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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles

Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermalization of nuclear matter in heavy-ion collisions at Fermi energies

We analyze the time evolution of the kinetic properties of nuclear matter produced in heavy-ion collisions at Fermi energies. The collision system is simulated using Constrained Molecular Dynamics (CoMD) transport calculations whose output is the isospin, position, and momentum of the nucleons. Focusing on central 35 A·MeV 40 Ca+ 40 Ca collisions we utilize this information to extract localized momentum distributions in volume elements of 8 fm 3 and time steps of 5 fm/$c$. We then parameterize the single-particle momentum distributions with thermally motivated fit functions in the local rest frame of each cell. While the transverse-momentum distributions are well reproduced by thermal ones, the longitudinal ones carry a marked imprint of the initial nuclear motion which we capture by introducing a centroid motion into our fit functions. In particular, we find that Fermi distributions yield significantly better fits than Boltzmann ones, a consequence of the Pauli blocking implemented in CoMD. From the fits we extract the time dependence of the thermodynamic and collective properties of the excited nuclear medium. We find that the transverse temperature gradually rises to about 6 MeV, which is accompanied by a dissipation of the initial centroid motion of the incoming nuclei which vanishes at about 100 fm/c after initial impact. In conclusion, we are therefore able to track the transition of beam energy into random kinetic energy for nucleons, suggesting a three-dimensional equilibration of energy in the late stages of the collision.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

The influence of temperature history and flow mixing on the vapor-phase speciation of uranium oxide nanoparticles

The transport of radioactive material following a nuclear event depends heavily on fallout characteristics (e.g., composition, shape, and size), which in turn are controlled by the conditions under which the fallout forms. To this end, we use a novel plasma flow reactor (PFR) to explore how conditions including temperature history and gas mixing influence the chemical speciation and physical characteristics of uranium oxide nanoparticles. The PFR consists of a glass tube attached to an inductively coupled plasma (ICP) torch via an adaptor piece (ring flow injector) located downstream of the plasma-generating RF coil. We increase the gas flow rates from normal ICP operating conditions to higher values both upstream at the RF coil and downstream at the ring flow injector to create four distinct temperature profiles and two distinct gas flow mixing conditions (normal and higher Ar atomic ratios). Ex situ transmission electron microscopy (TEM) analysis is used to determine the crystal structure, morphology, and size distribution of the synthesized particles as a function of temperature and mixing. The particles display a striking dependence on these conditions in terms of the resulting speciation of uranium oxide: lower temperature (higher upstream) and slower cooling (normal downstream with normal Ar atomic ratio mixing) favor the formation of α-UO 3 particles, while faster cooling (higher downstream with higher Ar atomic ratio mixing) and higher temperature (normal upstream) favor the formation of UO 2 particles. The extent of gas mixing dictates particle aggregation: better mixing encourages the particles to aggregate more extensively. Here these results demonstrate the sensitivity of uranium to initial local conditions and can be used to improve our understanding of the kinetics that drive uranium speciation and ultimately inform fallout transport models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Weibel-mediated filamentary structures observed in the ICF context

Here, in light of novel and past experimental results, we demonstrate how Weibel-mediated filamentary structures can develop in the expanding plasma plume of a laser-irradiated foil. The transverse ballistic cooling that occurs during the quasi-spherical plasma expansion naturally drives an electron pressure anisotropy, resulting in the growth of electron current filaments. This effect competes with electron–ion Coulomb collisions, which tend to isotropize the electron distribution function. Based on theoretical and particle-in-cell modeling, we provide estimates of the dominant wavelength and amplitude of the self-generated magnetic fluctuations, which are found to explain experimental data obtained at the OMEGA and Laser Megajoule facilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Observation of Same-Sign W W Production from Double Parton Scattering in Proton-Proton Collisions at s = 13 TeV

