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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 649 records · Page 36

Large Diffraction-Grade Single Crystal Diamond for Applications at New Generation Synchrotron and FEL X-Ray Sources

As a result of increasing performance of synchrotron and free-electron laser x-ray sources for high-flux applications, a new generation of optics is needed that can support the high energy densities utilized. To achieve this, the Department of Energy (DOW) has sought a commercially available, US-sourced supply of this material. Through a collaborative effort led by WD Advanced Materials (WD AM), in coordination with Euclid Beamlabs and Applied Diamond, Inc., and supported by Argonne National Laboratory, an effort has been made to begin the creation of such a diamond optic supply. Key material and optic parameters were identified, as well as characterization methods. A process of diamond synthesis that satisfies both extrinsic and intrinsic needs of the optics was formulated and demonstrated, and necessary steps to achieve high-quality epitaxy were evaluated and tested. Results of the first steps of this program are provided herein, as well as recommendations for a follow-up effort to complete the program and establish the needed supply of diamond optics for DOE x-ray applications.

36 MATERIALS SCIENCE↗

Assessment of MiniFuel Subcapsule Design Recommendations on Previous Experiments

MiniFuel describes the class of separate effects nuclear fuels irradiation experiments that have been conducted in the High Flux Isotope Reactor (HFIR) since 2018. These experiments comprise a stack of six fuel-bearing subcapsules contained in a stainless steel target housing that is in contact with HFIR coolant on its exterior. All MiniFuel targets have a near-standardized architecture, and the primary design variables that change between experiments are the radial gap size between the subcapsule and housing and the target fill gas composition. Finite element heat transfer models are used to determine the optimum gas composition and gap sizes, and recent studies were performed to identify model parameters that contribute the most uncertainty to fuel specimen temperature predictions. That work, which is referenced herein, also recommended a set of design modifications to the subcapsule internal architecture and assembly process. These modifications are intended to reduce fuel temperature uncertainty in future experiments. In this report, the subcapsule design modifications were retroactively applied to a previously conducted MiniFuel experiment to determine how these changes affect the established safety and performance envelope of the experimental capability. These effects were determined in two steps. First, the modifications were applied to the subcapsule design without any other changes to determine their isolated effect on the predicted fuel specimen temperatures. This portion of the analysis showed that fuel temperatures were modestly reduced because the implemented changes improved heat transfer efficacy. Next, traditional MiniFuel design activities (i.e., sizing the gas gaps and determining the fill gas composition) were reperformed, and they confirmed that the original desired fuel temperatures could be achieved while remaining within established safety limits. Therefore, this report demonstrates improved performance resulting from the subcapsule modifications, which mitigate uncertainty while meeting the objectives of past experiments. An additional benefit of the design changes is reduced sensitivity of the fuel temperature to the evolving flux spectrum in HFIR, leading to more stable temperatures and enhanced utility of MiniFuel as a separate effects irradiation platform.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Detecting and Characterizing Fracture Zones Using a Convolutional Neural Network

This project directly supports the Geothermal Technologies Office (GTO) objectives outlined in the Multi-Year Program Plan (MYPP) by advancing two key research areas: “Exploration and Characterization” and “Data, Modeling, and Analysis.” This project has successfully demonstrated a pre-drilling ability to image and characterize the distribution and connectivity of subsurface faults and fractures, key parameters for identifying permeable pathways that enable geothermal fluids to circulate and produce energy. Specifically, we developed and implemented innovative machine learning methodologies to enhance geothermal exploration. Large-scale faults were detected using a Convolutional Neural Network (CNN), while small-scale fractures were characterized using a novel Double-Beam Neural Network (DBNN). These tools have proven both technically effective and cost-efficient by reducing reliance on expensive exploratory drilling. Through collaboration with our geothermal industry partner, this research has significantly advanced techniques for identifying hidden geothermal systems and extending the productive lifespan of existing geothermal fields. We applied our methods to two geothermal fields—Soda Lake (Nevada) and Lightning Dock (New Mexico)—to identify shallow steam-charged fracture zones and characterize deep faults at depths of 1.5-2 km. The steam zone identified at the Soda Lake geothermal field showed excellent agreement with prior drilling data, validating the effectiveness of our approaches. In addition, the analysis revealed three new prospective drilling targets for further development and verification. The outcomes of this project improve our scientific understanding of geothermal reservoir behavior, enhance exploration efficiency, extend the economic life of existing geothermal plants. Ultimately, these advancements contribute to GTO’s goal of achieving more sustainable, affordable, and data-driven geothermal energy development across the United States.

