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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 415 records · Page 23

Path to Increasing p-B11 Reactivity via ps and ns Lasers

The Lawson criterion for proton-boron (p-11B) thermonuclear fusion is substantially higher than that for deuterium-tritium (DT) because the fusion cross section is lower and peaks at higher ion energies. The Maxwellian averaged p-11B reactivity peaks at several hundred keV, where bremsstrahlung radiation emission may dominate over fusion reactions if electrons and ions are in thermal equilibrium and the losses are unrestricted. Nonequilibrium burn has often been suggested to realize the benefits of this aneutronic reaction, but the predominance of elastic scattering over fusion reactivity makes this difficult to achieve. The development of ultrashort pulse lasers (USPL) has opened new possibilities for initiating nonequilibrium thermonuclear burns and significant numbers of p-11B alpha particles have been reported from several experiments. We present an analysis that shows that these significant alpha yields are the result of beam fusion reactions that do not scale to net energy gain. We further find that the yields can be explained by experimental parameters and recently updated cross sections such that a postulated avalanche mechanism is not required. We use this analysis to understand the underlying physics of USPL-driven nonequilibrium fusion reactions and whether they can be used to initiate fusion burns. We conclude by outlining a path to increasing the p-11B reactivity towards the goal of achieving ignition and describing the design principles that we will use to develop a computational point design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The impact of different neutrino transport methods on multidimensional core-collapse supernova simulations

Neutrinos play a crucial role in the core-collapse supernova (CCSN) explosion mechanism. The requirement of accurately calculating the transport of neutrinos makes simulations of the CCSN mechanism extremely challenging and computationally expensive. Historically, this stiff challenge has been met by making approximations to the full transport equation. In this work, we compare CCSN simulations in one- and two-dimensions with three approximate neutrino transport schemes, each implemented in the FLASH simulation framework. We compare a two-moment M1 scheme with an analytic closure (M1), the isotropic diffusion source approximation (IDSA), and the advanced spectral leakage method. We identify and discuss the advantages and disadvantages of each scheme. For each approximate transport scheme, we use identical grid setups, hydrodynamics, and gravity solvers to investigate the transport effects on supernova shock dynamics and neutrino quantities. We find that the transport scheme has a small effect on the evolution of protoneutron star (PNS) radius, PNS mass, and the mass accretion rate. The neutrino luminosities, mean energies, and shock radii have a ~10%–20% quantitative difference but the overall qualitative trends are fairly consistent between all three approximations. We find larger differences in the gain region properties, including the gain region mass and the net heating rate in the gain region, as well as the strength of PNS convection in the core. We investigate the progenitor, nuclear equation of state, and stochastic perturbation dependence of our simulations and find similar magnitudes of impact on key quantities. We also compare the computational expense of the various approximations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A machine learning study on spinodal clumping in heavy ion collisions

Possible observables of baryon number clustering due to the instabilities occurring at a first order QCD phase transition are discussed. The dynamical formation of baryon clusters at a QCD phase transition can be described by numerical fluid dynamics, augmented with a gradient term and an equation of state with a mechanically unstable region. It is shown that the dynamical description of this phase transition, in nuclear collisions, will lead to the formation of dense baryon clusters at the phase boundary. State-of-the-art machine learning methods find that the coordinate space clumping leaves characteristic imprints on the spatial net density distribution in almost every event. On the other hand the momentum distributions do not show any clear event-by-event features. Lastly, it is shown that the 'third order' cumulant, the skewness, shows a peak at the beam energy where the system, created in the heavy ion collision, reaches the deconfinement phase transition.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Formation and Properties of New Types of Metal–Dielectric Nanostructures for Creating Optical Metamaterials

“Herein, we consider the technologies of obtaining composite structures that can exhibit the properties of metamaterials, namely layered metal–dielectric (metal–polymer) structures and fish-net metal-polymeric structures. The dielectric and resonance properties of the synthesized structures are studied both theoretically and experimentally, and the excitation features of new types of quasi-non-diffraction plasmon-polaritons generated in them are established. Original methods and tools for characterizing the optical properties of the created composite structures (in particular, a differential polarization interferometer, a method and a device for detecting a negative refractive index) are proposed. Based on the developed and created metamaterials, a number of new devices are proposed and implemented, in particular, new configurations of flat lenses (so-called superlenses) of the near and far fields in the spectral range from ultraviolet to infrared radiation”.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

