This PDF file contains the front matter associated with SPIE Proceedings Volume 12656, including the Title Page, Copyright information, Table of Contents and Conference Committee list.

The development of modern spintronics materials ushered the need for novel characterization tools capable of characterizing nanometer-sized spin textures. Neutrons are a convenient probe for this task due to their angstrom-sized wavelengths, electric neutrality and robustly controllable spin state. Recent research has focused on enabling access to new degrees of freedom in order to provide a neutron toolbox capable of characterizing emerging materials. This includes the development of tomography techniques for characterizing the 3D bulk spin textures and the techniques for creating neutron helical and skyrmion-like spin-orbit states. Here we provide a concise overview of this work and discuss future prospects and applications.

A plane, monochromatic electromagnetic wave propagating in free space can have a certain amount of spin angular momentum but cannot possess any orbital angular momentum. Even the spin angular momentum of the plane-wave is difficult to evaluate without resort to certain mathematical limit arguments. Both spin and orbital angular momenta can be computed for a wavepacket of finite duration and finite cross-sectional area using standard methods of classical electrodynamics. Extending these results to finite wavepackets in quantum electrodynamics requires subtle arguments in conjunction with the multimodal structure of the wavepacket. This paper presents some of the nuances of classical as well as quantum-optical methods for analyzing the spin and orbital angular momenta of electromagnetic waves.

Magnetic thin films are proposed for a range of spintronic and other applications. While exploring so-called magnetic “dead layers” in La_0.7Sr_0.3MnO₃ thin films, we detect a magnetic phase competition between two types of magnetic order. This competition leads to spontaneous magnetization reversal, which had not previously been observed in epitaxial thin films. This effect allows switching the magnetization direction with very small applied magnetic fields, which could significantly benefit spintronic and other applications.

Van der Waals ferromagnets are an intersting class of materials for exploring fundamental physics of magnetic order in the 2D limit as well as for technological applicaitons due to possibility of creating novel heterostructures. These materials have shown to host magnetic skyrmion lattices with their organization controlled by the magnetic properties such as anisotropy, exchange, and Dzyaloshinkii-Moriya interaction. For technological applications, it is also necessary to understand to the behavior of skyrmions in response to electric currents. In this work, we show the effect of electric current pulses on the magnetic skyrmions formed in Fe3GeTe2which has a Curie temperature of 220 K. We demonstrate via real-space in situ imaging using Lorentz transmission electron microscopy (LTEM) the effect of temperture and pulse width.

Josephson elements are cornerstones of cryogenic classical and quantum superconducting technology, owing to their nonlinearity. Two important types of Josephson elements are often considered distinct: the tunnel junction (superconductor-insulator-superconductor, SIS) and the normal weak link (superconductor-normalsuperconductor, SNS) referring to any non-superconducting and non-insulating central region. SNS junctions and SIS junctions have appeared in related technological and basic science contexts over the last decade. In this perspective article, we review correspondences between SISIS junctions and SNS junctions in limiting regimes, in which a single, general energy-phase relationship describes the systems. We show how this insight helped to connect recent bodies of theoretical and experimental work in both systems. We conclude by describing a few important differences that also impact their use in applied contexts.

An overview of xMR (GMR and TMR) technology capabilities for sensing angular and linear magnetic fields is given and a comparison to Hall and AMR technologies is made to illustrate how xMR technologies improve sensor performances and flexibility of use, making them the best possible choice in many applications, including those with stringent conditions of operation such as automotive. Examples are given including speed, angular, and current sensors, and new opportunities offered by the technology are discussed.

While most ultrafast time-resolved optical pump-probe experiments in magnetic materials reveal the spatially homogeneous magnetization dynamics of ferromagnetic resonance (FMR), here we explore the magneto-elastic generation of GHz-to-THz frequency spin waves (exchange magnons). Using analytical magnon oscillator equations, we apply time-domain and frequency-domain approaches to quantify the results of ultrafast time-resolved optical pump-probe experiments in free-standing ferromagnetic thin films. Simulations show excellent agreement with the experiment, provide acoustic and magnetic (Gilbert) damping constants and highlight the role of symmetry-based selection rules in phonon-magnon interactions. The analysis is extended to hybrid multilayer structures to explore the limits of resonant phonon-magnon interactions up to THz frequencies.