15 GEOTHERMAL ENERGY↗

Development, Monitoring, and Control of Fracture Thermal Energy Storage (FTES) in Crystalline Rock Formations (DEMO-FTES) (CRADA Final Report)

The DEMO-FTES project sought to demonstrate the thermal efficiency of fracture thermal energy storage (FTES) through numerical simulations, laboratory and meso-scale field tests. A detailed dimensional and scaling analysis was performed to identify key parameters and how they can be most effectively scaled to the laboratory and decameter scale. Numerical models were developed and used for three purposes: 1. Before field experiments, numerical modelling can be used to estimate fracture properties based on previous data from the EGS Collab experiment and then predict thermal hydrological behaviors of the fracture system with hot water injection/withdrawal, therefore, help to design the experiments (e.g., to decide the duration of the cycles based on the flow rate the pump can provide, and the estimated fracture properties); 2. After the field experiment, to estimate the system properties during the experiment (as the size and shape of a fracture could change over time), and understand why system performance is different than what has been predicted, i.e., to help understand the meso-scale test; and, 3. To model the lab experiments and estimate fracture properties and storage efficiency. Ultimately, the experiment and numerical models could shed light on the processes and uncertainty happening during fracture activation and help understand the scaling between lab and field test, and finally, the design and optimization of potential fracture thermal energy storage systems.

25 ENERGY STORAGE↗

Modeling of a Four-Stage Linear Ionization Cooling Channel for a Muon Collider in g4Beamline

A previous study of an eight-stage rectilinear ionization cooling channel in the ICOOL software demonstrated a five-order-of-magnitude reduction in a muon beam’s 6D emittance. In this study, we look to compare the ways ICOOL and Muons, Inc.’s g4Beamline software model ionization cooling by comparing their modeling of the first four stages of this optimized cooling channel constructed in ICOOL. We begin by identifying the parameters used to construct the optimized ionization cooling channel in ICOOL. We then reconstruct this beam in g4Beamline with identical parameter specifications and simulate the cooling of an identical input beam. Finally, we compare the two simulations based on their beam transmission, longitudinal emittance, and transverse emittance along the channel length. Through this process, we demonstrate that G4Beamline accurately reproduces transverse cooling results but predicts systematically different longitudinal emittance evolution while maintaining similar overall cooling performance, reproducing a 97.9% reduction in 6D emittance over four stages.

Keeler, Dominic [Purdue U., West Lafayette] (ORCID↗

Sensitivity of a Subject-specific Ankle Sprain Simulation to Extrinsic Versus Intrinsic Biomechanical Factors

Ankle sprains are the most common musculoskeletal injury in sport and military activity, despite existing prophylactic strategies. The purpose of this report was to develop a probabilistic simulation of lateral ankle sprains during single-limb drop landing, towards accelerating innovation in ankle sprain prevention. A deterministic, subject-specific musculoskeletal model was extended with automation and probabilistic distributions on sprain-related biomechanical factors. Probabilistic simulations were generated using traditional Monte Carlo techniques and the advanced mean value method, a more computationally-efficient approach. Predicted distributions of peak ankle joint rotations, velocities, and moments borne by supporting passive structures agreed favorably with the deterministic model and with reports of real sprain biomechanics. Parameter sensitivities identified that predictions were most strongly influenced by drop height, subtalar joint posture at contact, invertor/evertor co-activation, and passive ankle stiffness. The advanced mean value method predicted confidence bounds comparable to a 1000-trial Monte Carlo simulation, and required only 14 model evaluations and 4-min processing time. The extended probabilistic simulation may be useful to virtually test new prophylactic strategies for ankle sprains, and is made available for open-source use (https://simtk.org/projects/sprain-sim).

60 APPLIED LIFE SCIENCES↗

Directional Crystallization of Conjugated Molecules during Coating Processes

The coating of organic molecules from the solution phase can result in directional crystal growth under certain conditions, even on a smooth isotropic surface and without the need of any kind of graphoexpitaxial preparation of the substrate. Based on reviewing the results from a variety of coating techniques and coating parameters, we identified that it is crucial for the coating speed to match the growth speed of the fastest growing crystal plane to achieve a high degree of directional crystallization.