The first observation of the production of W$^\pm$W$^\pm$ bosons from double parton scattering processes using same-sign electron-muon and dimuon events in proton-proton collisions is reported. The data sample corresponds to an integrated luminosity of 138 fb$^{-1}$ recorded at a center-of-mass energy of 13 TeV using the CMS detector at the CERN LHC. Multivariate discriminants are used to distinguish the signal process from the main backgrounds. A binned maximum likelihood fit is performed to extract the signal cross section. The measured cross section for production of same-sign W bosons decaying leptonically is 80.7 $\pm$ 11.2 (stat) $^{+9.5}_{-8.6}$ (syst) $\pm$ 12.1 (model) fb, whereas the measured fiducial cross section is 6.28 $\pm$ 0.81 (stat) $\pm$ 0.69 (syst) $\pm$ 0.37 (model) fb. The observed significance of the signal is 6.2 standard deviations above the background-only hypothesis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Numerical investigation of alpha particle confinement under the perturbation of neoclassical tearing modes and toroidal field ripple in CFETR

The confinement of alpha particles in burning plasma is a key issue in fusion reactor design, including particle interaction with instabilities. Here, we include two topics: the effect of neoclassical tearing modes (NTMs) and toroidal field ripple on alpha particle loss, and the assessment of particle redistribution under an NTM with a reduced model. We consider Chinese fusion engineering test reactor parameters, the alpha particle distribution given by TRANSP/NUBEAM and the NTM perturbation function given by the initial value code TM1. We show that the synergistic effect of the NTM and ripple is negligible; the particle loss fraction does not change with increasing NTM amplitude. Only passing particles are affected by the mode particle resonance, producing profile flattening but no increased loss because only trapped particles are influenced by ripple. To study alpha particle profile flattening, the work adopts an innovative method of phase vector rotation to determine regions of good and broken Kolmogorov–Arnold–Moser surfaces and equilibrates the particle density according to local stochasticity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Application of a Chemical Index to Aerosol Mass Spectrometry: Delta Plots and Functional Group Distributions

A better understanding of the chemical properties of organic aerosol (OA) particles will improve our ability to characterize their sources and predict their lifetime. The high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) is widely used to measure OA in real time using thermal vaporization followed by electron ionization (EI). EI creates fragment ions that can be assigned to functional groups using delta analysis, a method of classifying mass spectra according to the presence of different chemically related ion series. In this study, we demonstrate the application of delta analysis to characterize molecular structures using a new visualization method. We also use delta analysis to quantify the functional group distribution with an average absolute error of ∼5–6% for individual standard molecules, comparable to the error observed for OA mixtures from biomass and coal combustion fit with Fourier transform infrared spectroscopy. Finally, we apply delta functional group analysis to AMS positive matrix factorization (PMF) factors across seven different field campaigns and find a similar composition across the more oxidized factors with about 55% acid and 26% alcohol groups. The analysis method described here can be applied to any HR-ToF-AMS data set to provide quantitative relative functional group distributions for OA mixtures.

aerosol↗
DOE OSTI2023

Spatial Intermittency of Particle Distribution in Relativistic Plasma Turbulence

Abstract Relativistic magnetically dominated turbulence is an efficient engine for particle acceleration in a collisionless plasma. Ultrarelativistic particles accelerated by interactions with turbulent fluctuations form nonthermal power-law distribution functions in the momentum (or energy) space, f ( γ ) d γ ∝ γ − α d γ , where γ is the Lorenz factor. We argue that in addition to exhibiting non-Gaussian distributions over energies, particles energized by relativistic turbulence also become highly intermittent in space. Based on particle-in-cell numerical simulations and phenomenological modeling, we propose that the bulk plasma density has lognormal statistics, while the density of the accelerated particles, n , has a power-law distribution function, P ( n ) dn ∝ n − β dn . We argue that the scaling exponents are related as β ≈ α + 1, which is broadly consistent with numerical simulations. Non-space-filling, intermittent distributions of plasma density and energy fluctuations may have implications for plasma heating and for radiation produced by relativistic turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Synthesis of observed and simulated rain microphysics to inform a new Bayesian statistical framework for microphysical parameterization in climate models (Final Scientific Report)

