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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

The spectral imaging facility: Setup characterization

The SPectral IMager (SPIM) facility is a laboratory visible infrared spectrometer developed to support space borne observations of rocky bodies of the solar system. Currently, this laboratory setup is used to support the DAWN mission, which is in its journey towards the asteroid 1-Ceres, and to support the 2018 Exo-Mars mission in the spectral investigation of the Martian subsurface. The main part of this setup is an imaging spectrometer that is a spare of the DAWN visible infrared spectrometer. The spectrometer has been assembled and calibrated at Selex ES and then installed in the facility developed at the INAF-IAPS laboratory in Rome. The goal of SPIM is to collect data to build spectral libraries for the interpretation of the space borne and in situ hyperspectral measurements of planetary materials. Given its very high spatial resolution combined with the imaging capability, this instrument can also help in the detailed study of minerals and rocks. In this paper, the instrument setup is first described, and then a series of test measurements, aimed to the characterization of the main subsystems, are reported. In particular, laboratory tests have been performed concerning (i) the radiation sources, (ii) the reference targets, and (iii) linearity of detector response; the instrumental imaging artifacts have also been investigated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Efficient Stochastic Inversion Using Adjoint Models and Kernel-PCA

Performing stochastic inversion on a computationally expensive forward simulation model with a high-dimensional uncertain parameter space (e.g. a spatial random field) is computationally prohibitive even with gradient information provided. Moreover, the ‘nonlinear’ mapping from parameters to observables generally gives rise to non-Gaussian posteriors even with Gaussian priors, thus hampering the use of efficient inversion algorithms designed for models with Gaussian assumptions. In this work, we propose a novel Bayesian stochastic inversion methodology, characterized by a tight coupling between a gradient-based Langevin Markov Chain Monte Carlo (LMCMC) method and a kernel principal component analysis (KPCA). This approach addresses the ‘curse-of-dimensionality’ via KPCA to identify a low-dimensional feature space within the high-dimensional and nonlinearly correlated spatial random field. Moreover, non-Gaussian full posterior probability distribution functions are estimated via an efficient LMCMC method on both the projected low-dimensional feature space and the recovered high-dimensional parameter space. We demonstrate this computational framework by integrating and adapting recent developments such as data-driven statistics-on-manifolds constructions and reduction-through-projection techniques to solve inverse problems in linear elasticity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Emerging mobile lidar technology to study boundary layer winds influenced by operating turbines

The development of a microjoule-class pulsed Doppler lidar and deployment of this compact system on mobile platforms such as aircraft, ships, or trucks have opened a new opportunity to characterize the dynamics of complex mesoscale wind flows. The PickUp-based Mobile Atmospheric Sounder (PUMAS) truck-based lidar system was recently used during the American Wake Experiment (AWAKEN) to assess the general structure of boundary layer (BL) wind and turbulence around wind turbines in central Oklahoma. Wind speed profiles averaged over PUMAS transects influenced by the operating turbines (waked flow) show a 1–2 m s −1 reduction compared to mean undisturbed (free flow) wind speed profiles. Spatial variability in wind speed was observed in time–height cross-sections at different distances from turbines. The wind speeds were about 9–12 m s −1 at 6 km distance compared to 5–7 m s −1 at the transects near the turbines. The PUMAS dataset from AWAKEN demonstrated the capability of the mobile Doppler lidar system to document spatial variability in wind flows at different distances from wind turbines and obtain quantitative estimates of wind speed reduction in the waked flow. The high-frequency, simultaneous measurements of the horizontal and vertical winds provide a new approach for characterizing dynamic processes critical for wind farm wake analyses.

17 WIND ENERGY↗
DOE OSTI2024

Polysulfide-incompatible additive suppresses spatial reaction heterogeneity of Li-S batteries

Rational electrolyte engineering for practical pouch cells remains elusive because the correlation between the cathode/solid-electrolyte interphase layer and cell-level reaction behavior is poorly understood. Here, by combining multiscale characterization and computational modeling, we show that—counter to the conventional perception of polysulfide-incompatible additives—the spontaneous reaction of sparingly solvated polysulfides with Lewis acid additives (LAAs) can induce in situ formation of a homogeneous interphase on thick and tortuous S cathode. Multiscale synchrotron X-ray characterization consistently affirms that such interface design could effectively eliminate the notorious problems of polysulfide shuttle and lithium corrosion and, more importantly, provide an interconnected “ion transport highway” to alleviate the uneven ion transport within the tortuous S cathode. Hence, this design dramatically reduces the reaction heterogeneity of lithium-sulfur (Li-S) pouch cells under lean electrolyte conditions. Further, this work resolves controversy around the role of polysulfide-incompatible additives in high-energy Li-S pouch cells and highlights the importance of suppressing reaction heterogeneity for practical batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Iron-bound organic carbon in forest soils: quantification and characterization

