagnetism, Probabilistic Computing and Energy Efficient Switching,” “Orbitronics: From Orbital Currents Created by Charge Currents to Creation by Light or RF Excitation,” “Imaging Magnetic Textures at the Nanoscale,” and finally “Magnetization Dynamics in Two-Dimensional van der Waals Magnets.” These symposia highlighted a wide range of exciting new areas for magnetism, and were part of a total of 101 invited talks, 28% of which were presented by women. The contributed program was selected by the Program Committee from more than 900 submitted abstracts.

Indexing Topological Numbers on Images by Transferring Chiral Magnetic Textures

AbstractTopological analysis is widely adopted in various research fields to unveil intricate features and structural relationships implied in geometrical objects. Especially, in the fields of data analysis, exploring the topological properties of various images offers rich insights into the intrinsic geometrical information within them. In this study, a novel approach is proposed to investigate the topological properties of arbitrary grayscale images by employing a straightforward procedure used in 2D magnetism studies to calculate topological numbers. This method utilizes machine learning techniques to transfer chiral magnetic textures onto the images. Then, the topological number is then computed directly from the converted images by integrating the solid angles formed by adjacent spin vectors. The method successfully identifies the topological numbers of various grayscale images, showing stable performances against small noises. Furthermore, two applications of the method: are demonstrated topological analysis of the Modified National Institute of Standards and Technology (MNIST) dataset and the counting of blood cells in microscopic images.

Tunable spike-timing-dependent plasticity in magnetic skyrmion manipulation chambers

Magnetic skyrmions, as scalable and nonvolatile spin textures, can dynamically interact with fields and currents, making them promising for unconventional computing. This paper presents a neuromorphic device based on skyrmion manipulation chambers to implement spike-timing-dependent plasticity (STDP), a mechanism for unsupervised learning in brain-inspired computing. STDP adjusts synaptic weights based on the timing of pre-synaptic and post-synaptic spikes. The proposed three-chamber design encodes synaptic weight in the number of skyrmions in the center chamber, with left and right chambers for pre- and post-synaptic spikes, respectively. Micromagnetic simulations demonstrate that the timing between applied currents across the chambers controls the final skyrmion count (weight). The device exhibits adaptability and learning capabilities by manipulating chamber parameters, mimicking Hebbian and dendritic location-based plasticity. The device's ability to maintain state post-write highlights its potential for advancing adaptable neuromorphic devices.

Optimizing off-axis fields for two-axis magnetometry with point defects

Vector magnetometry is an essential tool for characterizing the distribution of currents and magnetization in a broad range of systems. Point defect sensors, like the nitrogen vacancy center in diamond, have demonstrated impressive sensitivity and spatial resolution for detecting these fields. Measuring the vector field at a single point in space using single defects, however, remains an outstanding challenge. We demonstrate that careful optimization of the static bias field can enable simultaneous measurement of multiple magnetic field components with enhanced sensitivity by leveraging the nonlinear Zeeman shift from transverse magnetic fields, realizing an improvement in transverse sensitivity from >200 μT/Hz (no bias field) to 30 μT/Hz. This work quantifies the trade-off between the increased frequency shift from second-order Zeeman effects with decreasing contrast as off-axis field components increase, demonstrating the measurement of multiple components of the magnetic field from an exemplar antiferromagnet with a complex magnetic texture.

Field-free transformations of topological spin textures in ferrimagnetic TbFeCo films

The generation of topological spin textures under ultrafast laser pulse excitations and field-free manipulation of topological transitions between different spin textures has attracted enormous interest from the perspective of spintronic applications. Here, we utilize ultrafast electron microscopy to showcase the femtosecond laser pulses excitation on magnetic materials and have generated multiple topological spin textures in an amorphous ferrimagnetic TbFeCo film. Furthermore, the following field-free topological transitions between skyrmions and bubbles with diversified topology are identified via in situ heating the sample in Lorentz transmission electron microscopy. The critical role of uniaxial anisotropy variation on changing the magnetic textures during the heating process is confirmed by micromagnetic simulations. Our results provide a perspective on the generation and transformation of topological spin textures.

