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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Recreating Fuel Cell Catalyst Degradation in Aqueous Environments for Identical-Location Scanning Transmission Electron Microscopy Studies

The recent surge in interest of proton exchange membrane fuel cells (PEMFCs) for heavy-duty vehicles increases the demand on the durability of oxygen reduction reaction electrocatalysts used in the fuel cell cathode. This prioritizes efforts aimed at understanding and subsequently controlling catalyst degradation. Identical-location scanning transmission electron microscopy (IL-STEM) is a powerful method that enables precise characterization of degradation processes in individual catalyst nanoparticles across various stages of cycling. Recreating the degradation processes that occur in PEMFC membrane electrode assemblies (MEAs) within the aqueous cell used for IL-STEM experiments is vital for generating an accurate understanding of these processes. In this work, we investigate the type and degree of catalyst degradation achieved by cycling in an aqueous cell compared to a PEMFC MEA. While significant degradation is observed in IL-STEM experiments performed on a traditional Pt catalyst using the standard accelerated stress test potential window (0.6-0.95 VRHE), degradation of a PtCo catalyst designed for heavy-duty vehicle use is very limited compared to that observed in MEAs. We therefore explore various experimental parameters such as temperature, acid type, acid concentration, ionomer content, and potential window to identify conditions that reproduce the degradation observed in MEAs. We find that by extending the cycling potential window to 0.4-1.0 V RHE in an electrolyte containing Pt ions, the degraded particle size distribution and alloy composition better match that observed in MEAs. In particular, these conditions increase the relative contribution of Ostwald ripening, which appears to play a more significant role in the degradation of larger alloy particles supported on high-surface-area carbons than coalescence. Results from this work highlight the potential for discrepancies between ex situ aqueous experiments and MEA tests. While different catalysts may require a unique modification to the AST protocol, strategies provided in this work enable future in situ and identical-location experiments that will play an important role in the development of robust catalysts for heavy-duty vehicle applications.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Simulation of radioactive plume transport in the atmosphere including dynamics of particle aggregation and breakup

Accurate prediction of the atmospheric transport of debris particles relies heavily on our knowledge of the size distribution of the particles within a debris cloud. Assuming a fixed particle size during simulations is not always viable since the size distribution of the debris can change during transport. Various microphysical processes, such as aggregation and breakup, influence debris particles and dictate any changes to the size distribution. To track those changes that can occur, a population balance model can be adopted and instituted within a model framework. Nonetheless, many of the models that simulate the transport of radioactive debris following a device-driven fission incident have historically neglected to consider these processes. As such, this work describes our effort to develop a modeling framework capable of simulating the transport and deposition of a radioactive plume generated from a fission incident with a dynamic population balance including particle aggregation and breakup. Herein the impact of aggregation and breakup, individually and collectively, on the particle size distribution is explored using the developed framework. When simulating aggregation, for example, six mechanisms, including Brownian coagulation, the convective enhancement to Brownian coagulation, van der Waals-viscous force correction for Brownian coagulation, gravitational collection, turbulent inertial motion, and turbulent shear, are considered. Brownian coagulation and its corrections have, as one would expect, a large impact on relatively small aggregates. Aggregates with a diameter that is less than or equal to 1.0 μm, for instance, comprise 50.6 vol % of all aggregates in the absence of aggregation and 31.2 vol % when Brownian coagulation and its corrections are considered. Gravitational collection and, to a much lesser extent, turbulent shear and turbulent inertial motion are, conversely, of great importance to relatively large aggregates (i.e., diameter greater than 3.0 μm). Additionally, the individual effects of atmospheric and particle parameters, such as wind speed and particle density, are examined. Of the parameters examined, turbulent energy dissipation and aggregate fractal dimension (i.e., aggregate shape with lower values representing more irregular particles) were of substantial importance since both terms directly impact aggregate stability and, by extension, the breakup rate. Large-scale transport and deposition simulations in a dry atmosphere are also presented and discussed as a proof of concept.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Far-from-equilibrium slow modes and momentum anisotropy in expanding plasma

