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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
NASA NTRS2011

Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

Liu, Yi↗
DOE OSTI2024

Techno-economic and life-cycle analysis of strategies for improving operability and biomass quality in catalytic fast pyrolysis of forest residues

Many of the challenges faced by the first commercial biorefineries were associated with feedstock handling, quality, and cost. Strategies are needed to enable further expansion of biorefineries and meet the growing demand for bio-based fuels and products. Here, we examine 2 key feedstock challenges and mitigation strategies in the context of a catalytic fast pyrolysis (CFP) biorefinery: (1) the operability of the feed system, which may be improved by modifying the minimum particle size fed to the reactor, and (2) the quality of the biomass, which may be improved by employing air classification to remove undesirable material and increase fuel yields. We conduct techno-economic analysis (TEA) and life-cycle analysis for these strategies, employing a discrete event simulation model for biomass preprocessing combined with a series of correlations developed from literature data and a rigorous CFP conversion model. Our results highlight the importance of balancing increased cost and material losses from preprocessing against improved operability and fuel yields. Economics and sustainability were optimized when operating at the lowest minimum particle size, emphasizing the importance of minimizing material losses while maintaining the operability of the process. Economically, additional costs and material losses from air classification could be acceptable due to improved biomass conversion, and an optimum air classification speed was identified; however, the fuel GHG emissions were minimized when air classification was not used. Valorizing material removed during preprocessing as a coproduct could improve economics and sustainability, decreasing the burden of material losses.

09 - BIOMASS FUELS↗
NASA NTRS1993

Measurement of polycyclic aromatic hydrocarbon (PAHs) in interplanetary dust particles

We report here the first definitive measurements of specific organic molecules (polycyclic aromatic hydrocarbons (PAH's)) in interplanetary dust particles (IDP's). An improved version of the microbeam-two-step laser mass spectrometer was used for the analysis. Two IDP's gave similar mass spectra showing an abundance of PAH's. Control samples, including particles of probable terrestrial origin from the same stratospheric collector, gave either null results or quite different spectra. We conclude that the PAH's are probably indigenous to the IDP's and are not terrestrial contaminants. The instrument used to study the particles is a two-step laser mass spectrometer. Constituent neutral molecules of the sample are first desorbed with a pulsed infrared laser beam focussed to 40 micrometers. In the second step, PAH's in the desorbed plume are preferentially ionized by a pulsed UV laser beam. Resulting ions produced by resonant absorption are extracted into a reflectron time-of-flight mass spectrometer. This instrument has high spatial resolution, high ion transmission, unlimited mass range, and multichannel detection of all ion masses from a single laser shot.

Clemett, S. J.↗
DOE OSTI2022

Critical Barriers to Successful Implementation of Earth-Abundant, Mn-Rich Cathodes for Vehicle Applications and Beyond: The Effect of Particle Morphology

As the search for improved and next-generation cathodes continues, it is clear that a deeper understanding of synthesis–structure–electrochemical property relationships is of critical importance. The effects of primary and secondary particle morphologies on various transition metal oxides have been studied, but new findings are still being reported. To date, few studies have focused on the effects of particle morphologies on Li- and Mn-rich oxides (>50% Mn) and even fewer studies have focused on the influence over key properties such as electrode-level impedance. In this study, we report the effects of particle morphologies on the area-specific-impedance (ASI) and thermal behavior of Li- and Mn-rich oxides. Samples with a fixed, layered–layered–spinel (LLS), composition were synthesized with differing primary morphologies and tested under standardized, full-cell protocols. The results suggest that smaller primary particle size (i.e., higher surface area) leads to lower overall ASI, a delay in the increasing impedance at low states-of-charge (SOCs), and surprisingly, improved thermal behavior.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Strategy and performance of the CMS long-lived particle trigger program in proton-proton collisions at $\sqrt{s}$ = 13.6 TeV

In the physics program of the CMS experiment during the CERN LHC Run 3, which started in 2022, the long-lived particle triggers have been improved and extended to expand the scope of the corresponding searches. These dedicated triggers and their performance are described in this paper, using several theoretical benchmark models that extend the standard model of particle physics. The results are based on proton-proton collision data collected with the CMS detector during 2022$-$2024 at a center-of-mass energy of 13.6 TeV, corresponding to integrated luminosities of up to 123 fb$^{-1}$.

