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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Spinon mediation of witness spin dynamics in herbertsmithite

The kagome lattice of spin-1/2 copper atoms in herbertsmithite is conjectured to sustain a quantum spin liquid state with spinon quasiparticles. Ideally, the kagome crystal planes are each separated by a plane of spinless zinc atoms. However, in real crystals, some spin-1/2 copper atoms substitute randomly onto these inter-kagome zinc sites. Here we reconceptualize such ‘impurity’ atoms as quantum witness spins whose dynamics is designed to probe the spin liquid state. We then introduce spin noise spectroscopy to measure the frequency and temperature dependence of witness spin dynamics, demonstrating that their phenomenology is consistent with extensive interactions between witness spins mediated by propagation of spinons through a quantum spin liquid. Ultimately, a sharp transition occurs at around 260 mK, below which the properties of both spin noise and magnetic susceptibility suggest that the witness spins form a spin glass phase. Among the theoretical models considered, we demonstrate that our observations are only consistent with spinon-mediated interactions between witness spins by either a Z 2 or U(1) quantum spin liquid, with the former model more closely matching the data. Our work demonstrates that quantum mechanical witness spins may now conceivably be used as a widely applicable probe of quantum spin liquid physics.

Takahashi, Hiroto [University of Oxford (United Ki↗
DOE OSTI2023

Attosecond time delay in atomic photoionization: Angular-dependent transition from dipole to quadrupole and spin-flip dynamics

The angular distribution of attosecond Wigner time delay has been investigated including both quadrupole and relativistic effects using the relativistic-random-phase approximation that is based on the Dirac equation and includes significant aspects of many-body correlations. Here the results show a dramatic evolution of the time delay from (essentially nonrelativistic) dipole to quadrupole and spin-flip dynamics as a function of angle, thereby providing a venue for studying these interactions at the attosecond level.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Electronic noise of a single skyrmion

To enable the practical use of skyrmion-based devices, it is essential to achieve a balance between energy efficiency and thermal stability while also ensuring reliable electrical detection against noise. Understanding how a skyrmion interacts with material disorder and external perturbations is thus essential. Here, we investigate the electronic noise of a single skyrmion under the influence of thermal fluctuations and spin currents in a magnetic thin film. We detect the thermally induced noise with a 1/ƒ $\gamma$ signature in the strong pinning regime but a random telegraph noise in the intermediate pinning regime. Both the thermally dominated and current-induced telegraphlike signals are detected in the weak pinning regime. Our results provide a comprehensive electronic noise picture of a single skyrmion, demonstrating the potential of noise fluctuation as a valuable tool for characterizing the pinning condition of a skyrmion. In conclusion, these insights could also aid in the development of low-noise and reliable skyrmion-based devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Social Learning and Solar Photovoltaic Adoption

Growing literature points to the effectiveness of leveraging social interactions and nudges to spur adoption of prosocial behaviors. This study investigates a large-scale behavioral intervention designed to actively leverage social learning and peer interactions to encourage adoption of residential solar photovoltaic systems. Municipalities choose a solar installer offering group pricing and undertake an informational campaign driven by volunteer ambassadors. We find a causal treatment effect of 37 installations per municipality from the campaigns and no evidence of harvesting or persistence. The intervention also lowers installation prices. Randomized controlled trials based on the intervention show that selection into the program is important, whereas group pricing is not. Our results suggest that the program provided economies of scale and lowered consumer acquisition costs, leading to low-cost emission reductions. This paper was accepted by Matthew Shum, marketing.

