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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Magnetic state switching in FeGa microstructures

This work demonstrates that magnetoelectric composite heterostructures can be designed at the length scale of 10µms that can be switched from a magnetized state to a vortex state, effectively switching the magnetization off, using electric field induced strain. This was accomplished using thin film magnetoelectric heterostructures of Fe 81.4 Ga 18.6 on a single crystal (011) [Pb(Mg 1/3 Nb 2/3 )O 3 ] 0.68 -[PbTiO 3 ] 0.32 (PMN-32PT) ferroelectric substrate. Here, the heterostructures were tripped from a multi-domain magnetized state to a flux closure vortex state using voltage induced strain in a piezoelectric substrate. FeGa heterostructures were deposited on a Si-substrate for superconducting quantum interference device magnetometry characterization of the magnetic properties. The magnetoelectric coupling of a FeGa continuous film on PMN-32PT was characterized using a magneto optical Kerr effect magnetometer with bi-axial strain gauges, and magnetic multi-domain heterostructures were imaged using x-ray magnetic circular dichroism—photoemission electron microscopy during the transition to the vortex state. The domain structures were modelled using MuMax 3 , a micromagnetics code, and compared with observations. The results provide considerable insight into designing magnetoelectric heterostructures that can be switched from an ‘on’ state to an ‘off’ state using electric field induced strain.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A domain wall-magnetic tunnel junction artificial synapse with notched geometry for accurate and efficient training of deep neural networks

Inspired by the parallelism and efficiency of the brain, several candidates for artificial synapse devices have been developed for neuromorphic computing, yet a nonlinear and asymmetric synaptic response curve precludes their use for backpropagation, the foundation of modern supervised learning. Spintronic devices—which benefit from high endurance, low power consumption, low latency, and CMOS compatibility—are a promising technology for memory, and domain-wall magnetic tunnel junction (DW-MTJ) devices have been shown to implement synaptic functions such as long-term potentiation and spike-timing dependent plasticity. In this work, we propose a notched DW-MTJ synapse as a candidate for supervised learning. Using micromagnetic simulations at room temperature, we show that notched synapses ensure the non-volatility of the synaptic weight and allow for highly linear, symmetric, and reproducible weight updates using either spin transfer torque (STT) or spin–orbit torque (SOT) mechanisms of DW propagation. We use lookup tables constructed from micromagnetics simulations to model the training of neural networks built with DW-MTJ synapses on both the MNIST and Fashion-MNIST image classification tasks. Accounting for thermal noise and realistic process variations, the DW-MTJ devices achieve classification accuracy close to ideal floating-point updates using both STT and SOT devices at room temperature and at 400 K. Our work establishes the basis for a magnetic artificial synapse that can eventually lead to hardware neural networks with fully spintronic matrix operations implementing machine learning.

42 ENGINEERING↗
DOE OSTI2022

A massively parallel time-domain coupled electrodynamics–micromagnetics solver

We present a high-performance coupled electrodynamics–micromagnetics solver for full physical modeling of signals in microelectronic circuitry. The overall strategy couples a finite-difference time-domain approach for Maxwell’s equations to a magnetization model described by the Landau–Lifshitz–Gilbert equation. The algorithm is implemented in the Exascale Computing Project software framework, AMReX, which provides effective scalability on manycore and GPU-based supercomputing architectures. Furthermore, the code leverages ongoing developments of the Exascale Application Code, WarpX, which is primarily being developed for plasma wakefield accelerator modeling. Our temporal coupling scheme provides second-order accuracy in space and time by combining the integration steps for the magnetic field and magnetization into an iterative sub-step that includes a trapezoidal temporal discretization for the magnetization. The performance of the algorithm is demonstrated by the excellent scaling results on NERSC multicore and GPU systems, with a significant (59×) speedup on the GPU using a node-by-node comparison. We demonstrate the utility of our code by performing simulations of an electromagnetic waveguide and a magnetically tunable filter.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Nanomagnet shape effects on magnetic reversal in artificial spin ice

We use micromagnetic simulations to study the influence of the shape of elongated nanomagnets that vary from rectangular to elliptical shapes in an artificial spin ice array. For weakly interacting ellipselike islands, the magnetic hysteresis loops align with the Stoner-Wohlfarth model, demonstrating nearly uniform magnetization at remanence and nearly coherent rotation. As expected, nonelliptical weakly interacting islands show deviations from the model due to the curling and pinning of the magnetization at the island edge. We find that increasing interisland coupling leads to an increasingly complex magnetic reversal process due to an interplay between internal and external degrees of freedom as the shape of the islands varies. Furthermore, our results open a roadmap for tailoring systems with desired magnetic properties by choosing the appropriate nanomagnet shape.