The momentum distribution of particle production in heavy-ion collisions encodes information about thermalization processes in the early-stage quark-gluon plasma. We use kinetic theory to study the far-from-equilibrium evolution of an expanding plasma with an anisotropic momentumspace distribution. We identify slow and fast degrees of freedom in the far-from-equilibrium plasma from the evolution of moments of this distribution. At late times, the slow modes correspond to hydrodynamic degrees of freedom and are naturally gapped from the fast modes by the inverse of the relaxation time, $τ$$^{–1}_{R}$. At early times, however, there are an infinite number of slow modes with a gap inversely proportional to time, τ –1 . From the evolution of the slow modes we generalize the paradigm of the far-from-equilibrium attractor to vector and tensor components of the energy momentum tensor, and even to higher moments of the distribution function that are not part of the hydrodynamic evolution. We predict that initial-state momentum anisotropy decays slowly in the far-from-equilibrium phase and may persist until the relaxation time.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Characterization of an aerosolized nanoparticle beam beyond the diffraction limit through strong field ionization

Abstract The study of nanomaterials is an active area of research for technological applications as well as fundamental science. A common method for studying properties of isolated nanoparticles is by an in-vacuum particle beam produced via an aerodynamic lens. Despite being common practice, characterization of such beams has proven difficult as light scattering detection techniques fail for particles with sizes beyond the diffraction limit. Here we present a new technique for characterizing such nanoparticle beams using strong field ionization. By focusing an ultrafast, mJ-level laser into the particle beam, a nanoparticle within the laser focus is ionized and easily detected by its ejected electrons. This method grants direct access to the nanoparticle density at the location of the focus, and by scanning the focus through the transverse and longitudinal profiles of the particle beam we attain the 3-dimensional particle density distribution for a cylindrically symmetric beam. Further, we show that strong field ionization is effective in detecting spherical nanoparticles as small as 10 nm in diameter. Additionally, this technique is an effective tool in optimizing the particle beam for specific applications. As an example we show that the particle beam density and width can be manipulated by restricting the gas flow into the aerodynamic lens.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Effects of NBI-induced energetic ions on internal kink stability in HL-2M

A systematic investigation is carried out, studying the effect of the neutral beam injection induced energetic particles (EPs) on the n = 1 (n is the toroidal mode number) internal kink (IK) instability in the HL-2M tokamak, utilizing the MARS-F/K code [Liu et al., Phys. Plasmas 7, 3681 (2000) and 15, 112503 (2008)]. A high-beta sawteething HL-2M scenario, simulated by the TRANSP code [Breslau et al. Computer Software (2018)], is chosen for this study. Compared to the fluid model, non-perturbative magnetohydrodynamic (MHD)-kinetic hybrid computations with MARS-K show a generally stabilization effect on the IK, due to drift kinetic resonances associated with EPs. Further, the bounce resonance of trapped EPs has minor influence on the mode stability. In the absence of the plasma equilibrium flow and with the assumed particle pitch distribution, the transit resonance of co-current (countercurrent) passing EPs destabilizes (stabilizes) the IK. With plasma flow, both co- and countercurrent passing EPs tend to stabilize the mode, but the effect is stronger with the countercurrent particles. These modeling results provide useful guidance for interpreting MHD instabilities in the future high-performance experiments in HL-2M.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

MFIX DEM Enhancement for Industry-Relevant Flows (Final Report)

