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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Manipulating the diffusion energy barrier at the lithium metal electrolyte interface for dendrite-free long-life batteries

Abstract Constructing an artificial solid electrolyte interphase (SEI) on lithium metal electrodes is a promising approach to address the rampant growth of dangerous lithium morphologies (dendritic and dead Li 0 ) and low Coulombic efficiency that plague development of lithium metal batteries, but how Li + transport behavior in the SEI is coupled with mechanical properties remains unknown. We demonstrate here a facile and scalable solution-processed approach to form a Li 3 N-rich SEI with a phase-pure crystalline structure that minimizes the diffusion energy barrier of Li + across the SEI. Compared with a polycrystalline Li 3 N SEI obtained from conventional practice, the phase-pure/single crystalline Li 3 N-rich SEI constitutes an interphase of high mechanical strength and low Li + diffusion barrier. We elucidate the correlation among Li + transference number, diffusion behavior, concentration gradient, and the stability of the lithium metal electrode by integrating phase field simulations with experiments. We demonstrate improved reversibility and charge/discharge cycling behaviors for both symmetric cells and full lithium-metal batteries constructed with this Li 3 N-rich SEI. These studies may cast new insight into the design and engineering of an ideal artificial SEI for stable and high-performance lithium metal batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

A rapid heating and high magnetic field thermal analysis technique

Abstract A new thermal analysis technique is described that allows measurements to be performed on bulk samples at extreme heating and cooling rates and in high magnetic fields. High heating rates, up to 1000 °C min −1 , are achieved through electromagnetic induction heating of a custom-built apparatus fitted with commercial thermal analysis heads and sensor. Rapid cooling rates, up to 100 °C min −1 , are enabled by gas quenching and the small thermal mass of the induction furnace. The custom apparatus is designed to fit inside a superconducting magnet capable of fields up to 9 Tesla. This study demonstrates that the instrument is capable of collecting accurate thermal analysis data in high magnetic fields and rapidly acquiring data for dynamic processes. While the full potential of the technique is still unrealized, currently, it can provide insight into phenomena at time scales relevant to heat treatment in many industrial processes and into little understood effects of high magnetic field processing.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Magnetic anisotropy and two-dimensional short-range chemical ordering in Ba 1−𝑥 ⁢Na 𝑥 ⁢Fe 2 ⁢As 2

A true understanding of the properties of pnictide superconductors requires the development of high-quality materials and performing measurements designed to unravel their intrinsic properties and short-range nematic correlations which are often obscured by extrinsic effects such as poor crystallinity, inhomogeneity, domain formation, and twinning. Here, in this paper, we report the systematic growth of high-quality Na-substituted BaFe 2 As 2 single crystals and their characterization using pulsed magnetic fields x-ray diffraction and x-ray diffuse scattering. Analysis of the properties and compositions of the highest-quality crystals shows that their actual Na stoichiometry is about 50-60% of the nominal content and that the targeted production of crystals with specific compositions is accessible. We derived a reliable equation to estimate the Na stoichiometry based on the measured superconducting T c of these materials. Attempting to force spin reorientation and induce tetragonality, orthorhombic Ba 1-x Na x Fe 2 As 2 single crystals subjected to out-of-plane magnetic fields up to 31.4T are found to exhibit strong in-plane magnetic anisotropy demonstrated by the insufficiency of such high fields in manipulating the relative population of their twinned domains or in suppressing the orthorhombic order. Broad x-ray diffuse-intensity rods observed at temperatures between 30 and 300 K uncover short-range structural correlations. Local structure modeling together with 3D-Δ pair-distribution function mapping of real-space interatomic vectors show that the diffuse scattering arises from in-plane short-range chemical correlations of the Ba and Na atoms coupled with short-range atomic displacements within the same plane due to an effective size difference between the two atomic species.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Approximate symmetries of guiding-centre motion