QCD equation of state at finite chemical potentials for relativistic nuclear collisions

In this work, we review the equation of state of QCD matter at finite densities. We discuss the construction of the equation of state with net baryon number, electric charge, and strangeness using the results of lattice QCD simulations and hadron resonance gas models. Its application to the hydrodynamic analyses of relativistic nuclear collisions suggests that the interplay of multiple conserved charges is important in the quantitative understanding of the dense nuclear matter created at lower beam energies. Several different models of the QCD equation of state are discussed for comparison.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Collision energy dependence of second-order off-diagonal and diagonal cumulants of net-charge, net-proton and net-kaon multiplicity distributions in Au+Au collisions

We report the first measurements of a complete second-order cumulant matrix of net-charge, netproton and net-kaon multiplicity distributions for the first phase of the beam energy scan program at RHIC. This includes the centrality and, for the first time, the pseudorapidity window dependence of both diagonal and off-diagonal cumulants in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7-200 GeV. Within the available acceptance of |η| < 0.5, the cumulants grow linearly with the pseudorapidity window. Relative to the corresponding measurements in peripheral collisions, the ratio of off-diagonal over 3 diagonal cumulants in central collisions indicates an excess correlation between net-charge and netkaon, as well as between net-charge and net-proton. The strength of such excess correlation increases with the collision energy. The correlation between net-proton and net-kaon multiplicity distributions is observed to be negative at $\sqrt{s_{NN}}$ = 200 GeV and change to positive at the lowest collision energy. Model calculations based on non-thermal (UrQMD) and thermal (HRG) production of hadrons cannot explain the data. Furthermore, these measurements will help map the QCD phase diagram, constrain hadron resonance gas model calculations and provide new insights on the energy dependence of baryon-strangeness correlations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Gate-Tunable Near-Field Heat Transfer

Active control over the flow of heat in the near-field holds promise for nanoscale thermal management, with applications in refrigeration, thermophotovoltaics, and thermal circuitry. Analogously to its electronic counterpart, the metal–oxide–semiconductor (MOS) capacitor, we propose a thermal switching mechanism based on accumulation and depletion of charge carriers in an ultrathin plasmonic film, via application of external bias. In our proposed configuration, the plasmonic film is placed on top of a polaritonic dielectric material that provides a surface phonon polariton (SPhP) thermal channel, while also ensuring electrical insulation for application of large electric fields. The variation of carrier density in the plasmonic film enables the control of the surface plasmon polariton (SPP) thermal channel. We show that the interaction of the SPP with the SPhP significantly enhances the net heat transfer. Here, we study SiC as the oxide and explore three classes of gate-tunable plasmonic materials, transparent conductive oxides, doped semiconductors, and graphene, and theoretically predict contrast ratios as high as 225%.

42 ENGINEERING↗

The High-redshift Clusters Occupied by Bent Radio AGN (COBRA) Survey: The Spitzer Catalog

We present 190 galaxy cluster candidates (most at high redshift) based on galaxy overdensity measurements in the Spitzer/IRAC imaging of the fields surrounding 646 bent, double-lobed radio sources drawn from the Clusters Occupied by Bent Radio AGN (COBRA) Survey. The COBRA sources were chosen as objects in the Very Large Array FIRST survey that lack optical counterparts in the Sloan Digital Sky Survey to a limit of m {sub r} = 22, making them likely to lie at high redshift. This is confirmed by our observations: the redshift distribution of COBRA sources with estimated redshifts peaks near z = 1 and extends out to z≈3. Cluster candidates were identified by comparing our target fields to a background field and searching for statistically significant (⩾2σ) excesses in the galaxy number counts surrounding the radio sources; 190 fields satisfy the ⩾2σ limit. We find that 530 fields (82.0%) have a net positive excess of galaxies surrounding the radio source. Many of the fields with positive excesses but below the 2σ cutoff are likely to be galaxy groups. Forty-one COBRA sources are quasars with known spectroscopic redshifts, which may be tracers of some of the most distant clusters known.