Artificial spin ice↗
DOE OSTI2021

Controllable Reset Behavior in Domain Wall–Magnetic Tunnel Junction Artificial Neurons for Task-Adaptable Computation

Neuromorphic computing with spintronic devices has been of interest due to the limitations of CMOS-driven von Neumann computing. Domain wall–magnetic tunnel junction (DW-MTJ) devices have been shown to be able to intrinsically capture biological neuron behavior. Edgy-relaxed behavior, where a frequently firing neuron experiences a lower action potential threshold, may provide additional artificial neuronal functionality when executing repeated tasks. In this letter, we demonstrate that this behavior can be implemented in DW-MTJ artificial neurons via three alternative mechanisms: shape anisotropy, magnetic field, and current-driven soft reset. Using micromagnetics and analytical device modeling to classify the Optdigits handwritten digit dataset, we show that edgy-relaxed behavior improves both classification accuracy and classification rate for ordered datasets while sacrificing little to no accuracy for a randomized dataset. This letter establishes methods by which artificial spintronic neurons can be flexibly adapted to datasets.

42 ENGINEERING↗
DOE OSTI2021

Switching between Magnetic Bloch and Néel Domain Walls with Anisotropy Modulations

It has been shown previously that the presence of a Dzyaloshinskii-Moriya interaction in perpendicularly magnetized thin films stabilizes N\'eel type domain walls. We demonstrate, using micromagnetic simulations and analytical modeling, that the presence of a uniaxial in-plane magnetic anisotropy can also lead to the formation of N\'eel walls in the absence of a Dzyaloshinskii-Moriya interaction. It is possible to abruptly switch between Bloch and N\'eel walls via a small modulation of both the in-plane, but also the perpendicular magnetic anisotropy. This opens up a route towards electric field control of the domain wall type with small applied voltages through electric field controlled anisotropies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Skyrmions Near Defects

We study the impact of an exchange-reducing defect on a skyrmion for a thin film of finite thickness. Attraction of the skyrmion to a defect is demonstrated in a lattice model by computing the micromagnetic energy accounting for the exchange, Dzyaloshinskii-Moriya interaction, magnetic anisotropy, and dipole-dipole coupling. The spiraling dynamics of the skyrmion towards the defect is illustrated by solving numerically the full Landau-Lifshitz-Gilbert equations on a lattice and, independently, the Thiele equation, with the two methods in agreement with each other. We find that the skyrmion deforms when approaching the defect. Here, deformation is small in the parameter space far from the phase boundary that determines stability of skyrmions. It increases dramatically near the phase boundary, leading to the transformation of the skyrmion by the defect into a snake-like magnetic domain.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Coexistence of soft and hard magnetic phases in single layer amorphous Tb–Co thin films

Amorphous, ferrimagnetic Tb-Co thin films prepared with a thin Ta underlayer and either a Ta or a Pt overlayer show evidence of both soft and hard magnetic phases. At room temperature, the films exhibit conventional ferromagnetism, but low temperature magnetometry measurements reveal the decoupling of the two magnetic phases with decreasing temperature due to increased anisotropy energy of the hard layer at lower temperatures. Decreasing the film thickness to 2 nm, slightly above the superparamagnetic limit found at 1 nm, a soft, low-density phase was isolated and found to be present in all the films as confirmed with x-ray reflectivity and Rutherford backscattering spectrometry measurements. For greater thicknesses, the bottom layer retains its soft magnetic nature, while the remainder of the film is denser and has strong perpendicular magnetic anisotropy, leading to the exchange-spring behavior when the anisotropy becomes large, either at low temperatures or via a Pt overlayer that adds a strong interfacial anisotropy to the layer. Micromagnetic simulations of a soft/hard bilayer model with the experimentally determined anisotropy and magnetization parameters into a soft/hard bilayer model reproduced the experimental hysteretic behavior very well. These findings demonstrate how the magnetic state and the response of a-Tb-Co films to external fields can be controlled, providing a high degree of tunability that is promising for high-performance nanoscale devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Eigenvalue-Based Micromagnetic Analysis of Switching in Spin-Torque-Driven Structures

We present an eigenvalue-based approach for studying the magnetization dynamics in magnetic nanostructures driven by spintronic excitations, such as spin-transfer torque and spin-orbit torque. The approach represents the system dynamics in terms of normal oscillation modes (eigenstates) with corresponding complex eigenfrequencies. The dynamics is driven by a small number of active eigenstates and often considering just a single eigenstate is sufficient. We develop a perturbation theory that provides semianalytical dynamic solutions by using eigenstates for the case in the absence of damping and spintronic excitations as a basis. The approach provides useful insights into dynamics in such systems and allows solving several difficulties in their modeling, such as extracting the switching current in magnetic random-access memories and understanding switching mechanisms. We show that the presented approach directly predicts the critical switching current, i.e., switching current for an infinite time. The approach also provides solutions for the switching dynamics allowing the switching current to be obtained for a finite switching time, provided that the system symmetry is broken, e.g., by tilting the polarizer, so that switching by a finite pulse is possible.