In a strong, inhomogeneous magnetic field, charged particle dynamics may be studied in the guiding-centre approximation, which is known to be Hamiltonian. When the magnetic field is quasisymmetric, the first-order guiding-centre (FGC) Hamiltonian structure admits a continuous symmetry, and therefore a conserved quantity in addition to the energy. Since the FGC system is only an approximation, it is also interesting to consider approximate symmetries of the guiding-centre Hamiltonian structure. We find that any approximate spatial symmetry coincides with quasisymmetry to leading order. For approximate phase-space symmetries, we derive weaker conditions than quasisymmetry. The latter include 'weak quasisymmetry' as a subcase, recently proposed by Rodríguez et al. Our results, however, show that weak quasisymmetry is necessarily non-spatial at first order. Finally, we demonstrate that if the magnetic field is constrained to satisfy magnetohydrostatic force balance then an approximate symmetry must agree with quasisymmetry to leading order.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Imaging the Breakdown and Restoration of Topological Protection in Magnetic Topological Insulator MnBi 2 Te 4

Quantum anomalous Hall (QAH) insulators transport charge without resistance along topologically protected chiral 1D edge states. Yet, in magnetic topological insulators to date, topological protection is far from robust, with zero-magnetic field QAH effect only realized at temperatures an order of magnitude below the Néel temperature T N , though small magnetic fields can stabilize QAH effect. Understanding why topological protection breaks down is therefore essential to realizing QAH effect at higher temperatures. Here a scanning tunneling microscope is used to directly map the size of exchange gap (E g,ex ) and its spatial fluctuation in the QAH insulator 5-layer MnBi 2 Te 4 . Long-range fluctuations of E g,ex are observed, with values ranging between 0 (gapless) and 70 meV, appearing to be uncorrelated to individual surface point defects. The breakdown of topological protection is directly imaged, showing that the gapless edge state, the hallmark signature of a QAH insulator, hybridizes with extended gapless regions in the bulk. Finally, it is unambiguously demonstrated that the gapless regions originate from magnetic disorder, by demonstrating that a small magnetic field restores E g,ex in these regions, explaining the recovery of topological protection in magnetic fields. The results indicate that overcoming magnetic disorder is the key to exploiting the unique properties of QAH insulators.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Efficient data-driven models for prediction and optimization of geothermal power plant operations

Increasing the capacity of geothermal energy as a renewable resource calls for development and deployment of efficient control and optimization technologies for geothermal power plants. A data-driven prediction and optimization model is presented as a cost-effective and efficient alternative to physics-based approach. The model predicts power output and operational cost by propagating the influence of control and disturbance variables within an artificial neural network (ANN). Numerical experiments with simulated and field data from a real geothermal power plant are first used to demonstrate the prediction performance of the ANN model. The model is then adopted to maximize the net predicted power production by automatically adjusting the working fluid circulation rate. The optimization performance of the model in evaluated using a thermodynamic flowsheet simulation model. The workflow is applied to model and control the effect of ambient temperature on an air-cooled binary cycle power plant, which is complex and costly to perform using a physics-based predictive model. As a result, the performance of the method is demonstrated by applying it to both simulated and field datasets from a binary cycle geothermal power plant.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Complex spin structure in co-trimer-chain Li 2 Co 3 Se 4 O 12