FOS: Physical sciences↗
DOE OSTI2024

Photocathode characterisation for robust PICOSEC Micromegas precise-timing detectors

The PICOSEC Micromegas detector is a precise-timing gaseous detector based on a Cherenkov radiator coupled with a semi-transparent photocathode and a Micromegas amplifying structure, targeting a time resolution of tens of picoseconds for minimum ionising particles. Initial single-pad prototypes have demonstrated a time resolution below σ = 25 ps, prompting ongoing developments to adapt the concept for High Energy Physics applications, where sub-nanosecond precision is essential for event separation, improved track reconstruction and particle identification. The achieved performance is being transferred to robust multi-channel detector modules suitable for large-area detection systems requiring excellent timing precision. To enhance the robustness and stability of the PICOSEC Micromegas detector, research on robust carbon-based photocathodes, including Diamond-Like Carbon (DLC) and Boron Carbide (B 4 C), is pursued. Results from prototypes equipped with DLC and B 4 C photocathodes exhibited a time resolution of σ ≈ 32 ps and σ ≈ 34.5 ps, respectively. Efforts dedicated to improve detector robustness and stability enhance the feasibility of the PICOSEC Micromegas concept for large experiments, ensuring sustained performance while maintaining excellent timing precision.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Leveraging machine learning to enhance aerosol classification using Single-Particle Mass Spectrometry

Advancing automated classification of atmospheric aerosols from Single-Particle Mass Spectrometry (SPMS) data remains challenging due to overlapping ion signatures, compositional diversity, and limited labeled data. This study evaluates supervised and semi-supervised learning frameworks to enhance aerosol identification by jointly leveraging labeled and unlabeled spectra. Four models were compared: a supervised Support Vector Machine (SVM), a self-training SVM, a stacked autoencoder classifier, and a stacked autoencoder trained using a temporal-ensembling Mean Teacher approach. All models achieved high and stable accuracies (90.0 %–91.1 %), surpassing previous results on the same dataset (87 %) and matching the performance of state-of-the-art deep learning methods. Despite small global metric differences (≤ 1 %), semi-supervised variants yielded up to 5 %–10 % improvements for compositionally rare particle types – such as soot (0.77 % of spectra, F1-score: 0.93–0.97) and hazelnut pollen (0.98 % of spectra, F1-score: 0.97–1.00) – equating to roughly ∼ 187 additional correctly classified spectra. These gains are scientifically significant, as such rare particles exert disproportionate influence on radiative absorption and ice nucleation processes; their improved detection reduces modeled uncertainties in aerosol absorption optical depth and mixed-phase cloud ice nucleation rates. The models' residual misclassifications (≈ 9 %) largely arise from true spectral overlap among chemically adjacent species (e.g., Na- vs. K-feldspar, coated vs. uncoated feldspars), reflecting physical compositional continuity rather than algorithmic error. Collectively, these findings demonstrate that leveraging unlabeled data to learn robust spectral representations and refine classification enhances both fidelity and interpretability, bridging data-driven analysis with aerosol–climate process understanding.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Multiphysics modeling of accelerators through code integration

This work aims to improve the ability of particle accelerator researchers to develop high-performance accelerator cavity designs by creating an overall multiphysics framework that integrates and couples existing application codes. This framework will allow accelerator researchers to build multiphysics models that will optimize cavity design, improve understanding of whole-device performance, and reduce the development and fabrication costs of accelerator research. We utilize the open-source VizSchema data standard as an intermediate data structure interface layer to standardize interfaces between individual application codes. VizScema is extensively documented online, and plugins for VizSchema are available for popular visualization packages, including VisIt and ParaView. Currently, the work focuses on coupling the EM field solver COMSOL and the electron gun code MICHELLE to allow COMSOL field-solve results to be seamlessly used by MICHELLE for particle-solve. Later work will extend this integration to include other fields, particles, and thermodynamics simulation codes.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Investigation of Coincidence Counting for Improving Minimal Detectable Activity of 110m Ag in Single Particle Gamma Analysis