Abstract. Iron oxide minerals play an important role in stabilizing organic carbon (OC) and regulating the biogeochemical cycles of OC on the earth surface. To predict the fate of OC, it is essential to understand the amount, spatial variability, and characteristics of Fe-bound OC in natural soils. In this study, we investigated the concentrations and characteristics of Fe-bound OC in soils collected from 14 forests in the United States and determined the impact of ecogeographical variables and soil physicochemical properties on the association of OC and Fe minerals. On average, Fe-bound OC contributed 37.8 % of total OC (TOC) in forest soils. Atomic ratios of OC : Fe ranged from 0.56 to 17.7, with values of 1–10 for most samples, and the ratios indicate the importance of both sorptive and incorporative interactions. The fraction of Fe-bound OC in TOC (fFe-OC) was not related to the concentration of reactive Fe, which suggests that the importance of association with Fe in OC accumulation was not governed by the concentration of reactive Fe. Concentrations of Fe-bound OC and fFe-OC increased with latitude and reached peak values at a site with a mean annual temperature of 6.6 °C. Attenuated total reflectance–Fourier transform infrared spectroscopy (ATR-FTIR) and near-edge X-ray absorption fine structure (NEXAFS) analyses revealed that Fe-bound OC was less aliphatic than non-Fe-bound OC. Fe-bound OC also was more enriched in 13C compared to the non-Fe-bound OC, but C ∕ N ratios did not differ substantially. In summary, 13C-enriched OC with less aliphatic carbon and more carboxylic carbon was associated with Fe minerals in the soils, with values of fFe-OC being controlled by both sorptive and incorporative associations between Fe and OC. Overall, this study demonstrates that Fe oxides play an important role in regulating the biogeochemical cycles of C in forest soils and uncovers the governing factors for the spatial variability and characteristics of Fe-bound OC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Multi-modal characterization of nitrate reduction nano-catalysts with periodic strain distribution

Strain engineering serves as a pivotal strategy to optimize catalytic activity in electrocatalysis. However, the catalyst sizes under industrial conditions are usually large and even beyond nanometer regime. The critical methodological limitations on strain imaging of such catalysts with both large field of view and high spatial resolution obscure the mechanistic understanding of strain-performance correlations. Here, we present an optimized four-dimensional scanning transmission electron microscopy (4D-STEM) method to acquire strain mapping of both bulk and surface across particles up to 500 nm with 0.6 nm spatial resolution and 0.55% precision. We observe the ripple-like periodic strain coupled with elemental fluctuations inside a perovskite-type hydroxide CuCoSn(OH) 6 and find it correlated to electrocatalytic nitrate reduction (NO 3 – RR) absorption energy to achieve the 92.6% Faradaic efficiency and long-term test over 1000 h at membrane electrode assembly (MEA) for ammonia electrosynthesis. This universal framework design offers a practical method that not only develops an advanced measurement combining multi-modal characterization techniques but also reveals the intrinsic structure-property constitutive law of industry-level catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Probing the Structure and Dynamics of Fluid Mixtures in Porous Materials Through Ultrafast Vibrational Spectro-Microscopy and Many-Body Molecular Dynamics