Advances in machine learning and artificial intelligence on various cognitive tasks, including computer vision and natural language processing, have been accompanied by a surge in hardware development to meet the high computational requirements. However, machine intelligence processed in conventional von-Neumann architectures are still orders of magnitude more inefficient than the biological brain. Moreover, building energy-efficient ML hardware accelerators for edge applications faces further challenges, due to constraints of power budget and on-chip memory. Hence, fundamentally new approaches are needed to sustain a continuous growth in the performance of computers beyond the end of CMOS technology roadmap. In order to achieve a better match between the hardware primitives and computational models, exploring new paradigms of computing necessitates a multi-disciplinary endeavor across the stack consisting of devices, circuits, hardware architectures, and learning algorithms. Specifically, such holistic endeavors will involve exploration of novel learning algorithms inspired by bio-plausible principles, design of hardware architectures best suited for data-intensive machine learning models, together with the creation and integration of novel device technologies (such as spintronic devices) that can efficiently mimic neuronal/synaptic operations in biological brains. In this talk, I will discuss our recent exploration of exploiting spintronic devices for emerging computing paradigms such as analog in-memory computing, systolic array, and neuromorphic computing in pursuit of robust and efficient ML hardware. I will first present sparsity-aware device circuit co-design of spin-orbit-torque MRAM for robust crossbar-based ML inference engine. Significant energy improvement with near-software accuracy is demonstrated leveraging robust crossbar arrays with low precision analog-to-digital conversion. We further investigate technology selection among various emerging non-volatile memory under realistic area budgets, and identified the scenarios where spin-orbit-torque MRAM may have advantages in the hardware performance compared to non-volatile memory. Moreover, towards the development of bio-plausible neuromorphic hardware I will introduce a multi-granular spintronic device that can mimic a leaky integrate-and-fire spiking neuron with compact footprints and high energy efficiency. Incorporation of such neuronal devices into the training of a deep convolution spiking neural network for image classification demonstrates improved robustness against various types of noise injection. We conclude with a brief discussion on potential opportunities and directions for future work.

Due to their interesting physical properties, myriad operational regimes, small size, and industrial fabrication maturity, magnetic tunnel junctions are uniquely suited for unlocking novel computing schemes for in-hardware neuromorphic computing. In this paper, we focus on the stochastic response of magnetic tunnel junctions, illustrating three different ways in which the probabilistic response of a device can be used to achieve useful neuromorphic computing power.

One of the most striking features of superconductors without inversion symmetry is the possibility of “helical” nonuniform superconducting states in the presence of a magnetic field or even without any field. Their origin can be traced to the first-order gradient terms in the Ginzburg-Landau energy, known as the Lifshitz invariants. I will review the microscopic mechanisms leading to these terms and also discuss the properties of the resulting nonuniform states. I will also show that the FFLO superconductors conduct electric current in a way which is very different from the usual case and, in particular, may exhibit the superconducting diode effect.

The interaction between magnons and mechanical vibrations dynamically modify a mechanical oscillator’s properties such as its frequency and decay rate. Such modifications are known as dynamical backaction. It provides a versatile tool for manipulating mechanical vibrations. For example, dynamical backaction is used in cooling a mechanical resonator to its ground state, in driving phonon lasing, and in the generation of entangled states, among other things. However, dynamical backaction is also detrimental for specific applications. In this article, we directly observe the impact of magnon-induced dynamical backaction on a spherical magnetic sample’s mechanical vibrations and demonstrate the implementation of a cavity magnomechanical measurement that fully evades dynamical backaction effects.

In-situ control of system dynamics is critical for coherent information processing, but it has been challenging for the emerging field of hybrid magnonics, thus limiting its potential applications. This work will show novel approaches to introduce dynamical control in conventional hybrid magnonic devices. Using fast temporal modulation in system parameters such as the bias field, real-time tuning of the coherent magnon-microwave photon coupling can be obtained at time scales that are much shorter than the magnon and photon lifetimes. This allows real-time control of the coherent information exchange between magnons and microwave photons.

