arXiv subjects

Andrea Meo

Publications and source records attributed to Andrea Meo.

17 recordsLinked to original sources

arXiv2026

A magneto-mechanical gyroscope with spintronic readout

Gyroscopes are essential elements in navigation, consumer electronics, robotics, and aerospace applications. Most micro electro-mechanical systems (MEMS) implementations rely on capacitive sensing mechanisms, which limit the dimensional scaling to the micrometer scale. In this work, we introduce a MEMS-like two-degree-of-freedom (2-DOF) gyroscope that exploits the rectification functionality of magnetic tunnel junctions (MTJs) as its readout mechanism and as the transducer of the mechanical dynamics. Experimentally characterized MTJs have been used to calibrate and perform an experiment-informed design of the magneto-mechanical model combining micromagnetic theory with 2-DOF mechanical equations. We demonstrated that the output is linear with angular rate, and that the proposed device is able to extract the angular rate in dynamic cases exploiting a homodyne demodulation approach. The results open a path towards a compact, complementary metal-oxide semiconductor (CMOS)-compatible readout pathway that relaxes reliance on tight capacitive gaps and motivates multi-physics designs of the device.

cond-mat.mes-hall↗

arXiv2026

Beyond conventional skyrmions in synthetic antiferromagnets

Magnetic skyrmions are topologically protected spin textures that can act as reconfigurable nanoscale information carriers. In synthetic antiferromagnets (SAFs), interlayer exchange coupling offers an additional control parameter beyond the interfacial Dzyaloshinskii-Moriya interaction (DMI) and magnetic anisotropy. Here, we engineer a SAF composed of two chemically distinct ferromagnets (CoB and CoFeB), in which the external magnetic field and interlayer exchange act asymmetrically on the sublattices. The competition of these effects, acting as a resultant effective-field, gives rise to two distinct skyrmion families in different field regimes. In large fields, conventional-polarity skyrmions nucleate, with core antiparallel to the external field, whereas in smaller fields an inverse-polarity skyrmion state emerges as the effective-field reverses sign and almost saturates the CoFeB layers. Return-point memory measurements confirm independent nucleation pathways for the two families. Using element-resolved x-ray magnetometry, correlative magnetic force and Lorentz transmission electron microscopies, and parameter-matched micromagnetic modelling, we show that all textures reside only in the CoFeB layers, which experience a Ruderman-Kittel-Kasuya-Yosida (RKKY) exchange field originating from the CoB layers. This effective-field method provides a robust route to programmable three-dimensional spin textures with controlled polarity in selected layers of a multilayer with potential for applications in skyrmion-based computing and spin-logic architectures.

cond-mat.mes-hall↗

arXiv2026

Laser-written reconfigurable energy landscapes and programmable Moir\'e spin textures

Magnetic textures are central to emerging spintronic and unconventional computing technologies due to their rich dynamics, topological properties and nanoscale dimensions. A major challenge remains achieving tunable, reversible, and spatially resolved control over these textures and their evolution as a function of external stimuli, by spatially reprogramming the magnetic energy landscape that governs their nucleation and stability. Here, we exploit a focused laser-assisted local field cooling technique that establishes a fast, non-contact and scalable platform for grayscale spin texture engineering. By non-destructively controlling the exchange-bias anisotropy with nanoscale resolution in thin-film heterostructures, this approach enables grayscale, reprogrammable control of the local energy profile, which we use to create magnetic patterns with highly controlled hysteresis, field-dependent readability and tunable switching thresholds. Leveraging this capability, we demonstrate information encoding with magnetic field-gated readability, and artificial spin metamaterials, stabilizing spin lattices with field-reconfigurable symmetries and creating artificial Moir\'e spin textures via the geometric superposition of twisted magnetic potentials. These results establish a versatile, reprogrammable platform that bridges the gap between application-oriented magnetic memory and fundamental studies of emergent order in artificial lattices.

cond-mat.mtrl-sci↗

arXiv2026

Data-Driven Estimation of the interfacial Dzyaloshinskii-Moriya Interaction with Machine Learning