Business & Economics↗
NASA NTRS1981

Sound measurements of the MOD-2 wind turbine generator

Sound measurements were made for the MOD-2 wind turbine generator for wind conditions of 7.6 to 13.4 m/sec and for output power ratings of about 1 to 2 NW. Both broad band and narrow band data wre obtained for a range of distances and azimuth angles from the machine. The rotor sound spectra are random in character and peak in the frequency ranges 30 to 50 Hz and 800 to 1300 Hz. Both peaks are predictable from experience with helicopter rotors and propellers. Results suggest that the lower frequency peak is due to the effects of inflow turbulence and the higher frequency peak is due to the interactions of the turbulent boundary layers with the trailing edges of the blades. The boundary layer related sound is the dominant component in the audible frequency range and determines the detectability of the machine. It could be detected at a distance of 1350 m in the upwind direction where the background noise was 30 dB (A) and at distances in excess of 2100 m in the downwind direction. Discrete frequency sound components associated with the power generation equipment are measurable in the direction normal to the axis of rotation but are not believed to be significant for detection or community response.

Hubbard, H. H.↗
NASA NTRS1982

On the origin of relativistic particles and gamma-rays in quasars

A model for a class of quasars and active galactic nuclei is proposed in which a shock around a massive black hole randomizes the infall kinetic energy of spherically accreting matter producing a nonthermal spectrum of high energy protons. It is suggested that these protons are responsible for the secondary production (via proton decay) of the radio emitting high energy electrons and also of high energy gamma-rays (via proton decay and inverse Compton interactions of the electrons). The correlation between radio and gamma-ray emission implied by the model is in good agreement with observations of 3C273. Observation of the flux of high energy neutrinos from quasars may provide a test for the model.

Protheroe, R. J.↗
NASA NTRS1992

Periglacial and glacial analogs for Martian landforms

The list of useful terrestrial analogs for Martian landforms has been expanded to include: features developed by desiccation processes; catastrophic flood features associated with boulder-sized materials; and sorted ground developed at a density boundary. Quantitative analytical techniques developed for physical geography have been adapted and applied to planetary studies, including: quantification of the patterns of polygonally fractured ground to describe pattern randomness independent of pattern size, with possible correlation to the mechanism of origin and quantification of the relative area of a geomorphic feature or region in comparison to planetary scale. Information about Martian geomorphology studied in this project was presented at professional meetings world-wide, at seven colleges and universities, in two interactive televised courses, and as part of two books. Overall, this project has expanded the understanding of the range of terrestrial analogs for Martian landforms, including identifying several new analogs. The processes that created these terrestrial features are characterized by both cold temperatures and low humidity, and therefore both freeze-thaw and desiccation processes are important. All these results support the conclusion that water has played a significant role in the geomorphic history of Mars.

Rossbacher, Lisa A.↗
NASA NTRS2021

The Near and Intermediate Wake of a Thick Flat Plate with a Circular Trailing Edge

The near and intermediate wake regions of a thick flat plate with a circular trailing edge (TE) are investigated with a direct numerical simulation (DNS). The focus is on the region x/D < 43.0(D is the diameter of the TE). The upper and lower separating boundary layers are both turbulent and are statistically identical; the resulting wake is symmetric in the mean. The present study is a continuation of an earlier investigation (Case AX). The earlier research dealt with shed vortex structure, in particular the persistence of the coherence of these vortices with increasing streamwise distance (except for infrequent, random disruption/rupture). In addition, across-centerline movement (ACM)of shed vortices, that is prevalent past x/D = 20.0 in a cylinder case at a comparable Reynolds number, was found to be essentially absent in Case AX. In the present investigation, an underlying cause for the occasional disruption/rupture of shed vortices is explored. Strong interactions between subsequent shed vortices in the trailing edge region is found to be an important contributor to this phenomenon. The distributions of phase-averaged streamwise and cross-stream components of intensity and the corresponding budget terms in the near wake are compared with those obtained in the intermediate wake here. In addition, the main features of the distribution of the phase-averaged velocity pressure-gradient term are compared with those of the production term, for the two intensity components. Except for a change in sign, the important features in the two budget terms are qualitatively similar for both components.