Spin-wave based devices offer several advantages, such as the absence of Joule losses and the sub-μm wavelength in the GHz-THz range, and have been proposed as promising alternatives to the standard CMOS technology. In this context, synthetic antiferromagnetic systems have been extensively studied for the development of nanomagnonic devices, thanks to their high degree of tunability. Moreover, spin textures have recently been demonstrated as efficient means for the generation and emission of spin waves. Here, we show that with the newly proposed phase nanoengineering methodology it is possible to magnetically nanopattern spin textures via thermally assisted magnetic Scanning Probe Lithography in a 200-nm-thick exchange-biased synthetic antiferromagnetic multilayer. In such nanopatterned structures, we demonstrate via time-resolved scanning transmission x-ray microscopy the generation and manipulation of different types of coherent spin-wave modes. By strongly enhancing the robustness and quality of the spin-wave wavefronts propagating for multiple wavelengths in thick synthetic antiferromagnetic systems, this work opens the possibility to expand the comprehension of the spin-wave phenomenology also to the third dimension and to study the complex spin-wave properties through the volume of the magnetic systems, enabling their control for the design of novel three-dimensional nanomagnonic devices.

Ferrimagnets (FiM) embody an intriguing magnetic order in between ferromagnets (FM) and anti-ferromagnets (AF). We examine the optical of spin dynamics in FiM systems using complementary time resolved probes: magneto-optical Kerr effect (tr-MOKE) using visible light, extreme UV probes generated by high harmonic generation (HHG).

The reciprocal interconversion between spin polarization and charge current (CSC) is the focus of intensive theoretical and experimental investigation in spintronics research. Its physical origin stems from the Rashba spin-orbit coupling (SOC) induced by the breaking of the structure inversion symmetry. The steady-state interconversion efficiency is the result of the non-trivial spin textures of the electric-field distorted Fermi surface. Its full understanding and evaluation requires the consideration of disorder-induced relaxation effects in the presence of spin-orbit induced band splitting. In this paper the additional effect of the orbital degree of freedom is analyzed in a two-subband quantum well with both conventional and unconventional Rashba SOC in the presence of disorder impurity scattering. The latter is treated at the level of the Born approximation in the Green’s function self-energy and with the inclusion of vertex corrections in the linear response functions for the charge current and the spin polarization. By explicitly considering the symmetry properties of the Hamiltonian the matrix structure of the correlation functions is shown to decompose in independent blocks of symmetry-related physical observables. We find that the inclusion of vertex corrections is important for the correct estimate of the CSC efficiency, which also depends on the position of the Fermi level. We also find that the relative sign of the Rashba SOC in the two subbands plays a key role in determining the behavior of the CSC. Finally, we point out how the two-subband model compares with the standard single-band two-dimensional electron gas.

The manipulation of the spin degree of freedom is highly sought after in the field of spintronics. This study looks at the emergence of Rashba physics in group IV materials, such as p-i-n diodes that contain Ge quantum wells and Si_0.15Ge_0.85barriers. By using optical spin orientation, it was found that the circular polarization degree of the direct emission can be increased by increasing the power of the optical pump, while the device remains unbiased. This is attributed to the optical-induced changes in the built-in Rashba field due to the asymmetric doping of the diode structure. These findings can provide a new way to fine-tune the material properties for spin quantum electronic and optical applications.