36 MATERIALS SCIENCE↗

Comparison of Multi-Objective Evolutionary Algorithms to Solve the Modular Cell Design Problem for Novel Biocatalysis

A large space of chemicals with broad industrial and consumer applications could be synthesized by engineered microbial biocatalysts. However, the current strain optimization process is prohibitively laborious and costly to produce one target chemical and often requires new engineering efforts to produce new molecules. To tackle this challenge, modular cell design based on a chassis strain that can be combined with different product synthesis pathway modules has recently been proposed. This approach seeks to minimize unexpected failure and avoid task repetition, leading to a more robust and faster strain engineering process. In our previous study, we mathematically formulated the modular cell design problem based on the multi-objective optimization framework. In this study, we evaluated a library of state-of-the-art multi-objective evolutionary algorithms (MOEAs) to identify the most effective method to solve the modular cell design problem. Using the best MOEA, we found better solutions for modular cells compatible with many product synthesis modules. Furthermore, the best performing algorithm could provide better and more diverse design options that might help increase the likelihood of successful experimental implementation. We identified key parameter configurations to overcome the difficulty associated with multi-objective optimization problems with many competing design objectives. Interestingly, we found that MOEA performance with a real application problem, e.g., the modular strain design problem, does not always correlate with artificial benchmarks. Overall, MOEAs provide powerful tools to solve the modular cell design problem for novel biocatalysis.

Garcia, Sergio (ORCID:000000023998986X)↗

Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for Atmospheric Science during the LAPSE-RATE Campaign

Small unmanned aircraft systems (sUAS) are rapidly transforming atmospheric research. With the advancement of the development and application of these systems, improving knowledge of best practices for accurate measurement is critical for achieving scientific goals. We present results from an intercomparison of atmospheric measurement data from the Lower Atmospheric Process Studies at Elevation—a Remotely piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. We evaluate a total of 38 individual sUAS with 23 unique sensor and platform configurations using a meteorological tower for reference measurements. We assess precision, bias, and time response of sUAS measurements of temperature, humidity, pressure, wind speed, and wind direction. Most sUAS measurements show broad agreement with the reference, particularly temperature and wind speed, with mean value differences of 1.6 ± 2.6 ° C and 0.22 ± 0.59 m/s for all sUAS, respectively. sUAS platform and sensor configurations were found to contribute significantly to measurement accuracy. Sensor configurations, which included proper aspiration and radiation shielding of sensors, were found to provide the most accurate thermodynamic measurements (temperature and relative humidity), whereas sonic anemometers on multirotor platforms provided the most accurate wind measurements (horizontal speed and direction). We contribute both a characterization and assessment of sUAS for measuring atmospheric parameters, and identify important challenges and opportunities for improving scientific measurements with sUAS.

47 OTHER INSTRUMENTATION↗

Quantification of Type I Interferon Inhibition by Viral Proteins: Ebola Virus as a Case Study

Type I interferons (IFNs) are cytokines with both antiviral properties and protective roles in innate immune responses to viral infection. They induce an antiviral cellular state and link innate and adaptive immune responses. Yet, viruses have evolved different strategies to inhibit such host responses. One of them is the existence of viral proteins which subvert type I IFN responses to allow quick and successful viral replication, thus, sustaining the infection within a host. We propose mathematical models to characterise the intra-cellular mechanisms involved in viral protein antagonism of type I IFN responses, and compare three different molecular inhibition strategies. We study the Ebola viral protein, VP35, with this mathematical approach. Approximate Bayesian computation sequential Monte Carlo, together with experimental data and the mathematical models proposed, are used to perform model calibration, as well as model selection of the different hypotheses considered. Finally, we assess if model parameters are identifiable and discuss how such identifiability can be improved with new experimental data.

59 BASIC BIOLOGICAL SCIENCES↗

Magellan/M2FS spectroscopy of Tucana 2 and Grus 1

We present results from spectroscopic observations with the Michigan/Magellan Fiber System (M2FS) of 147 stellar targets along the line of sight to the newly discovered “ultrafaint” stellar systems Tucana 2 (Tuc 2) and Grus 1 (Gru 1). Based on simultaneous estimates of line of sight velocity and stellar-atmospheric parameters, we identify 8 and 7 stars as probable members of Tuc 2 and and Gru 1, respectively. Our sample for Tuc 2 is sufficient to resolve an internal velocity dispersion of 8.6{sub −2.7}{sup +4.4} km s{sup −1} about a mean of −129.1{sub −3.5}{sup +3.5} km s{sup −1} (solar rest frame), and to estimate a mean metallicity of [Fe/H] = −2.23{sub −0.12}{sup +0.18}. These results place Tuc 2 on chemodynamical scaling relations followed by dwarf galaxies, suggesting a dominant dark matter component with dynamical mass 2.7{sub −1.3}{sup +3.1}×10{sup 6} M{sub ⊙} enclosed within the central ∼160 pc, and dynamical mass-to-light ratio 1913{sub −950}{sup +2234} M{sub ⊙}/L{sub V,⊙}. For Gru 1 we estimate a mean velocity of −140.5{sub −1.6}{sup +2.4} km s{sup −1} and a mean metallicity of [Fe/H] = −1.42{sub −0.42}{sup +0.55} but our sample does not resolve Gru 1's velocity dispersion. The radial coordinates of Tuc 2 and Gru 1 in Galactic phase space suggest that their orbits are among the most energetic within a distance of ≲300 kpc. Moreover, their proximity to each other in this space arises naturally if both objects are trailing the Large Magellanic Cloud.