This research program focused on the characterization of both molecular structure and dynamics of aqueous solutions in various metal-organic frameworks (MOFs) and organic polymers that have recently been proposed for applications in water treatment technologies. This was accomplished by integrating ultrafast vibrational spectroscopy and microscopy, which are sensitive to local environments, molecular orientation, and dynamical couplings, with many-body molecular dynamics (MB-MD) simulations, which enable realistic modeling of aqueous systems and porous materials under different thermodynamic conditions. Our studies allowed for identifying the physical mechanisms and characterizing the underlying molecular interactions between water and host materials that determine the adsorption and transport processes of water in various MOFs and β-cyclodextrin polymers – prototypical examples of porous materials and polymers, that have recently been proposed for technological applications in water purification. By combining bulk- and surface-sensitive, spatially resolved ultrafast vibrational spectroscopy with MB-MD simulations, it was possible to gain broad insight into the structure and mobility of water under heterogeneous confinement at various length scales. In particular, measurements of surface- and bulk-sensitive vibrational spectra at single crystal level, integrated with MB-MD simulations were used to characterize domain-specific, structure–binding affinity relationships. Besides providing specific information about the behavior of aqueous solutions in prototypical MOFs and organic polymers for potential applications in water treatment technologies, our studies also provided fundamental insights into the properties of aqueous solutions in confined heterogeneous environments, which have broad implications in many areas, ranging from heterogeneous catalysis to oil recovery, ion transport processes, and reaction-diffusion processes in crowded systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Arctic River Delta Morphologic Variability and Implications for Riverine Fluxes to the Coast

Arctic riverine fluxes are anticipated to increase as the Arctic warms and have a large impact on the Arctic ocean. Deltas modify the spatial and temporal distributions of riverine fluxes, but no thorough studies have been conducted to analyze Arctic delta morphologies to determine their influence on land–ocean fluxes. We performed an analysis of six high–latitude deltas (Colville, Kolyma, Lena, Mackenzie, Yenisei, and Yukon) to characterize delta morphologies and determine the influence of morphology on the distribution of fluxes to the coast. All six deltas deliver material to the coast at discrete locations across small areas despite differences in delta shoreline length. Large Arctic deltas exhibit large variability in channel width, which we hypothesize is due to a feedback with ice cover and retreat that favors the growth of large channels over geologic timescales. Spatial variability in island sizes suggests variability in channel activity, island nourishment, and susceptibility to drowning by sea level rise. Potential lake storage is highest on the Mackenzie delta, thus providing a means for reducing nutrient and sediment loading of the coastal ocean. Here, the connected lakes are also prevalent on the Colville and Yukon deltas, suggesting that these deltas can filter riverine fluxes even when the deltas are not flooded. Differences in Arctic delta morphologies can be explained by varying levels of riverine and marine influence, antecedent topography, and local channel dynamics. Ice cover also plays a large role in controlling Arctic delta morphologies and dynamics that has not been previously represented in interpretations of existing delta metrics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Automated Quantitative Analysis of Extended Irradiation Defects - Dislocations, Voids and Precipitates in Neutron Irradiated HT-9 Steel

Structural alloys that make up the core components of nuclear reactors are exposed to radiation that can substantially alter the microstructure and mechanical properties of the material. Irradiation can cause the formation of extended defects including dislocation line and loops, voids and various types of precipitates. To understand the irradiation effects, it is critical to characterize these defects individually and collectively to quantify how they evolve throughout irradiation stages. Transmission electron microscopy (TEM) is a standard tool for providing extensive size, number density and spatial distribution of extended irradiation defects, however, manual measurement of defect size and number density requires time-intensive effort to analyze enough defects that provide a statistically meaningful result and are prone to errors of subjectivity. In this work, we developed a set of MATLAB algorithms offering robust and automated identification and quantification of extended irradiation defects like dislocation lines, voids and precipitates commonly observed in neutron irradiated cladding alloys [1]. Using a neutron-irradiated HT-9 martensitic alloy irradiated at 412°C to 111.8 dpa, we demonstrate the capability of these algorithms for quantitative defect analysis. Figure 1 presents defect images of the HT-9 using an advanced diffraction contrast imaging scanning transmission electron microscopy (DCI STEM) that suppresses bend contours and provides better defect contrast compared to conventional TEM [2]. The first step of defect analysis is defect identification, a process that can be digitally achieved by contrast thresholding (for simple defect contrast) and by machine learning computer vision for defect semantic segmentation [3]. Here, labeled binary defect images (Figures 2a and 2c) were used. For dislocation density quantification, we employed an optimized circular-grid intersection method first introduced by Dr. John Steeds [4]. This method is shown in Figures 2a and 2b, where the number of intersections of dislocation lines with circular traces was measured. This produces an unbiased sampling of dislocation lines, regardless of their orientation. This process was optimized with automated digital intersection number and grid length registration. Interestingly, it was found that a relatively large number of circles in a set circular gird is was needed to produce an invariant result (Figure 2b), with a low systematic measurement error. This demonstrates the main advantage of computer-based defect analysis, in performing repetitive operations quickly with a reduced systematic error. For the quantitative analysis of voids and precipitates a challenge encountered with automated defect analysis is feature overlap, particularly when the density of voids/precipitates is high. To mitigate this problem, as shown in Figure 2d, we modified the popular circular Hough transformation and treated ‘circular shape’ as the particle descriptor for voids/precipitates, efficiently resolving the overlapping particles. In summary, this automated digital quantification together with machine learning enabled defect identification [3] opens new opportunities for standardizing the characterization workflow for quantitative analysis of extended irradiation defects.