The realization of a regular distribution of defects or step edges with a specific orientation at the surface of a semiconductor or a semimetal, such as Bi, might have interesting implications for both fundamental studies and applications, due to the electronic properties stemming from their peculiar topology. Here we present an accurate comparison of the morphological and electronic structure of thin Bi film (with a thickness of 10 nm) grown on Ge(111) and on a high index Ge(111) vicinal surface, Ge(223). We make use of low energy electron diffraction (LEED) and spin-resolved photoemission spectroscopy (SR-PES) for the crystallographic and electronic characterization, respectively. We show that on both substrates it is possible to grow thin Bi films showing the hexagonal Bi(111) surface orientation, whose spin-resolved electronic structure is reminiscent of the one characteristic of bulk Bi(111). At variance with the films grown on Ge(111), those grown on Ge(223) present some specific features, namely the presence of a splitting in the LEED diffraction spots and a reduced momentum dispersion of the electronic states. We interpret these features as evidences that the peculiar morphology of the substrate can be indeed used to modulate the growth of the Bi film leading to the formation of a stepped Bi surface.

This paper provides the review of essential magnetics to create innovative magnetic data storage technology of perpendicular magnetic recording (PMR) and the high-density recording performance which stand on the stacked system foundation. The building blocks are physics of spins, 3D material controls, device design, system integration, and storage system architectures together with non-volatile memories to unleash the intrinsic performance. The prospect of future storage technology and the system architecture from the multi-scale view of the storage system development will be shown. A new computational storage system aiming at unifying computation power on data store and brain-inspired system considerations will be discussed.

Spin-orbit torque (SOT) devices are being pursued for various memory and in-memory compute applications. At nanoscale dimensions, electric current flowing through the SOT channel can be non-uniform due to incomplete current redistribution. Such effects were ignored in the prior modeling works. We present a comprehensive modeling framework for SOT devices that capture the effects of incomplete current redistribution along with interface spin-mixing, and non-uniform resistivity. Our transfer matrix-based formalism along with finite element simulations can account for any local variation in resistivity and spin diffusion length along with accounting for various spin-scattering mechanisms. In addition, we quantify the optimal SOT layer thickness to minimize the write energy in terms of its resistivity and spin diffusion length. To improve the bit density of SOT magnetic random-access memory (MRAM), we explore area saving schemes based on sharing SOT channel among multiple magnetic tunnel junctions (MTJs) with the help of voltage-controlled magnetic anisotropy (VCMA) effect and spin-transfer torque (STT). Using micromagnetic simulations, we study various tradeoffs among write time, current, error rate, and the number of MTJs. Our results show that the number of MTJs on the shared SOT channel is limited by the voltage drop over the SOT channel and write error rate, and having more than 4 MTJs on a SOT channel poses major challenges in terms of reliability.

We consider the role of crystalline symmetries to yield Cooper pairs with non-trivial orbital moment. To this aim, we focus on two-dimensional multi-orbital spin-singlet superconductors and introduce interactions that can break the mirrors and rotation symmetries. The low degree of spatial symmetry content is able to generate Cooper pairs with high-orbital moment that are marked by distinct phase texture in the momentum space. We show how the corresponding superconducting phase pattern depends on the orientation of the orbital moment of the Cooper pairs and on the amplitude of its projection. In doing that we determine the evolution of the superconducting order parameters by self-consistent approach and explicitly present the profile of the superconducting phase in momentum space in terms of the crystalline symmetry breaking couplings. These findings can be relevant for the design of superconducting inteferometric devices that are fully rooted on the phase pattern of the orbitally polarized Cooper pairs.

Applying the Bogoliubov-de Gennes equations with density-functional theory, it is possible to formulate first principles description of current-phase relationships in superconducting/normal (magnetic)/superconducting tri-layers. Such structures are the basis for the superconducting analog of Magnetoresistive random access memory devices (JMRAM). In a recent paper1 we presented results from the first attempt to formulate such a theory, applied to the Nb/Ni/Nb trilayers. In the present work we provide computational details, explaining how to construct key ingredient (scattering matrices SN ) in a framework of linear muffin-tin orbitals (LMTO).

In this work, we theoretically investigate the coupled spin, charge and orbital dynamics induced by a precessing magnetization in a planar bilayer heterostructure. To do so, we developed a theory of adiabatic pumping using the Keldysh formalism and Wigner expansion to the first order in magnetization dynamics. This approach enables us to model the pumping mechanism beyond the weak spin-orbit coupling limit. We carry out simulations using a model system to determine the parameters that control the pumping of spin and orbital moments into adjacent non-magnetic metals and show that in principle orbital pumping can be as large as spin pumping. We then extend our study to realistic bilayers involving both heavy metals (Pt, W) and light metals (Cu) computed by first principles calculations. We show that, alike spin pumping, strong orbital relaxation in the non-magnetic metal is necessary to maintain strong orbital pumping.

