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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Recovery Timescales of the Dayside Martian Magnetosphere to IMF Variability

In this work we revisit an event observed by Mars Atmosphere and Volatile Evolution MissioNin the solar wind where the interplanetary magneticfield (IMF) rotates around the Mars‐Sun axis during∼6 min. Based on a time‐dependent LATMOS Hybrid Simulation, we determine recovery timescales of thedayside Martian magnetosphere normalized by the IMF variability timescale. Particularly, wefind thatsuch recovery timescales range between 8 s and 11 min for an∼90° IMF rotation that lasted 50 s (observed aspart of the 6‐min time interval), depending on the considered magnetospheric region. We alsofind thatthe O+plume recovery timescales range between 40 and 120 s, taking greater values for further downstreamdistances (at least up to 1RMdownstream from the terminator plane). This range is on the order of themagnetosheath O+gyroperiod, showing the kinetic nature of the plume recovery process.

Romanelli, N.↗
DOE OSTI2024

Bayesian reduced-order deep learning surrogate model for dynamic systems described by partial differential equations

We propose a reduced-order deep-learning surrogate model for dynamic systems described by time-dependent partial differential equations. This method employs space–time Karhunen–Loève expansions (KLEs) of the state variables and space-dependent KLEs of space-varying parameters to identify the reduced (latent) dimensions. Subsequently, a deep neural network (DNN) is used to map the parameter latent space to the state variable latent space. An approximate Bayesian method is developed for uncertainty quantification (UQ) in the proposed KL-DNN surrogate model. The KL-DNN method is tested for the linear advection–diffusion and nonlinear diffusion equations, and the Bayesian approach for UQ is compared with the deep ensembling (DE) approach, commonly used for quantifying uncertainty in DNN models. It was found that the approximate Bayesian method provides a more informative distribution of the PDE solutions in terms of the coverage of the reference PDE solutions (the percentage of nodes where the reference solution is within the confidence interval predicted by the UQ methods) and log predictive probability. The DE method is found to underestimate uncertainty and introduce bias. For the nonlinear diffusion equation, we compare the KL-DNN method with the Fourier Neural Operator (FNO) method and find that KL-DNN is 10% more accurate and needs less training time than the FNO method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Antimicrobial Peptides Can Facilitate Whole Blood Safety from Bacteria: A Proof of Concept

With continuous improvements to blood donor deferrals and the availability of sensitive tests for donation screening for infectious agents, bacterial contamination of whole blood (WB) and blood components stored for transfusion is a rare event. Nonetheless, it still occurs and remains a transfusion-associated risk in terms of septic transfusion reactions (STRs) and transfusion-transmitted bacterial infections with morbidity and mortality outcomes. One of the risk mitigation strategies for bacterial contamination is to implement treatment with currently available proactive pathogen reduction technologies (PRTs) for these transfusion products. Here, as a proof of concept, we tested two recently developed unique cationic antimicrobial peptides (AMPs; D-CONGA and D-CONGA-Q7) for WB safety from bacterial contamination. In this study, WB was inoculated with Escherichia coli and Staphylococcus epidermidis and treated with the two peptides to evaluate their bactericidal efficacy. The results demonstrated that D-CONGA and D-CONGA-Q7 exhibit potent inhibitory activity against the bacteria with a minimal inhibitory concentration (MIC) range of 4–8 and 1–8 μM, respectively, depending on the bacterial species tested. Time-kill kinetics further confirmed that the peptides exhibit bactericidal efficacy at 8 μM by achieving a 5-log 10 reduction (99.999%) of the bacterial load in WB with a time-dependent killing profile. Furthermore, even at 20 μM, the AMPs did not negatively impact hemolysis or hemostatic properties. We have further demonstrated using a cationic exchange resin that the cationic AMPs can be separated and removed from WB after the peptide treatments. During 35-day WB storage at 2–8 °C, 4 μM D-CONGA-Q7 one-time treatment prevented S. epidermidis growth and preserved WB quality and integrity. Overall, the results described here provide the first proof of concept that certain AMPs, such as D-CONGA and D-CONGA-Q7, can facilitate WB safety from bacteria during storage.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1989

Observations of ionosphere/magnetosphere interactions from the Dynamics Explorer satellites

The Dynamics Explorer program was a dual spacecraft mission designed to study the interactions between the upper atmosphere, ionosphere and magnetosphere. The global auroral images acquired from the high altitude spacecraft have provided a revolutionary new time-dependent frame of reference for the interpretation of data acquired in situ. Using data especially from the low altitude spacecraft, interrelationships are developed between the various electrodynamic parameters measured. Ionospheric irregularities are found to be especially intense in regions of electric field convection shears, which are closely related to the dusk hemisphere field-aligned currents. These region 1 currents are spatially connected to the boundary plasma sheet electron precipitation. At all local times, there appears to be a universal relationship between regions where div E is less than 0 and electron precipitation structures. Depending upon the characteristics of the electrons bombarding the atmosphere, the atmosphere will radiate various spectral optical emissions, which can be imaged from high above the polar caps, with temporal resolution sufficient to follow the time-dependent evolution of a substorm. It is concluded that with further detailed analyses of the electrodynamic parameters obtained from in situ measurements, analyses of auroral images will yield specific information on many of the important ionospheric parameters over an entire auroral oval and polar cap, including regions of intense ionospheric irregularities.

