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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 OSTI2020

Measurement of Low-$Q^2$ Protons from Neutral Current Events in Argon with MicroBooNE

The MicroBooNE experiment is an 85 ton active mass liquid-argon time projection chamber located at the Fermilab Booster Neutrino Beamline. MicroBooNE’s ability to detect low-energy protons allows us to study single-proton events with a four-momentum transfer squared Q 2 as low as 0.10 GeV 2 . We present a differential cross-section measurement of a signal with one proton and no other particles (NC1p) in the final state. We report the flux-averaged NC1p differential cross section dσ/dT for neutrinos scattering on argon as a function of proton kinetic energy T using a subset of MicroBooNE’s data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Interacting radiation after Planck and its implications for the Hubble tension

Standard cosmology predicts that prior to matter-radiation equality about 41% of the energy density was in free-streaming neutrinos. In many beyond Standard Model scenarios, however, the amount and free-streaming nature of this component is modified. For example, this occurs in models with new neutrino self-interactions or an additional dark sector with interacting light particles. Here, we consider several extensions of the standard cosmology that include a non-free-streaming radiation component as motivated by such particle physics models and use the final Planck data release to constrain them. This release contains significant improvements in the polarization likelihood which plays an important role in distinguishing free-streaming from interacting radiation species. Fixing the total amount of energy in radiation to match the expectation from standard neutrino decoupling we find that the fraction of free-streaming radiation must be ffs > 0.8 at 95% CL (combining temperature, polarization and baryon acoustic oscillation data). Allowing for arbitrary contributions of free-streaming and interacting radiation, the effective number of new non-free-streaming degrees of freedom is constrained to be Nfld < 0.6 at 95% CL. Cosmologies with additional radiation are also known to ease the discrepancy between the local measurement and CMB inference of the current expansion rate H0. We show that including a non-free-streaming radiation component allows for a larger amount of total energy density in radiation, leading to a mild improvement of the fit to cosmological data compared to previously discussed models with only a free-streaming component.

particle physics - cosmology connection↗
DOE OSTI2020

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

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

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Experimental Study of the Fundamental Properties of Warm Dense Mixtures

The aim of the proposed research was to provide a multi-scale study of the properties of warm dense hydrocarbons, by studying the thermodynamic properties through the equation of state and the microscopic properties by x-ray scattering. Understanding the fundamental properties of warm dense mixtures is an intellectual challenge due to the complexity of the system. Unlike liquids or gases, where constituent particle interactions occur through collisions or bonding between valence electrons, in these strongly coupled systems the atoms will be partially ionized and compressed so tightly together that interactions between the inner core electrons can play a role in the systems chemistry. Advances in computational capabilities and development of new theoretical models have been used to predict the properties of mixtures but there is currently no experimental data of the fundamental interaction between the particles in mixtures to test these predictions against. The proposed research was to experimentally investigate the interaction of the different species in hydrocarbons by measuring the compressibility of substances with different carbon and hydrogen ratios and the complexity of the microscopic interactions through elastic and inelastic x-ray scattering. To study the bulk properties of warm dense hydrocarbons we established the Warm Dense Matter Research Laboratory (WDMRL) in the Institute for Shock Physics at Washington State University. The goal was for experiments in the WDMRL to determine shock loading conditions of interest in the hydrocarbon mixtures. We planned on using Hugoniot EOS measurements and a range of carbon and hydrogen concentrations to determine conditions when the EOS of the mixture varied significantly from that of the classical mixing model. Even though shock transit measurements through aluminum foils suggested pressures upto 400GPa, the experiments in the WDMRL were unsuccessful in getting usable shockwave compression data above 100GPa in polystyrene which was below the pressure of interest for hydrocarbon mixtures (>200GPa). To complete the project, we tested a technique using x-ray phase contrast imaging to map the location of tracer layers in a test sample of polycarbonate to record the material motion in dynamically compressed samples. A technique that will be useful for future warm dense matter experiments. These experiments used <200nm gold layers in polycarbonate samples to measure the material velocity and shock speed using x-ray phase contrast imaging. These results were compared to continuum surface measurements performed at ISP and show that the tracer layer technique can measure hydrodynamic properties accurately in dynamically compressed materials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Global quantification of the dispersion effect with POLDER satellite data