79 ASTRONOMY AND ASTROPHYSICS↗

On the formation mechanism of the ring-like microstructure of high-pressure die-cast A390 alloy

Highlights: • High-pressure die casting A390 alloy exhibited ring-like microstructure consisted of PSPs-free and PSPs-rich zones. • With 3D data, the size and morphology distribution of PSPs showed similar tendency regardless of the location. • The latent heat released from the PSPs led to the formation of ring-like band. • Widely observed defect band was inhibited because of the precipitation and growth of PSPs during solidification. - Abstract: The microstructure of the A390 alloy during high pressure die casting (HPDC), including pores, primary silicon particles (PSPs) and Cu-rich phases was characterized using synchrotron X-ray tomography. On the cross section of the sample exhibited ring-like or band microstructure, which comprised multiple PSPs-free and PSPs-rich zones. The PSPs distributed evenly in both size and morphology regardless of the ring-like microstructure. The size of aluminum dendrites changed according to the location of the ring-like microstructure, and was highly dependent on the local latent heat released from the PSPs as well as the distribution of the ‘net’ Cu-rich phases. Along the radial direction of the sample exhibited an abrupt increase of pores, indicating a tendency for forming a defect band in but such tendency was inhibited because of the huge amount of latent heat released by the PSPs during solidification, which was quite different from that of either magnesium alloys or hypoeutectic aluminum alloys.

36 MATERIALS SCIENCE↗

Thermodynamic Cloud Phase Classifications Using Machine Learning at NSA and ANX

Vertically resolved thermodynamic cloud phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) THERMOCLDPHASE Value-Added Product (VAP) uses a multi-sensor approach to classify thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave radiometer-derived liquid water path, and radiosonde temperature measurements. The measured voxels are classified as ice, snow, mixed-phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multilayer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with one year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1-score, and mean Intersection over Union (IOU). Analysis of ML confidence scores shows ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential datastreams for ML thermodynamic cloud phase predictions. The ML models’ generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. Finally, we evaluate the ML models’ response to simulated instrument outages and signal degradation.

54 ENVIRONMENTAL SCIENCES↗

Data, Photographs, Videos, and Information for the Niwot Ridge Subalpine Forest (US-NR1) AmeriFlux site

This data package contains data and information about the operation of the Niwot Ridge Subalpine Forest AmeriFlux site (US-NR1) between Nov 1998 to the present (2020). This data archive supplements the primary 30-min data storage for the US-NR1 data (i.e., https://doi.org/10.17190/AMF/1246088) by providing the following: (i) five-minute statistics (means, variances, covariances) of all data measured by the data system between Nov 1998 and September 2020 in netCDF format, (ii) CSV data files saved within the memory of the CR23X data loggers (as well as an archive of the data logger programs), (iii) an archive of previous 30-min ASCII data versions of the US-NR1 AmeriFlux data and information related to each data release (a replica of what can be found at http://urquell.colorado.edu/data_ameriflux/), (iv) a web calendar (in HTML format) documenting activity at the site (a replica of http://urquell.colorado.edu/calendar/), (v) photos (over 15,000) and video taken at the site between years 2001 and present day (2020), and (vi) several auxiliary datasets, primary related to trees near the site, soil moisture and soil temperature, and subcanopy radiation data. The data package is setup so that the web calendar, photos, and electronic logbook can be easily accessed on a local computer using a web browser. The provided data files are in either netCDF, CSV, ASCII, or MATLAB format. To obtain a better understanding about the archive, please start by reading the PDF: README_ESS_DIVE_USNR1_readme_first.pdf.

54 ENVIRONMENTAL SCIENCES↗

Design-informed neutronics assessment of long-lived fission product transmutation in a tokamak fusion reactor blanket

This study presents a neutronics-based assessment of the feasibility and viability of transmuting six major long-lived fission products (LLFPs) from light-water reactors, namely 99 Tc, 129 I, 79 Se, 93 Zr, 126 Sn, and 135 Cs, within the blanket region of a tokamak fusion reactor, using the MIT ARC design as a concrete fusion configuration. Monte Carlo neutronics simulations were performed to evaluate LLFP transmutation and to compare the results with a reference boiling water reactor (BWR). The results indicate that transmutation of all six LLFPs is neutronics-feasible in fusion reactors, with transmutation half-lives significantly shorter than their natural decay half-lives. For elemental targets, transmutation of 135 Cs, 126 Sn, and 93 Zr was found potentially viable, as the net mass transmuted exceeded that achievable in the reference BWR under identical target volume and irradiation time. When isotopically separated targets were considered, transmutation of 126 Sn and 93 Zr appeared potentially viable. A parametric study demonstrated that plasma geometry modifications can enhance local neutron flux, increasing the transmuted 93 Zr mass by approximately 33% and reducing the transmutation half-life from approximately 240 years to 180 years. Repositioning the target and adjusting material layer thickness reduced the transmutation half-life of 93 Zr to 67 years and increased the net mass transmuted by a factor of 50. Furthermore, these results demonstrate that fusion reactors can enable LLFP transmutation beyond the practical limits of thermal fission reactors and highlight the critical role of reactor and blanket design optimization. Engineering and fuel-cycle considerations required for deployment are beyond the scope of this neutronics-focused study.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Classifying thermodynamic cloud phase using machine learning models