Hoffman, R. A.↗
DOE OSTI2021

JWST Noise Floor. II. Systematic Error Sources in JWST NIRCam Time Series

The James Webb Space Telescope (JWST) holds great promise for characterizing atmospheres of transiting exoplanets, potentially providing insights into Earth-sized planets within the habitable zones of M-dwarf host stars if photon-limited performance can be achieved. Here, we discuss the systematic error sources that are expected to be present in grism time-series observations with the NIRCam instrument. We find that pointing jitter and high-gain antenna moves in addition to the detectors’ subpixel crosshatch patterns will produce relatively small variations (less than 6 parts per million, ppm). The time-dependent aperture losses due to thermal instabilities in the optics can also be kept to below 2 ppm. To achieve these low noise values, it is important to employ a sufficiently large (more than 11) extraction aperture. Persistence due to charge-trapping will have a minor (less than 3 ppm) effect on the time series 20 minutes into an exposure and is expected to play a much smaller role than it does for the Hubble Space Telescope WFC3 detectors. We expect detector temperature fluctuations to contribute less than 3 ppm. In total, our estimated noise floor from known systematic error sources is only 9 ppm per visit. We urge caution, however, because unknown systematic error sources could be present in flight and will only be measurable on astrophysical sources such as quiescent stars. We find that reciprocity failure may introduce a perennial instrument offset at the 40 ppm level, so corrections may be needed when a multi-instrument multi-observatory spectrum is stitched together over wide wavelength ranges.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

A Converse to Lieb–Robinson Bounds in One Dimension Using Index Theory

Abstract Unitary dynamics with a strict causal cone (or “light cone”) have been studied extensively, under the name of quantum cellular automata (QCAs). In particular, QCAs in one dimension have been completely classified by an index theory. Physical systems often exhibit only approximate causal cones; Hamiltonian evolutions on the lattice satisfy Lieb–Robinson bounds rather than strict locality. This motivates us to study approximately locality preserving unitaries (ALPUs). We show that the index theory is robust and completely extends to one-dimensional ALPUs. As a consequence, we achieve a converse to the Lieb–Robinson bounds: any ALPU of index zero can be exactly generated by some time-dependent, quasi-local Hamiltonian in constant time. For the special case of finite chains with open boundaries, any unitary satisfying the Lieb–Robinson bound may be generated by such a Hamiltonian. We also discuss some results on the stability of operator algebras which may be of independent interest.

Physics↗
DOE OSTI2026

Mu2e straw tube tracker gas flow quality control

Here, we present a tracker gas flow quality control method developed for the Mu2e straw tube tracker. Using time-dependent current measurements, we quantify the onset time of ionization gain induced by an 55 F source during gas exchange, which is correlated to the gas conductance in the straw. This allows for the identification of channels with inadequate flow. This approach is broadly applicable to other gaseous detectors that require high-channel-count screening.

Flow↗
DOE OSTI2026

Ground and excited state gradients with end-to-end differentiable semiempirical quantum chemistry

Accurate and efficient gradients of molecular energy with respect to nuclear degrees of freedom are essential for geometry optimization and molecular dynamics, including simulations that go beyond the Born–Oppenheimer regime. A common approach involves deriving analytical formulas for new electronic structure methods, which is often conceptually difficult and requires tedious coding. Here, we implement analytical, semi-numerical, and automatic differentiation (AD)-based gradient pathways for semiempirical Hamiltonian models in the PYSEQM software package, leveraging both graphics processing unit (GPU) and central processing unit (CPU) architectures. We further extend these capabilities to excited states calculated using the configuration interaction singles and time-dependent Hartree–Fock ansätze. We benchmark wall time, peak memory usage, and accuracy across three molecular families of varying chemical complexity, including systems of up to a thousand atoms. For ground-state simulations, analytical and AD gradients achieve near-identical GPU runtimes, while semi-numerical gradients are slower on GPU but remain competitive on CPU. For excited states, both analytical and custom AD approaches using implicit differentiation show similar performance and low memory requirements, whereas gradients with full AD are memory-limited. AD gradients match analytical ones in accuracy across all tested systems, aided by a quaternion-based diatomic frame rotation for two-center quantities that ensures smooth energy surfaces. Overall, automatic differentiation emerges as a practical alternative to analytical gradients in semiempirical quantum chemistry, offering high accuracy while allowing seamless integration in AI-driven workflows and popular packages, such as PyTorch and JAX. Our results provide actionable guidance for selecting optimal gradient strategies in large-scale ground- and excited-state molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Fermionic mean-field dynamics for spin systems beyond free fermions

We introduce the fermionized time-dependent Hartree–Fock (fTDHF), a real-time quantum dynamics method for spin-1/2 Hamiltonians following their mapping to fermions via the Jordan-Wigner transformation. fTDHF is formally equivalent to exact dynamics in the case of free fermions, and can efficiently handle non-local string operators arising from long-range interactions via transition matrix elements between non-orthogonal Slater determinants. We show that the fTDHF method can be implemented on a classical computer with a cost that scales polynomially with system size, and linearly with the time steps. We benchmark fTDHF against exact dynamics on three separate spin-1/2 models, representing adiabatic preparation of states with long-range correlations, disorder-driven observation of many-body localization, and particle production in the Schwinger model. For each of these systems, fTDHF is shown to reproduce the qualitative dynamics generated by the exact evolutions, while maintaining a simple physical picture due to its mean-field nature.