Increased aerosols can modify the shape of the cloud Particle Size Distribution (PSD), thereby influencing the radiative properties of clouds, known as the Dispersion Effect (DE). However, a global, observation-based quantification of its impact on Aerosol-Cloud Interactions (ACI) is lacking, leading to DE being typically ignored in satellite-based estimates of ACI forcing. Here we propose a physics-based method that combines polarimetric satellite data on cloud PSD to achieve global observational quantification of DE’s impact on ACI in liquid-phase stratiform clouds. Globally, DE offsets ACI changes induced by droplet number concentration variation and liquid water path adjustment by 7% and −1.4%, respectively. Furthermore, a parameterization based on the global dataset of PSD shape parameters is developed to improve DE estimation in large-scale models. Both the quantification and parameterization enhance our understanding of DE and facilitate the inclusion of this non-negligible impact of DE on ACI in estimating aerosol climate forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Assembly of small silica nanoparticles using lipid-tethered DNA ‘bonds’

Single-stranded DNA molecules modified with cholesterol functional groups are physically tethered to silica nanoparticles (diameter 25 nm) that are encapsulated in a lipid bilayer. Such tethering increases the azimuthal mobility of the DNA molecules across the nanoparticle surface and enables nonspecific bonding, eliminating the need for specialized surface chemistries (such as silane or thiol ligands). To induce assembly, double-stranded DNA ‘bridge’ molecules are then added with complementary nucleotides to the DNA ‘anchor’ molecules that are physically tethered to the lipids on the surface of the particles. Assembly is observed to occur at room temperature and without the need for temperature annealing. Using automated liquid handling tools, assemblies are created in high throughput and rapidly characterized using SAXS. It is determined that the relative concentration of DNA-to-silica and the ionic strength of the solution are important parameters that affect the resulting assembly. Analysis of SAXS data is performed using coarse-grained particle dynamics simulations. The results support the spontaneous formation of semi-crystalline particle assemblies by particle condensation, where the interparticle distance is tuned by the sequence of the DNA ‘bridge’ used to link the particles. Crystallinity analysis performed on the resulting simulations, optimized to match SAXS observations, suggest that particle clusters display increased crystallinity in the center of the clusters, but their maximum size remains relatively small (sub-micron) before settling occurs, which limits the extent of crystallization.

Chiang, Huat Thart [Univ. of Washington, Seattle, ↗
DOE OSTI2020

CR-39 nuclear track detector response to inertial confinement fusion relevant ions

The detection properties of CR-39 were investigated for protons, deuterons, and tritons of various energies. Two models for the relationship between the track diameter and particle energy are presented and demonstrated to match experimental data for all three species. Data demonstrate that CR-39 has 100% efficiency for protons between 1 MeV and 4 MeV, deuterons between 1 MeV and 12.2 MeV, and tritons between 1 MeV and 10 MeV. The true upper bounds for deuterons and tritons exceed what could be measured in data. Simulations were developed to further explore the properties of CR-39 and suggest that the diameter–energy relationship of alpha particles cannot be captured by the conventional c-parameter model. These findings provide confidence in CR-39 track diameter based spectroscopy of all three species and provide invaluable insight for designing filtering for all CR-39 based diagnostics.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Kinetic-energy dissipation and fluctuations in strongly damped heavy-ion collisions within the stochastic mean-field approach

