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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

In-Situ Spatial Mapping of Hydrogen in Yttrium Hydrides at LANSCE (FY23 Version, Rev. 1)

This report summarizes the development of neutron imaging capabilities and experimental activities performed at the Los Alamos Neutron Science Center (LANSCE) with the main goal of measuring temperature-driven hydrogen diffusion within bulk-yttrium hydride (YH x ) materials. Yttrium hydride is the leading candidate to serve as a solid neutron moderator in microreactor cores, owing to its high density of hydrogen atoms as well as its superior thermal stability compared to all other metal hydrides. The experimental results and technique developments reported herein support the U.S. Department of Energy Office of Nuclear Energy’s (DOE-NE) Microreactor Program under Technology Maturation. In particular, it addresses the critical need to experimentally validate and verify hydrogen-diffusion models of metal hydrides used in high-temperature microreactor designs by means of high-spatial-resolution neutron imaging. These capabilities were designed to apply large temperature gradients across centimeter-sized YH x pellets to simulate conditions faced in the microreactor environment. In principle, neutron imaging, combined with in-situ sample heating, enables near real-time tracking of hydrogen diffusion in YH x on the sub-millimeter scale. In this report, an overview of neutron imaging methodology and technologies are given in the context of recent spatial measures of hydrogen concentrations in similar metal hydrides. Additionally, the commissioning and operation of a custom-built compact dual-zone furnace is given along with details on three in-situ heating measurements of YH x performed over the 2020 to 2022 LANSCE operation cycles. The aims of these experiments ranged from furnace commissioning, determining sample quality, i.e., hydrogen uniformity via neutron computed tomography, and studying the effects of applied temperature-gradients on YH x pellets. Analyses and results from these neutron imaging measurements are given along with outlooks and guidelines for optimal future hydrogen diffusion measurements. Our conclusions are as follows. Image analyses indicate that centimeter-sized yttrium hydride cylindrical pellets exhibit uniform, whole-body hydrogen desorption and absorption without clear temperature dependence as reflected in the image attenuation at the opposing ends of each sample. This suggests that despite the large magnitude in temperature gradients applied by the furnace heating elements, the sample equilibrates to an unknown intermediate temperature. The origin of this result is likely the combination of short sample length (∼1cm) and use of a TZM can for containment where the latter created a thermal short across the sample. Nevertheless, the results from the most recent measurements indicate that neither significant concentration gradients of hydrogen were formed in centimeter-sized samples through the entire temperature range (25 °C to 950 °C) nor any formed due to temperature gradients on the order of 50 °C/cm up to 700 °C/cm. Furthermore, images from the FY2021 and FY2022 measurements indicate that samples of YH x , fabricated from either the direct hydride or powder metallurgy methods, are highly uniform in their hydrogen concentration to within the measurements’ spatial resolutions. The following questions arise from these latest results: 1) What is the intermediate temperature of the pellets in the TZM cans? 2) How quickly does the temperature equilibrate within the sample? and, 3) Do the observed changes in image attenuation follow known pressure-composition-temperature relations of yttrium hydride?

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Nanocompression of 20 nm Silver Nanoparticles: In situ Aberration‐Corrected TEM and Atomistic Simulations

Single‐crystalline nanoparticles play an increasingly important role in a wide variety of fields including pharmaceuticals, advanced materials, catalysts for fuel cells, energy materials, as well as environmental detection and monitoring. Yet, the deformation mechanisms of very small nanoparticles are still poorly understood, in particular the role played by single dislocations and their interaction with surfaces. Here, in this work, silver nanoparticles with particularly small dimensions (≈20 nanometers in diameter) are compressed in situ in an aberration‐corrected transmission electron microscopy (TEM) and molecular dynamics (MD) simulations. During compression, the emergence of both dislocations and nanotwins are observed. However, these defects prove to be unstable and disappear upon removal of the indenter. Atomistic simulations confirm the role played by image stresses associated with the nearby surfaces and the reduction in dislocation line length as it approaches the free surface, thereby supporting the experimental observations. These results provide justification for the frequent observation of the absence of dislocations in nanoparticles of a few nanometers in size during in situ experiments, even after significant deformation. This phenomenon contributes to the self‐healing of samples through dislocation ejection toward the surfaces.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Learning neural representations for X-ray ptychography reconstruction with unknown probes