The overall goal of this two-phase project is to implement performance improvements of the Multiphase Flow with Interphase Exchanges (MFIX) Discrete Element Model (DEM) code that enable a transformative shift for industrial use. Prior to this effort, the largest simulations performed using MFIX are O(10 7 ) particles. This falls short of the O(10 9 ) particle simulations that must be completed on a timescale of days or weeks (vs. months or years) to enable simulations with physically-relevant domain sizes to be incorporated into industrial design cycles within five years. This was accomplished by tailoring best-in-class practices to bear on the unique challenges posed by the MFIX-DEM algorithm and code base. Scientific simulations (e.g., in cosmology, turbulent combustion) routinely use massively parallel computing to update far more particles in short wall clock times. Results from Phase 1 (1.5 years in duration) indicated significant gains in speed were possible for a wide range of benchmark cases. Moreover, a survey sent to >35 companies indicates that the timing is ideal for such an enhanced tool, with >80% of the respondents indicating that DEM is already value-added or will be within the next 5 years, and >70% of the respondents indicating that improved speed is the top computational priority. In Phase 2 (3.5 years in duration), the two major barriers that hinder industry from effectively using multiphase Computational Fluid Dynamics (CFD) to cut costs and improve performance, namely computational overhead and confidence in predictions, continued to be addressed. Regarding the former, the results from Phase 1 to guide the effort, with enhancements focused on an improved time-stepping algorithm and particle sorting. Four target problems of 1 billion particles each and increasing complexity were identified: homogeneous cooling, tumbler with continuous particle size distribution, discharge from a rectangular hopper and a cylindrical riser. Each of these were successfully simulated for relevant time scales (on order of seconds) using less than 24 hours of wall clock time. These represent the first 1-billion particle DEM simulations performed with MFIX, namely using the MFIX-Exa code. This code is currently under development at NETL in collaboration with Lawrence Berkeley National Laboratory. Regarding the second barrier on predictive uncertainty, experiments from Phase 1 (interacting nozzles - hydrodynamics only) and Phase 2 (very small-scale segregation experiments) were used to demonstrate the ability of two simplified approaches to uncertainty quantification (UQ). By limiting the number of particles, UQ based on the simplified treatment was compared to standard UQ, which was shown to have much higher computational demands. Experiments were also performed on a pilot-scale stripper unit to provide validation data for future CFD-DEM simulations and UQ.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Quantifying Uncertainty in Ice Particle Velocity–Dimension Relationships Using MC3E Observations

Abstract Ice particle terminal fall velocity ( V t ) is fundamental for determining microphysical processes, yet remains extremely challenging to measure. Current theoretical best estimates of V t are functions of Reynolds number. The Reynolds number is related to the Best number, which is a function of ice particle mass, area ratio ( A r ), and maximum dimension ( D max ). These estimates are not conducive for use in most models since model parameterizations often take the form , where ( α , β ) depend on habit and D max . A previously developed framework is used to determine surfaces of equally plausible ( α , β ) coefficients whereby ice particle size/shape distributions are combined with V t best estimates to determine mass- ( V M ) or reflectivity-weighted ( V Z ) velocities that closely match parameterized V M ,SD or V Z ,SD calculated using the ( α , β ) coefficients using two approaches. The first uses surfaces of equally plausible ( a , b ) coefficients describing mass ( M )–dimension relationships (i.e., ) to calculate mass- or reflectivity-weighted velocity from size/shape distributions that are then used to determine ( α , β ) coefficients. The second investigates how uncertainties in A r , D max , and size distribution N ( D ) affect V M or V Z . For seven of nine flight legs flown on 20 and 23 May 2011 during the Mesoscale Continental Convective Clouds Experiment (MC3E), uncertainty from natural parameter variability—namely, the variability in ice particle parameters in similar meteorological conditions—exceeds uncertainties arising from different A r assumptions or D max estimates. The combined uncertainty between A r , D max , and N ( D ) produced smaller variability in ( α , β ) compared to varying M ( D ), demonstrating M ( D ) must be accurately quantified for model fall velocities. Primary sources of uncertainty vary considerably depending on environmental conditions. Significance Statement Ice particle fall velocity is fundamental for numerous processes within clouds, and hence is a critical property that must be accurately represented in weather and climate models. Using aircraft observations of ice particle shapes and sizes obtained in clouds behind midlatitude thunderstorms, this work develops a new framework for estimating ice particle fall velocities and their uncertainty, including quantifying the importance of different uncertainty sources from cloud microphysics measurements. Natural parameter variability contributes the most uncertainty in ice particle fall velocity estimates, although other sources can also be important contributors to uncertainty in certain conditions. Additional work examining ice particle data is needed to further understand how dependent uncertainty in certain ice particle properties are to local environmental conditions.