Microscopic mean-field approaches have been successful in describing the most probable reaction outcomes in low-energy heavy-ion reactions. However, those approaches are known to severely underestimate dispersions of observables around the average values that has limited their applicability. Recently it has been shown that a quantal transport approach based on the stochastic mean-field (SMF) theory significantly improves the description, while its application has been limited so far to fragment mass and charge dispersions. In this work, we extend the quantal transport approach based on the SMF theory for relative kinetic energy dissipation and angular momentum transfer in low-energy heavy-ion reactions. Based on the SMF concept, analytical expressions are derived for the radial and tangential friction and associated diffusion coefficients. Those quantal transport coefficients are calculated microscopically in terms of single-particle orbitals within the time-dependent Hartree-Fock (TDHF) approach. As the first application of the proposed formalism, we consider the radial linear momentum dispersion, neglecting the coupling between radial and angular momenta. We analyze the total kinetic energy (TKE) distribution of binary reaction products in the 136 Xe + 208 Pb reaction at E c.m. =526 MeV and compare with experimental data. From time evolution of single-particle orbitals in TDHF, the radial diffusion coefficient is computed on a microscopic basis, while a phenomenological treatment is introduced for the radial friction coefficient. By solving the quantal diffusion equation for the radial linear momentum, the dispersion of the radial linear momentum is obtained, from which one can construct the TKE distribution. We find that the calculations provide a good description of the TKE distribution for strongly damped events with large energy losses, TKEL ≳ 150 MeV. However, the calculations underestimate the TKE distribution for smaller energy losses. Further studies are needed to improve the technical details of calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Bulk observables at 5.02 TeV using quasiparticle anisotropic hydrodynamics

Abstract We compare predictions of 3+1D quasiparticle anisotropic hydrodynamics (aHydroQP) for a large set of bulk observables with experimental data collected in 5.02 TeV Pb–Pb collisions. We make predictions for identified hadron spectra, identified hadron average transverse momentum, charged particle multiplicity as a function of pseudorapidity, the kaon-to-pion ( $$K/\pi $$ K / π ) and proton-to-pion ( $$p/\pi $$ p / π ) ratios, identified particle and charged particle elliptic flow, and HBT radii. We compare to data collected by the ALICE collaboration in 5.02 TeV Pb–Pb collisions. We find that, based on available data, these bulk observables are well described by aHydroQP with an assumed initial central temperature of $$T_0=630$$ T 0 = 630 MeV at $$\tau _0 = 0.25$$ τ 0 = 0.25 fm/c and a constant specific shear viscosity of $$\eta /s=0.159$$ η / s = 0.159 , which corresponds to a peak specific bulk viscosity of $$\zeta /s = 0.048$$ ζ / s = 0.048 . In particular, we find that the momentum dependence of the kaon-to-pion ( $$K/\pi $$ K / π ) and proton-to-pion ( $$p/\pi $$ p / π ) ratios reported recently by the ALICE collaboration are extremely well described by aHydroQP in the 0–5% centrality class.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Understanding protein-complex assembly through grand canonical maximum entropy modeling

Inside a cell, heterotypic proteins assemble in inhomogeneous, crowded systems where the abundance of these proteins vary with cell types. While some protein complexes form putative structures that can be visualized with imaging, there are far more protein complexes that are yet to be solved because of their dynamic associations with one another. Nevertheless, it is possible to infer these protein complexes through a physical model. However, it is often not clear to physicists what kind of data from biology is necessary for such a modeling endeavor. Here, we aim to model these clusters of coarse-grained protein assemblies from multiple subunits through the constraints of interactions among the subunits and the chemical potential of each subunit. We obtained the constraints on the interactions among subunits from the known protein structures. We inferred the chemical potential that dictates the particle number distribution of each protein subunit from the knowledge of protein abundance from experimental data. Guided by the maximum entropy principle, we formulated an inverse statistical mechanical method to infer the distribution of particle numbers from the data of protein abundance as chemical potentials for a grand canonical multicomponent mixture. Using grand canonical Monte Carlo simulations, we captured a distribution of high-order clusters in a protein complex of succinate dehydrogenase with four known subunits. The complexity of hierarchical clusters varies with the relative protein abundance of each subunit in distinctive cell types such as lung, heart, and brain. When the crowding content increases, we observed that crowding stabilizes emergent clusters that do not exist in dilute conditions. We, therefore, proposed a testable hypothesis that the hierarchical complexity of protein clusters on a molecular scale is a plausible biomarker of predicting the phenotypes of a cell.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Data for The impact of aerosol mixing state on immersion freezing: Insights from classical nucleation theory and particle-resolved simulations

This dataset contains the values directly shown in the figures of the article "The impact of aerosol mixing state on immersion freezing: Insights from classical nucleation theory and particle-resolved simulations". This article is in preparation for submission to the journal Atmospheric Chemistry and Physics. The dataset consists of 12 NetCDF files processed from the raw output of the PartMC model. It does not include the theoretical values of frozen fraction, which can be computed using the equations provided in the paper. *New in V2: adding data for a newly included figure (INP_spectrum.nc), removing files that are no longer used in the revised manuscript figures (e.g., UNC_A_ratio=0.9_Dp=0.1.nc, UNC_A_ratio=0.9_Dp=10.0.nc, UNC_A_ratio=0.1_Dp=0.1.nc, and UNC_A_ratio=0.1_Dp=10.0.nc), and updating README.pdf accordingly.