Post-irradiation examination (PIE) of fuel particles from the fourth Advanced Gas Reactor Fuel Development and Qualification (AGR) Program irradiation (AGR-5/6/7) is being performed at Oak Ridge National Laboratory (ORNL). Tristructural isotropic (TRISO)-coated particles and associated compacts for the AGR-5/6/7 experiment fabricated by BWX Technologies Nuclear Operations Group were formed into a graphite matrix compact and irradiated at the Advanced Test Reactor at Idaho National Laboratory. At ORNL, particles are deconsolidated from the graphite matrix compact and individually scanned for emitted gamma rays with the Irradiated Microsphere Gamma Analyzer (IMGA). The IMGA system comprises a single high purity germanium (HPGe) detector, an automated particle handling vacuum system, and an ORTEC DSPEC-50 digital spectrometer for gamma ray analysis. IMGA quantifies gamma ray-emitting fission product inventories of individual TRISO particles, and these inventories can be compared with the measured average inventories per particle and radionuclide inventories predicted by AGR-5/6/7 physics calculations to determine if a particle experienced radionuclide release. Details on IMGA data collection methods can be found in the literature. The TRISO particle’s SiC layer provides structural support, as well as a barrier for fission product release during irradiation or subsequent safety testing. A weakened or compromised SiC layer can be identified by the release of radionuclides, such as 137 Cs, which is detected by IMGA. However, select radionuclides, such as 90 Sr, 110 mAg, and 154 Eu have been shown to migrate through an intact SiC layer. Measurement of the radionuclide 110 mAg is significant as its release has been shown to be particularly sensitive to in-reactor conditions (e.g., temperature) with broad variable particle to-particle release behaviors observed within a single compact. As such, 110 mAg activity is often used for particle selection for comprehensive PIE as bounding 110 mAg retention particles are hypothesized to represent limits in particle behaviors within a compact. As TRISO particle fuel PIE activities continue over time, IMGA measurements of the 110 mAg inventory are eventually hindered because of its relatively short half-life (~250 days). As the fuel ages from its end of irradiation (EOI) date, the measurement uncertainty and minimum detectable activity (MDA) of 110m Ag increase because the detector background continuum begins to dominate. For particles from the second AGR irradiation experiment (AGR-2), the 110m Ag MDA was above 20% of the calculated average particle inventory after approximately five half-lives, and 110m Ag activity was no longer measurable with IMGA after approximately seven half-lives. Therefore, coincidence counting approaches have been explored to determine feasibility of leveraging new approaches to overcome limitations associated with increasing MDA over time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1977

Effect of the Shuttle contaminant environment on a sensitive infrared telescope

A sensitive IR telescope on the Space Shuttle Orbiter will be limited in its performance by fluctuations in the IR radiation from the natural environment and the contaminant atmosphere. Models of the Orbiter's contaminant atmosphere were used to predict its spectral radiance from 3 to 300 microns. At 350 km, statistical fluctuations in the radiation from a water vapor column, and a noise equivalent power were measured. This noise is somewhat smaller than the expected contribution from zodiacal light from 5 to 30 microns. The column density of all IR emitting molecules can be kept low only if restrictions on rocket firings and liquid vents are maintained. The relatively low frequency of particle sightings from Skylab, coupled with improvements in Orbiter venting techniques, indicate that sightings of particles 2 microns and larger in radius will not seriously hamper telescope performance provided that liquid vents and rocket firings are properly restricted.

Simpson, J. P.↗
NASA NTRS2014

Recalibrated Equations for Determining Effect of Oil Filtration on Rolling Bearing Life

In 1991, Needelman and Zaretsky presented a set of empirically derived equations for bearing fatigue life (adjustment) factors (LFs) as a function of oil filter ratings. These equations for life factors were incorporated into the reference book, "STLE Life Factors for Rolling Bearings." These equations were normalized (LF = 1) to a 10-micrometer filter rating at Beta(sub x) = 200 (normal cleanliness) as it was then defined. Over the past 20 years, these life factors based on oil filtration have been used in conjunction with ANSI/ABMA standards and bearing computer codes to predict rolling bearing life. Also, additional experimental studies have been made by other investigators into the relationship between rolling bearing life and the size, number, and type of particle contamination. During this time period filter ratings have also been revised and improved, and they now use particle counting calibrated to a new National Institute of Standards and Technology (NIST) reference material, NIST SRM 2806, 1997. This paper reviews the relevant bearing life studies and describes the new filter ratings. New filter ratings, Beta(sub x(c)) = 200 and Beta(sub x(c)) = 1000, are benchmarked to old filter ratings, Beta(sub x) = 200, and vice versa. Two separate sets of filter LF values were derived based on the new filter ratings for roller bearings and ball bearings, respectively. Filter LFs can be calculated for the new filter ratings.