Complex magnetic materials are extremely attractive for revealing unconventional spin states and novel magnetic excitations. Here, we report the structural, thermodynamic, and magnetic properties of a novel magnetic material Li 2 Co 3 Se 4 O 12 based on x-ray and neutron diffraction, specific heat, magnetization, and x-ray photoelectron spectroscopy measurements. X-ray and neutron diffraction refinements reveal two Co sites Co (1) and Co (2) even though both are in the octahedral environment. While they are not connected along the b and c directions, these octahedra are edge-shared forming the Co (2) – Co (1) – Co (2) trimer chain along the a direction. The magnetic susceptibility exhibits the Curie-Weiss (CW) temperature dependence at high temperatures (above ∼50 K) with the negative CW temperature, a dip centered at T ⁎ ∼ 8.0 K, and an antiferromagnetic transition at T N = 3.3 K. The specific heat confirms that there is a phase transition at T N and a hump at T ⁎ . The long-range magnetic transition at T N implies that, in addition to the intra-chain interaction, there is strong inter-chain interaction, which is likely due to polarized SeO 3 bridging between chains. Single crystal neutron diffraction refinement reveals a complex magnetic structure with the angle between Co (1) and Co (2) moments ∼105°. Within the Co (2) – Co (1) – Co (2) trimer, two Co (2) moments are parallelly aligned. Surprisingly, the Co (1) moment (1.92μB) is only half of the Co (2) moment (3.96μB). There is likely the spin-state change for Co (1) from the high-spin state at T > T ⁎ to the low-spin state at T < T ⁎ , causing a dip in the magnetic susceptibility and a hump in the specific heat. When the magnetic field is applied, multiple metamagnetic transitions are found in all directions, implying field-driven magnetic excitations. Our results demonstrate rich magnetic properties of Li 2 Co 3 Se 4 O 12 that are sensitive to the external stimuli such as the magnetic field.

Antiferromagnetism↗
DOE OSTI2021

Tunable chiral symmetry breaking in symmetric Weyl materials

Asymmetric Weyl semimetals, which possess an inherently chiral structure, have different energies and dispersion relations for left- and right-handed fermions. They exhibit certain effects not found in symmetric Weyl semimetals, such as the quantized circular photogalvanic effect and the helical magnetic effect. In this work, we derive the conditions required for breaking chiral symmetry by applying an external field in symmetric Weyl semimetals. Here, we explicitly demonstrate that in certain materials with the T d point group, magnetic fields along low symmetry directions break the symmetry between left- and right-handed fermions; the symmetry breaking can be tuned by changing the direction and magnitude of the magnetic field. In some cases, we find an imbalance between the number of type I left- and right-handed Weyl cones (which is compensated by the number of type II cones of each chirality).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Advanced Photon Acceleration Schemes for Tunable XUV/Soft X-Ray Sources

We report on the advances made under the purview of DOE award number DE-SC0019135 that was active during the period: 09/01/2018–08/31/2021. The grant investigated the application of a “flying focus” to the problem of photon acceleration—in which a dynamic refractive index gradient is used to continuously upshift a probe beam’s frequency. Codes were written to describe the creation of ionization waves of arbitrary velocity (IWAVs) for use as a photon-accelerating medium, as well as the behavior of a witness pulse residing in said medium. Experiments first verified the spatiotemporal control over laser intensity provided by a chromatic flying focus, then used that ability to produce small-diameter IWAVs in the far-field with the expected dynamics, and finally demonstrated even further flexibility by producing large-diameter IWAVs in the laser quasi-far-field that maintained the beneficial dynamics. Multiple innovative diagnostics—spectrally resolved Schlieren and spectrally resolved interferometry—were pioneered in order to diagnose the IWAVs. For IWAV production in the laboratory, however, beam quality was identified as a key limitation in the quasi-far-field. Since the original chromatic flying focus was found to result in relatively long (ps duration) intensity peaks, which could limit some applications including photon acceleration, additional techniques were invented to provide similar spatiotemporal control while also retaining ultrashort intensity peaks. While simulations have identified several interesting regimes for photon acceleration—first predicting the upshift of a counterpropagating witness pulse from the optical to the extreme ultraviolet in less than 1 cm, and later obtaining similar shifts in less than 100 μm in a simpler self-seeded configuration—experimental demonstration is left for future work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Time-Dependent Boundary Modeling to Inform Design of SPARC Diagnostic and Actuators