Meteorology & Atmospheric Sciences↗
DOE OSTI2021

Instance Segmentation for Direct Measurements of Satellites in Metal Powders and Automated Microstructural Characterization from Image Data

In this work, we propose instance segmentation as a useful tool for image analysis in materials science. Instance segmentation is an advanced technique in computer vision which generates individual segmentation masks for every object of interest that is recognized in an image. Using an out-of-the-box implementation of Mask R-CNN, instance segmentation is applied to images of metal powder particles produced through gas atomization. Leveraging transfer learning allows for the analysis to be conducted with a very small training set of labeled images. As well as providing another method for measuring the particle size distribution, we demonstrate the first direct measurements of the satellite content in powder samples. After analyzing the results for the labeled data dataset, the trained model was used to generate measurements for a much larger set of unlabeled images. The resulting particle size measurements showed reasonable agreement with laser scattering measurements. The satellite measurements were self-consistent and showed good agreement with the expected trends for different samples. Finally, we present a small case study showing how instance segmentation can be used to measure spheroidite content in the UltraHigh Carbon Steel DataBase, demonstrating the flexibility of the technique.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Can classical DEM simultaneously capture compressibility and flowability of milled biomass?

Accurate prediction of the rheological behavior of biomass is essential for the design and operation of hoppers, feeders, and storage systems in biorefineries. This study examines whether the classical, coarse-grained discrete element method (DEM) formulation can simultaneously reproduce the compressibility and flowability of milled herbaceous biomass, using Miscanthus × giganteus as a representative material. The model represents particles as rigid spheres interacting through Hertz-Mindlin elastic-frictional contacts augmented with an area-dependent cohesion term. Laboratory cyclic compression and wedge-shaped hopper discharge experiments were used as calibration benchmarks. Although the model can independently reproduce each behavior by appropriately tuning particle Young's modulus E and cohesion energy density k, an extensive parametric investigation comprising more than 600 simulations reveals that the optimal parameter regions for compression and hopper flow are distinct and non-overlapping in (E, k) space. Surrogate surface analysis further shows that the corresponding objective-function valleys exhibit similar trends but are approximately parallel and spatially offset, precluding a unified calibration within the explored domain. Sensitivity analysis indicates that compressibility is governed predominantly by stiffness and cohesion, whereas the slope of the mass flow rate-opening relation in hopper discharge is primarily controlled by tangential friction. Extensions incorporating particle size distribution and clumped-sphere representations do not eliminate the incompatibility. These results systematically reveal, for the first time, the structural limitation of simplified DEM formulations in representing biomass rheological behavior, underscoring the necessity for models incorporating additional physical mechanisms, such as particle deformability or enhanced interlocking, to achieve unified predictive capability for biomass handling behavior.

09 BIOMASS FUELS↗
DOE OSTI2026

Measurement of the azimuthal anisotropy of charged particles in sNN=5.36TeV O16+O16 and Ne20+Ne20 collisions with the ATLAS detector

This paper presents the first measurements of the azimuthal anisotropy coefficients , which quantify the -order Fourier modulation of charged-particle azimuthal distributions, for in and collisions recorded with the ATLAS detector at the CERN Large Hadron Collider in 2025. The coefficients are measured as a function of transverse momentum ( ), collision centrality, and event multiplicity. They are extracted using two complementary methods: two-particle correlations with a template-fit subtraction of short-range nonflow contributions, and four-particle subevent cumulants, which intrinsically suppress nonflow effects and provide sensitivity to flow fluctuations. The results show a clear hierarchy and a nonmonotonic dependence on , reaching a maximum around , consistent with trends observed in heavy-ion collisions. Detailed comparisons between the two collision systems reveal an enhanced in central collisions, consistent with theory expectations based on the predicted prolate deformation of neon nuclei, in contrast to the slightly tetrahedral structure predicted for oxygen. The four-particle cumulant results highlight strong event-by-event fluctuations and provide the greatest sensitivity to nuclear shape effects. These measurements can place new constraints on the initial geometry and the hydrodynamic response in light-ion collisions, offering valuable input for models of nuclear structure.