Machine learning offers powerful tools to support experimental techniques, particularly for extracting latent features from large datasets. In magnetic materials, accurately estimating the interfacial Dzyaloshinskii-Moriya interaction strength remains challenging, as existing experimental methods often rely on indirect measurements and can yield inconsistent results across techniques. Because this interaction is often extracted experimentally from bubble domain expansion, we investigate whether bubble textures alone contain sufficient and reliable information for data driven DMI inference. We therefore develop a compact convolutional neural network trained on a comprehensive micromagnetic dataset of magnetic bubble domains designed to emulate magneto optical Kerr effect imaging, including structural non uniformity, additive noise, and image pixelation. The proposed network demonstrates strong robustness against sample inhomogeneities, noise, and reduced spatial resolution. Furthermore, it exhibits reliable generalization by accurately predicting DMI values outside the trained interval. These results support the use of machine learning as a fast and quantitative tool to characterize magnetic textures with interfacial DMI.

cond-mat.mtrl-sci↗

arXiv2026

Magneto-mechanical reservoir computing combining a two-dimensional network of nonlinear mass-spring resonators with magnetic tunnel junctions

Coupled networks of mass-spring resonators have attracted growing attention across multiple fundamental and applied research directions, including reservoir computing for artificial intelligence. This has led to the exploration of platforms capable of tasks such as acoustic-wave classification, smart sensing, predictive maintenance, and adaptive vibration control. This work introduces a multiphysics reservoir based on a two-dimensional network of coupled nonlinear mass-spring resonators. Each mass has a magnetic tunnel junction on top of it, working as spin diode, used as a spintronic read-out. As a proof-of-concept, we have benchmarked this reservoir with the task of vowel-recognition reaching accuracy above 95$\%$. Because the device accepts elastic excitations directly, signal injections are simplified, making it well-suited for realtime sensing and edge computation. We also studied the effect of nonlinearity, demonstrating how it influences the reservoir dynamics, and assessed its robustness under node-to-node variation of the elastic constants.

cond-mat.mes-hall↗

arXiv2025

Octupole-driven spin torque switching of antiferromagnetic tunnel junctions

Magnetic tunnel junctions (MTJs) based on ferromagnets are canonical devices in spintronics, with wide-ranging applications in data storage, computing, and sensing. They simultaneously exhibit mechanisms for electrical detection and control of magnetic order through the tunneling magnetoresistance (TMR) and spin-transfer torque (STT) effects, respectively. It was long assumed that neither of these effects could be sizeable in all-antiferromagnetic tunnel junctions (AATJs), since they exhibit no net magnetization. Recently, however, it was shown that AATJs based on chiral antiferromagnets do exhibit TMR due to their non-relativistic momentum-dependent spin polarization and cluster magnetic octupole moment (CMO), which are manifestations of their spin-split band structure. However, the reciprocal effect, i.e., the antiferromagnetic counterpart of STT, has been assumed non-existent due to the total electric current being spin-neutral. Here, we report nanoscale AATJs exhibiting this reciprocal effect, which we term octupole-driven spin-transfer torque (OTT). We demonstrate current-induced OTT switching of PtMn3|MgO|PtMn3 AATJs, exhibiting a TMR value of 363% at room temperature and switching current densities of the order of 10 MA/cm2. Our theoretical modeling explains the origin of OTT in terms of the imbalance between intra- and inter-sublattice spin currents across the AATJ, and equivalently, in terms of the non-zero net cluster octupole polarization of each PtMn3 layer. This work establishes a new materials platform for antiferromagnetic spintronics and provides a pathway towards deeply scaled magnetic memory and room-temperature terahertz technologies.

cond-mat.mtrl-sci↗

arXiv2025

Spintronic temperature nanosensor based on the resonance response of a skyrmion-hosting magnetic tunnel junction