Aerosol mixing state↗
DOE OSTI2025

Search for hadronic decays of feebly-interacting particles at NA62

The NA62 experiment at CERN has the capability to collect data in a beam-dump mode, where 400 GeV protons are dumped on an absorber. In this configuration, New Physics particles, including dark photons, dark scalars, and axion-like particles, may be produced in the absorber and decay in the instrumented volume beginning approximately 80 m downstream of the dump. A search for these particles decaying in flight to hadronic final states is reported, based on an analysis of a sample of 1.4 x 10 17 protons on dump collected in 2021. No evidence of a New Physics signal is observed, excluding new regions of parameter spaces of multiple models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Interparticle Characterization of Mechanical Biomass Particle-Particle and Particle-Wall Interactions

The biomass materials industry faces significant challenges in managing material variability and its impact on storage and handling systems. Physical properties such as moisture content, particle size, and density fluctuate considerably, leading to operational issues like bridging and ratholing that disrupt material flow. These variations create a complex cascade effect throughout the process chain, affecting transportation, storage, and conversion processes. The economic consequences of this variability manifest in increased operational costs, maintenance requirements, and system downtime. Environmental factors further complicate the situation, as weather conditions and seasonal availability influence material properties and system performance. Engineers employ specialized equipment design, material characterization protocols, and pre-processing steps like size reduction and homogenization to address these challenges. A critical knowledge gap exists between continuous-level constitutive models and particle-scale behavior. This project developed a novel device to quantify interparticle mechanics between biomass particles, measuring friction and adhesion forces between particles and wall materials. The research focused on corn stover and southern pine forest residue, creating a comprehensive database of particle interactions. This breakthrough enables direct application in particle-based computational modeling, advancing the field's understanding of biomass handling characteristics and supporting the development of more reliable and efficient storage and handling systems. The project's outcomes contribute significantly to understanding biomass's mechanical and flow characteristics, particularly how variability at the particle level affects larger-scale handling operations. This knowledge is crucial for engineering feedstock supply systems that consistently meet quality and cost specifications for various conversion processes. The innovative experimental setup developed through this research represents a significant advancement in biomass characterization methodology. Providing precise measurements of particle-level interactions establishes a foundation for more accurate predictive modeling of bulk material behavior. This enhanced understanding of fundamental particle mechanics enables engineers to anticipate better and address handling challenges before they manifest in full-scale operations. This research opens new avenues for optimizing biomass handling systems through data-driven design approaches. The comprehensive database of particle interactions serves as a valuable resource for future research and development efforts, potentially leading to more efficient and cost-effective biomass processing solutions. This advancement in particle-level mechanics could revolutionize how biomass handling systems are designed and operated, contributing to more sustainable and reliable renewable energy production.

09 BIOMASS FUELS↗
DOE OSTI2026

On-chip probabilistic inference for charged-particle tracking at the sensor edge

Modern scientific instruments operate under increasingly extreme constraints on bandwidth, latency, and power. Inference at the sensor edge determines experimental data collection efficiency by deciding which information to save for further analysis. Particle tracking detectors at the Large Hadron Collider exemplify this challenge: pixelated silicon sensors generate rich spatiotemporal ionization patterns, yet most of this information is discarded due to data-rate limitations. Concurrently, advancements in co-design tools provide rapid turn-around for incorporating machine learning into application-specific integrated circuits, motivating designs for particle detectors with new integrated technologies. We demonstrate that neural networks embedded in the front-end electronics can infer charged-particle kinematic parameters from a single silicon layer. We regress hit positions and incident angles with calibrated uncertainties, while satisfying stringent constraints on numerical precision, latency, and silicon area. Our results establish a path toward probabilistic inference directly at the edge, opening new opportunities for intelligent sensing in high-rate scientific instruments.