NASA is developing quantum metrology capabilities for potential space-based quantum components in future navigation and communications systems. Innate knowledge of component operation is key for the space qualification of these components. The primary focus of aircraft icing research has been on ice accretion on wings for its serious adverse consequences. When icing occurs on a wing, the change in airfoil shape results in a decrease in lift and an increase in drag, leading to potentially fatal accidents. Although the issue was recognized in the 1920s, the icing problem is still an area of ongoing research due to the complexity of the icing phenomena. A much-improved understanding of how certain weather conditions produce different icing characteristics will lead to new mitigation methods and better quantification of current methods. This can be done by a better understanding of the molecular binding energy produced by ice polytype combinations when interacting with different surface materials in various environments. This work is currently developing models that more accurately describe the quantum signatures of H₂O states (i.e. supercooled, ice, liquid, glass phase...) and chip-based detectors to evaluate these signatures. These sensors utilize ion defects in Silicon Carbide (SiC) as extremely sensitive atomic magnetic detectors. This effort leverages both the decades-long SiC development expertise and infrastructure at NASA Glenn and its growing capabilities in quantum metrology.

Previously, the enhanced photonic spin Hall effect (PSHE) in plasmonic devices was only possible with horizontal polarization (H-polarized). The wave-guiding surface plasmonic resonance (SPR) effect is used to report enhanced PSHE of reflected light for both horizontal and vertical polarized waves in this work. Further findings suggest the manipulation of active polarization mode and control in PSHE enhancement by simply adjusting the thickness of the wave-guiding layer. A finite element technique simulation study is used to investigate the influence of an additional thin dielectric waveguiding layer on PSHE. This research opens up the possibility of using both horizontal and vertical polarization-based quantum devices and sensors, in which light spin plays an important role.

It is well known that the Gilbert relaxation time of a magnetic moment scales inversely with the magnitude of the externally applied field, H, and the Gilbert damping, α. Therefore, in ultrashort optical pulses, where H can temporarily be large, the Gilbert relaxation time can momentarily be extremely short, reaching even picosecond timescales. Here we show that for typical ultrashort pulses, the magnetization can respond within the optical cycle such that the optical control of the magnetization emerges by merely considering the optical magnetic field in the Landau-Lifshitz-Gilbert (LLG) equation. Interestingly, when circularly polarized optical pulses are introduced to the LLG equation, an optically induced helicitydependent torque results. We find that the strength of the interaction is determined by η = αγΗ/f_opt, where f_optand γ are the optical frequency and gyromagnetic ratio. Our results illustrate the generality of the LLG equation to the optical limit and the pivotal role of the Gilbert damping in the general interaction between optical magnetic fields and spins in solids.

Interfacing superconductors with magnetic or topological materials offers a playground where novel phenomena like topological superconductivity, Majorana zero modes, or superconducting spintronics are emerging. In this work, we discuss recent developments in the Kohn-Sham Bogoliubov-de Gennes method, which allows to perform material-specific simulations of complex superconducting heterostructures on the basis of density functional theory. As a model system we study magnetically-doped Pb. In our analysis we focus on the interplay of magnetism and superconductivity. This combination leads to Yu-Shiba-Rusinov (YSR) in-gap bound states at magnetic defects and the breakdown of superconductivity at larger impurity concentrations. Moreover, the influence of spin-orbit coupling and on orbital splitting of YSR states as well as the appearance of a triplet component in the order parameter is discussed. These effects can be exploited in S/F/S-type devices (S=superconductor, F=ferromagnet) in the field of superconducting spintronics.

