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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 739 records · Page 41

On the effects of a weak magnetic field on turbulent transport

We discuss the effects of a weak large-scale magnetic field on turbulent transport. We show by means of a series of two-dimensional numerical experiments that turbulent diffusion can be effectively suppressed by a (large scale) magnetic field whose energy is small compared to equipartition. The suppression mechanism is associated with a subtle modification of the Lagrangian energy spectrum, and it does not require any substantial reduction of the turbulent amplitude. We exploit the relation between diffusion and random walking to emphasize that the effect of a large-scale magnetic field is to induce a long-term memory in the field of turbulence. The implications of the general case of three-dimensional transport are briefly discussed.

Cattaneo, F.↗

Fluid Physics Under a Stochastic Acceleration Field

The research summarized in this report has involved a combined theoretical and computational study of fluid flow that results from the random acceleration environment present onboard space orbiters, also known as g-jitter. We have focused on a statistical description of the observed g-jitter, on the flows that such an acceleration field can induce in a number of experimental configurations of interest, and on extending previously developed methodology to boundary layer flows. Narrow band noise has been shown to describe many of the features of acceleration data collected during space missions. The scale of baroclinically induced flows when the driving acceleration is random is not given by the Rayleigh number. Spatially uniform g-jitter induces additional hydrodynamic forces among suspended particles in incompressible fluids. Stochastic modulation of the control parameter shifts the location of the onset of an oscillatory instability. Random vibration of solid boundaries leads to separation of boundary layers. Steady streaming ahead of a modulated solid-melt interface enhances solute transport, and modifies the stability boundaries of a planar front.

Vinals, Jorge↗

Spectroscopic Signatures of Phonon Character in Molecular Electron Spin Relaxation

Spin–lattice relaxation constitutes a key challenge for the development of quantum technologies, as it destroys superpositions in molecular quantum bits (qubits) and magnetic memory in single molecule magnets (SMMs). Gaining mechanistic insight into the spin relaxation process has proven challenging owing to a lack of spectroscopic observables and contradictions among theoretical models. Here, we use pulse electron paramagnetic resonance (EPR) to profile changes in spin relaxation rates (T 1 ) as a function of both temperature and magnetic field orientation, forming a two-dimensional data matrix. For randomly oriented powder samples, spin relaxation anisotropy changes dramatically with temperature, delineating multiple regimes of relaxation processes for each Cu(II) molecule studied. We show that traditional T 1 fitting approaches cannot reliably extract this information. Single-crystal T 1 anisotropy experiments reveal a surprising change in spin relaxation symmetry between these two regimes. We interpret this switch through the concept of a spin relaxation tensor, enabling discrimination between delocalized lattice phonons and localized molecular vibrations in the two relaxation regimes. Variable-temperature T 1 anisotropy thus provides a unique spectroscopic method to interrogate the character of nuclear motions causing spin relaxation and the loss of quantum information.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spin-crossover complexes: Self-interaction correction vs density correction

Complexes containing a transition metal atom with a 3d 4 –3d 7 electron configuration typically have two low-lying, high-spin (HS) and low-spin (LS) states. The adiabatic energy difference between these states, known as the spin-crossover energy, is small enough to pose a challenge even for electronic structure methods that are well known for their accuracy and reliability. In this work, we analyze the quality of electronic structure approximations for spin-crossover energies of iron complexes with four different ligands by comparing energies from self-consistent and post-self-consistent calculations for methods based on the random phase approximation and the Fermi–Löwdin self-interaction correction. Considering that Hartree–Fock densities were found by Song et al., J. Chem. Theory Comput. 14, 2304 (2018), to eliminate the density error to a large extent, and that the Hartree–Fock method and the Perdew–Zunger-type self-interaction correction share some physics, we compare the densities obtained with these methods to learn their resemblance. Here, we find that evaluating non-empirical exchange-correlation energy functionals on the corresponding self-interaction-corrected densities can mitigate the strong density errors and improves the accuracy of the adiabatic energy differences between HS and LS states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Total absorption spectroscopy of the β decay of 101,102 Zr and 109 Tc

The β decay of 101,102 Zr and 109 Tc was studied using the technique of total absorption spectroscopy. The experiment was performed at the National Superconducting Cyclotron Laboratory using the Summing NaI(Tl) (SuN) detector in the first-ever application of total absorption spectroscopy with a fast beam produced via projectile fragmentation. The β -decay feeding intensity and Gamow-Teller transition strength distributions were extracted for these three decays. The extracted distributions were compared to three different quasiparticle random-phase approximation (QRPA) models based on different mean-field potentials. A comparison with calculations from one of the QRPA models was performed to learn about the ground-state shape of the parent nucleus. For 101 Zr and 102 Zr, calculations assuming a pure shape configuration (oblate or prolate) were not able to reproduce the extracted distributions. These results may indicate that some type of mixture between oblate and prolate shapes is necessary to reproduce the extracted distributions. For 109 Tc, a comparison of the extracted distributions with QRPA calculations suggests a dominant oblate configuration. The other two QRPA models are commonly used to provide β-decay properties in r-process network calculations. This work shows the importance of making comparisons between the experimental and theoretical β-decay distributions, rather than just half-lives and β-delayed neutron emission probabilities, as close to the r-process path as possible.