Aad, G↗
DOE OSTI2024

Far-from-equilibrium slow modes and momentum anisotropy in an expanding plasma

The momentum distribution of particle production in heavy-ion collisions encodes information about thermalization processes in the early-stage quark-gluon plasma. We use kinetic theory to study the far-from-equilibrium evolution of an expanding plasma with an anisotropic momentum-space distribution. We identify slow and fast degrees of freedom in the far-from-equilibrium plasma from the evolution of moments of this distribution. At late times, the slow modes correspond to hydrodynamic degrees of freedom and are naturally gapped from the fast modes by the inverse of the relaxation time, τ R − 1 . At early times, however, there are an infinite number of slow modes with a gap inversely proportional to time, τ − 1 . From the evolution of the slow modes we generalize the paradigm of the far-from-equilibrium attractor to vector and tensor components of the energy-momentum tensor, and even to higher moments of the distribution function that are not part of the hydrodynamic evolution. We predict that initial-state momentum anisotropy decays slowly in the far-from-equilibrium phase and may persist until the relaxation time. Published by the American Physical Society 2024

Brewer, Jasmine (ORCID:0000000230840663)↗
DOE OSTI2020

Radar-based Snow Property Profile Retrievals for NSA

The product contains estimated snow microphysical properties retrieved primarily from vertically-profiling radar observations using a priori constraints that are dependent on atmospheric state. The product provides data at 1-minute time resolution, including snowfall rate at the surface and vertical profiles at 300-meter resolution of snow particle size distribution parameters and snow water contents. Estimated uncertainties for the snowfall rates and snow water contents are also provided. The product is obtained using an optimal estimation retrieval in which radar forward model and a priori state characteristics are based on expected snow particle microphysical and radar scattering properties evaluated from field experiment data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Computational Information Criterion for Particle-Tracking with Sparse or Noisy Data

Traditional probabilistic methods for the simulation of advection-diffusion equations (ADEs) often overlook the entropic contribution of the discretization, e.g., the number of particles, within associated numerical methods. Many times, the gain in accuracy of a highly discretized numerical model is outweighed by its associated computational costs or the noise within the data. Herein, we address the question of how many particles are needed in a simulation to best approximate and estimate parameters in one-dimensional advective-diffusive transport. To do so, we use the well-known Akaike Information Criterion (AIC) and a recently-developed correction called the Computational Information Criterion (COMIC) to guide the model selection process. Random-walk and mass-transfer particle tracking methods are employed to solve the model equations at various levels of discretization. Numerical results demonstrate that the COMIC provides an optimal number of particles that can describe a more efficient model in terms of parameter estimation and model prediction compared to the model selected by the AIC even when the data is sparse or noisy, the sampling volume is not uniform throughout the physical domain, or the error distribution of the data is non-IID Gaussian.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Time-drift Aware RF Optimization with Machine Learning Techniques

The Fermilab Linac delivers 400 MeV H- beam to the rest of the accelerator chain. Providing stable intensity, energy, and emittance is key since it directly affects downstream machines. To operate high current beam, accelerators must minimize uncontrolled particle loss; this can be accomplished by minimizing beam longitudinal emittance via RF parameter optimization. However, RF tuning is required daily since the resonance frequency of the accelerating cavities is affected by ambient temperature and humidity variations and thus drifts with time. In addition, the energy and phase space distribution of particles emerging from the ion source are subject to fluctuations. Such drift is not unique to Fermilab, but rather affects most laboratories. We are exploring machine learning (ML) algorithms for automated RF tuning for 2 objectives: optimization of Linac output energy and phase oscillation correction, with an emphasis on time-drift aware modeling that can account for conditions changing over time.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: exploring the halo occupation distribution model for emission line galaxies