We propose an alternative route to stabilize magnetic skyrmions which does not require Dzyaloshinkii-Moriya interactions, magnetic anisotropy, or an external Zeeman field. Our so-called magnetic skyrmion catalysis (MSC) solely relies on the emergence of flux in the system’s ground state. We review scenarios that allow for a nonzero flux and summarize the magnetic skyrmion phases that it induces. Among these, we focus on the so-called skyrmionic spin-whirl crystal (Sk-SWC₄) phase. We discuss aspects of MSC using a concrete model for topological superconductivity, which describes the surface states of a topological crystalline insulator in the presence of proximity induced pairing. By assuming that the surface states can exhibit the Sk-SWC₄ phase, we detail how the addition of a pairing gap generates a chiral superconductor. For this purpose, we construct a low-energy model which renders the mechanism for topological superconductivity transparent. Moreover, by employing this model, we perform a self-consistent investigation of the appearance of the Sk-SWC₄ phase for different values of the pairing gap and the ground state’s flux. Our analysis verifies the catalytic nature of our mechanism in stabilizing the Sk-SWC₄ phase, since the magnetization modulus becomes enhanced upon ramping up the flux. The involvement of MSC further shields magnetism against the suppression induced by the pairing gap. Remarkably, even if the pairing gap fully suppresses the Sk-SWC₄ phase for a given value of flux, this skyrmion phase can be restored by further increasing the flux. Our findings demonstrate that MSC enables topological superconductivity in a minimal and robust fashion.

Understanding topological spin textures is important because of scientific interests and technological applications. However, observing nanoscale magnetization and mapping out their interactions in 3D have been challenging–due to the lack of nondestructive vector nanoimaging techniques that penetrate thick samples. Recently, we developed a new characterization technique, soft x-ray vector ptycho-tomography, to image spin textures with a 3D vector spatial resolution of 10 nm. Using 3D magnetic metamaterial as an example, we demonstrated the creation and observation of topological magnetic monopoles and their interactions. We expect this method to be applied broadly to image vector fields in magnetic samples and beyond.

In this article, the focus is on using machine learning methods to analyse non-volatile memory devices. This is important because the production of integrated circuits in the sub-micrometre range depends on advancements in manufacturing process technology, and it is crucial to evaluate how manufacturing tolerances affect the functionality of contemporary integrated circuits. Traditionally, Monte Carlo-based techniques have been used to accurately evaluate the impact of manufacturing tolerances on the functionality of integrated circuits. However, these techniques are computationally time-consuming. We will propose a scheme to "learn" the variation of the read margin (parallel and anti-parallel resistance) performance of spintronics devices. The machine learning approach, artificial neural network, is focused on this study (Read margin of spin transfer torque (STT)) spintronics devices. The accuracy for STT by Artificial Neural Network (ANN) is calculated with the help of the MATLAB deep learning toolbox. Regression models using machine learning (ML) are fast and precise over a variety of input ranges, making them ideal for device modelling. The ML algorithm has emerged as a potential substitute for Monte Carlo-based techniques. It can reduce the computational load needed in a Monte Carlo simulation covering all process corners, design parameters, and operating conditions. The article demonstrates the effectiveness of the ML algorithm by performing various simulations on spin transfer torque (STT) non-volatile memory. The proposed scheme involves "learning" the variation of the read margin performance of spintronic devices as a function of its material and geometric parameters. In conclusion, the use of machine learning techniques based on the different regression methods is a promising approach to increase the prediction time of result analysis as compared to SPICE simulation time.

The propagation of spin waves and their interaction with the spin solitons like skyrmions, domain walls and vortex are one of the promising ways for designing nanoscale spintronic devices. Magnetic skyrmion, a particle-like nanoscale object has potential applications in next-generation spintronic devices. In this paper, the unidirectional motion of the skyrmion under the influence of spin wave is studied using micromagnetic simulations. Here, two different magnetic anisotropies are considered on a nanotrack that creates an energy gradient. As a result, the repulsive forces act on the skyrmion and is responsible for the motion of the skyrmion in one direction. The spin wave driving force leads the skyrmion to move in forward direction and the anisotropy gradient is responsible to prevent the skyrmion motion in reverse direction. The skyrmion moves from higher perpendicular magnetic anisotropy region to lower energy region, leading to a unidirectional transport of the skyrmion. This proposed device has less Joule heating and is more energy efficient as compared to other spin transfer torque (STT) and spin orbit torque (SOT) driven techniques. This is due to the fact that spin wave can generate a flow of magnetic momentum without generating an electron flow. This spin wave driven skyrmionics device is a promising pathway towards the development of a complete non-charge based magnetic devices.