X-ray ptychography provides exceptional nanoscale resolution and is widely applied in materials science, biology, and nanotechnology. However, its full potential is constrained by the critical challenge of accurately reconstructing images when the illuminating probe is unknown. Conventional iterative methods and deep learning approaches are often suboptimal, particularly under the low-signal conditions inherent to low-dose and high-speed experiments. These limitations compromise reconstruction fidelity and restrict the broader adoption of the technique. In this work, we introduce the Ptychographic Implicit Neural Representation (PtyINR), a self-supervised framework that simultaneously addresses the object- and probe-recovery problem. By parameterizing both as continuous neural representations, PtyINR performs end-to-end reconstruction directly from raw diffraction patterns without requiring any pre-characterization of the probe. Extensive evaluations demonstrate that PtyINR achieves superior reconstruction quality on both simulated and experimental data, with remarkable robustness under challenging low-signal conditions. Furthermore, PtyINR offers a generalizable, physics-informed framework for addressing probe-dependent inverse problems, making it applicable to a wide range of computational microscopy problems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Imaging Field–Driven Melting of a Molecular Solid at the Atomic Scale

Solid–liquid phase transitions are basic physical processes, but atomically resolved microscopy has yet to capture their full dynamics. A new technique is developed for controlling the melting and freezing of self–assembled molecular structures on a graphene field–effect transistor (FET) that allows phase–transition behavior to be imaged using atomically resolved scanning tunneling microscopy. This is achieved by applying electric fields to 2,3,5,6–tetrafluoro–7,7,8,8–tetracyanoquinodimethane–decorated FETs to induce reversible transitions between molecular solid and liquid phases at the FET surface. Nonequilibrium melting dynamics are visualized by rapidly heating the graphene substrate with an electrical current and imaging the resulting evolution toward new 2D equilibrium states. An analytical model is developed that explains observed mixed–state phases based on spectroscopic measurement of solid and liquid molecular energy levels. The observed nonequilibrium melting dynamics are consistent with Monte Carlo simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Requirements for Soldering Fluxes Research using the B-53 Test Board

IPC J-STD-004B standard prescribes general requirements for the classification and testing of soldering flux for high qualify interconnections. This standard defines the classification of soldering materials through specifications of test methods and inspection criteria. The materials include liquid flux, paste flux, solderpaste flux, solder preform flux, and flux-cored solder. This research will use the proposed IPC-53 Surface Insulation Resistance (SIR) test patterns by means of an open comb (2D) and closed comb (3D to simulate a component over the comb pattern). The 2D open comb has uniformity of conductor spacing, sheet resistance, and flux outgassing. The 3D-closed comb simulates the effect of leadless or bottom-terminated components, which have non-uniform sheet resistance and flux outgassing. The response variables will include SIR testing and visual imaging. The objective is to investigate IPC test method improvements for characterizing soldering fluxes when using leadless components with narrow pad-to-pad spacing.

Diamond, Louis↗
DOE OSTI2024

Wall heating by subcritical energetic electrons generated by the runaway electron avalanche source *

