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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Characterizing Defects Inside Hexagonal Boron Nitride Using Random Telegraph Signals in van der Waals 2D Transistors

Single-crystal hexagonal boron nitride (hBN) is used extensively in many two-dimensional electronic and quantum devices, where defects significantly impact performance. Therefore, characterizing and engineering hBN defects are crucial for advancing these technologies. Here, we examine the capture and emission dynamics of defects in hBN by utilizing low-frequency noise (LFN) spectroscopy in hBN-encapsulated and graphene-contacted MoS 2 field-effect transistors (FETs). The low disorder of this heterostructure allows the detection of random telegraph signals (RTS) in large device dimensions of 100 μm 2 at cryogenic temperatures. Analysis of gate bias- and temperature-dependent LFN data indicate that RTS originates from a single trap species within hBN. By performing multi-space density functional theory (MS-DFT) calculations on a gated defective hBN/MoS 2 heterostructure model, we assign substitutional carbon atoms in boron sites as the atomistic origin of RTS. This study demonstrates the utility of LFN spectroscopy combined with MS-DFT analysis on a low-disorder all-vdW FET as a powerful means for characterizing the atomistic defects in single-crystal hBN.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Boosting H I -Galaxy Cross-Clustering Signal through Higher-Order Cross-Correlations

After reionization, neutral hydrogen (${\rm H\, \small {I}}$) traces the large-scale structure (LSS) of the Universe, enabling ${\rm H\, \small {I}}$ intensity mapping (IM) to capture the LSS in 3D and constrain key cosmological parameters. We present a new framework utilizing higher-order cross-correlations to study ${\rm H\, \small {I}}$ clustering around galaxies, tested using real-space data from the IllustrisTNG300 simulation. This approach computes the joint distributions of k-nearest neighbor (kNN) optical galaxies and the ${\rm H\, \small {I}}$ brightness temperature field smoothed at relevant scales (the kNN-field framework), providing sensitivity to all higher-order cross-correlations, unlike two-point statistics. To simulate ${\rm H\, \small {I}}$ data from actual surveys, we add random thermal noise and apply a simple foreground cleaning model, filtering out Fourier modes of the brightness temperature field with k ∥ < k min,∥ . Under current levels of thermal noise and foreground cleaning, typical of a Canadian Hydrogen Intensity Mapping Experiment (CHIME)-like survey, the ${\rm H\, \small {I}}$-galaxy cross-correlation signal in our simulations, using the kNN-field framework, is detectable at >30σ across r = [3, 12] h –1 Mpc. In contrast, the detectability of the standard two-point correlation function (2PCF) over the same scales depends strongly on the foreground filter: a sharp k ∥ filter can spuriously boost detection to 8σ due to position-space ringing, whereas a less sharp filter yields no detection. Nonetheless, we conclude that kNN-field cross-correlations are robustly detectable across a broad range of foreground filtering and thermal noise conditions, suggesting their potential for enhanced constraining power over 2PCFs.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1975

The large-scale magnetic field in the solar wind

A large-scale, three dimensional magnetic field in the interplanetary medium with an expected classical spiral pattern to zeroth order is discussed. Systematic and random deviations which are expected are treated. The sector structure which should be evident at high latitudes is examined. Interplanetary streams are discussed as determining the patterns of magnetic field intensity. It was proposed that the large-scale spiral field can induce a meridional flow which might alter the field geometry somewhat. The nonuniformities caused by streams will probably significantly influence the motion of solar and galactic particles. It was concluded that knowledge of the 3-dimensional field and its dynamical effects can be obtained by in situ measurements by a probe which goes over the sun's poles. Diagrams of the magnetic fields are given.

Burlaga, L. F.↗
NASA NTRS1977

Optimal spatial sampling techniques for ground truth data in microwave remote sensing of soil moisture

The paper examines optimal sampling techniques for obtaining accurate spatial averages of soil moisture, at various depths and for cell sizes in the range 2.5-40 acres, with a minimum number of samples. Both simple random sampling and stratified sampling procedures are used to reach a set of recommended sample sizes for each depth and for each cell size. Major conclusions from statistical sampling test results are that (1) the number of samples required decreases with increasing depth; (2) when the total number of samples cannot be prespecified or the moisture in only one single layer is of interest, then a simple random sample procedure should be used which is based on the observed mean and SD for data from a single field; (3) when the total number of samples can be prespecified and the objective is to measure the soil moisture profile with depth, then stratified random sampling based on optimal allocation should be used; and (4) decreasing the sensor resolution cell size leads to fairly large decreases in samples sizes with stratified sampling procedures, whereas only a moderate decrease is obtained in simple random sampling procedures.