Direct Numerical Simulations of Flat Plate Wake↗
NASA NTRSDate not supplied

Nearest-Neighbor Machine Learning Feature Selection for Interpretation of Microbial Molecular Signatures from Isotope Ratio Mass Spectrometry Data

Mass spectrometry (MS) promises to be a powerful tool for potential biosignature detection during astrobiological missions on ocean worlds in our solar system. Accurate and generalizable machine learning methods could enhance science return on investment by predicting seawater chemistry and classifying isotopic biosignatures, either as a signature consistent with microbial life (biotic) or as a novelty (unclassified/unique). However, machine learning models are likely to be complex and involve interactions between MS features, making biosignatures difficult to interpret. Feature selection methods provide biological and chemical context that help interpret the mechanisms of machine learning models, but these methods also need the ability to detect complex interactions. Previously, we developed a machine learning feature selection algorithm called nearest-neighbor projected distance regression (NPDR) that has the ability to identify important model features that involve complex interactions and automatically reduce correlation and the dimensionality in a high-dimensional variable space. The standard distance metrics used in NPDR – Manhattan and Euclidean – assume the multivariate data are isotropic, which is often violated in real data due to differences in the covariance between variables. Thus, we extend NPDR to include a random forest distance, and other anisotropic distance metrics, for computing nearest neighbors. We also augment the isotope-ratio MS data with time-series features from the raw MS signal to improve biotic classification. We test NPDR on our novel experimental ocean world seawater analog MS data. We measure isotope fractionations of volatile CO 2 that could be measured in exospheres or plumes. Samples include baseline abiotic conditions using a range of possible seawater chemistry consistent with Europa and Enceladus, and biotic samples that include microbes in these seawaters. We use penalized NPDR with random forest proximity to identify interpretable microbial molecular signatures. We compare features with random forest importance, and we train a classifier that discriminates between biotic and abiotic samples with high accuracy. These ML-trained ocean-world analog MS data could be used to assist in identifying biosignatures during future missions.

geochemistry↗
DOE OSTI2025

Likelihood-Based Particle Identification in the Short-Baseline Near Detector

Accurate particle identification is crucial in any high-energy physics experiment, allowing scientists to understand the unique interactions and mechanisms at play in a detector. In this project, I develop and study a new particle identification (PID) algorithm for the Short-Baseline Near Detector, a likelihood-based approach, different from out current $\chi^2$ method. A likelihood estimation offers a more physically motivated strategy for PID. The distribution random energy losses of charged particles traveling through a medium are described by the Vavilov probability density function. By using this model, we can account for random energy losses and construct likelihood functions specific to each particle type, potentially enabling a more accurate method for PID.

Vanderwaal, Sophia [U. Alabama, Huntsville] (ORCID↗
DOE OSTI2023

Stochastic transition in synchronized spiking nanooscillators

This work reports that synchronization of Mott material-based nanoscale coupled spiking oscillators can be drastically different from that in conventional harmonic oscillators. We investigated the synchronization of spiking nanooscillators mediated by thermal interactions due to the close physical proximity of the devices. Controlling the driving voltage enables in-phase 1:1 and 2:1 integer synchronization modes between neighboring oscillators. Transition between these two integer modes occurs through an unusual stochastic synchronization regime instead of the loss of spiking coherence. In the stochastic synchronization regime, random length spiking sequences belonging to the 1:1 and 2:1 integer modes are intermixed. The occurrence of this stochasticity is an important factor that must be taken into account in the design of large-scale spiking networks for hardware-level implementation of novel computational paradigms such as neuromorphic and stochastic computing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Low-energy enhancement in the magnetic dipole γ-ray strength functions of heavy nuclei

A low-energy enhancement (LEE), which was observed experimentally in the gamma-ray strength function (γSF) describing the decay of compound nuclei, would have profound effects on r-process nucleosynthesis if it persists in heavy neutron-rich nuclei. The LEE was shown to be a feature of the magnetic dipole (M1) strength function in configuration-interaction shell-model calculations in medium-mass nuclei. However, its existence in heavy open-shell nuclei remains an open question. Here, using a combination of many-body methods, we identify a LEE in the M1 γSFs of heavy samarium nuclei. In particular, we use the static-path plus random-phase approximation (SPA+RPA), which includes static and small-amplitude quantal fluctuations beyond the mean field. Using the SPA+RPA strength as a prior, we apply the maximum-entropy method (MEM) to obtain finite-temperature M1 γSFs from exact imaginary-time response functions calculated with the shell model Monte Carlo (SMMC) method. We find that the slope of the LEE in samarium isotopes is roughly independent of the average initial energy over a wide range below the neutron separation energy. As the neutron number increases, strength transfers to a low-energy excitation, which we interpret as the scissors mode built on top of excited states.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Identifying the Best High‐Biomass Sorghum Hybrids Based on Biomass Yield Potential and Feedstock Quality Affected by Nitrogen Fertility Management Under Various Environments