This paper discusses the analysis of FeFET for low-power applications. The persistent scaling of computer capacity is necessary to handle the data's rapidly rising volume and complexity. CMOS technology's opportunities are shrinking as transistor size reduction approaches physical constraints. The new nanotechnologies have ability to replace the currently used CMOS and other technologies in energy-efficient computer devices. For information systems, ferroelectric FETs (FeFETs) are a potential candidate to continue improving power consumption. The FeFET analysis is carried out by evaluating drain current, transconductance, electric field, acceptor concentrations, and electric potential. Due to their energy, area efficiency and combined logic-memory functions, FeFETs, at the edge of semiconductor technology, are capable of meeting the requirements of integrated data computer applications. The proposed FeFET device has high ON current and small OFF current. The device exhibits a sub-threshold slope of 9.3 mV/dec, and the threshold voltage of 0.26 V. The proposed structure of FeFET is designed and simulated using the Silvaco TCAD tool. Proposed FeFET devices provides high-density and low-power circuit applications and would act as a promising candidate for the scientific and research community working in this area.

The magnetic skyrmion has distinct features like nanoscale size, particle-like behavior, low driving current, and topologically stable which makes it a suitable candidate for neuromorphic computing. Synthetic antiferromagnetic (SAF) skyrmions consist of a pair of coupled ferromagnetic (FM) skyrmions, each in its respective sub-layers that are favourable over the FM skyrmions as they follow the straight trajectories and prevent its annihilation at the nanotrack edge. In this work, a leaky integrate and fire neuronal device model is proposed based on SAF skyrmions with voltage control magnetic anisotropy (VCMA) as a leaky effect for the tunability of the device. The anisotropy is directly correlated with the size of the skyrmion meaning that in the region with larger anisotropy, the skyrmion size is smaller and hence, more energy. However, the skyrmions have the tendency to move toward the minimum energy state means it will move towards the lower anisotropy. This behavior of SAF skyrmion on a nanotrack with anisotropy gradient corresponds to the leaky-integrate-fire (LIF) functionality of the neuron device. Moreover, device performance is also realized at room temperature for practical implementation. Hence, the proposed device possesses an energy-efficient artificial neuron opens up the path for the development of next-generation skyrmionic devices for neuromorphic computing.

In this work, we quantify the non-uniformity in the spin current density generated by spin-orbit torque (SOT) at the nanoscale and its impact on the switching of SOT magnetic random-access memories (MRAMs). In recent years, SOTMRAMs have emerged as promising non-volatile candidates for last-level (L3/L4) cache due to their high endurance, sufficiently low read/write latency, long retention times, and scalability. In these devices, a conduction current is passed through the non-magnetic (NM) layer, which generates a spin current flowing towards the ferromagnetic (FM) layer due to the Spin Hall Effect (SHE). Using conventional drift-diffusion models, which consider the electric current distribution to be uniform within the FM and NM layers, can lead to erroneous results in the case of nanoscale devices. In this paper, we use the spin current distribution calculated based on finite element simulations and drift-diffusion equations in micromagnetic simulation. We demonstrate that spin current density can be significantly lower at the two edges of the magnet compared to the middle and this non-uniformity can affect the magnet switching dynamics. We investigate the impact of this non-uniformity for both perpendicular magnetic anisotropy (PMA) and in-plane magnetic anisotropy (IMA) based magnetic tunnel junctions (MTJs). Our results show that when resistive NM layers are used, the impact of nonuniform spin current density on write times is more significant for larger FMs. In addition, the variation in write times is more significant in the case of PMA FM than IMA FM.