The increasing need for efficient thermal management in nanoelectronics requires innovative thermal sensing solutions, as conventional sensors often exhibit nonlinear responses, low sensitivity, and complex calibration. We predict a temperature dependence in the response of existing skyrmion based spintronic diodes and propose their use as nanoscale thermal sensors. These devices leverage magnetic skyrmions topologically protected spin textures known for their robustness, nanoscale dimensions, and low power dynamics. We demonstrate high thermal sensitivity with a linear temperature response over a wide range. This linearity, observed in both the amplitude and frequency of the skyrmion excitation, ensures redundancy that enables precise and reliable temperature measurement. In addition, the use of multilayer systems enhances the sensitivity and robustness of the device. These results provide a foundation for skyrmion-based caloritronic devices with promising applications in spintronic sensors, thermal management, nanoelectronics, and skyrmion-caloritronics.

cond-mat.mes-hall↗

arXiv2025

Spin wave eigenmodes in nanoscale magnetic tunnel junctions with perpendicular magnetic anisotropy

Magnetic tunnel junctions (MTJs) are key enablers of spintronic technologies used in a variety of applications including information storage, microwave generation and detection, as well as unconventional computing. Here, we present experimental and theoretical studies of quantized spin wave eigenmodes in perpendicular MTJs focusing on a coupled magnetization dynamics in the free (FL) and reference (RL) layers of the MTJ, where the RL is a synthetic antiferromagnet (SAF). Spin-torque ferromagnetic resonance (ST-FMR) measurements reveal excitation of two spin wave eigenmodes in response to applied microwave current. These modes show opposite frequency shifts as a function of out-of-plane magnetic field. Our micromagnetic simulations accurately reproduce the dependence of the mode frequencies on magnetic field and reveal the spatial profiles of the excitations in the FL and RL. The FL and RL modes generate rectified voltage signals of opposite polarity, which makes this device a promising candidate for a tunable dual-frequency microwave signal detector. The simulations show that weak interlayer exchange coupling within the SAF enhances the mode amplitudes. We also calculate the response of the detector as a function of in-plane magnetic field bias and find that its sensitivity significantly increases with increasing field. We experimentally confirm this prediction via ST-FMR measurements as a function of in-plane magnetic field. Our results provide deeper understanding of quantized spin wave eigenmodes in nanoscale MTJs with perpendicular magnetic anisotropy and demonstrate the potential of these devices for frequency-selective dual-channel microwave signal detectors.

cond-mat.mes-hall↗

arXiv2025

Skyrmions in Nanotechnology: Fundamental Properties, Experimental Advances, and Emerging Applications

Skyrmions, topologically protected textures, have been observed in different fields of nanotechnology and have emerged as promising candidates for different applications due to their topological stability, low-power operation, and dynamic response to external stimuli. First introduced in particle physics, skyrmions have since been observed in different condensed matter fields, including magnetism, ferroelectricity, photonics, and acoustics. Their unique topological properties enable robust manipulation and detection, paving the way for innovative applications in room temperature sensing, storage, and computing. Recent advances in materials engineering and device integration have demonstrated several strategies for an efficient manipulation of skyrmions, addressing key challenges in their practical implementation. In this review, we summarize the state-of-the-art research on skyrmions across different platforms, highlighting their fundamental properties and characteristics, recent experimental breakthroughs, and technological potential. We present future perspectives and remaining challenges, emphasizing the interdisciplinary impact of skyrmions on nanotechnology.

cond-mat.mes-hall↗

arXiv2023

A magneto-mechanical accelerometer based on magnetic tunnel junctions

Accelerometers have widespread applications and are an essential component in many areas such as automotive, consumer electronics and industrial applications. Most commercial accelerometers are based on micro-electromechanical system (MEMS) that are limited in downscaling and power consumption. Spintronics-based accelerometers have been proposed as alternatives, however, current proposals suffer from design limitations that result in reliability issues and high cost. Here we propose spintronic accelerometers with magnetic tunnel junctions (MTJs) as building block, which map accelerations into a measurable voltage across the MTJ terminals. The device exploits elastic and dipolar coupling as a sensing mechanism and the spintronic diode effect for the direct read out of the acceleration. The proposed technology represents a potentially competitive and scalable solution to current capacitive MEMS-based approaches that could lead to a step forward in many of the commercial applications.