42 ENGINEERING↗
DOE OSTI2024

Simulation-trained machine learning models for Lorentz transmission electron microscopy

Understanding the collective behavior of complex spin textures, such as lattices of magnetic skyrmions, is of fundamental importance for exploring and controlling the emergent ordering of these spin textures and inducing phase transitions. It is also critical to understand the skyrmion–skyrmion interactions for applications such as magnetic skyrmion-enabled reservoir or neuromorphic computing. Magnetic skyrmion lattices can be studied using in situ Lorentz transmission electron microscopy (LTEM), but quantitative and statistically robust analysis of the skyrmion lattices from LTEM images can be difficult. In this work, we show that a convolutional neural network, trained on simulated data, can be applied to perform segmentation of spin textures and to extract quantitative data, such as spin texture size and location, from experimental LTEM images, which cannot be obtained manually. This includes quantitative information about skyrmion size, position, and shape, which can, in turn, be used to calculate skyrmion–skyrmion interactions and lattice ordering. We apply this approach to segmenting images of Néel skyrmion lattices so that we can accurately identify skyrmion size and deformation in both dense and sparse lattices. The model is trained using a large set of micromagnetic simulations as well as simulated LTEM images. This entirely open-source training pipeline can be applied to a wide variety of magnetic features and materials, enabling large-scale statistical studies of spin textures using LTEM.

McCray, Arthur R. C. (ORCID:0000000160774698)↗
DOE OSTI2024

Exascale-Enabled Models and Algorithms for Microelectronics Applications (MicroEleX) v1

The MicroEleX code package contains a variety of models and algorithms for physical modeling of microelectronic circuitry, including electrostatics, electrodynamics, superconducting physics, micromagnetics, multi-ferroic systems, and quantum transport. MicroEleX leverages the AMReX software framework to provide scalability on GPU-based supercomputing architectures. The code is open source and designed to be algorithmically flexible so developers can incorporate enhanced or customized physics.

Nonaka, Andy↗
DOE OSTI2023

Coupled magnetostructural continuum model for multiferroic BiFeO 3

Here, a continuum approach to study magnetoelectric multiferroic BiFeO 3 (BFO) is proposed. Our modeling effort marries the ferroelectric (FE) phase field method and micromagnetic simulations to describe the entire multiferroic order parameter sector (polarization, oxygen antiphase tilts, strain, and magnetism) self-consistently on the same time- and length scale. In this paper, we discuss our choice of FE and magnetic energy terms and demonstrate benchmarks against known behavior. We parametrize the lowest order couplings of the structural distortions against previous predictions from density functional theory calculations giving access to simulations of the FE domain wall (DW) topology. This allows us to estimate the energetic hierarchy and thicknesses of the numerous structural DWs. We then extend the model to the canted antiferromagnetic order and demonstrate how the FE domain boundaries influence the resulting magnetic DWs. We also highlight some capabilities of this model by providing two examples relevant for applications. We demonstrate spin-wave transmission through the multiferroic domain boundaries which identify rectification in qualitative agreement with recent experimental observations. As a second example of application, we model fully dynamical magnetoelectric switching, where we find a sensitivity on the Gilbert damping with respect to switching pathways. We envision that this modeling effort will set the basis for further work on properties of arbitrary 3D nanostructures of BFO (and related multiferroics) at the mesoscale.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Collective Ferromagnetism of Artificial Square Spin Ice

In this work, we study the temperature and magnetic field dependence of the total magnetic moment of large-area permalloy artificial square spin ice arrays. The temperature dependence and hysteresis behavior are consistent with the coherent magnetization reversal expected in the Stoner-Wohlfarth model, with clear deviations due to interisland interactions at small lattice spacing. Through micromagnetic simulations, we explore this behavior and demonstrate that the deviations result from increasingly complex magnetization reversal at small lattice spacing, induced by interisland interactions, and depending critically on details of the island shapes. These results establish new means to tune the physical properties of artificial spin ice structures and other interacting nanomagnet systems, such as patterned magnetic media.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Anisotropic MagnetoMemristance