The purpose of this work was to inform the design of diagnostic and actuator systems for a new experimental facility for Commonwealth Fusion Systems (CFS), called SPARC [Creely2020], using time-dependent plasma boundary simulations with the Scrape Off Layer Plasma Simulator (SOLPS) code [Wiesen2015]. The SPARC tokamak is a device that aims to demonstrate fusion energy production and high-field plasma operating scenarios. The developed technologies will be incorporated into a net-electricity pilot that will demonstrate approximately 200MW of electric power. A major difference from other private industry fusion companies is the use of a standard aspect ratio, but at a high magnetic field strength, which provides a well-established physics basis and a modest extrapolation to reactor operation. Time-dependent simulations were used to inform the design of main-chamber plasma facing components, which are protected by feedback control of the heat and particle loads during high power operation. The simulations provide the timescales and magnitudes of plasma and neutral particle response useful for determining the position and operation of diagnostics and actuators that will enable control. The plasma response and phase-space diagrams also provide input into advanced model-based control schemes, which are envisioned for later SPARC operation. Model-based control can reduce the risk of component failure, which would require expensive in-situ repairs and the associated delays, by predicting the system response to actuators over a short time-horizon.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Detecting Quantum Critical Points of Correlated Systems by Quantum Convolutional Neural Network Using Data from Variational Quantum Eigensolver

Machine learning has been applied to a wide variety of models, from classical statistical mechanics to quantum strongly correlated systems, for classifying phase transitions. The recently proposed quantum convolutional neural network (QCNN) provides a new framework for using quantum circuits instead of classical neural networks as the backbone of classification methods. We present the results from training the QCNN by the wavefunctions of the variational quantum eigensolver for the one-dimensional transverse field Ising model (TFIM). We demonstrate that the QCNN identifies wavefunctions corresponding to the paramagnetic and ferromagnetic phases of the TFIM with reasonable accuracy. The QCNN can be trained to predict the corresponding ‘phase’ of wavefunctions around the putative quantum critical point even though it is trained by wavefunctions far away. The paper provides a basis for exploiting the QCNN to identify the quantum critical point.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Current Status of the High Field Cable Test Facility at Fermilab

Fermi National Accelerator Laboratory (FNAL) and Lawrence Berkeley National Laboratory (LBNL) are collaborating to construct a new High Field Vertical Magnet Test Facility (HFVMTF) designed for testing superconducting cables in high magnetic fields. This state-of-the-art facility will be situated at Fermilab and will provide capabilities comparable to EDIPO at PSI and FRESCA2 at CERN. The HFVMTF’s background magnetic field, reaching 15 T, will be generated by a magnet supplied by LBNL. The HFVMTF is a collaborative effort supported by the US DOE Offices of Science, High Energy Physics, and Fusion Energy Sciences. It will serve as a vital testbed for superconducting HTS cables, subjecting them to high magnetic fields and a wide range of temperatures, benefiting both scientific communities. Additionally, this facility will play a key role in testing high-field superconducting magnet models and demonstrators, including hybrid magnets, developed by the US Magnet Development Pro gram (MDP). These hybrid magnets, utilizing both LTS and HTS superconductors, are significant advancements toward achieving 18+ T dipoles for future hadron-hadron colliders. The presentation outlines the current status of the facility, covering aspects such as construction progress, cryostat designs, top and lambda plates, and systems for powering, quench protection, and monitoring.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Early season prediction of within-field crop yield variability by assimilating CubeSat data into a crop model

Accurate early season predictions of crop yield at the within-field scale can be used to address a range of crop production, management, and precision agricultural challenges. While the remote sensing of within-field insights has been a research goal for many years, it is only recently that observations with the required spatio-temporal resolutions, together with efficient assimilation methods to integrate these into modeling frameworks, have become available to advance yield prediction efforts. Here we explore a yield prediction approach that combines daily high-resolution CubeSat imagery with the APSIM crop model. The approach employs APSIM to train a linear regression that relates simulated yield to simulated leaf area index (LAI). That relationship is then used to identify the optimal regression date at which the LAI provides the best prediction of yield: in this case, approximately 14 weeks prior to harvest. Instead of applying the regression on satellite imagery that is coincident, or closest to, the regression date, our method implements a particle filter that integrates CubeSat-based LAI into APSIM to provide end-of-season high-resolution (3 m) yield maps weeks before the optimal regression date. The approach is demonstrated on a rainfed maize field located in Nebraska, USA, where suitable collections of both imagery and in-situ data were available for assessment. The procedure does not require in-field data to calibrate the regression model, with results showing that even with a single assimilation step, it is possible to provide yield estimates with good accuracy up to 21 days before the optimal regression date. Yield spatial variability was reproduced reasonably well, with a strong correlation to independently collected measurements (R 2 = 0.73 and rRMSE = 12%). When the field averaged yield was compared, our approach reduced yield prediction error from 1 Mg/ha (control case based on a calibrated APSIM model), to 0.5 Mg/ha (using satellite imagery alone), and then to 0.2 Mg/ha (results with assimilation up to three weeks prior to the optimal regression date). Such a capacity to provide spatially explicit yield predictions early in the season has considerable potential to enhance digital agricultural goals and improve end-of-season yield predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Probing vibronic coherence in charge migration in molecules using strong-field sequential double ionization