This project aimed to investigate a new approach to bulk microphysics schemes. We identified the need to move beyond the fixed structural assumptions and approximation of existing schemes. For example, most schemes assume some functional form for the rain drop size distribution (e.g. a gamma or exponential distribution). Most schemes then evolve some number of statistical moments of that distribution via various processes, such as evaporation, sedimentation, collision-coalescence, and collisional breakup. These microphysical processes, in turn, are typically some fixed functional form derived from either some other (more detailed) model, or using some single-particle rates that are then integrated over the size distribution. While these process rate functions may have some free parameters to adjust, in other cases doing so is impossible (e.g. when the process rates are analytical or piecewise solutions to some target function). Our goal was to build and test a scheme that assumed no size distribution form, and used a series of power laws as the basis for the process rates. Moments of the size distribution would be predicted, but no underlying size distribution would be specified. Any number or choice of size distribution moments could be used, and any number of power laws could be employed to model the process rates. Thus, our approach is flexible, and can seamlessly scale across levels of complexity, as demanded by the data. Bayesian inference then would provide the formalism to estimate the model parameters and structure, allowing for robust uncertainty quantification. We proposed testing this framework in idealized simulations using bin microphysical schemes as a data source. We also proposed using real data to inform our microphysics scheme, and also that we would integrate our scheme into WRF.

58 GEOSCIENCES↗
DOE OSTI2022

Evaluation of assumptions made by Hygroscopic Tandem Differential Mobility Analyzer inversion routines

The Hygroscopic Tandem Differential Mobility Analyzer (H-TDMA) measures the hygroscopicity of atmospheric particles, and many atmospheric processes that change this hygroscopicity also change the atmospheric size distribution. Two assumptions made during H-TDMA inversion create spurious hygroscopic trends as a function of the changing inlet size distribution. These two assumptions—that the particles exiting the first Differential Mobility Analyzer (DMA1) are singly charged and that the inlet size distribution has a slope of zero (flat)— generate Multi-Charge Dispersion (MCD) bias and Slope bias, respectively. First, we use a model, named TAO, to show that the inlet size distribution could theoretically change the measured ammonium sulfate hygroscopicity by 10%–20% as a function of diameter or experimental time with no change in relative humidity. Secondly, we show experimentally that aerosol emitted from the flaming combustion of grass creates MCD bias. Here, in this experiment, we measure the CPC response of the first three charges and invert these responses using a new routine named Junior. Junior's inversion of each charge shows that one growth factor distribution describes all measured diameters (no growth dependence on diameter). As in the modeling study above, previous publications of this aerosol system, using traditional inversion assumptions, report a decrease in hygroscopicity as DMA1 diameter increases. Unlike traditional inversions, Junior's inversion does not assume the particles are singly charged nor does it make the flat inlet size distribution assumption. Instead, both the inlet size distribution and each charge's CPC response are measured quantities. Thus, the discrepancy between our inversion results and previous publications is likely due to the traditional inversion routine assumptions. This underscores the importance for accounting for Slope and MCD bias during inversions. Experimental results should be carefully analyzed when reporting hygroscopic trends with respect to diameter or experimental time when using the traditional inversion assumptions.

42 ENGINEERING↗
DOE OSTI2025

GPU-accelerated kinetic Hall thruster simulations in WarpX

Abstract Two-dimensional (axial-azimuthal) simulations of a Hall thruster are performed using the open-source particle-in-cell code WarpX. The simulation conditions are chosen to match those of the axial-azimuthal benchmark first reported by Charoy et al. in 2019. A range of numerical and solver parameters is investigated in order to find those which yield the best performance. It is found that WarpX completes the benchmark case in 3.8 days on an Nvidia V100 GPU, and in as low as 1.5 days on a more recent Nvidia H100 GPU. Of the numerical parameters investigated, it is determined that the field-solve tolerance and particle resampling thresholds have the largest effect on the simulation wall time and that particle resampling may artificially widen electron velocity distribution functions, leading to unphysical heating. A semi-implicit scheme for the electrostatic field solve is tested and is found to produce results consistent to within 10% of the benchmark in less than twelve hours. The scaling properties of the electrostatic solver to multiple GPUs are also assessed on a uniform plasma test problem. The results of this work are discussed in the context of advancements in GPU hardware and the suitability of kinetic Hall thruster simulations for engineering applications.