physics.app-ph↗

arXiv2022

Spin-transfer and spin-orbit torques in the Landau-Lifshitz-Gilbert equation

Dynamic simulations of spin-transfer and spin-orbit torques are increasingly important for a wide range of spintronic devices including magnetic random access memory, spin-torque nano-oscillators and electrical switching of antiferromagnets. Here we present a computationally efficient method for the implementation of spin-transfer and spin-orbit torques within the Landau-Lifshitz-Gilbert equation used in micromagnetic and atomistic simulations. We consolidate and simplify the varying terminology of different kinds of torques into a physical action and physical origin that clearly shows the common action of spin torques while separating their different physical origins. Our formalism introduces the spin torque as an effective magnetic field, greatly simplifying the numerical implementation and aiding the interpretation of results. The strength of the effective spin torque field unifies the action of the spin torque and subsumes the details of experimental effects such as interface resistance and spin Hall angle into a simple transferable number between numerical simulations. We present a series of numerical tests demonstrating the mechanics of generalised spin torques in a range of spintronic devices. This revised approach to modelling spin-torque effects in numerical simulations enables faster simulations and a more direct way of interpreting the results, and thus it is also suitable to be used in direct comparisons with experimental measurements or in a modelling tool that takes experimental values as input.

physics.comp-ph↗

arXiv2022

Models of Advance Recording Systems: A Multi-timescale Micromagnetic code for granular thin film magnetic recording systems

Micromagnetic modelling provides the ability to simulate large magnetic systems accurately without the computational cost limitation imposed by atomistic modelling. Through micromagnetic modelling it is possible to simulate systems consisting of thousands of grains over a time range of nanoseconds to years, depending upon the solver used. Here we present the creation and release of an open-source multi-timescale micromagnetic code combining three key solvers: Landau-Lifshitz-Gilbert; Landau-Lifshitz-Bloch; Kinetic Monte Carlo. This code, called MARS (Models of Advanced Recording Systems), is capable of accurately simulating the magnetisation dynamics in large and structurally complex single- and multi-layered granular systems. The short timescale simulations are achieved for systems far from and close to the Curie point via the implemented Landau-Lifshitz-Gilbert and Landau-Lifshitz-Bloch solvers respectively. This enables read/write simulations for general perpendicular magnetic recording and also state of the art heat assisted magnetic recording (HAMR). The long timescale behaviour is simulated via the Kinetic Monte Carlo solver, enabling investigations into signal-to-noise ratio and data longevity. The combination of these solvers opens up the possibility of multi-timescale simulations within a single software package. For example the entire HAMR process from initial data writing and data read back to long term data storage is possible via a single simulation using MARS. The use of atomistic parameterisation for the material input of MARS enables highly accurate material descriptions which provide a bridge between atomistic simulation and real world experimentation. Thus MARS is capable of performing simulations for all aspects of recording media research and development. This ranges from material characterisation and optimisation to system design and implementation.

physics.comp-ph↗

arXiv2020

Magnetisation dynamics of granular HAMR media by means of a multiscale model

Heat assisted magnetic recording (HAMR) technology represents the most promising candidate to replace the current perpendicular recording paradigm to achieve higher storage densities. To better understand HAMR dynamics in granular media we need to describe accurately the magnetisation dynamics up to temperatures close to the Curie point. To this end we propose a multiscale approach based on the micromagnetic Landau-Lifshitz-Bloch (LLB) equation of motion parametrised using atomistic calculations. The LLB formalism describes the magnetisation dynamics at finite temperature and allows to efficiently simulate large system sizes and long time scales. Atomistic simulations provide the required temperature dependent input quantities for the LLB equation, such as the equilibrium magnetisation and the anisotropy, and can be used to capture the detailed magnetisation dynamics. The multiscale approach makes possible to overcome the computational limitations of atomistic models in dealing with large systems, such as a recording track, while incorporating the basic physics of the HAMR process. We investigate the magnetisation dynamics of a single FePt grain as function of the properties of the temperature profile and applied field and test the micromagnetic results against atomistic calculations. Our results prove the appropriateness and potential of the approach proposed here where the granular model is able to reproduce the atomistic simulations and capture the main properties of a HAMR medium.

cond-mat.mtrl-sci↗

arXiv2019

Atomistic investigation of the temperature and size dependence of the energy barrier of CoFeB/MgO nanodots