Needelman, William M.↗
DOE OSTI2024

Predicting Adhesion Energies of Metal Nanoparticles to Support Surfaces, Which Determines Metal Chemical Potential versus Particle Size and Thus Catalyst Performance

Improved catalysts and electrocatalysts composed of transition metal nanoparticles dispersed on high-area supports are essential for energy and environmental technologies. The chemical potential of the metal atoms in these supported nanoparticles is an important descriptor that correlates with both their catalytic activity and deactivation rate. This descriptor (μ M ) is predictably determined by the particle size and the adhesion energy per unit area at the metal/support interface (E adh ). We show here that the adhesion energies for different metals on a given support scale linearly with a simple property of the metal: for oxides, it is proportional to the metal oxophilicity, and for the carbon support, it increases linearly with metal carbophilicity (both divided by the area per metal atom). Furthermore, these relationships allow predicting E adh for other metal/support combinations, thus allowing estimation of μ M versus particle size and thereby better structure-based predictions of catalysts’ performance, which can aid in designing improved catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

High velocity pulsed wire-arc spray

Wire arc spraying using repetitively pulsed, high temperature gas jets, usually referred to as plasma jets, and generated by capillary discharges, substantially increases the velocity of atomized and entrained molten droplets. The quality of coatings produced is improved by increasing the velocity with which coating particles impact the coated surface. The effectiveness of wire-arc spraying is improved by replacing the usual atomizing air stream with a rapidly pulsed high velocity plasma jet. Pulsed power provides higher coating particle velocities leading to improved coatings. 50 micron aluminum droplets with velocities of 1500 m/s are produced. Pulsed plasma jet spraying provides the means to coat the insides of pipes, tubes, and engine block cylinders with very high velocity droplet impact.

Witherspoon, F. Douglas↗
DOE OSTI2021

A new hypothesis for air loss in cement systems containing fly ash

Although there are many benefits gained from incorporating fly ash into concrete, carbon contamination in the fly ash has been shown to interfere with the efficacy of organic additives in an unpredictable manner. This work uses surface tension measurements to quantify the adsorption of air-entraining agents (AEA) onto cement and fly ash. Both the adsorption capacity of the adsorbents and the adsorption isotherms indicate that the fly ash particles, rather than the carbon itself, dominate adsorption in a carbon-contaminated ash in cement pore solution. We propose that adsorption onto fly ash particles and cement actually improve air entrainment via Pickering stabilization. While the carbon is still expected to contribute to air loss via hydrophobic adsorption of the surfactants, we suggest that the primary way in which the carbon interferes is by shielding surfactant-coated fly ash particles from participating in air development and Pickering stabilization during mixing.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Transforming U.S. Particle Physics Education: A Snowmass 2021 Study

The pursuit of knowledge in particle physics requires constant learning. As new tools become available, new theories are developed, and physicists search for new answers with ever-evolving methods. However, it is the case that formal educational systems serve as the primary training grounds for particle physicists. Graduate school (and undergraduate school to a lesser extent) is where researchers learn most of the technical skills required for research, develop scientific problem-solving abilities, learn how to establish themselves in their field, and begin developing their career. It is unfortunate, then, that the skills gained by physicists during their formal education are often mismatched with the skills actually required for a successful career in physics. We performed a survey of the U.S. particle physics community to determine the missing elements of graduate and undergraduate education and to gauge how to bridge these gaps. In this contributed paper, part of the 2021-22 Snowmass Community Planning Exercise, we report the results of this survey. We also recommend several specific community actions to improve the quality of particle physics education; the "community" here refers to physics departments, national labs, professional societies, funding agencies, and individual physicists.