Sym4state.jl: An efficient computation package for magnetic materials

Exploring magnetic configurations of magnets often involves utilizing the four-state method to obtain the magnetic interaction matrix, and Monte Carlo method to simulate spin textures and phase transition processes. However, computing the interaction matrix between magnetic atoms using the four-state method requires plenty of individual calculations. Despite manual simplifying the number of individual calculations based on material's symmetry is possible, there remains a necessity for an automated approach to streamline the process for high-throughput screening of magnetic materials. Meanwhile, the traditional sequential Monte Carlo simulation encounters challenges of low efficiency and long time consuming in dealing with large systems. Furthermore, the prior parallelism in the Heisenberg model was limited to parallel computation of the system's energy or run several replicas in parallel. Hence, in our pursuit of comprehensive parallelization for the Heisenberg model, we have introduced a novel adaptation of the checkerboard algorithm, enabling a fully parallelizable simulation of the Heisenberg model. To address these problems, we have developed Sym4state.jl, a program specifically designed to simplify the computation of magnetic interaction matrix and simulate spin textures under various environmental conditions. This program, available as a Julia package, can be freely accessed at https://github.com/A-LOST-WAPITI/Sym4state.jl. Program summaryProgram title: Sym4state.jlCPC Library link to program files:https://doi.org/10.17632/s6dkmgrjfw.1Developer's repository link:https://github.com/A-LOST-WAPITI/Sym4state.jlLicensing provisions: MITProgramming language: JuliaNature of problem: Employing the four-state method to calculate magnetic interaction matrix for magnetic materials can be simplified based on material symmetry, however, there is a lack of automated approach to streamline the simplification. Additionally, the commonly used Metropolis method for simulating magnetic texture can only make parallel computation of the system's energy or run several replicas in parallel, which could hardly boost the performance when simulating the large-scale magnetic textures.Solution method: We simplify the four-state method calculations by utilizing the principles of energy invariance under symmetry operations and time reversal operations. To enhance the efficiency of the Metropolis algorithm, we have designed a strategy to divide the entire 2D lattice into multiple domains. We then execute the Metropolis algorithm in parallel for each individual domain, thereby improving the overall computational efficiency.Additional comments including restrictions and unusual features: While the methods aimed at simplifying the four-state method and parallelizing the Metropolis algorithm are applicable to both 2D and 3D systems, the current program is specifically designed for the calculation and simulation of magnetism in 2D materials. As a result, compatibility with 3D systems has not yet been implemented.

Macroscopic tunneling probe of Moiré spin textures in twisted CrI3

Various noncollinear spin textures and magnetic phases have been predicted in twisted two-dimensional CrI3 due to competing ferromagnetic (FM) and antiferromagnetic (AFM) interlayer exchange from moiré stacking—with potential spintronic applications even when the underlying material possesses a negligible Dzyaloshinskii–Moriya or dipole–dipole interaction. Recent measurements have shown evidence of coexisting FM and AFM layer order in small-twist-angle CrI3 bilayers and double bilayers. Yet, the nature of the magnetic textures remains unresolved and possibilities for their manipulation and electrical readout are unexplored. Here, we use tunneling magnetoresistance to investigate the collective spin states of twisted double-bilayer CrI3 under both out-of-plane and in-plane magnetic fields together with detailed micromagnetic simulations of domain dynamics based on magnetic circular dichroism. Our results capture hysteretic and anisotropic field evolutions of the magnetic states and we further uncover two distinct non-volatile spin textures (out-of-plane and in-plane domains) at ≈1° twist angle, with a different global tunneling resistance that can be switched by magnetic field.

Plasmon-driven creation of magnetic topological structures

We demonstrate the creation and control of magnetic topological textures in thin film structures by plasmonic effects. From electromagnetic and photothermal models, the heat and absorption were determined, then the results were implemented in micromagnetic formalism to study the dynamics of magnetization under various conditions. The laser pulse duration and the contact area between nanoparticles and the magnetic layer are key parameters in the formation of topological textures. It is possible to generate a single skyrmion, multiple skyrmions, and skyrmioniums in the range of picoseconds. These results highlight the possibility of manipulating magnetic textures by using plasmonic effects, which presents significant opportunities for spintronics and non-conventional computer applications.

Machine learning inspired models for Hall effects in non-collinear magnets

The anomalous Hall effect has been front and center in solid state research and material science for over a century now, and the complex transport phenomena in nontrivial magnetic textures have gained an increasing amount of attention, both in theoretical and experimental studies. However, a clear path forward to capturing the influence of magnetization dynamics on anomalous Hall effect even in smallest frustrated magnets or spatially extended magnetic textures is still intensively sought after. In this work, we present an expansion of the anomalous Hall tensor into symmetrically invariant objects, encoding the magnetic configuration up to arbitrary power of spin. We show that these symmetric invariants can be utilized in conjunction with advanced regularization techniques in order to build models for the electric transport in magnetic textures which are, on one hand, complete with respect to the point group symmetry of the underlying lattice, and on the other hand, depend on a minimal number of order parameters only. Here, using a four-band tight-binding model on a honeycomb lattice, we demonstrate that the developed method can be used to address the importance and properties of higher-order contributions to transverse transport. The efficiency and breadth enabled by this method provides an ideal systematic approach to tackle the inherent complexity of response properties of noncollinear magnets, paving the way to the exploration of electric transport in intrinsically frustrated magnets as well as large-scale magnetic textures.

Anomalous Hall effect sensitive to magnetic monopoles and skyrmion helicity in spin–orbit coupled systems

Magnetic textures, such as skyrmions and domain walls, engender rich transport phenomena, including anomalous Hall effect and nonlinear response. In this work, we discuss an anomalous Hall effect proportional to the net magnetic monopole charge and dependent on the skyrmion helicity that occurs by a skew scattering in a noncentrosymmetric two-dimensional magnet. This mechanism, which arises from the spin–orbit interaction (SOI), gives rise to a finite anomalous Hall effect in a ferromagnetic domain wall whose spins rotate in the xy plane despite no out-of-plane magnetic moment. We show that the presence and absence of the monopole contribution is related to crystal symmetry, which gives a guideline for finding candidate materials beyond the Rashba model. The results demonstrate the rich features arising from the interplay of SOI and magnetic textures, and their potential for detecting various magnetic textures in micrometer devices.