79 ASTRONOMY AND ASTROPHYSICS↗

Real Space Quantum Cluster Formulation for the Typical Medium Theory of Anderson Localization

We develop a real space cluster extension of the typical medium theory (cluster-TMT) to study Anderson localization. By construction, the cluster-TMT approach is formally equivalent to the real space cluster extension of the dynamical mean field theory. Applying the developed method to the 3D Anderson model with a box disorder distribution, we demonstrate that cluster-TMT successfully captures the localization phenomena in all disorder regimes. As a function of the cluster size, our method obtains the correct critical disorder strength for the Anderson localization in 3D, and systematically recovers the re-entrance behavior of the mobility edge. From a general perspective, our developed methodology offers the potential to study Anderson localization at surfaces within quantum embedding theory. This opens the door to studying the interplay between topology and Anderson localization from first principles.

36 MATERIALS SCIENCE↗

The particle background observed by the X-ray detectors onboard Copernicus

The design and characteristics of low energy detectors on the Copernicus satellite are described. The functions of the sensors in obtaining data on the particle background. The procedure for processing the data obtained by the satellite is examined. The most significant positive deviations are caused by known weak X-ray sources in the field of view. In addition to small systemic effects, occasional random effects where the count rate increases suddenly and decreases within a few frames are analyzed.

Davison, P. J. N.↗

A technique for evaluating the influence of spatial sampling on the determination of global mean total columnar ozone

A technique is described for providing a means of evaluating the influence of spatial sampling on the determination of global mean total columnar ozone. A finite number of coefficients in the expansion are determined, and the truncated part of the expansion is shown to contribute an error to the estimate, which depends strongly on the spatial sampling and is relatively insensitive to data noise. First and second order statistics are derived for each term in a spherical harmonic expansion which represents the ozone field, and the statistics are used to estimate systematic and random errors in the estimates of total ozone.

Tolson, R. H.↗

Scale lengths in quasi-parallel shocks

A review was carried out of ISEE and Voyager spacecraft magnetometer data to determine if quasi-parallel bow shocks are really broad, disordered regions. The key parameter was the deceleration scale (thickness, Lp) across which random energy would need to increase and a localized electrostatic field (E) would be present. Lp would define the breadth of the shock and be associated with a plasma deceleration. The ISEE 1 satellite collected data on the electron density, bulk speed, magnetic intensity, and electron temperature in November 1977 during five traverses of the bow shock. Similar data were gathered from an interplanetary shock wave in 1981. The evidence supported the concept of a plasma deceleration across a thin layer (Lp) in both types of shocks. The layers were about 50 times (interplanetary) and 20 times (earth) thinner than surrounding magnetic fluctuation regions. It is asserted that the regions of deceleration, although much thinner, are the actual shocks and not the entire regions of magnetic fluctuations.

Scudder, J. D.↗

Accurate Visual Heading Estimation at High Rotation Rate Without Oculomotor or Static-Depth Cues

It has been claimed that either oculomotor or static depth cues provide the signals about self-rotation necessary approx.-1 deg/s. We tested this hypothesis by simulating self-motion along a curved path with the eyes fixed in the head (plus or minus 16 deg/s of rotation). Curvilinear motion offers two advantages: 1) heading remains constant in retinotopic coordinates, and 2) there is no visual-oculomotor conflict (both actual and simulated eye position remain stationary). We simulated 400 ms of rotation combined with 16 m/s of translation at fixed angles with respect to gaze towards two vertical planes of random dots initially 12 and 24 m away, with a field of view of 45 degrees. Four subjects were asked to fixate a central cross and to respond whether they were translating to the left or right of straight-ahead gaze. From the psychometric curves, heading bias (mean) and precision (semi-interquartile) were derived. The mean bias over 2-5 runs was 3.0, 4.0, -2.0, -0.4 deg for the first author and three naive subjects, respectively (positive indicating towards the rotation direction). The mean precision was 2.0, 1.9, 3.1, 1.6 deg. respectively. The ability of observers to make relatively accurate and precise heading judgments, despite the large rotational flow component, refutes the view that extra-flow-field information is necessary for human visual heading estimation at high rotation rates. Our results support models that process combined translational/rotational flow to estimate heading, but should not be construed to suggest that other cues do not play an important role when they are available to the observer.