Das, Arghya Ranjan [Purdue U.] (ORCID:000000018451↗
DOE OSTI2023

End-to-End Pipeline for Trigger Detection on Hit and Track Graphs

There has been a surge of interest in applying deep learning in particle and nuclear physics to replace labor-intensive offline data analysis with automated online machine learning tasks. This paper details a novel AI-enabled triggering solution for physics experiments in Relativistic Heavy Ion Collider and future Electron-Ion Collider. The triggering system consists of a comprehensive end-to-end pipeline based on Graph Neural Networks that classifies trigger events versus background events, makes online decisions to retain signal data, and enables efficient data acquisition. Here, the triggering system first starts with the coordinates of pixel hits lit up by passing particles in the detector, applies three stages of event processing (hits clustering, track reconstruction, and trigger detection), and labels all processed events with the binary tag of trigger versus background events. By switching among different objective functions, we train the Graph Neural Networks in the pipeline to solve multiple tasks: the edge-level track reconstruction problem, the edge-level track adjacency matrix prediction, and the graph-level trigger detection problem. We propose a novel method to treat the events as track-graphs instead of hit-graphs. This method focuses on intertrack relations and is driven by underlying physics processing. As a result, it attains a solid performance (around 72% accuracy) for trigger detection and outperforms the baseline method using hit-graphs by 2% higher accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Exploratory investigation on the use of low-cost alternative media for ultrafine grinding of coal

In this study, the energy efficiency of three alternative grinding media including, coarse silica beads, fine silica beads, and granular sand, were evaluated and compared against standard stainless steel. Stirred mill test results show that both silica beads and granular sand were more efficient than stainless steel in producing ultrafine particles following the order of coarse silica beads>granular sand>fine silica beads>stainless steel. The finest product size corresponding to a P 80 value of 2.33 μm was generated by coarse silica beads with a nominal size of 420×1190 μm, which also consumed the least amount of grinding energy. The specific energy input was reduced by almost 50% as opposed to that of stainless steel, while the operating work index was reduced by 87%. Overall, the test data indicate that grinding media density, media particle size and shape all play a role in determining the optimized grinding behavior of the coal material.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Data Storage for HEP Experiments in the Era of High-Performance Computing

As particle physics experiments push their limits on both the energy and the intensity frontiers, the amount and complexity of the produced data are also expected to increase accordingly. With such large data volumes, next-generation efforts like the HL-LHC and DUNE will rely even more on both high-throughput (HTC) and high-performance (HPC) computing clusters. Full utilization of HPC resources requires scalable and efficient data-handling and I/O. For the last few decades, ROOT has been used by most HEP experiments to store data. However, other storage technologies like HDF5 may perform better in HPC environments. Initial explorations with HDF5 have begun using ATLAS, CMS and DUNE data; the DUNE experiment has also adopted HDF5 for its data-acquisition system. This paper presents the future outlook of the HEP computing and the role of HPC, and a summary of ongoing and future works to use HDF5 as a possible data storage technology for the HEP experiments to use in HPC environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Search for an axion-like particle in B → K (*) a(→ γγ) decays at Belle

We report a search for an axion-like particle a in B → K (*) a decays using data collected with the Belle detector at the KEKB asymmetric-energy electron-positron collider. The search is based on a 711 fb −1 data sample collected at the Υ(4S) resonance energy, corresponding to a sample of 772 × 10 6 Υ(4S) events. In this study, we search for the decay of the axion-like particle into a pair of photons, a → γγ. We scan the two-photon invariant mass in the range 0.16 GeV–4.50 GeV for the K modes and 0.16 GeV–4.20 GeV for the K * modes. No significant signal is observed in any of the modes, and 90% confidence level upper limits are established on the coupling to the W boson, g aW , as a function of a mass. The limits range from 3 × 10 −6 GeV −1 to 3 × 10 −5 GeV −1 , improving the current constraints on g aW by a factor of two over the most stringent previous experimental results.

B physics↗