79 ASTRONOMY AND ASTROPHYSICS↗

Spinning dust emission from ultra-small silicates: emissivity and polarization spectrum

Anomalous microwave emission (AME) is an important Galactic foreground of cosmic microwave background radiation. It is believed that AME arises from rotational emission by spinning polycyclic aromatic hydrocarbons in the interstellar medium (ISM). In this paper, we suppose that a new population of ultra-small silicate grains perhaps exists in the ISM, and quantify the rotational emissivity from these tiny particles and its polarization spectrum. We find that spinning silicate nanoparticles can produce strong rotational emission when the tiny grains follow a log-normal size distribution. The polarization fraction of spinning dust emission from tiny silicates increases with decreasing dipole moment per atom (β) and can reach P∼20% for β∼0.1 D at a grain temperature of 60 K. We identify a parameter space (β,Y{sub Si}), with Y{sub Si} being the fraction of Si abundance in nanoparticles, in which its rotational emission can adequately reproduce both the observed AME and the polarization of the AME, without violating the observational constraints of ultraviolet extinction and polarization of starlight. Our results reveal that rotational emission from spinning silicate may be an important source of AME.

79 ASTRONOMY AND ASTROPHYSICS↗

Integrating Light Curve and Atmospheric Modeling of Transiting Exoplanets

Spectral retrieval techniques are currently our best tool to interpret the observed exoplanet atmospheric data. Said techniques retrieve the optimal atmospheric components and parameters by identifying the best fit to an observed transmission/emission spectrum. Over the past decade, our understanding of remote worlds in our galaxy has flourished thanks to the use of increasingly sophisticated spectral retrieval techniques and the collective effort of the community working on exoplanet atmospheric models. A new generation of instruments in space and from the ground is expected to deliver higher quality data in the next decade; it is therefore paramount to upgrade current models and improve their reliability, their completeness, and the numerical speed with which they can be run. In this paper, we address the issue of reliability of the results provided by retrieval models in the presence of systematics of unknown origin. More specifically, we demonstrate that if we fit directly individual light curves at different wavelengths (L-retrieval), instead of fitting transit or eclipse depths, as it is currently done (S-retrieval), the said methodology is more sensitive against astrophysical and instrumental noise. This new approach is tested, in particular, when discrepant simulated observations from Hubble Space Telescope/Wide Field Camera 3 and Spitzer/IRAC are combined. We find that while S-retrievals converge to an incorrect solution without any warning, L-retrievals are able to flag potential discrepancies between the data sets.

79 ASTRONOMY AND ASTROPHYSICS↗

Radiation and Polarization Signatures from Magnetic Reconnection in Relativistic Jets. I. A Systematic Study

Blazars are relativistic magnetized plasma outflows from supermassive black holes that point very close to our line of sight. Their emission is nonthermal-dominated and highly variable across the entire electromagnetic spectrum. Relativistic magnetic reconnection has been proposed as the driver of particle acceleration during blazar flares. While recent particle-in-cell (PIC) simulations have self-consistently studied the evolution of magnetic reconnection and particle acceleration therein, the resulting radiation signatures have not been systematically explored. In particular, the polarization signatures, which directly reflect the characteristic strongly dynamical evolution of magnetic field during reconnection, have not been carefully investigated. In this paper, we present a systematic study of radiation and polarization signatures arising from magnetic reconnection in blazars, based on combined PIC and polarized radiation transfer simulations with various physical parameters. We identify a harder-when-brighter trend in the spectral evolution. Moreover, higher-frequency bands (ultraviolet to X-ray) tend to flare earlier than lower-frequency bands (infrared to optical) in the synchrotron spectral component. Most importantly, polarization signatures appear more variable with higher frequencies. We find that the variation in temporal polarization depends strongly on the guide field strength. Specifically, reconnection with a significant guide field component leads to a very high polarization degree that contradicts typical blazar observations, while large polarization angle rotations are unique signatures of magnetic reconnection between nearly antiparallel magnetic field lines. These rotations are at least 90° and can extend to >180°, and they may be in either direction. Furthermore, these results imply that blazars that have shown large polarization angle rotations intrinsically have more nearly antiparallel magnetic field morphology.