The growing interest in high-biomass sorghum ( Sorghum bicolor L. Moench), hereafter referred to as sorghum, as a bioenergy feedstock in the United States requires an understanding of geographical adaptation to identify the most suitable hybrids for the Midwest. In this study, 13 sorghum hybrids (H1–H13) were evaluated for biomass yield potential in central and southern IL over two growing seasons (2022 and 2023). In addition to biomass yield, the effects of nitrogen (N) fertilization on yield, nutrient removal (N, P, and K), and feedstock composition (cellulose, hemicellulose, lignin, and soluble fractions) were determined to identify the best-performing sorghum hybrid across environmental gradients. The experimental design was a split-plot arrangement within a randomized complete block design with four replications at each of two locations: N rates (0 and 112 kg-N ha −1 ) as a whole plot factor and 13 sorghum hybrids as a subplot factor. As a result, complex genotypes (13 hybrids) by environment (2 sites and 2 years) and management (2 N rates) interactions were observed in biomass yield. The best hybrids at both sites were H1 (ATx2932/F10702_PSL) and H13 (TX08001), which were very photoperiod sensitive (PS). These hybrids produced superior biomass yield, and they also exhibited less nutrient removal and high energy-rich feedstock compositions (cellulose, hemicellulose, and lignin). Biomass yield potential was associated with morphological and phenological traits according to environmental conditions. Low-yielding hybrids were short-stature (H5 and H6) with pollinators (F10801_PSL-3dw and F10805_PSL-3dw) that are recessive at the Dw3 locus. Moderate PS hybrids (H7, H8, H11, and H12) that produced grain panicles at harvest showed high biomass yield plasticity and excessive nutrient removal as they accumulated high K concentrations in biomass tissues and high N and P in grain panicles.

09 BIOMASS FUELS↗
DOE OSTI2024

Tools for Water Ingress Testing

The Safety Storage and Engineering Team, as part of the Production Support Services division (PSS-2), is tasked with ensuring the safety of containers used for handling and storage of nuclear materials. As part of this work, water ingress tests are conducted to evaluate the water-tightness of containers intended for in-glovebox use. In collaboration, the statistics group of the Computer and Computational Sciences Division (CCS-6) provided support in developing a statistically defensible approach for determining appropriate sample sizes for water ingress testing. Water ingress testing involves multiple measurements on multiple containers. Our approach uses a simple random effects model to analyze a pilot data set, implementing prediction limits to evaluate the efficacy of collecting additional data. Although this study capitalizes on available data, our approach can be used with estimates of the ratio of between and within variability and average values, often available from past testing or expert knowledge. An interactive Shiny tool was developed as a final user-friendly product for future testing. The Shiny interface is an open-source package providing a framework for building web applications. Raw data exploration and prediction interval-based sample size assessments can quickly be conducted by the engineering team without needing to interact with the underlying code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1972

Manipulation of particles by weak forces

Quantitative relations between various force fields and their effects on the motion of particles of various sizes and physical characteristics were studied. The forces considered were those derived from light, heat, microwaves, electric interactions, magnetic interactions, particulate interactions, and sound. A physical understanding is given of the forces considered as well as formulae which express how the size of the force depends on the physical and electrical properties of the particle. The drift velocity in a viscous fluid is evaluated as a function of initial acceleration and the effects of thermal random motion are considered. A means of selectively sorting or moving particles by choosing a force system and/or environment such that the particle of interest reacts uniquely was developed. The forces considered and a demonstration of how the initial acceleration, drift velocity, and ultimate particle density distribution is affected by particle, input, and environmental parameters are tabulated.