Abstract Subcritical energetic electrons (SEEs) produced by the runaway electron (RE) avalanche source at energies below the runaway threshold are found to be the primary contributor to surface heating of plasma-facing components (PFCs) during final loss events. This finding is supported by theoretical analysis, computational modeling with the Kinetic Orbit Runaway electrons Code (KORC), and qualitative agreement with DIII-D experimental observations. The avalanche source generates significantly more secondary electrons below the runaway threshold, which thermalize rapidly when well-confined. However, during a final loss event, the RE beam impacts the first wall, and SEEs are deconfined before they can thermalize. Additionally, because the energy deposition length decreases faster than energy, the deposited energy density, and thus the maximum PFC surface temperature change, is larger for SEEs than REs. KORC simulations employ an analytic first wall to model particle deconfinement onto a non-axisymmetric wall composed of individual tiles. PFC surface heating is calculated using a 1D model extended to include an energy-dependent deposition length scale. Simulations of DIII-D qualitatively agree with infrared (IR) imaging only when SEEs from the avalanche source are included. These results demonstrate that SEEs are the dominant contributor to PFC surface heating and indicate that the avalanche source plays a critical role in the PFC damage caused during final loss events. The prominence of SEEs also has important implications for interpreting IR imaging, one of the primary diagnostics for RE-wall interaction diagnosis, despite REs dominating the energy and current density. This result improves predictions of wall damage due to post-disruption REs to estimate material lifetime and design RE mitigation systems for ITER and future reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Rapid 3D nanoscale coherent imaging via physics-aware deep learning

Phase retrieval, the problem of recovering lost phase information from measured intensity alone, is an inverse problem that is widely faced in various imaging modalities ranging from astronomy to nanoscale imaging. The current process of phase recovery is iterative in nature. As a result, the image formation is time consuming and computationally expensive, precluding real-time imaging. Here, we use 3D nanoscale X-ray imaging as a representative example to develop a deep learning model to address this phase retrieval problem. We introduce 3D-CDI-NN, a deep convolutional neural network and differential programing framework trained to predict 3D structure and strain, solely from input 3D X-ray coherent scattering data. Our networks are designed to be “physics-aware” in multiple aspects; in that the physics of the X-ray scattering process is explicitly enforced in the training of the network, and the training data are drawn from atomistic simulations that are representative of the physics of the material. We further refine the neural network prediction through a physics-based optimization procedure to enable maximum accuracy at lowest computational cost. 3D-CDI-NN can invert a 3D coherent diffraction pattern to real-space structure and strain hundreds of times faster than traditional iterative phase retrieval methods. Our integrated machine learning and differential programing solution to the phase retrieval problem is broadly applicable across inverse problems in other application areas.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Fused x-ray and fast neutron CT reconstruction for imaging large and dense objects

Megavolt x-ray computed tomography (CT) is a powerful tool for three-dimensional characterization. However, its utility is limited for large objects composed of high-atomic number (Z) materials, where x rays fail to penetrate. Information from fast neutron CT (FNCT) can complement x-ray CT reconstructions since fast neutrons can more readily penetrate high-Z objects. In this work, we demonstrate a method for combining FNCT and x-ray CT data to create a single reconstruction, more accurate than could be achieved with either x rays or fast neutrons alone. The algorithm was tested on an exemplar comprising multiple concentric, nested cylinders of different materials. Simulated and empirical x-ray CT data were acquired for the exemplar using a 9 MV bremsstrahlung spectrum. Additional simulated and empirical FNCT data were acquired using an accelerator based fast neutron source. The FNCT data were used to synthesize x-ray CT data and augment the x-ray CT data missing due to lack of penetration. This approach mitigates artifacts that would otherwise negatively affect the accuracy and resolution of a single-modality reconstructed volume.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Object-space optimization of tomographic reconstructions for additive manufacturing

Volumetric 3D printing motivated by computed axial lithography enables rapid printing of homogeneous parts but requires a high dimensionality gradient-descent optimization to calculate image sets. Here we introduce a new, simpler approach to image-computation that algebraically optimizes a model of the printed object, significantly improving print accuracy of complex parts under imperfect material and optical precision by improving optical dose contrast between the target and surrounding regions. Quality metrics for volumetric printing are defined and shown to be significantly improved by the new algorithm. The approach is extended beyond binary printing to grayscale control of conversion to enable functionally graded materials. The flexibility of the technique is digitally demonstrated with realistic projector point spread functions, printing around occluding structures, printing with restricted angular range, and incorporation of materials chemistry such as inhibition. Finally, simulations show that the method facilitates new printing modalities such as printing into flat, rather than cylindrical packages to extend the applications of volumetric printing.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Micro-mechanical investigation of the thermo-mechanical properties of micro-architectured tungsten coatings