Dutta, Rishab↗
DOE OSTI2021

Neuromorphic learning with Mott insulator NiO

Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence found in nature in the solid state can serve as inspiration for algorithmic simulations in artificial neural networks and potential use in neuromorphic computing. In this work, we demonstrate nonassociative learning with a prototypical Mott insulator, nickel oxide (NiO), under a variety of external stimuli at and above room temperature. Similar to biological species such as Aplysia, habituation and sensitization of NiO possess time-dependent plasticity relying on both strength and time interval between stimuli. A combination of experimental approaches and first-principles calculations reveals that such learning behavior of NiO results from dynamic modulation of its defect and electronic structure. An artificial neural network model inspired by such nonassociative learning is simulated to show advantages for an unsupervised clustering task in accuracy and reducing catastrophic interference, which could help mitigate the stability–plasticity dilemma. Mott insulators can therefore serve as building blocks to examine learning behavior noted in biology and inspire new learning algorithms for artificial intelligence.

42 ENGINEERING↗
DOE OSTI2020

Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

In this paper, we describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Weak-coupling theory of magic-angle twisted bilayer graphene

Strong correlations occur in magic-angle twisted bilayer graphene (MATBG) when the octet of flat moiré minibands centered on charge neutrality (CN) is partially occupied. The octet consists of a single valence band and a single conduction band for each of four degenerate spin-valley flavors. Motivated by the importance of Hartree electrostatic interactions in determining the filling-factor-dependent band structure, we use a time-dependent Hartree approximation to gain insight into electronic correlations. We find that the electronic compressibility is dominated by Hartree interactions, that paramagnetic states are stable over a range of density near CN, and that the dependence of energy on flavor polarization is strongly overestimated by mean-field theory. Published by the American Physical Society 2024

Materials Science↗
DOE OSTI2022

Attosecond coherent electron motion in Auger-Meitner decay

In quantum systems, coherent superpositions of electronic states evolve on ultrafast time scales (few femtoseconds to attoseconds; 1 attosecond = 0.001 femtoseconds = 10 -18 seconds), leading to a time-dependent charge density. Here we performed time-resolved measurements using attosecond soft x-ray pulses produced by a free-electron laser, to track the evolution of a coherent core-hole excitation in nitric oxide. Using an additional circularly polarized infrared laser pulse, we created a clock to time-resolve the electron dynamics and demonstrated control of the coherent electron motion by tuning the photon energy of the x-ray pulse. Core-excited states offer a fundamental test bed for studying coherent electron dynamics in highly excited and strongly correlated matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Quantitative assessment of Distributed Acoustic Sensing at the Source Physics Experiment, Phase II

In this report, we assess the data recorded by a Distributed Acoustic Sensing (DAS) cable deployed during the Source Physics Experiment, Phase II (DAG) in comparison with the data recorded by nearby 4.5-Hz geophones. DAS is a novel recording method with unprecedented spatial resolution, but there are significant concerns around the data fidelity as the technology is ramped up to more common usage. Here we run a series of tests to quantify the similarity between DAS data and more conventional data and investigate cases where the higher spatial resolution of the DAS can provide new insights into the wavefield. These tests include 1D modeling with seismic refraction and bootstrap uncertainties, assessing the amplitude spectra with distance from the source, measuring the frequency dependent inter-station coherency, estimating time-dependent phase velocity with beamforming and semblance, and measuring the cross-correlation between the geophone and the particle velocity inferred from the DAS. In most cases, we find high similarity between the two datasets, but the higher spatial resolution of the DAS provides increased details and methods of estimating uncertainty.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Quantitative assessment of Distributed Acoustic Sensing at the Source Physics Experiment (Phase II)

In this report, we assess the data recorded by a Distributed Acoustic Sensing (DAS) cable deployed during the Source Physics Experiment, Phase II (DAG) in comparison with the data recorded by nearby 4.5-Hz geophones. DAS is a novel recording method with unprecedented spatial resolution, but there are significant concerns around the data fidelity as the technology is ramped up to more common usage. Here we run a series of tests to quantify the similarity between DAS data and more conventional data and investigate cases where the higher spatial resolution of the DAS can provide new insights into the wavefield. These tests include 1D modeling with seismic refraction and bootstrap uncertainties, assessing the amplitude spectra with distance from the source, measuring the frequency dependent inter-station coherency, estimating time-dependent phase velocity with beamforming and semblance, and measuring the cross-correlation between the geophone and the particle velocity inferred from the DAS. In most cases, we find high similarity between the two datasets, but the higher spatial resolution of the DAS provides increased details and methods of estimating uncertainty.

58 GEOSCIENCES↗