Adler, M. S.↗
NASA NTRS1994

Structure and Dynamics of the Solar Corona

Advanced computational techniques were used to study solar coronal heating and coronal mass ejections. A three dimensional, time dependent resistive magnetohydrodynamic code was used to study the dynamic response of a model corona to continuous, slow, random magnetic footpoint displacements in the photosphere. Three dimensional numerical simulations of the response of the corona to simple smooth braiding flows in the photosphere were calculated to illustrate and understand the spontaneous formation of current filaments. Two dimensional steady state helmet streamer configurations were obtained by determining the time asymptotic state of the interaction of an initially one dimensinal transponic solar wind with a spherical potential dipole field. The disruption of the steady state helmet streamer configuration was studied as a response to shearing of the magnetic footpoints of the closed field lines under the helmet.

Schnack, D. D.↗
NASA NTRS2010

Gender Differences in Isokinetic Strength after 60 and 90 d Bed Rest

Recent reports suggest that changes in muscle strength following disuse may differ between males and females. PURPOSE: To examine potential gender differences in strength changes following 60 and 90 d of experimental bed rest. METHODS: Isokinetic extensor and flexor strength of the knee (60deg and 180deg/s, concentric only), ankle (30deg/s, concentric and eccentric), and trunk (60deg/s, concentric only) were measured following 60 d (males: n=4, 34.5+/-9.6 y; females: n=4, 35.5+/-8.2 y) and 90 d (males: n=10, 31.4+/-4.8 y; females: n=5, 37.6+/-9.9 y) of 6-degree head-down-tilt bed rest (BR; N=23). Subjects were fed a controlled diet (55%/15%/ 30%, CHO/PRO/FAT) that maintained body weight within 3% of the weight recorded on Day 3 of bed rest. After a familiarization session, testing was conducted 6 d before BR and 2 d after BR completion. Peak torque and total work were calculated for the tests performed. To allow us to combine data from both 60- and 90-d subjects, we used a mixed-model statistical analysis in which time and gender were fixed effects and bed rest duration was a random effect. Log-transformations of strength measures were utilized when necessary in order to meet statistical assumptions. RESULTS: Main effects were seen for both time and gender (p<0.05), showing decreased strength in response to bed rest for both males and females, and males stronger than females for most strength measures. Only one interaction effect was observed: females exhibited a greater loss of trunk extensor peak torque at 60 d versus pre-BR, relative to males (p=0.004). CONCLUSION: Sixty and 90 d of BR induced significant losses in isokinetic muscle strength of the locomotor and postural muscles of the knee, ankle, and trunk. Although males were stronger than females for most of the strength measures that we examined, only changes in trunk extensor peak torque were greater for females than males at day 60 of bed rest

English, K. L.↗
DOE OSTI2021

Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal–Organic Frameworks

Computational high-throughput screening using molecular simulations is a powerful tool for identifying top-performing metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges are often required to model the electrostatic interactions between the MOF and the adsorbate, especially when the adsorption involves molecules with dipole or quadrupole moments such as water and CO 2 . Although ab initio methods can be used to calculate accurate partial atomic charges, these methods are impractical for screening large material databases because of the high computational cost. We developed a random forest machine learning model to predict the partial atomic charges in MOFs using a small yet meaningful set of features that represent both the elemental properties and the local environment of each atom. The model was trained and tested on a collection of about 320 000 density-derived electrostatic and chemical (DDEC) atomic charges calculated on a subset of the Computation-Ready Experimental Metal–Organic Framework (CoRE MOF-2019) database and separately on charge model 5 (CM5) charges. The model predicts accurate atomic charges for MOFs at a fraction of the computational cost of periodic density functional theory (DFT) and is found to be transferable to other porous molecular crystals and zeolites. In conclusion, a strong correlation is observed between the partial atomic charge and the average electronegativity difference between the central atom and its bonded neighbors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