The thermo-mechanical response of micro-architectured tungsten coatings is characterized in the temperature range of 293 to 673 K using both in situ micro-compression experiments inside a scanning electron microscope (SEM) as well as image-based crystal plasticity finite element method (CPFEM) simulations. The experiments were conducted on micropillar-like specimens that were focus ion beam milled into the coatings, while the simulations were conducted on columnar-grained micropillar simulation cells constructed based on the statistics of the coating’s microstructure. The experimental results show that the stress–strain response and deformation mode exhibit a strong temperature-dependence. At room temperature, catastrophic failure is observed shortly after yield and is manifested in the form of intergranular fracture and buckling of individual columnar grains. With increasing temperature, this catastrophic failure is gradually suppressed and the material exhibits a steadier strain hardening response at 693 K. The CPFEM simulations are also shown to be in good agreement with the experimental results, and these simulations indicate that the material response is strongly influenced by the local crystallographic anisotropy and microstructure inhomogeneity. Furthermore, the simulations capture the underlying mechanisms that control the temperature-dependent transition in deformation mode. The current results highlight that the micro-architectured microstructure offers a great combination of excellent mechanical strength and structural integrity at elevated temperatures, which is of importance for high temperature applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Imaging the breaking of electrostatic dams in graphene for ballistic and viscous fluids

The charge carriers in a material can, under special circumstances, behave as a viscous fluid. Here, in this work, we investigated such behavior by using scanning tunneling potentiometry to probe the nanometer-scale flow of electron fluids in graphene as they pass through channels defined by smooth and tunable in-plane p-n junction barriers. We observed that as the sample temperature and channel widths are increased, the electron fluid flow undergoes a Knudsen-to-Gurzhi transition from the ballistic to the viscous regime characterized by a channel conductance that exceeds the ballistic limit, as well as suppressed charge accumulation against the barriers. Our results are well modeled by finite element simulations of two-dimensional viscous current flow, and they illustrate how Fermi liquid flow evolves with carrier density, channel width, and temperature.

Science & Technology - Other Topics↗
DOE OSTI2023

Toward accurate measurement of electromagnetic field by retrieving and refining the center position of non-uniform diffraction disks in Lorentz 4D-STEM

Recent advancement in scanning transmission electron microscopy (STEM) allows the use of 4D-STEM, a technique that captures an electron diffraction pattern at each scan point in STEM, to measure electrostatic and magnetic potential and field in materials. However, accurate measurement, separation of the magnetic and electric signals, and removal of artifacts remain challenging, especially in the presence of complex non-uniform diffraction contrast within the disks. In this work, based on dynamic simulations of 4D-STEM patterns built upon superstructures consisting of millions of atoms to account for different sample thickness and edge geometries, we show how the shape and intensity distribution of the central disk are affected by multiple scattering. We propose a robust refinement procedure through iteration of the spin-sensitive peak position of the disk-center in the circular Hough transform filtered images from experimental Lorentz 4D-STEM dataset after minimizing the possible artifacts, such as those due to the change of thickness, dynamic scattering, and scanning process. We verify that caution must be taken as in practice the rigid-disk-shift model used to reconstruct induction maps can easily break down due to disk-protrusion when there exists a nonconstant phase gradient or thickness within the width of the probe. Through quantitative analysis and comparing experiment with calculation the effect of the non-spin-related intensity distribution inside the disk as well as that causes the disk shift due to the intensity-protrusion can be removed, and high-quality magnetic field mapping is possible.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Quantification of LEU Holdup using gamma ray imaging and inverse transport solver