Sainju, Rajat↗
DOE OSTI2022

Using aircraft measurements to characterize subgrid-scale variability of aerosol properties near the Atmospheric Radiation Measurement Southern Great Plains site

Abstract. Complex distributions of aerosol properties evolve in space and time as a function of emissions, new particle formation, coagulation, condensational growth, chemical transformation, phase changes, turbulent mixing and transport, removal processes, and ambient meteorological conditions. The ability of chemical transport models to represent the multi-scale processes affecting the life cycle of aerosols depends on their spatial resolution since aerosol properties are assumed to be constant within a grid cell. Subgrid-scale-dependent processes that affect aerosol populations could have a significant impact on the formation of particles, their growth to cloud condensation nuclei (CCN) sizes, aerosol–cloud interactions, dry deposition and rainout and hence their burdens, lifetimes, and radiative forcing. To address this issue, we characterize subgrid-scale variability in terms of measured aerosol number, size, composition, hygroscopicity, and CCN concentrations made by repeated aircraft flight paths over the Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystem (HI-SCALE) campaign. Subgrid variability is quantified in terms of both normalized frequency distributions and percentage difference percentiles using grid spacings of 3, 9, 27, and 81 km that represent those typically used by cloud-system-resolving models as well as the current and next-generation climate models. Even though the SGP site is a rural location, surprisingly large horizontal gradients in aerosol properties were frequently observed. For example, 90 % of the 3, 9, and 27 km cell mean organic matter concentrations differed from the 81 km cell around the SGP site by as much as ∼ 46 %, large spatial variability in aerosol number concentrations and size distributions were found during new particle formation events, and consequently 90 % of the 3, 9, and 27 km cell mean CCN number concentrations differed from the 81 km cell mean by as much as ∼ 38 %. The spatial variability varied seasonally for some aerosol properties, with some having larger spatial variability during the spring and others having larger variability during the late summer. While measurements at a single surface site cannot reflect the surrounding variability of aerosol properties at a given time, aircraft measurements that are averaged within an 81 km cell were found to be similar to many, but not all, aerosol properties measured at the ground SGP site. This analysis suggests that it is reasonable to directly compare most ground SGP site aerosol measurements with coarse global climate model predictions. In addition, the variability quantified by the aircraft can be used as an uncertainty range when comparing the surface point measurements with model predictions that use coarse grid spacings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Probing the Contribution of Lateral Pathways to Out–of–Plane Charge Transport in Organic Bulk Heterojunctions

The nanoscale interpenetrating electron donor–acceptor network in organic bulk heterojunction (BHJ) solar cells results in efficient charge photogeneration but creates complex 3D pathways for charge transport. At present, little is known about the extent to which out-of-plane charge flow relies on lateral electrical connectivity. In this work, a procedure, based on conductive atomic force microscopy, is introduced to quantify lateral current spreading during out-of-plane charge transport. Using the developed approach, the dependence of lateral spreading on BHJ phase separation, composition, and molecule type (small molecule vs polymer) is studied. In the small-molecule BHJ, 7,7'-(4,4-bis(2-ethylhexyl)-4H-silolo[3,2-b:4,5-b']dithiophene-2,6-diyl)bis(6-fluoro-4-(5'-hexyl-[2,2'-bithiophen]-5-yl)benzo[c]-[1,2,5]thiadiazole):(6,6)-Phenyl-C 71 -butyric acid methyl ester (p-DTS(FBTTh 2 ) 2 :PC 71 BM), an increase is observed in lateral hole current spreading as the population of donor crystallites, bearing an edge-on molecular orientation, is increased. When integrated into BHJs, the polymer donor poly(3-hexylthiophene-2,5-diyl) (P3HT) leads to greater lateral hole current spreading and more spatially uniform charge transport than the small-molecule donor, owing to in-plane charge transport along the polymer backbone. Finally, through the newly introduced electrical characterization scheme, these experiments bring to light the role of lateral electrical connectivity in assisting charge navigation across BHJs.