Rao, R. G. S.↗
DOE OSTI2021

State densities of heavy nuclei in the static-path plus random-phase approximation

We report that nuclear state densities are important inputs to statistical models of compound-nucleus reactions. State densities are often calculated with self-consistent mean-field approximations that do not include important correlations and must be augmented with empirical collective enhancement factors. Here, we benchmark the static-path plus random-phase approximation (SPA + RPA) to the state density in a chain of samarium isotopes 148–155 Sm against exact results (up to statistical errors) obtained with the shell-model Monte Carlo (SMMC) method. The SPA + RPA method incorporates all static fluctuations beyond the mean field together with small-amplitude quantal fluctuations around each static fluctuation. Using a pairing plus quadrupole interaction, we show that the SPA + RPA state densities agree well with the exact SMMC densities for both the even- and odd-mass isotopes. For the even-mass isotopes, we also compare our results with mean-field state densities calculated with the finite-temperature Hartree-Fock-Bogoliubov (HFB) approximation. We find that the SPA + RPA repairs the deficiencies of the mean-field approximation associated with broken rotational symmetry in deformed nuclei and with the violation of particle-number conservation in the pairing condensate. In particular, in deformed nuclei the SPA + RPA reproduces the rotational enhancement of the state density relative to the mean-field state density.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Machine Learning Inference of Random Medium Properties

Earth materials are heterogeneous across a range of spatial scales, but the resolvability of small structures is limited by sparse data coverage, noise, bandlimitedness, and other difficulties. In practice, heterogeneities below a certain size cannot be recovered from seismic data except through statistical medium descriptions, which even then can be difficult to uniquely determine. To improve the characterization of such heterogeneities, we develop a novel supervised machine learning (ML) model that provides insight about the recoverability of statistical medium properties from elastic waveform data and succeeds despite cycle-skipping and other challenges well known from elastic waveform inversion. We demonstrate the approach using random media generated by superimposing self-affine random variations on homogeneous and layered background structures. After training on sparsely-recorded, high-frequency waveforms from hundreds of different random medium realizations, we show the ability of our ML model to recover correlation lengths and other statistical properties of interest to near-surface and crustal seismology, among other fields. For frequency passbands and spatial offsets encountered in seismology, Gaussian correlation lengths and the amplitude of the random variations relative to the background model are recovered even in challenging scenarios involving unknown medium parameters, complex crustal structures, and low signal-to-noise ratio. In comparison, von Kármán correlation lengths, which are related to larger-wavelength variations of the medium than Gaussian correlation lengths, are not as well recovered. These results provide one of the first and most systematic investigations of the recoverability of statistical properties of heterogeneities below the resolution limit of deterministic seismic tomography, and suggest practical ML strategies for high-frequency waveform seismology.

58 GEOSCIENCES↗
NASA NTRS1990

The effects of fixation and restricted visual field on vection-induced motion sickness

Approximately 60 percent of healthy human subjects experience motion sickness when exposed to a rotating optokinetic drum. Here, the effects of certain visual factors on susceptibility to motion sickness were determined. Vection data (illusory self-motion), horizontal eye movement recordings, subjective motion sickness report, and a measure of gastric myoelectric activity were obtained from 45 subjects, who were randomly divided into the following three groups: a control group that observed the entire visual field with no fixation, a group that fixated on a central target, and a third group that had a visual field restricted to 15 deg. The experimental session was divided into three 12-min periods: baseline, drum rotation, and recovery. The results showed that fixation greatly reduced nystagmus and slightly reduced vection. The restricted visual field slightly reduced nystagmus and greatly reduced vection. Both of these manipulations significantly reduced symptoms of motion sickness and abnormal gastric myoelectric activity.

Stern, Robert M.↗
DOE OSTI2025

Randomized Adiabatic Quantum Linear Solver Algorithm with Optimal Complexity Scaling and Detailed Running Costs

Solving linear systems of equations is a fundamental problem with a wide variety of applications across many fields of science, and there is increasing effort to develop quantum linear solver algorithms. Subaşı et al. [Phys. Rev. Lett. 122, 060504 (2019)] proposed a randomized algorithm inspired by adiabatic quantum computing, based on a sequence of random Hamiltonian simulation steps, with suboptimal scaling in the condition number 𝜅 of the linear system and the target error 𝜖. Here we go beyond these results in several ways. Firstly, using filtering [Lin and Tong, Quantum 4, 361 (2020)] and Poissonization techniques [Cunningham and Roland, ArXiv:2406.03972 (2024)], the algorithm complexity is improved to the optimal scaling 𝑂⁡(𝜅⁢log (1/𝜖))—an exponential improvement in 𝜖, and a shaving of a log 𝜅 scaling factor in 𝜅. Secondly, the algorithm is further modified to achieve constant factor improvements, which are vital as we progress towards hardware implementations on fault-tolerant devices. We introduce a cheaper randomized walk operator method replacing Hamiltonian simulation—which also removes the need for potentially challenging classical precomputations; randomized routines are sampled over optimized random variables; circuit constructions are improved. We obtain a closed formula rigorously upper bounding the expected number of times one needs to apply a block-encoding of the linear system matrix to output a quantum state encoding the solution to the linear system. The upper bound is 837⁢𝜅 at 𝜖 = 10 −10 for Hermitian matrices.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2020