Abstract In the last decade, nanoscale resistive devices with memory have been the subject of intense study because of their possible use in brain-inspired computing. However, operational endurance is one of the limiting factors in the adoption of such technology. For this reason, we discuss the emergence of current-induced memristance in magnetic materials, known for their durability. We show analytically and numerically that a single ferromagnetic layer can possess GHz memristance, due to a combination of two factors: a current-induced transfer of angular momentum (Zhang-Li torque) and the anisotropic magnetoresistance (AMR). We term the resulting effect the anisotropic magneto-memristance (AMM). We connect the AMM to the topology of the magnetization state, within a simple model of a one-dimensional annulus-shaped magnetic layer, confirming the analytical results with micromagnetic simulations for permalloy. Our results open a new path towards the realization of single-layer magnetic memristive devices operating at GHz frequencies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Magnetic anisotropy in permalloy antidot square lattice

Here, magnetic anisotropy of Permalloy (Py) antidot square lattice was investigated by torquemetry method using Rotation Magneto-Optic Kerr Effect (ROTMOKE). We find that there exists a field-dependent 4-fold magnetic anisotropy with the easy magnetization axis along the axis of the antidot square lattice. In addition, there also exists an artifact of a uniaxial magnetic anisotropy in ROTMOKE result. We show that both results are due to the period wiggling of the magnetization in space which was confirmed by magnetic imaging using magnetic transmission soft x-ray microscopy (MTXM). Micromagnetic simulation from MuMax3 supports the wiggling structure of the magnetization, as well as reproduces ROTMOKE result. A simplified model was developed based on the periodic wiggling of the magnetization and successfully explored the physical origin of the field-dependent 4-fold anisotropy and the artifact of the uniaxial anisotropy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ferromagnetic Resonance Modes in the Exchange-Dominated Limit in Cylinders of Finite Length

We analyze the magnetic mode structure of axially magnetized finite-length nanoscopic cylinders in a regime where the exchange interaction dominates, along with simulations of the mode frequencies of the ferrimagnet yttrium iron garnet. For the bulk modes, we find that the frequencies can be represented by an expression given by Herring and Kittel by using wavevector components obtained by fitting the mode patterns emerging from these simulations. In addition to the axial, radial, and azimuthal modes that are present in an infinite cylinder, we find localized “cap modes” that are “trapped” at the top and bottom cylinder faces by the inhomogeneous dipole field emerging from the ends. Semiquantitative explanations are given for some of the modes, in terms of a one-dimensional Schrodinger equation, which is valid in the exchange-dominant case. The assignment of the azimuthal-mode number is carefully discussed, and the frequency splitting of a few pairs of nearly degenerate modes is determined through the beat pattern emerging from them.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Advances in relaxation and memory effects of magnetic nanoparticles for biomedical applications

Functionalized magnetic nanoparticles are pivotal in magnetic resonance imaging, computed tomography, controlled drug delivery, and hyperthermia treatments due to their exceptional magnetic relaxation and functional properties. The magnetic core composition and structure significantly affects the complex magnetic properties of these nanoparticles necessitating a thorough examination of magnetism fundamentals related to these systems. One important aspect is the ability of magnetic nanoparticles to retain previous magnetic state configurations known as memory effect, primarily governed by domain structure and magnetic anisotropy. Despite its relevance to advanced applications, comprehensive studies on magnetic relaxation and memory effects remain limited. Here, the present review aims to bridge this gap by investigating relaxation mechanisms, synthesis strategies, and applications, fostering further innovation. It investigates the memory effects and their dependence on particle composition and morphology along with key synthesis techniques for large-scale production in industrial adoption. Structured into focused sections on magnetic properties and their influence on biomedical and technological applications, this review provides essential insights into memory effects, magneto-relaxation mechanisms, influencing factors, and both experimental and theoretical methodologies. It also delves into computational modelling and AI-driven design, which are revolutionizing the prediction, discovery, and optimization of materials with tailored properties.

36 MATERIALS SCIENCE↗
NASA NTRS1977

On the origin of stable remanence in pseudo-single domain grains

A critique is presented of the quantitative model for the magnetic moment of pseudo-single domain grains (hypothetical magnetite grains larger than the critical size threshold for single domain behavior, yet also difficult to demagnetize), derived by Stacey and Banerjee (1974). Evidence from theoretical studies in micromagnetics demonstrates that the spin orientations in such grains are too complex to permit ready prediction of the magnetic moments. However, this limitation in the theory may be overcome by experiments involving rare earth-cobalt alloys and yttrium iron garnet crystals; these studies have suggested that surface anisotropy is the predominant cause of the high coercivity of pseudo-single domain grains.

Banerjee, S. K.↗