Stone, Leland S.↗

Advancing Methodologies for Applying Machine Learning and Evaluating Spatiotemporal Models of Fine Particulate Matter (PM 2.5 ) Using Satellite Data Over Large Regions

Reconstructing the distribution of fine particulate matter (PM 2.5 ) in space and time, even far from ground monitoring sites, is an important exposure science contribution to epidemiologic analyses of PM 2.5 health impacts. Flexible statistical methods for prediction have demonstrated the integration of satellite observations with other predictors, yet these algorithms are susceptible to overfitting the spatiotemporal structure of the training datasets. We present a new approach for predicting PM 2.5 using machine-learning methods and evaluating prediction models for the goal of making predictions where they were not previously available. We apply extreme gradient boosting (XGBoost) modeling to predict daily PM 2.5 on a 1 x 1 km 2 resolution for a 13 state region in the Northeastern USA for the years 2000–2015 using satellite-derived aerosol optical depth and implement a recursive feature selection to develop a parsimonious model. We demonstrate excellent predictions of withheld observations but also contrast an RMSE of 3.11 μg/m 3 in our spatial cross-validation withholding nearby sites versus an overfit RMSE of 2.10 μg/m 3 using a more conventional random ten-fold splitting of the dataset. As the field of exposure science moves forward with the use of advanced machine-learning approaches for spatiotemporal modeling of air pollutants, our results show the importance of addressing data leakage in training, overfitting to spatiotemporal structure, and the impact of the predominance of ground monitoring sites in dense urban sub-networks on model evaluation. The strengths of our resultant modeling approach for exposure in epidemiologic studies of PM 2.5 include improved efficiency, parsimony, and interpretability with robust validation while still accommodating complex spatiotemporal relationships.

air pollution↗

Performance of a 2-micrometer coherent Doppler lidar for wind measurements

Measurements of boundary layer winds are presented using a 2-micrometer coherent Doppler lidar and the optimal performance of the maximum likelihood estimator. The systematic error for single-shot estimates was estimated as 3.6 cm/s using measurements from a stationary hard target. The estimation error for measurements of the radial component of the wind field was determined, as well as the fraction of the estimates that are randomly distributed over the velocity search space, when the signal power is low and speckle fading is important. The results from actual data are compared with the results from ideal simulations. The first direct estimation of the spatial structure function of the radial wind field and of the energy dissipation rate is presented for both horizontal and vertical directions of propagation. The rms estimation error of the velocity estimates is found to be within 30% of ideal performance based on simulation.

Frehlich, Rod↗

Determining The Nanoflare Heating Frequency of an X-Ray Bright Point Observed by MaGIXS

Nanoflares are thought to be one of the prime candidates that can heat the solar corona to its multi-million kelvin temperature. Individual nanoflares are difficult to detect with the present generation instruments, however their presence can be inferred by comparing simulated nanoflare-heated plasma emissions with the observed emission. Using HYDRAD coronal loop simulations, we model the emission from an X-ray bright point (XBP) observed by the Marshall Grazing Incidence X-ray Spectrometer (MaGIXS), along with nearest-available observations from the Atmospheric Imaging Assembly (AIA) onboard Solar Dynamics Observatory (SDO) and X-Ray Telescope (XRT) onboard Hinode observatory. The length and magnetic field strength of the coronal loops are derived from the linear-force-free extrapolation of the observed photospheric magnetogram by Helioseismic and Magnetic Imager (HMI) onboard SDO. Each loop is assumed to be heated by random nanoflares, whose magnitude and frequency are determined by the loop length and magnetic field strength. The simulation results are then compared and matched against the measured intensity from AIA, XRT, and MaGIXS. Our model results indicate the observed emissions from the XBP under study could be well matched by a distribution of nanoflares with average delay times 1500 s to 3000 s, which suggest that the heating is dominated by high-frequency events. Further, we demonstrate the high sensitivity of MaGIXS and XRT to diagnose the heating frequency using this method, while AIA passbands are found to be the least sensitive.

coronal heating↗

Interplanetary field enhancements in the solar wind Statistical properties at 0.72 AU

A new class of disturbance in the interplanetary magnetic field has been discovered. This disturbance consists of an enhancement in the magnetic field strength lasting tens of minutes to hours. The strength of the enhancement is variable ranging up to over double the background field strength. The peak field pressure can be as high as 10 percent of the solar wind dynamic pressure. These events occur randomly with respect to the position of the spacecraft relative to Venus but not randomly with respect to Venus solar ecliptic longitude. There is a significant tendency for these events to cluster near certain ecliptic longitudes. The field distortion is often greater in the direction perpendicular to the solar wind flow rather than along it. These characteristics suggest that the source of the disturbances are weakly outgassing objects, possibly dispersed along their orbits such as in meteor streams.