Designing an Optimal Ensemble Strategy for GMAO S2S Forecast System

GMAO Sub/Seasonal prediction system (S2S) is being readied for a major upgrade to GEOS-S2S Version 3. An important factor in successful extended range forecast is the definition of an ensemble For initialization of the ensemble we propose a combination of lagged and burst initial conditions. We plan to run a relatively large ensemble of 40 members for sub-seasonal forecast (up to 3 months), at which point we sub-sample the ensemble, and continue the forecast with 10 members (up to 12 months). Here we present the results of the extensive testing of various ways to generate the perturbations to the initial conditions and the validation of the stratified sampling strategy we chose.To generate perturbations for the burst ensemble members we used scaled differences of pairs of analysis states separated by 1-10 days, randomly chosen from a corresponding season. We considered perturbing separately only the atmospheric fields or only the ocean or both of the forecast initial conditions. Considering varying separation times between the analysis states, we were able to produce perturbations sampling various modes of variability. Focusing on the ENSO SST indices, we found that all types of perturbations are important for the ensemble spread.Our ensemble size for sub-seasonal forecasts was determined as to maximize the skill of predicting some of the leading modes of boreal winter atmospheric modes, NAO, PNA and AO. It is not feasible to run equally large ensemble for seasonal forecasts. Using a stratified sampling procedure we can identify the emerging directions of error growth. By comparing the stratified ensemble with randomly sampled ensemble of the same size, we were able to show that the former better estimates the mean of the original large ensemble.

Borovikov, Anna↗
NASA NTRS1993

Heterodyne efficiency for a coherent laser radar with diffuse or aerosol targets

The performance of a Coherent Laser Radar is determined by the statistics of the coherent Doppler signal. The heterodyne efficiency is an excellent indication of performance because it is an absolute measure of beam alignment and is independent of the transmitter power, the target backscatter coefficient, the atmospheric attenuation, and the detector quantum efficiency and gain. The theoretical calculation of heterodyne efficiency for an optimal monostatic lidar with a circular aperture and Gaussian transmit laser is presented including beam misalignment in the far-field and near-field regimes. The statistical behavior of estimates of the heterodyne efficiency using a calibration hard target are considered. For space based applications, a biased estimate of heterodyne efficiency is proposed that removes the variability due to the random surface return but retains the sensitivity to misalignment. Physical insight is provided by simulation of the fields on the detector surface. The required detector calibration is also discussed.

Frehlich, R. G.↗
NASA NTRS1990

Simple model of plasma acceleration in a magnetic nozzle

A collisionless, steady-state, cold-plasma model is used to calculate the three-dimensional trajectory of a plasma as it is accelerated through a diverging magnetic field. The magnetic field is assumed to be axisymmetric with nonzero radial and axial components and zero azimuthal component. Although random thermal motion of plasma species is neglected in the cold plasma approximation, an important effect of plasma thermal energy is accounted for in the model as the kinetic energy of electrons in their Larmor motion about magnetic field lines. Calculations based on this model confirm previous studies which suggested that plasma separation from the field of a magnetic nozzle can take place even in the absence of collisional diffusion. It is shown that plasma divergence in a magnetic nozzle can be controlled by tailoring the field geometry.

Sercel, Joel C.↗
DOE OSTI2025

Fuel performance analysis of fully-resolved TRISO compact

The TRi-structural ISOtropic (TRISO) fuel multilayered coating structure offers multiple barriers to fission product release, enhancing safety and performance. The heterogeneous nature of TRISO fuel compacts, comprising thousands of randomly distributed coated fuel particles embedded in a graphite matrix, creates intricate stress fields and thermal gradients that cannot be accurately modeled using simplified one-dimensional or homogenized approaches. Consequently, three-dimensional modeling enables the prediction of fuel compact dimensional changes, internal pressure buildup, and fission product transport pathways under diverse irradiation and thermal conditions. This capability facilitates detailed analysis of particle-to-particle interactions, matrix cracking mechanisms, and the statistical distribution of coating failures, which directly impact fuel performance and safety margins. This capability is particularly critical for advanced reactors, such as high-temperature gas-cooled reactors and other Generation IV reactor designs where TRISO fuel operates at elevated temperatures and burn-up levels. This work introduces a novel method to generate an optimized packing of TRISO compacts and a complete 3D mesh with random distribution of TRISO particles, which are discretized into each coating component layer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2018