We propose a scheme for probing vibronic coherence in charge migration in molecules utilizing strong-field sequential double ionization. To demonstrate the feasibility of this approach, we perform full simulations of a pump-probe scheme employing few-cycle intense infrared pulses for N 2 and O 2 . We predict that the vibronic coherence between the pumped states will be directly imprinted in experimental observables such as kinetic energy release spectra and branching ratios of the dissociative dications. Our simulations are based on the recently developed density matrix approach for sequential double ionization model, which is capable of efficiently accounting for molecular orientations and enabling direct comparison with experimental results. Lastly, our findings strongly encourage the use of this probing scheme in future charge migration experiments.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Artificial Soiling Replication of Field Losses on Commercial Photovoltaic Modules

Here, this study demonstrates the capabilities of an indoor artificial soiling approach developed to closely replicate the natural, cyclic soil accumulation processes in the field-dust suspension, deposition, and sedimentation/cementation-for a subtropical climate. In this work, a near-field environment is replicated in an artificial soiling cubic chamber through controlled regulation of humidity, temperature, dust type, and dust concentration, based on site-specific historical climate data. Two different models (MA and MB) of full-size commercial photovoltaic modules from a single manufacturer, installed side by side in the mid-Atlantic United States, were retrieved and subjected to artificial soiling experiments and various characterization measurements, including short-circuit current, colorimetry, reflectance, X-ray fluorescence, laser diffraction, and optical microscopy. Both in the field and in our improved field-representative artificial soiling tests, the MA model experienced roughly twice the soiling loss as the MB model. To closely replicate the field soiling losses for a site-specific climate, it is critical to include: 1) The use of field-collected dust with identical dust chemistry and particle distribution instead of standardized ISO 12103 Arizona Road dusts, 2) the use of only a small amount of field-collected dust inside the chamber during the deposition process (e.g., 0.15 g), and 3) the preconditioning of the surface coating for the partial/full dose of UV stress as experienced in the field during sunlight exposure and the abrasion as experienced in the field during regular module cleaning activities, if/as needed. The field-representative artificial soiling method developed here could potentially be adopted for rank ordering of various antisoiling coatings developed by researchers and industry stakeholders.

14 SOLAR ENERGY↗
DOE OSTI2025

Building confidence in models for complex barrier systems for radionuclides

The modeling and simulation of the Cement-clay Interaction-Diffusion field (CI-D) experiment at the Mont Terri site in Switzerland presented here demonstrates that it is possible to capture the multiscale physical and chemical features of natural and engineered barrier systems for radionuclides. The simulations are successfully carried out with the newly developed CrunchODiTi high-performance computing software that accounts for multiple continua, including a continuum representing the electrical double layer (EDL) developed along negatively charged clay particles in clay rock. The simulation also accounts for both the complex three-dimensional (3D) geometry, expected as the norm in a geological waste repository, and the anisotropy of the geological formation. In addition, the high resolution of the model makes it possible to include "skin effects" developed at the interface between highly reactive materials, in this case between the high pH cement and the circumneutral but electrostatic Opalinus Clay. The successful history matching with the field experiment demonstrates that the distinct geochemical and physical properties of the cement and the Opalinus Clay in the CI-D experiment can be accounted for. Such analyses are essential for developing a defensible safety case for the underground storage of radioactive waste.