14 SOLAR ENERGY↗
DOE OSTI2017

The reason for a high Ca2+-sensitivity associated with Arg91Gly substitution in TPM2 gene is the abnormal behavior and high flexibility of tropomyosin during the ATPase cycle

Highlights: • Mutation R91G initiates abnormally high flexibility of β-tropomyosin (TM). • Troponin moves R91G-TM to the blocked position at low Ca{sup 2+}. • This mutation does not alter the ability of troponin to switch off actin monomers. • R91G-TM is located near the open position during the ATPase cycle at low Ca{sup 2+}. • Mutation R91G increases the fraction of rigor myosin heads at low Ca{sup 2+}. Substitution of Arg for Gly residue in 91th position in β-tropomyosin caused by a point mutation in TPM2 gene is associated with distal arthrogryposis, characterized by a high Ca{sup 2+}-sensitivity of myofilament and contracture syndrome. To understand the mechanisms of this defect, we studied multistep changes in mobility and spatial arrangement of tropomyosin, actin and myosin heads during the ATPase cycle in reconstituted ghost fibres, using the polarized fluorescence microscopy. The mutation was shown to markedly decrease the bending stiffness of β-tropomyosin in the thin filaments. In the absence of the myosin heads the mutation did not alter the ability of troponin to shift tropomyosin to the blocked position and to switch actin monomers off at low Ca{sup 2+}. During the ATPase cycle the movement of the mutant tropomyosin is restrained, it is located near the open position, which allows strong binding of the myosin heads to actin even at low Ca{sup 2+}. This may be the reason for both high Ca{sup 2+}-sensitivity and contractures associated with the Arg91Gly mutation. The use of reagents that decrease the Ca{sup 2+}sensitivity of the troponin complex may not be appropriate to restore muscle function in patients with this mutation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Ambient Metabolic Profiling and Imaging of Biological Samples with Ultrahigh Molecular Resolution using Laser Ablation Electrospray Ionization 21 Tesla FTICR Mass Spectrometry

Mass spectrometry (MS) has been an indispensable analytical tool in capturing the complexity and array of biomolecules within biological systems. However, conventional MS-based analytical workflows are limited in both throughput and measuring the native molecular state these systems, due in large part to sample handling and preparation. The development of ambient ionization methods capable of sampling directly from tissues circumvent many of these issues but requires the use of high-performance MS to resolve the molecular complexity within these samples. Herein, we demonstrate the unique combination of laser ablation electrospray ionization (LAESI) coupled with a 21 Tesla Fourier transform ion cyclotron resonance (21T-FTICR-MS) for MS imaging applications. This analytical platform provides isotopic fine structure information directly from native tissues, delivering a higher degree of confidence for molecular identification. The ability to capture and visualize the complex metabolic behavior of living organisms in situ is a bioanalytical grand challenge that has yet to be fully realized. Due to their excellent sensitivity and selectivity, mass spectrometry (MS)-based platforms offer a unique opportunity to characterize an array of biomolecules from a variety of biological samples.[1] One method in particular, MS imaging (MSI), has demonstrated the ability to simultaneously determine the spatial distributions for hundreds of biomolecules, e. g., metabolites, lipids, peptides, and xenobiotics, within complex biological systems simultaneously.[2-3] Matrix-assisted laser desorption/ionization (MALDI)-MSI remains the most common of these methods.[4] However, the application of an exogenous matrix, and the limited availability of commercial sources that operate under atmospheric pressure,[5] has significantly prohibited the ability of MALDI to be useful for biomolecular mapping of living systems. Ambient ionization methods that require minimal to no sample preparation, like desorption electrospray ionization (DESI and nano-DESI) and laser ablation electrospray ionization (LAESI), demonstrated the ability to spatially map biomolecule distributions within live organisms.