Marks, Thomas A.↗
DOE OSTI2024

A Eulerian three-fluid flow framework for the study of fuel dispersal behavior under loss-of-coolant accident conditions

As the nuclear industry explores new fuel designs to accommodate increased burnup, studying fuel behavior during loss-of-coolant accidents is essential for ensuring the safe operation of light-water reactors. Here, this study presents a computational model to simulate the intricate three-phase flow dynamics of fuel dispersal following cladding breach, where solid fuel particles and carrier fission gases interact with the surrounding liquid or gas medium. The model utilizes a Eulerian three-fluid framework to depict the phase interaction within interpenetrating continua, treating fragmented fuel as granular material. Closure relationships for bulk-flow properties of the solid phase and detailed interfacial exchange terms in high-temperature, high-speed gas-solid-liquid flow scenarios are proposed. The model was validated using adiabatic experimental results in the literature, focusing on characterizing fuel dispersal behavior during loss-of-coolant accidents conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched probability density functions reported in experimental studies. Key highlights of this study include the theoretical description of a coupled three-phase flow with phase change, interpretation of the high-pressure boundary conditions and insights into the transient behavior of gas-solid-liquid phase dynamics during a simulated high-speed dispersal event.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Advanced Closures for Nonlinear Fluid Simulations of Plasmas (Final Report)

Advanced Closures for Nonlinear Fluid Simulations of Plasmas E. Held, Utah State University (Principal Investigator) J.-Y. Ji, Utah State University (Co-Investigator) Utah State University (USU) continued to develop and apply closures for hybrid fluid/kinetic simulations of magnetized fusion plasmas. The closures developed by USU's fusion theory and computation group use the drift ordering and are referred to as "continuum" and "general moment" approaches. They differ in their representation for the distribution functions which probabilistically describe the density of particles in 5 dimensional phase space. The two chosen velocity variables, needed in studies of kinetic physics for magnetized plasmas, are the speed and the component of a particle's velocity along the magnetic field. In magnetized plasmas, the charged particle trajectories are tied closely to the magnetic field lines. Both approaches account for binary interactions between particles using the Coulomb collision operator. Theoretical and computational development along both lines provided avenues for verification between the two approaches. This funding allowed USU to further develop physically accurate and numerically efficient models that advance our understanding of kinetic physics in experiments like the International Thermonuclear Experimental Reactor (ITER). The ITER device will likely prove the physical practicality of thermonuclear fusion by producing 500 megawatts of clean, abundant fusion power. This work helped to realize this goal by advancing our simulation capability using hybrid fluid/kinetic models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM

FIDASIM is a code that models signals produced by charge-exchange reactions between neutrals and ions (both fast and thermal) in magnetically confined plasmas. With the ion distribution function as input, the code predicts the efflux to a neutral particle analyzer diagnostic and the photon radiance of Balmer-alpha light to a fast-ion D α diagnostic, in addition to many other related quantities. A new, parallelized version of the Monte Carlo code FIDASIM has been developed in Fortran90 that is substantially faster than the original interactive data language version. Modified algorithms include more accurate treatments of the time dependent collisional-radiative equations that describe neutral energy levels, of the cloud of ‘halo’ neutrals that surround the injected neutral beam, and of finite Larmor radius effects. Enhanced physics capabilities include modelling ‘passive’ signals from cold edge neutrals, the ability to treat general three-dimensional magnetic confinement configurations, and calculations of diagnostic-specific weight functions that enable tomographic reconstructions of the fast-ion distribution function. Neutral beam attenuation, beam emission, and fast-ion birth profiles are also modelled. Finally, the new algorithms have been successfully validated against experimental data and new features have been tested through benchmarks between two independently developed versions of the code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Particle charge distributions in the effluent of a flow-through atmospheric pressure low temperature plasma