The balance between low power consumption and high efficiency in memory devices is a major limiting factor in the development of new technologies. Magnetic random access memories (MRAM) based on CoFeB/MgO magnetic tunnel junctions (MTJs) have been proposed as candidates to replace the current technology due to their non-volatility, high thermal stability and efficient operational performance. Understanding the size and temperature dependence of the energy barrier and the nature of the transition mechanism across the barrier between stable configurations is a key issue in the development of MRAM. Here we use an atomistic spin model to study the energy barrier to reversal in CoFeB/MgO nanodots to determine the effects of size, temperature and external field. We find that for practical device sizes in the 10-50 nm range the energy barrier has a complex behaviour characteristic of a transition from a coherent to domain wall driven reversal process. Such a transition region is not accessible to simple analytical estimates of the energy barrier preventing a unique theoretical calculation of the thermal stability. The atomistic simulations of the energy barrier give good agreement with experimental measurements for similar systems which are at the state of the art and can provide guidance to experiments identifying suitable materials and MTJ stacks with the desired thermal stability.

cond-mat.mtrl-sci↗

arXiv2019

Magnetic stray fields in nanoscale magnetic tunnel junctions

The magnetic stray field is an unavoidable consequence of ferromagnetic devices and sensors leading to a natural asymmetry in magnetic properties. Such asymmetry is particularly undesirable for magnetic random access memory applications where the free layer can exhibit bias. Using atomistic dipole-dipole calculations we numerically simulate the stray magnetic field emanating from the magnetic layers of a magnetic memory device with different geometries. We find that edge effects dominate the overall stray magnetic field in patterned devices and that a conventional synthetic antiferromagnet structure is only partially able to compensate the field at the free layer position. A granular reference layer is seen to provide near-field flux closure while additional patterning defects add significant complexity to the stray field in nanoscale devices. Finally we find that the stray field from a nanoscale antiferromagnet is surprisingly non-zero arising from the imperfect cancellation of magnetic sublattices due to edge defects. Our findings provide an outline of the role of different layer structures and defects in the effective stray magnetic field in nanoscale magnetic random access memory devices and atomistic calculations provide a useful tools to study the stray field effects arising from a wide range of defects.

cond-mat.mtrl-sci↗

arXiv2019

The role of faceting and elongation on the magnetic anisotropy of magnetite Fe3O4 nanocrystals

Fe3O4 nanoparticles are one of the most promising candidates for biomedical applications such as magnetic hyperthermia and theranostics due to their bio-compatibility, structural stability and good magnetic properties. However, much is unknown about the nanoscale origins of the observed magnetic properties of particles due to the dominance of surface and finite size effects. Here we have developed an atomistic spin model of elongated magnetite nanocrystals to specifically address the role of faceting and elongation on the magnetic shape anisotropy. We find that for faceted particles simple analytical formulae overestimate the magnetic shape anisotropy and that the underlying cubic anisotropy makes a significant contribution to the energy barrier for moderately elongated particles. Our results enable a better estimation of the effective magnetic anisotropy of highly crystalline magnetite nanoparticles and is a step towards quantitative prediction of the heating effects of magnetic nanoparticles.

cond-mat.mes-hall↗

arXiv2017

Thermally nucleated magnetic reversal in CoFeB/MgO nanodots

Power consumption is the main limitation in the development of new high performance random access memory for portable electronic devices. Magnetic RAM (MRAM) with CoFeB/MgO based magnetic tunnel junctions (MTJs) is a promising candidate for reducing the power consumption given its non-volatile nature while achieveing high performance. The dynamic properties and switching mechanisms of MTJs are critical to understanding device operation and to enable scaling of devices below 30 nm in diameter. Here we show that the magnetic reversal mechanism is incoherent and that the switching is thermally nucleated at device operating temperatures. Moreover, we find an intrinsic thermal switching field distribution arising on the sub-nanosecond timescale even in the absence of size and anisotropy distributions or material defects. These features represent the characteristic signature of the dynamic properties in MTJs and give an intrinsic limit to reversal reliability in small magnetic nanodevices.

cond-mat.mtrl-sci↗