Predicting the Operational Acceptance of Airborne Flight Reroute Requests Using Data Mining

For tools that generate more efficient flight routes or reroute advisories, it is important to ensure compatibility of automation and autonomy decisions with human objectives so as to ensure acceptability by the human operators. In this paper, the authors developed a proof of concept predictor of operational acceptability for route changes during a flight. Such a capability could have applications in automation tools that identify more efficient routes around airspace impacted by weather or congestion and that better meet airline preferences. The predictor is based on applying data mining techniques, including logistic regression, a decision tree, a support vector machine, a random forest and Adaptive Boost, to historical flight plan amendment data reported during operations and field experiments. Cross validation was used for model development, while nested cross validation was used to validate the models. The model found to have the best performance in predicting air traffic controller acceptance or rejection of a route change, using the available data from Fort Worth Air Traffic Control Center and its adjacent Centers, was the random forest, with an F-score of 0.77. This result indicates that the operational acceptance of reroute requests does indeed have some level of predictability, and that, with suitable data, models can be trained to predict the operational acceptability of reroute requests. Such models may ultimately be used to inform route selection by decision support tools, contributing to the development of increasingly autonomous systems that are capable of routing aircraft with less human input than is currently the case.

Operational Acceptability↗
DOE OSTI2020

Spectral form factors of clean and random quantum Ising chains

We compute the spectral form factor of two integrable quantum-critical many-body systems in one spatial dimension. The spectral form factor of the quantum Ising chain is periodic in time in the scaling limit described by a conformal field theory; we also compute corrections from lattice effects and deviation from criticality. Iin this work, criticality in the random Ising chain is described by rare regions associated with a strong randomness fixed point, and these control the long-time limit of the spectral form factor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1985

A case study of the effects of random errors in rawinsonde data on computations of ageostrophic winds

Data input for the AVE-SESAME I experiment are utilized to describe the effects of random errors in rawinsonde data on the computation of ageostrophic winds. Computer-generated random errors for wind direction and speed and temperature are introduced into the station soundings at 25 mb intervals from which isentropic data sets are created. Except for the isallobaric and the local wind tendency, all winds are computed for Apr. 10, 1979 at 2000 GMT. Divergence fields reveal that the isallobaric and inertial-geostrophic-advective divergences are less affected by rawinsonde random errors than the divergence of the local wind tendency or inertial-advective winds.

Moore, J. T.↗
DOE OSTI2025

Grain Boundary Segregation Suppresses Local Short‐Range Ordering in Nanocrystalline High‐Entropy Alloys

Multi-principal-element alloys like high-entropy alloys (HEAs) have potential applications in many engineering fields due to their unique mechanical/functional properties. While HEAs are generally considered random solid solutions, recent studies revealed that they are prone to short-range-ordering (SRO) due to the complex multi-pair-wise interactions among the constituent elements. Meanwhile, SROs' evolution can sometimes be deleterious, and it is necessary to have control over their evolution. Examining the AlCoCrFe-Zr model alloy, long-range ordering occurs following the expectation of enthalpic predictions. Advanced characterization techniques—transmission electron microscopy, high-energy synchrotron X-ray diffraction/pair distribution function, and atom probe tomography, reveal that SRO is suppressed in as-milled and GB-decorated NC-(AlCoCrFe)100-xZrx (x = 0–1.5 atomic %). Warren-Cowley coefficient calculations are further used to validate the suppression of SRO. Besides the low segregation enthalpies of Cr, Fe, and Zr, and the high-mixing enthalpy of Cr and Fe, the short diffusion path to GBs due to high-GB density in the NC-HEAs and the higher energy state of the GBs than the matrix promotes GB-segregation that further alters the matrix chemistry and consequently disfavors SRO formation within the matrix. Despite the GB-segregation of Cr, Fe, and Zr, the matrices and GBs remain in a random solid solution.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A supersymmetric SYK model with a curious low energy behavior

We consider N = 2,4 supersymmetric SYK models that have a peculiar low energy behavior, with the entropy going like S = S 0 + (constant)T a , where a ≠ 1. The large N equations for these models are a generalization of equations that have been previously studied as an unjustified truncation of the planar diagrams describing the BFSS matrix quantum mechanics or other related matrix models. Here we reanalyze these equations in order to better understand the low energy physics of these models. We find that the scalar fields develop large expectation values which explore the low energy valleys in the potential. The low energy physics is dominated by quadratic fluctuations around these values. These models were previously conjectured to have a spin glass phase. We did not find any evidence for this phase by using the usual diagnostics, such as searching for replica symmetry breaking solutions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