Russell, C. T.↗

On-Orbit Multi-Field Wavefront Control with a Kalman Filter

A document describes a multi-field wavefront control (WFC) procedure for the James Webb Space Telescope (JWST) on-orbit optical telescope element (OTE) fine-phasing using wavefront measurements at the NIRCam pupil. The control is applied to JWST primary mirror (PM) segments and secondary mirror (SM) simultaneously with a carefully selected ordering. Through computer simulations, the multi-field WFC procedure shows that it can reduce the initial system wavefront error (WFE), as caused by random initial system misalignments within the JWST fine-phasing error budget, from a few dozen micrometers to below 50 nm across the entire NIRCam Field of View, and the WFC procedure is also computationally stable as the Monte-Carlo simulations indicate. With the incorporation of a Kalman Filter (KF) as an optical state estimator into the WFC process, the robustness of the JWST OTE alignment process can be further improved. In the presence of some large optical misalignments, the Kalman state estimator can provide a reasonable estimate of the optical state, especially for those degrees of freedom that have a significant impact on the system WFE. The state estimate allows for a few corrections to the optical state to push the system towards its nominal state, and the result is that a large part of the WFE can be eliminated in this step. When the multi-field WFC procedure is applied after Kalman state estimate and correction, the stability of fine-phasing control is much more certain. Kalman Filter has been successfully applied to diverse applications as a robust and optimal state estimator. In the context of space-based optical system alignment based on wavefront measurements, a KF state estimator can combine all available wavefront measurements, past and present, as well as measurement and actuation error statistics to generate a Maximum-Likelihood optimal state estimator. The strength and flexibility of the KF algorithm make it attractive for use in real-time optical system alignment when WFC alone cannot effectively align the system.

Lou, John↗

Semiconductor Crystal Growth in Static and Rotating Magnetic fields

Magnetic fields have been applied during the growth of bulk semiconductor crystals to control the convective flow behavior of the melt. A static magnetic field established Lorentz forces which tend to reduce the convective intensity in the melt. At sufficiently high magnetic field strengths, a boundary layer is established ahead of the solid-liquid interface where mass transport is dominated by diffusion. This can have a significant effect on segregation behavior and can eliminate striations in grown crystals resulting from convective instabilities. Experiments on dilute (Ge:Ga) and solid solution (Ge-Si) semiconductor systems show a transition from a completely mixed convective state to a diffusion-controlled state between 0 and 5 Tesla. In HgCdTe, radial segregation approached the diffusion limited regime and the curvature of the solid-liquid interface was reduced by a factor of 3 during growth in magnetic fields in excess of 0.5 Tesla. Convection can also be controlled during growth at reduced gravitational levels. However, the direction of the residual steady-state acceleration vector can compromise this effect if it cannot be controlled. A magnetic field in reduced gravity can suppress disturbances caused by residual transverse accelerations and by random non-steady accelerations. Indeed, a joint program between NASA and the NHMFL resulted in the construction of a prototype spaceflight magnet for crystal growth applications. An alternative to the suppression of convection by static magnetic fields and reduced gravity is the imposition of controlled steady flow generated by rotating magnetic fields (RMF)'s. The potential benefits of an RMF include homogenization of the melt temperature and concentration distribution, and control of the solid-liquid interface shape. Adjusting the strength and frequency of the applied magnetic field allows tailoring of the resultant flow field. A limitation of RMF's is that they introduce deleterious instabilities above a critical magnetic field value. Growth conditions in which static magnetic fields rotational magnetic fields, and reduced gravitational levels can have a beneficial role will be described.

Volz, Martin↗

Understanding and control of Zener pinning via phase field and ensemble learning

Zener pinning refers to the dispersion of fine particles which influences grain size distribution via movement of grain boundaries in a polycrystalline material. Grain size distribution in polycrystals has a significant impact on their properties including physical, chemical, mechanical, and optical to name a few. We explore the use of Phase-field modeling and machine-learning techniques to understand and improve the control of grain size distribution via Zener pinning in polycrystalline materials. We develop a machine learning model that determines the relative importance of various parameters to exercise microstructure control via Zener pinning. Our workflow combines high-throughput phase-field simulations and machine learning to address the computational bottlenecks associated with large-scale simulations as well as identify features necessary for microstructure control in polycrystals. A random forest (RF) regression model was developed to predict grain sizes based on five Phase-field model parameters, achieving an average prediction error of 0.72 nm for the training data and 1.44 nm for the test data. The importance of the input parameters is analyzed using the SHapley Additive exPlanations (SHAP) approach which reveals that diffusivity, volume fraction, and particle diameter are the most important parameters in determining the final grain size. These findings will allow us to select the best second-phase particles, optimize grain size distributions and thus design microstructures with the desired properties. The developed method is a highly versatile and generalizable approach that can be used to assess the combined effects of individual features in the presence of multiple variables.

36 MATERIALS SCIENCE↗