Holdup is the residual amount of special nuclear material (SNM) remaining in a processing facility after the bulk materials have been cleaned out. In commercial uranium processing facilities, quantification of holdup is a major challenge because of the highly variable shapes and sizes of the deposits. Any method that attempts to generalize and calibrate deposit shapes in order to quantify holdup will be prone to high uncertainties. Uncertainties on the order of ±50% are typical in holdup results. In international safeguards applications, a ±50% uncertainty can result in a large amount of material unaccounted for (MUF) thereby increasing the difficulty of detecting material diversion and facility misuse. An imaging-based methodology has been developed with the objective of significantly reducing this uncertainty by using the true deposit shape, instead of relying on oversimplified geometric assumptions. The project is a collaboration between ORNL, Y-12, and the University of Tennessee, Knoxville, TN. Uranium sources of known masses were measured using the Germanium Gamma-ray Imager (GeGI), a high-resolution imaging spectrometer, creating a pixelated map for each spectral bin. Two different gamma imaging methods are employed in this work: coded aperture imaging and Compton imaging. A validated MonteCarlo model of the detector has been developed using the GEANT4 code for determining the intrinsic response of the detector, its enclosure, and the coded aperture mask. An inverse transport solver based on the Markov Chain Monte-Carlo approach known as Differential Evolution Adaptive Metropolis (DREAM) is employed to use the measurement data from the image pixels (coded aperture or Compton) to solve for the mass of 235 U in the deposit. A reliable method based on the DREAM solver has been developed to flag the infinite thickness condition of a uranium deposit. The project team is working towards improving the image reconstruction for Compton imaging so that a better localization of the source can be achieved. Besides treating the coded aperture and Compton imaging methods independently, the project is also evaluating a combined method that uses the Compton scatter data from a coded aperture measurement. GEANT4 simulations are being performed to evaluate the combined approach. The impact on the DREAM optimization as the source thickness progressively approaches infinite thickness is being evaluated. A number of uranium sources available at ORNL have been measured, and the DREAM results have been tested and validated for the coded aperture imaging. A similar effort will be carried out to validate the Compton based method once the development of algorithms for better localization are complete. The imaging based quantification is very amenable to unattended monitoring of holdup accumulation at key measurement points. A proof of concept measurement has been completed to demonstrate this capability The current work used the high energy resolution imager GeGI. However, the approach and methodologies are applicable to other imagers such as the cadmium zin telluride (CZT) based imager manufactured by H3D, Inc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

X-ray topography characterization of gallium nitride substrates for power device development

Gallium nitride substrates grown by the hydride vapor phase epitaxy (HVPE) method using a patterned growth process have been characterized by synchrotron monochromatic beam X-ray topography in the grazing incidence geometry. Images reveal a starkly heterogeneous distribution of dislocations with areas as large as 0 3 mm 2 containing threading dislocation densities below 10 3 cm -2 in between a grid of strain centers with higher threading dislocation densities (> 10 4 cm -2 ). Basal plane dislocation densities in these areas are as low as 104 cm -2 . By comparing the recorded images of dislocations with ray tracing simulations of expected dislocations in GaN, the Burgers vectors of the dislocations have been determined. The distribution of threading screw/mixed dislocations (TSDs/TMDs), threading edge dislocations (TEDs) and basal plane dislocations (BPDs) is discussed with implications for fabrication of power devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Oxide nucleation via threshold-driven volume instability in Ni oxidation

Oxide nucleation dictates the onset of metal oxidation, yet the atomistic pathways bridging initial oxygen adsorption to bulk phase transformation remain elusive. Here, we utilize in-situ atomic-resolution imaging to directly capture the nucleation of nickel oxide, revealing a threshold-driven, cooperative transformation of Ni into NiO. Our observations identify a distinct incubation period during which oxygen progressively accumulates in subsurface layers. Once a critical concentration and penetration depth are reached, a collective lattice reconfiguration is triggered, abruptly converting multiple Ni layers into NiO. Atomistic simulations corroborate this mechanism, identifying a cooperative lattice instability induced by subsurface oxygen saturation. These results establish subsurface oxygen incorporation as the missing mechanistic link between surface adsorption and three-dimensional oxide formation, providing an atomistic framework to understand and control reactive phase transformations in materials synthesis, catalysis, and degradation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mirostructure Characterization of Friction Consolidated Copper-Nickel using a Machine Learning Approach: Developing Process to Microstructure Associations