Sarsenbayev, Dauren↗
DOE OSTI2025

DeFault: DEep‐Learning‐Based FAULT Delineation Using the IBDP Passive Seismic Data at the Decatur CO2 Storage Site

Abstract The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection offer vital insights into subsurface structures and the ability to monitor fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high‐quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, , specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain‐adaptation, allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using , the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of on a field case study involving injection related microseismic data from Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and could aid in potential damage induced by seismicity. Our results highlight the potential of as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. This research bolsters the understanding of subsurface characterization in CCUS, illustrating machine learning’s capacity to refine these methods. Ultimately, our work has significant implications for CCUS technology deployment, an essential strategy in combating climate change. Plain Language Summary In our quest to tackle climate change, we use a strategy known as carbon capture, utilization, and storage (CCUS) to keep greenhouse gases out of the atmosphere. This strategy relies heavily on our ability to understand what's happening deep under the earth's surface. To make sure we store super critical safely, we need to accurately map out the geological structure, especially faults, but this is tough without high‐quality data and complex computer programs. We've developed a new tool called “DeFault,” which uses advanced machine learning to improve how we find and map these underground features. “DeFault” is smart enough to learn from numerically simulated data and then apply what it’s learned to real‐world situations. It groups together seismic activity—tiny tremors and shifts in the earth—based on when and where they happen, which helps us spot where there might be cracks or faults. We tested “DeFault” in Illinois, where CO 2 is injected underground, and it successfully pinpointed where these tremors occurred and mapped out the faults, helping to prevent accidents accurately in the future. Our study shows that “DeFault” will be a powerful ally in making CCUS safer and more effective, especially for the Illinois Basin Decatur Project. Key Points Faults and fractures introduced by carbon storage can be monitored by passive seismicity DeFault algorithm enables an automatic process for accurate and efficient passive seismic event locating and clustering

58 GEOSCIENCES↗
DOE OSTI2019

Microscopic subsurface characterization of layered magnetic materials using magnetic resonance force microscopy

This project resulted in the following accomplishments: 1) The invention of scanned probe ferromagnetic resonance microscopy. Upon implementation and refinement this approach was used to measure static and dynamic magnetic resonance properties of ferromagnets with an unprecedented combination of spectral and spatial resolution. 2) Demonstration and study of spin pumping in a pristine ferromagnet across a boundary defined entirely by a magnetic field gradient, and so free of materials discontinuities. 3) First demonstrated highly efficient dynamic spin injection from Y 3 Fe 5 O 12 (YIG) into NiO, an antiferromagnetic (AF) insulator and robust spin propagation in AF NiO over distances up to 100-nm thickness; both spin injection and spin transport are mediated by the AF spin correlations. 4) Demonstration of exceptionally high efficiency conversion of spin current to charge current achieved in spin pumping from the dynamic magnetization of a ferromagnetic insulator into a variety of adjacent metal films. 5) Seminal study of the nature of spin-orbit coupling in d-electron metals that revealed the dominant sensitivity of the d-orbital moment to the d-electron count and revealing the important roles of both d-electron configuration and atomic number in the physics of the spin Hall effect. 6) Demonstration of observation of FMR by means of optically-detected NV diamond relaxometry that provided a highly sensitive, spatially resolved FMR detection method and revealed spin pumping across 100-nm length scales by means of dipolar coupling. 7) Using magnetic field localization, developed for FMR imaging, demonstrated a novel approach to discretizing spin wave modes to improve the characteristics of auto-oscillators driven by pure spin currents produced by the spin Hall effect. 8) We demonstrated large spin pumping signals from propagating high wavevector spinwaves in thin film YIG find that the spin pumping efficiency was insensitive to wavevector thus emphasizing the promise of thin YIG films for spinwave-based spintronics by allowing for predictable down-scaling of device dimensions and enabling a broad range of operational frequencies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