Naëmi Leo

Bloch points are three-dimensional topological singularities in magnetization that play a key role in topological transformations of spin textures such as skyrmion creation or annihilation. While topology often enforces the existence of Bloch points in confined geometries such as cylindrical nanowires, deterministic control over their position and magnetic configuration remains challenging. Here, we demonstrate the generation of Bloch points with controlled spin texture by engineering geometrical boundary conditions in three-dimensional nanomagnets. By introducing a chirality interface between two three-dimensional double-helix nanowires of opposite handedness, forming a kinked, noncollinear structure, we impose competing topological constraints that uniquely define the magnetization configuration surrounding the Bloch point. A saturating magnetic field nucleates head-to-head or tail-to-tail domain configurations at the chirality interface, producing a Bloch-point domain wall with deterministic polarity, circulation, and helicity. This geometrical approach enables full three-dimensional control of Bloch point domain walls, allowing deterministic engineering of their spin texture and its selective coupling to current-induced Oersted fields.

Magnetoelectric multiferroics promise direct cross control between coexisting ferroelectric and ferromagnetic orders, which is of interest for applications in magnetism and spintronics. A particularly interesting type of cross control is found in spin-spiral multiferroic Mn 2 GeO 4 , in which a ferroelectric multidomain distribution can be globally inverted by a single magnetic field sweep. In this work we show that this repeatable response is not obtained immediately after entering the multiferroic phase via zero-field coolling. Instead, an initial metastable multidomain state forms in which polarization, magnetization, and antiferromagnetic order do not yet minimize the trilinear magnetoelectric coupling. Using optical second-harmonic generation for ferroelectric domain imaging, we demonstrate that a single field cycle deterministically drives the system from the initial metastable state into an equilibrium domain configuration that shows repeatable domain interconversion. This initialization behavior originates from a deterministic pathway from metastable to equilibrium domain patterns, in contrast to the more common—and less reliable—stochastic domain “training” procedures that require repeated field cycles. Understanding the initial domain evolution thus enables reliable cross control in magnetoelectric devices with highly interlinked order parameters.

High-resolution imaging of magnetic nanostructures is essential for understanding fundamental spin phenomena and designing advanced devices. Recent developments in three-dimensional (3D) nanomagnetism have highlighted the growing need for imaging techniques that can capture magnetic structures across curved or tilted surfaces with high sensitivity. Though widely used as a powerful technique for imaging magnetization states, conventional magneto-optical Kerr effect (MOKE) microscopy faces inherent limitations in measuring nonplanar systems due to its shallow depth of field (DOF). Here, we present an extended depth-of-field MOKE imaging approach, combining through-focus scanning with image-stitching-based reconstruction, to obtain sharp and well-resolved magnetic domain images across nonplanar sample geometries. The method is validated on both perpendicularly and in-plane magnetized films tilted on purpose for this study, enabling quantitative analysis of domain morphology and detection sensitivity. This laboratory-accessible technique provides a fast and versatile route for 3D magnetic imaging, complementing large-scale x-ray-based methods and offering a practical tool for investigating nonplanar magnetic samples with tilted or curved 3D geometries.

Double-helix (DH) nanowires provide a platform to study the influence of geometric chirality on spin chirality. Their three-dimensional (3D) helical architecture and tunable inter-strand coupling enable control of spin chirality, including the stabilization of topological 3D magnetic states such as helical domains and domain walls, topological stray fields, and extended helical vortex/skyrmion tubes. So far, the study of these and other 3D nanostructures is usually confined to a limited number of magnetic microscopy experiments in large facilities. Here, we investigate the reversal mechanism of a single DH nanowire using dark-field magneto-optical Kerr effect (DF-MOKE) magnetometry under external 3D magnetic fields. By analyzing the angular dependence of the DF-MOKE signal, we fit the reversal process using established models for domain-wall nucleation and propagation, finding a characteristic behavior similar to that reported for cylindrical nanowires. Micromagnetic simulations indicate that the reversal process goes through nucleation of the helical vortex tube in a curling manner, while ptychographic x-ray magnetic circular dichroism data reveal that this helical vortex tube state forms through a mixed nucleation-propagation process. These observations provide a consistent microscopic picture of reversal mediated by a helical vortex tube extending along the nanowire. Our work provides a comprehensive characterization of magnetization reversal in DH nanowires and demonstrates that DF-MOKE magnetometry is effective for probing reversal mechanisms in single 3D nanostructures. This lab-based approach expands the range of accessible experiments beyond large-scale facilities, enabling extensive exploration of the rich spin states supported by 3D nano-geometries.

X-ray photon correlation scattering measurements are undertaken on a thermally active artificial spin ice based on the square lattice, referred to as artificial square ice, to probe the fluctuation timescales as a function of temperature as the system passes through the paramagnetic-antiferromagnetic phase transition, which belongs to the two-dimensional Ising universality class. In the paramagnetic regime, a single exponential timescale is seen, whereas at and below the critical temperature, a stretched exponential decorrelation is observed, with the stretching exponent decreasing from unity down to below one-half as the temperature reduces. This trend is confirmed by kinetic Monte Carlo simulations of a simplified point-dipolar square ice system, and is in agreement with past theoretical work on the kinetic Ising model where stretched exponential relaxation due to equilibrium domain wall dynamics below the critical temperature was found.