Mass Spectometry, fourier transform ion cyclostron↗
DOE OSTI2015

Characterization of a new electrostatic storage ring for photofragmentation experiments

We describe the design of and the first commissioning experiments with a newly constructed electrostatic storage ring named SAPHIRA (Storage Ring in Aarhus for PHoton-Ion Reaction Analysis). With an intense beam of Cu{sup −} at 4 keV, the storage ring is characterized in terms of the stored ion beam decay rate, the longitudinal spreading of an injected ion bunch, as well as the direct measurements of the transverse spatial distributions under different conditions of storage. The ion storage stability in SAPHIRA was investigated systematically in a selected region of its electrical configuration space.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Rapid retrieval of first-order spatiotemporal distortions for ultrashort laser pulses

High-intensity, ultrashort laser sources are a foundational pillar for High-Energy-Density (HED) physics, and as the repetition-rates of these systems increase, diagnostics must be developed to match their data collection speed. Characterization of any spatiotemporal distortions in the laser pulse is necessary in order to standardize results across facilities. Here, we have previously developed a laser diagnostic called Spatially and Temporally Resolved Intensity and Phase Evaluation Device: Full Information from a Single Hologram, or STRIPED FISH, to measure the full spatiotemporal laser electric field on a single shot. In order to provide rapid feedback, we here adapt the STRIPED FISH retrieval algorithm, which typically has computation times of up to 30 minutes due to the high spatial resolution of the device and its retrieval of the complete four-dimensional pulse field, to distill the key electric field quantities into a handful of scalars for rapid assessment of the pulse's first order distortions. Here, our new, rapid non-iterative retrieval algorithm is validated with simulated and experimental data, and it provides, within seconds, the same first-order information as given by the full analysis. This algorithm is suitable for on-shot assessment of spatiotemporal distortions and can be adapted to assess high repetition-rate laser quality in HED experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Linear systematics mitigation in galaxy clustering in the Dark Energy Survey Year 1 Data

ABSTRACT We implement a linear model for mitigating the effect of observing conditions and other sources of contamination in galaxy clustering analyses. Our treatment improves upon the fiducial systematics treatment of the Dark Energy Survey (DES) Year 1 (Y1) cosmology analysis in four crucial ways. Specifically, our treatment (1) does not require decisions as to which observable systematics are significant and which are not, allowing for the possibility of multiple maps adding coherently to give rise to significant bias even if no single map leads to a significant bias by itself, (2) characterizes both the statistical and systematic uncertainty in our mitigation procedure, allowing us to propagate said uncertainties into the reported cosmological constraints, (3) explicitly exploits the full spatial structure of the galaxy density field to differentiate between cosmology-sourced and systematics-sourced fluctuations within the galaxy density field, and (4) is fully automated, and can therefore be trivially applied to any data set. The updated correlation function for the DES Y1 redMaGiC catalogue minimally impacts the cosmological posteriors from that analysis. Encouragingly, our analysis does improve the goodness-of-fit statistic of the DES Y1 3 × 2pt data set (Δχ2 = −6.5 with no additional parameters). This improvement is due in nearly equal parts to both the change in the correlation function and the added statistical and systematic uncertainties associated with our method. We expect the difference in mitigation techniques to become more important in future work as the size of cosmological data sets grows.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Simultaneous Optical and Electrical Spin-Torque Magnetometry with Phase-sensitive Detection of Spin Precession

Spin-based coherent information processing and encoding utilize the precession phase of spins in magnetic materials. However, the detection and manipulation of spin precession phases remain a major challenge for advanced spintronic functionalities. By using simultaneous electrical and optical detection, we demonstrate the direct measurement of the spin precession phase of a permalloy device driven by the spin-orbit torques from adjacent heavy metals. The spin Hall angle of the heavy metals can be independently determined from concurrent electrical and optical signals. The phase-sensitive optical detection also allows spatially-resolved measurements of local spin-torque parameters and ferromagnetic resonance with comprehensive amplitude and phase information. Here, our study offers a route toward future advanced characterizations of spin-torque oscillators, magnonic circuits, and tunneling junctions, where measuring the current-induced spin dynamics of individual nanomagnets is required.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Structured illumination for surface-resolved grazing-incidence X-ray scattering

Grazing-incidence (GI) scattering techniques are widely used to characterize thin films, offering high surface sensitivity and insight into morphology and structure. However, these approaches typically provide statistical averaged information due to elongated footprint or limited spatial resolution due to beam size. Here we introduce a method that combines structured illumination with GI X-ray scattering and leverages our computational imaging approach to resolve local structural details. We demonstrate that our method captures local features of an organic semiconductor thin film without the need for sample rotation as in tomography. The method expands GI techniques from statistical averaging to high-resolution imaging, thereby providing the capability for detailed analysis of local material properties, such as domain shape, orientation and polymorphism, which are critical for advancing material design towards more efficient and tailored materials.

97 MATHEMATICS AND COMPUTING↗