Bitter, O.↗
DOE OSTI2025

Simulating Alpha Particles Incident on MKID Chips for Quantum Sensitivity Analysis

Superconducting quantum devices, such as microwave kinetic inductance detectors (MKIDs), are highly sensitive instruments used in quantum computing and advanced sensing technologies. However, their extreme sensitivity also makes them vulnerable to background noise from natural sources like radiation. One significant contributor to this noise is alpha particles emitted by 210Po, a radon decay daughter that accumulates on surfaces near the detector. This project investigates how alpha particles emitted from 210Po interact with MKID chips. These particles can deposit energy on the detector surface, disrupting its operation and generating false signals. Understanding the energy and behavior of these particles is crucial for improving the design and reliability of quantum devices. To explore this, we first modeled the decay chain starting from 210Pb to 210Po using differential equations. This allowed us to predict how the activity of alpha-emitting isotopes changes over time, reaching a steady state after about two years. Next, we simulated alpha particle interactions with the MKID chip using the Geant4 software toolkit. We built a detailed computer model of the detector housing, including the copper lid where alpha particles originate, the silicon chip, and a thin aluminum sensor layer. Alpha particles were emitted isotropically from just beneath the copper lid’s surface, mimicking natural decay conditions. The simulation tracked how these particles deposit energy on the chip, generating electron-hole pairs and phonons. The results provide insight into the behavior of the resultant electron-hole pairs and phonons, giving us a clear understanding of the energy deposition distribution on the chip. This work supports efforts to mitigate background noise in superconducting sensors, advancing their use in quantum computing and sensitive physics experiments.

Hall, Matthew [Fermilab; UCLA]↗
DOE OSTI2021

Data-Driven Specification of Earth's Magnetic Field

As our society is increasingly dependent on technologies in space, predicting space weather becomes ever more important. We have come to rely on technologies such as cellphones, GPS, the Internet, and other commercial and military assets. In order to protect these systems a high priority is to develop better understanding of the harmful conditions of space weather encountered in the near-Earth radiation environment which are mostly dictated by the dynamics of energetic charged particles. The main objective of our proposal was to improve the specification and forecast of the particle distribution in the Earth’s inner magnetosphere using data assimilation together with machine learning (ML) algorithms in our ring current-atmosphere interactions model with self-consistent magnetic and electric fields (RAM-SCBE). Specifically, we explored the application of machine learning algorithms to emulate and improve, through infusion of observational data, the magnetic field (SCBE) of our ring current model. Our work advanced towards the characterization of the RAM-SCBE particle flux field and its potentially different simulation scenarios. We explored how the model behaves in a number of simulation scenarios in order to better understand how the model reacts to perturbations in the solar wind. We were able to capture this behavior through the simulation of an ensemble of RAM-SCB model solutions. The ensemble showed the important correlations between the particle fluxes and the magnetic field. We were able to start the training of a neural network (Autoencoder) to identify the dominant features of the magnetic field, and the main correlations (linear and non-linear) between the particle fluxes and the magnetic field. Our next steps consists of training a neural network to capture the time evolution of the dominant features and obtain a consistent surrogate model for the RAM-SCB.

42 ENGINEERING↗
NASA NTRS2021

Indirect Dark Matter Searches at Ultrahigh Energy Neutrino Detectors

High to ultrahigh energy neutrino detectors can uniquely probe the properties of dark matterχby searching for the secondary products produced through annihilation and/or decay processes. We evaluate the sensitivities to dark matter thermally averaged annihilation cross section〈σv〉and partial decay width into neutrinos Γ χ→ν ̄ν (in the mass scale 10 7 ≤ m χ /GeV ≤ 10 15 ) for next generation observatories like POEMMA and GRAND. We show that in the range 10 7 ≤ m χ /GeV ≤ 10 11 , space-based Cherenkov detectors like POEMMA have the advantage of full-sky coverage and rapid slewing, enabling an optimized dark matter observation strategy focusing on the Galactic center. We also show that ground-based radio detectors such as GRAND can achieve high sensitivities and high duty cycles in radio quiet areas. We compare the sensitivities of next generation neutrino experiments with existing constraints from IceCube and updated 90% C.L. upper limits on〈σv〉and Γ χ→ν ̄ν using results from the Pierre Auger Collaboration and ANITA. We show that in the range 10 7 ≤ m χ /GeV ≤ 10 11 POEMMA and GRAND10k will improve the neutrino sensitivity to particle dark matter by factors of 2 to 10 over existing limits, whereas GRAND200k will improve this sensitivity by two orders of magnitude. In the range 10 11 ≤ m χ /GeV ≤ 10 15 , POEMMA’s fluorescence observation mode will achieve an unprecedented sensitivity to dark matter properties. Finally, we highlight the importance of the uncertainties related to the dark matter distribution in the Galactic halo, using the latest fit and estimates of the Galactic parameters.

Particle astrophysics↗