Multidomain states of square artificial spin ice show a range of different morphologies ranging from simple stripelike domains to more organically shaped coral domains. To model the relevant dynamics leading to the emergence of such diverse domain structures, simplified descriptions of the switching behavior of individual nanomagnets are necessary. In this work, we employ kinetic Monte Carlo simulations of the demagnetization of square artificial spin ice toward its ground state and compare how the choice of transition barriers affect the emergence of mesoscale domains. We find that the commonly used mean-field barrier model (informed by equilibrium energetics only) results in propagation of ground-state string avalanches. In contrast, taking into account chiral barrier splitting enabled by state-dependent local torques supports the emergence of complex-shaped coral domains and their successful relaxation towards the ground state in later relaxation stages. Our results highlight that intrinsic contributions to switching barriers, in addition to the effect of extrinsic defects often attributed to nanofabrication irregularities, can subtly shift favored transition pathways and result in different emergent mesoscale features. Future kinetic Monte Carlo models that describe the evolution of artificial spin systems should thus account for these effects.

The spin–orbit field and interfacial exchange field (IEF) are two major interface phenomena, and the detection and manipulation of these fields can enable a variety of nanoscale spintronics devices. Optimizing the IEF, which governs the spin-dependent scattering asymmetry at (ferromagnetic insulator)|(normal metal) interfaces, will pave the way for next-generation nanoscale, low-power insulator spintronics devices. Here, we demonstrate an experimental pathway to detect an IEF between insulating ferromagnet EuS and non-magnetic Cu using magnetoresistance (MR) measurements, and show that the spin-dependent scattering at the common interface can lead to a significant current-in-plane MR in Py | Cu | EuS trilayer Hall-bar device. Our experiment suggests that simple magnetoresistance measurements can be used to experimentally detect the IEF and thereby the magnetic state of a ferromagnetic insulator.

In operando techniques enable real-time measurement of intricate physical properties at the micro- and nano-scale under external stimuli, allowing the study of a wide range of materials and functionalities. In nanomagnetism, in operando techniques greatly benefit from precise three-dimensional (3D) magnetic field control, enabling access to complex magnetic states forming in systems where multiple energies are set to compete with each other. However, achieving such precision is challenging and uncommon, as specific applications impose constraints on the type and geometry of magnetic field sources, limiting their capabilities. Here, we introduce an approach that leverages machine learning algorithms to achieve precise 3D magnetic field control using a hexapole electromagnet that is composed of three independent, non-collinear dipole electromagnets. In our experimental setup, magnetic field sensors are placed at a distance from the sample position due to inherent constraints, leading to indirect field measurements that differ from the magnetic field experienced by the sample. We find that the existing relationship between the remote and sample frames of reference is non-linear, thus requiring a more complex calibration method. To address this, we employ a multi-layer perceptron neural network that processes multiple inputs from a dynamic magnetic field sequence, effectively capturing the time-dependent non-linear field response. The network achieves high calibration accuracy and demonstrates exceptional generalization to unseen magnetic field sequences. This study highlights the significant potential of machine learning in achieving high-precision control and calibration, crucial for in operando experiments where direct measurement at the point of interest is not possible.

In this study, we demonstrate an enhancement of the measured spin Seebeck coefficient in Fe3O4/Pt bilayer films due to an increase in Fe nanodroplets formed by pulsed laser deposition. Four bilayer films were deposited at the same time from a highly textured target, resulting in a general increase in droplet formation that was confirmed to be Fe rich by scanning electron microscope and transmission electron microscope-dispersive x-ray spectroscopy. Of these four films, there were two distinct groupings with differing density of α-Fe droplets, where the bilayer with higher droplet density exhibited a 64% increase in the measured spin Seebeck coefficient from 38 to 63 nV m/W.

Magnetotoroidal order, also called ferrotoroidicity, is the most recently established type of ferroic state. It is based on a spontaneous and uniform alignment of unit-cell-sized magnetic whirls, called magnetotoroidal moments, associated with a macroscopic toroidization. Because of its intrinsic linear magnetoelectric coupling, this new ferroic state could be useful in the development of spintronic devices. We exploit two-dimensional periodic arrays of magnetostatically coupled nanomagnets as model systems for the investigation of long-range magnetotoroidal order. We present two pathways promoting this order, namely, (i) structures comprising a ring of uniformly magnetized sub-micrometer-sized bar magnets and (ii) structures in which each magnetic building block itself hosts a magnetic vortex. For both cases, calculations of the magnetic-dipole interaction and micromagnetic simulations reveal the conditions for the formation of spontaneous magnetotoroidal order. We confirm this order and the formation of magnetotoroidal domains in our arrays with magnetic force microscopy. We identify the presence of two types of domain-wall states emerging from the competition of two intrinsic microscopic couplings. Our work not only identifies the microscopic conditions promoting spontaneous magnetotoroidal order but also highlights the possibility to tailor mesoscale magnetic arrays toward elusive types of ferroic order.