Friction consolidation (FC) is a solid phase processing approach where discrete material forms such as powders, chips, nuggets, etc. are densified via shear deformation. The precursors are placed in a billet container and brought in contact with a rotating tool that applying the desirable amount of normal force. Under the combined action of the rotation and normal pressure, the discrete precursor is consolidated through porosity reduction and shear deformation. FC is increasingly being studied as an attractive approach to manufacturing fully dense parts from powder forms owing to its ability to mix, alloy and consolidate difficult-to-process precursors in minimal number of process steps. Material consolidation and deformation in shear consolidation processes have been studied extensively previously for different material combinations previously. However, despite the extensive research in this area, understanding of the mechanistic processes in pore consolidation, deformation-induced mixing and material solubility during FC is still evolving. Material development using solid phase processing approaches such as FC is often performed based on research experience/education, which can be biased. Conventional analysis and simulation tools in this area tend to be successful only when material thermodynamic pathways and microstructural evolution sequences resulting from processing are clearly defined or known. They are not as effective for emerging advanced manufacturing technologies where material evolution pathways are not well established. The ability to predict optimal process parameters based on material chemistry and bulk properties is essential to accelerate materials design and processing, as are an understanding of the relevant structure-processing-property relationships. These structure-processing-property-performance relationships are at the core of materials science research. Microstructure characterization provides the link to these four core areas, often through visualizing material microstructure using imaging techniques. However, linking microstructure image data (i.e., micrographs) to variables of interest (e.g., processing parameters, material chemistry) in a reproducible, generalizable, and quantitative manner is a significant challenge. Typically, quantitatively linking image data to processing history relies on significant domain knowledge and manual or subject matter expert (SME)-heuristic based image analysis. Such an approach to image analysis has the potential to be biased, inefficient, and difficult to replicate.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Shock state distributions in porous tantalum and characterization with multipoint velocimetry

Heterogenous materials under shock compression can be expected to reach different shock states throughout the material according to local differences in microstructure and the history of wave propagation. Here, in this work, a compact, multiple-beam focusing optic assembly is used with high-speed velocimetry to interrogate the shock response of porous tantalum films prepared through thermal-spray deposition. The distribution of particle velocities across a shocked interface is compared to results obtained using a set of defocused interferometric beams that sampled the shock response over larger areas. The two methods produced velocity distributions along the shock plateau with the same mean, while a larger variance was measured with narrower beams. The finding was replicated using three-dimensional, mesoscopically resolved hydrodynamics simulations of solid tantalum with a pore structure mimicking statistical attributes of the material and accounting for radial divergence of the beams, with agreement across several impact velocities. Accounting for pore morphology in the simulations was found to be necessary for replicating the rise time of the shock plateau. The validated simulations were then used to show that while the average velocity along the shock plateau could be determined accurately with only a few interferometric beams, accurately determining the width of the velocity distribution, which here was approximately Gaussian, required a beam dimension much smaller than the spatial correlation lengthscale of the velocity field, here by a factor of ∼30×, with implications for the study of other porous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Van der Waals Interface Hosting Two Groups of Magnetic Skyrmions

Multiple magnetic skyrmion phases add an additional degree of freedom for skyrmion-based ultrahigh-density spin memory devices. Extending the field to 2D van der Waals magnets is a rewarding challenge, where the realizable degree of freedoms (e.g., thickness, twist angle, and electrical gating) and high skyrmion density result in intriguing new properties and enhanced functionality. In this work, a van der Waals interface, formed by two 2D ferromagnets Cr 2 Ge 2 Te 6 and Fe 3 GeTe 2 with a Curie temperature of ≈65 and ≈205 K, respectively, hosting two groups of magnetic skyrmions, is reported. Two sets of topological Hall effect signals are observed below 6s0 K when Cr 2 Ge 2 Te 6 is magnetically ordered. These two groups of skyrmions are directly imaged using magnetic force microscopy, and supported by micromagnetic simulations. Interestingly, the magnetic skyrmions persist in the heterostructure with zero applied magnetic field. The results are promising for the realization of skyrmionic devices based on van der Waals heterostructures hosting multiple skyrmion phases.

2D magnetism↗