Vertically resolved thermodynamic cloud-phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Thermodynamic Cloud Phase (THERMOCLDPHASE) value-added product (VAP) uses a multi-sensor approach to classify the thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave-radiometer-derived liquid water path, and radiosonde temperature measurements. The measured pixels are classified as ice, snow, mixed phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multi-layer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with 1 year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1 score, and mean intersection over union (IOU). Analysis of ML confidence scores shows that ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential data streams for ML thermodynamic cloud-phase predictions. Lidar measurements exhibit lower feature importance due to rapid signal attenuation caused by the frequent presence of persistent low-level clouds at the NSA site. The ML models' generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. The models demonstrated similar performance to that observed at the NSA site. Finally, we evaluate the ML models' response to simulated instrument outages and signal degradation and show that a CNN U-Net model trained with input channel dropouts performs better when input fields are missing.

ARM Aerial Facility↗

The diurnal susceptibility of subtropical clouds to aerosols

The diurnal susceptibility of clouds and their radiative properties to aerosols is examined during their Lagrangian transition from subtropical stratocumulus to shallow cumulus regimes. Using large-eddy simulations, we analyze the six-day evolution of an air mass along a 3800 km observed trajectory from the coast of Peru toward the equator. Pristine and polluted scenarios are simulated with forcing imposed from weather reanalysis. The polluted scenario exhibits stronger diurnal variations in cloud water, cloud fraction, and albedo, with enhanced nighttime entrainment and suppressed precipitation. The overall response of cloud properties and outgoing shortwave radiation to droplet number concentration follows a distinct diurnal pattern: strong positive cloud adjustments dominate at night and in the morning, while weak negative adjustments prevail in the afternoon. This cycle is driven by the competition between precipitation suppression, which enhances cloud water and coverage, and entrainment drying, which depletes them. In polluted conditions, enhanced entrainment leads to a deeper and more decoupled boundary layer that cannot be sustained by surface fluxes in the afternoon, resulting in negative cloud adjustments. The enhanced entrainment rate under polluted conditions is caused by the reduced sedimentation of cloud and precipitation water from the entrainment zone. While the Twomey effect dominates the diurnal average albedo response, the diurnal variation in the competing cloud adjustments lead to a near-neutral net susceptibility in the afternoon, highlighting the critical role of diurnally varying processes in aerosol-cloud interactions.

Geosciences↗

Experimental study and demonstration of pilot-scale oxy-coal combustion at elevated temperatures and pressures

High pressure oxy-fuel firing is a promising next-generation combustion technology for electricity generation, allowing net efficiency improvement compared to traditional oxy-fuel firing systems. Oxy-coal combustion has been extensively investigated at ambient pressure, but limited experimental data is available regarding this combustion method at elevated pressures at pilot or full scale. The study presented here investigates the operational performance of a high pressure, high temperature pilot-scale oxy-fuel combustor. Pulverized Utah bituminous coal in form of coal-water slurry was combusted at pressures up to 14 bar, temperatures up to 1600 °C and firing rates up to 300 kW. Eight different runs were selected for presentation and the measurements include flue gas composition (CO, CO 2 , CH 4 , SO 2 , O 2 ), carbon and sulfur content of fly ash, combustor temperature profile and flame radiation profile. The flame radiation measurements were carried out with a novel narrow beam radiometer which measures local radiant heat flux at a specific location in the combustor. The radiation ranged from 108 to 279 kW/m 2 depending mainly on combustor temperature. Additionally, the temperature significantly impacted the carbon content of fly ash: 2.66% was measured near 1600 °C, while the concentration increased to 36.7% when the temperature was decreased to 1300°C. Furthermore, the successful experimental demonstrations showed that increasing pressure is a viable combustion method and a step towards enhancing the efficiency in oxy-fuel firing based power plants.