We study the modelling of the halo occupation distribution (HOD) for the eBOSS DR16 emission line galaxies (ELGs). Motivated by previous theoretical and observational studies, we consider different physical effects that can change how ELGs populate haloes. We explore the shape of the average HOD, the fraction of satellite galaxies, their probability distribution function (PDF), and their density and velocity profiles. Our baseline HOD shape was fitted to a semi-analytical model of galaxy formation and evolution, with a decaying occupation of central ELGs at high halo masses. We consider Poisson and sub/super-Poissonian PDFs for satellite assignment. We model both Navarro–Frenk–White and particle profiles for satellite positions, also allowing for decreased concentrations. We model velocities with the virial theorem and particle velocity distributions. Additionally, we introduce a velocity bias and a net infall velocity. We study how these choices impact the clustering statistics while keeping the number density and bias fixed to that from eBOSS ELGs. The projected correlation function, w p , captures most of the effects from the PDF and satellites profile. The quadrupole, ξ 2 , captures most of the effects coming from the velocity profile. We find that the impact of the mean HOD shape is subdominant relative to the rest of choices. Here, we fit the clustering of the eBOSS DR16 ELG data under different combinations of the above assumptions. The catalogues presented here have been analysed in companion papers, showing that eBOSS RSD+BAO measurements are insensitive to the details of galaxy physics considered here. These catalogues are made publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Model-based iterative reconstruction with adaptive regularization for artifact reduction in electron tomography

Obtaining high-quality 3D reconstructions from electron tomography of crystalline particles embedded in lighter support elements is crucial for various material systems such as catalysts for fuel cell applications. However, significant challenges arise due to the limited tilt range, sparse and low signal-to-noise ratio of the measurements. In addition, small metal particles can cause strong streaking and shading artifacts in the 3D reconstructions when using conventional reconstruction algorithms due to the presence of Bragg diffraction and the large scattering cross-section difference between the materials of the particles and the background support regions. These artifacts lead to errors in the downstream characterization affecting extraction of critical features such as the size of the metal particles, their distribution and the volume of the lighter support regions. In this paper, we present a two-stage algorithm based on metal artifact reduction, utilizing model-based iterative reconstruction methods with adaptive adjustment of regularization parameters. Our approach yields high-quality 3D reconstructions compared to traditional algorithms, accurately capturing both the metal particles as well as the background support. We demonstrate the effectiveness of our algorithm through simulated and experimental bright-field electron tomography data, showing significant improvements in reconstruction quality compared to traditional methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Silicon nanocluster anion-argon cation recombination via hybrid continuum-molecular dynamics calculations

Prediction of the charge distribution on particles in an aerosol is critical not only in electrical mobility based characterization methods, but also in understanding the role that charging plays in particle growth in gas phase synthesis reactors. The latter is particularly important in non-thermal plasma synthesis reactors, wherein nanoclusters form and grow from vapor phase precursors in a high electron and high ion density environment. In plasmas, because free electrons are much less massive and much more mobile than positive gas ions, nanocluster charge distributions are biased negative. Furthermore, neutral or even positively charged nanoclusters may exist, depending on the rate of nanocluster-gas ion recombination, and nanocluster-nanocluster collisions may greatly contribute to nanocluster growth if not Coulombically suppressed.

42 ENGINEERING↗
DOE OSTI2023

Molecular dynamics analysis of particle number fluctuations in the mixed phase of a first-order phase transition

Molecular dynamics simulations are performed for a finite nonrelativistic system of particles with Lennard-Jones potential. We study the effect of liquid-gas mixed phase on particle number fluctuations in coordinate subspace. A metastable region of the mixed phase, the so-called nucleation region, is analyzed in terms of a noninteracting cluster model. Large fluctuations due to spinodal decomposition are observed. They arise due to the interplay between the size of the acceptance region and that of the liquid phase. These effects are studied with a simple geometric model. The model results for the scaled variance of particle number distribution are compared with those obtained from the direct molecular dynamic simulations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