Atmospheric pressure low-temperature plasmas are often utilized to perform particle synthesis, treatment, and removal. It is well-known that dust particles are highly negatively charged in these plasmas; however, little is known about dust particle charging behavior as particles leave the plasma volume and pass through the spatial afterglow region. In this work, monodisperse particles of various sizes and work functions were introduced into an atmospheric pressure radiofrequency capacitively coupled flow-through plasma. Dust particle electrical mobility distributions downstream of the flow-through plasma were measured utilizing a differential mobility analyzer in conjunction with a condensation particle counter at various gas flow velocities. Charge distributions were determined from the measured electrical mobility distributions. Experiments confirm that particles become less negatively charged, and even net-positively charged after leaving the plasma volume, with a distribution that follows a shifted Boltzmann charge distribution. Additionally, particle charge in the effluent of the flow-through plasma is negligibly dependent on work function but highly size and flow velocity dependent. Larger particles were shown to have a higher magnitude of charge under all studied conditions; however, particle polarity was switchable by varying gas flow velocity. The charging dynamics were simulated utilizing a constant number Monte Carlo model that accounts for electron temperature decay and the transition from ambipolar to free diffusion of electrons and ions in the spatial afterglow. Simulation results also suggest that, at the same flow velocity, larger particles obtain a greater magnitude of charge, negative or positive. Furthermore, the decrease in electron mobility and the difference between ion and electron convective loss rates create an ion-rich region in the plasma effluent that promotes ion–particle collisions and drives particle charge removal and even reversal of polarity. Larger particles more favorably collide with energetic species in these environments, which results in higher charge states.

atmospheric pressure low temperature plasma↗
DOE OSTI2023

Measurements of azimuthal anisotropies at forward and backward rapidity with muons in high-multiplicity p–Pb collisions at $\sqrt{s_{NN}} = 8.16$ TeV

The study of the azimuthal anisotropy of inclusive muons produced in p–Pb collisions at $\sqrt{s_{NN}}$ = 8.16 TeV, using the ALICE detector at the LHC is reported. The measurement of the second-order Fourier coefficient of the particle azimuthal distribution, v 2 , is performed as a function of transverse momentum p T in the 0–20% high-multiplicity interval at both forward (2.03 < y CMS < 3.53) and backward (-4.46 < y CMS < -2.96) rapidities over a wide pT range, 0.5 < p T < 10 GeV/c, in which a dominant contribution of muons from heavy-flavour hadron decays is expected at p T > 2 GeV/c. The v 2 coefficient of inclusive muons is extracted using two different techniques, namely two-particle cumulants, used for the first time for heavy-flavour measurements, and forward–central two-particle correlations. Both techniques give compatible results. A positive v 2 is measured at both forward and backward rapidities with a significance larger than 4.7σ and 7.6σ, respectively, in the interval 2 < p T < 6 GeV/c. Comparisons with previous measurements in p–Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV, and with AMPT and CGC-based theoretical calculations are discussed. The findings impose new constraints on the theoretical interpretations of the origin of the collective behaviour in small collision systems

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Partially Ionized Plasma Physics and Technological Applications

Partially ionized plasma physics has attracted increased attention recently due to numerous technological applications made possible by the increased sophistication of computer modelling, the depth of the theoretical analysis, and the technological applications to a vast field of manufacturing for computer components. Partially ionized plasma is characterized by a significant presence of neutral particles in contrast to the fully ionized plasma. The theoretical analysis is based upon solutions of the kinetic Boltzmann equation, yielding the non-Maxwellian electron energy distribution function (EEDF), thereby emphasizing the difference with a fully ionized plasma. The impact of the effect on discharges in inert and molecular gases is described in detail, yielding the complex nonlinear phenomena resulting in plasma selforganization. A few examples of such phenomena are given, including the non-monotonic EEDFs in the discharge afterglow in a mixture of argon with the molecular gas NF3; the explosive generation of cold electron populations in capacitive discharges, hysteresis of EEDF in inductively coupled plasmas. Recently, highly advanced computer codes were developed in order to address the outstanding challenges in plasma technology. These developments are briefly described in general terms.

non-Maxwellian electron energy distribution functi↗