01 COAL, LIGNITE, AND PEAT↗

Effects of Surface and Top Wind Shear on the Spatial Organization of Marine Stratocumulus-Topped Boundary Layers

Typically, the convective nature of Stratocumulus topped boundary layers (STBL) involves the motion of updrafts and downdrafts, driven by surface fluxes and radiative cooling, respectively. The balance between shear and buoyant forcings at the surface can determine the organization of updrafts between cellular and roll structures. We investigate the effect of varying shear at the surface and top of the STBL using Large Eddy Simulations, taking DYCOMS II RF01 as a base case. We focus on spatial identification of the following features: coherent updrafts and downdrafts, and observe how they are affected by varying shear. Stronger surface shear organizes the updrafts in rolls, causes less well-mixed thermodynamic profiles, and decreases cloud fraction and liquid water path (LWP). Stronger top shear also decreases cloud fraction and LWP more than surface shear, by thinning the cloud from the top. Features with stronger top than surface shear are associated with a net downward momentum transport and show early signs of decoupling. Classifying updrafts and downdrafts based on their vertical span and horizontal size confirms the dominance of tall objects spanning the whole STBL. Tall objects occupy 30% of the volume in the STBL, while short ones occupy less than 1%. For updraft and downdraft fluxes, these tall objects explain 65% of the vertical velocity variance and 83% of the buoyancy flux, on average. Stronger top shear also weakens the contribution of downdrafts to the turbulent fluxes and tilts the otherwise vertical development of updrafts.

54 ENVIRONMENTAL SCIENCES↗

Viability Assessment of Wind and Solar Renewable Energy Generation in Support of Nationwide Vehicle Electrification

In 2022, the U.S. transportation sector was the largest source of greenhouse gas emissions in the country, with the combination of passenger and commercial vehicles contributing 80% of these emissions. As adoption of passenger electric vehicles continues to climb, sights are being set on the electrification of heavy-duty commercial vehicle (HDCV) fleets. The sustainability of these shifts relies in part on the addition of significant renewable energy generation resources to both bolster the grid in the face of increased demand, and to prevent a shift in the source of greenhouse gas (GHG) emissions to the grid, as opposed to a true net reduction. Additionally, it is necessary to quantify the variations in economic viability across the country for these technologies as it pertains to their productive capabilities. Doing so will encourage investment and ensure that the transition to electrified HDCV fleets is commercially viable, as well as sustainable. In an effort to meet these goals, multiple computational frameworks are used to locate suitable land for renewable infrastructure development, and to quantify spatiotemporal variations in the potential energy generation and financial viability of development sites across the Unites States. First, the Oak Ridge Siting Analysis for power Generation Expansion tool (OR-SAGE) is used to assess the suitability of land for potential wind and solar energy development across the contiguous U.S. From there, resource data from the National Solar Radiation Database (NSRDB) and the Wind Integration National Dataset (WIND) are used in concert with the National Renewable Energy Laboratory (NREL) Renewable Energy Potential (ReV) model to calculate the variation in potential generation capacity for each resource. Additionally, the capital and operational expenditures are calculated for an example configuration of each renewable technology. These measures are then used to calculate the levelized cost of energy (LCOE) of potential sites. All of these results are then processed and analyzed to determine where in the U.S. solar and wind energy are most viable. This viability is based on available generation potential, consistency and stability of energy generation over time, and economic viability with respect to LCOE.

Miller, Brandon [ORNL] (ORCID:0009000300169201)↗

“Interpenetration Isomerism” of Triptycene-Based Hydrogen-Bonded Organic Frameworks

In this work, we describe an example of “interpenetration isomerism” in three-dimensional (3D) hydrogen-bonded organic frameworks (HOFs). By exploiting the crystallization conditions for a peripherally extended triptycene H6PET, we can modulate the interpenetration of the assembled frameworks, yielding a two-fold interpenetrated structure PETHOF-1 (acs-2c topology) and a five-fold interpenetrated structure PETHOF-2 (acs-5c topology) as “interpenetration isomers”. In PETHOF-1, two individual nets are related by inversion symmetry and form an interwoven topology with a strikingly large guest-accessible volume of about 80%. In PETHOF-2, five individual nets are related by translational symmetry and are stacked in an alternating fashion. Additionally, the activated materials show permanent porosity with high Brunauer–Emmett–Teller (BET) areas exceeding 1100 m2•g-1. Finally, we believe that synthetic control over the framework interpenetration can serve as a new design strategy to construct diverse and complex supramolecular architectures from simple organic building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