79 ASTRONOMY AND ASTROPHYSICS↗

The NANOGrav 15 yr Data Set: Search for Signals from New Physics

The 15 yr pulsar timing data set collected by the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) shows positive evidence for the presence of a low-frequency gravitational-wave (GW) background. In this paper, we investigate potential cosmological interpretations of this signal, specifically cosmic inflation, scalar-induced GWs, first-order phase transitions, cosmic strings, and domain walls. We find that, with the exception of stable cosmic strings of field theory origin, all these models can reproduce the observed signal. When compared to the standard interpretation in terms of inspiraling supermassive black hole binaries (SMBHBs), many cosmological models seem to provide a better fit resulting in Bayes factors in the range from 10 to 100. However, these results strongly depend on modeling assumptions about the cosmic SMBHB population and, at this stage, should not be regarded as evidence for new physics. Furthermore, we identify excluded parameter regions where the predicted GW signal from cosmological sources significantly exceeds the NANOGrav signal. These parameter constraints are independent of the origin of the NANOGrav signal and illustrate how pulsar timing data provide a new way to constrain the parameter space of these models. Finally, we search for deterministic signals produced by models of ultralight dark matter (ULDM) and dark matter substructures in the Milky Way. We find no evidence for either of these signals and thus report updated constraints on these models. In the case of ULDM, these constraints outperform torsion balance and atomic clock constraints for ULDM coupled to electrons, muons, or gluons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Evidence for Evolved Stellar Binary Mergers in Observed B-type Blue Supergiants

Blue supergiants are the brightest stars in their host galaxies, and yet their evolutionary status has been a long-standing problem in stellar astrophysics. In this pioneering work, we present a large sample of 59 early B-type supergiants in the Large Magellanic Cloud with newly derived stellar parameters and identify the signatures of stars born from binary mergers among them. We simulate novel 1D merger models of binaries consisting of post main-sequence giants with helium-rich cores (primaries) and main-sequence companions (secondaries), and consider the effects of interaction of the secondary with the core of the primary along with the mixing induced by the merger in the envelope. Thereafter, the evolution of the newborn 17–43 M ⊙ stars is followed until core-carbon depletion, close to their final pre-explosion stage. Unlike stars born alone with comparable masses, stars born from mergers of evolved binaries are blue throughout their core helium-burning phase and replicate the surface gravities and Hertzsprung–Russell diagram positions of most of our sample, thus indicating that B-type supergiants structurally resemble stars born from such mergers. Moreover, the large nitrogen-to-carbon and nitrogen-to-oxygen number ratios, coupled with helium enhancements exhibited by at least half our data sample, is uniquely reproduced by our merger models. Collectively, these findings provide compelling evidence toward the important role of binary mergers in producing the currently observed population of blue supergiants in our Universe.

79 ASTRONOMY AND ASTROPHYSICS↗

Bistable dynamics and Hopf bifurcation in a refined model of early stage HIV infection

Recent clinical studies have shown that HIV disease pathogenesis can depend strongly on many factors at the time of transmission, including the strength of the initial viral load and the local availability of CD4+ T-cells. In this article, a new within-host model of HIV infection that incorporates the homeostatic proliferation of T-cells is formulated and analyzed. Due to the effects of this biological process, the influence of initial conditions on the proliferation of HIV infection is further elucidated. The identifiability of parameters within the model is investigated and a local stability analysis, which displays additional complexity in comparison to previous models, is conducted. The current study extends previous theoretical and computational work on the early stages of the disease and leads to interesting nonlinear dynamics, including a parameter region featuring bistability of infectious and viral clearance equilibria and the appearance of a Hopf bifurcation within biologically relevant parameter regimes.

59 BASIC BIOLOGICAL SCIENCES↗

CLM5 CAMELS Basins Ensemble

Land surface models such as Community Land Model Version 5 (CLM5) are essential tools for simulating the behaviors of the terrestrial system. Despite the extensive application of CLM5, limited attention has been paid to the underlying uncertainties associated with its hydrologic parameters and the implications that these uncertainties have on water resources applications. To address this long-standing issue, we conduct a comprehensive hydrologic parameter uncertainty characterization (UC) of CLM5 over the hydroclimatic gradients of the Conterminous United States using five meteorological datasets. Key datasets produced from the UC experiment include a benchmark dataset of CLM5 default hydrological performance, parameter sensitivity identified for 28 hydrological metrics, and large ensemble outputs for hydrological predictions. The presented datasets can assist CLM5 calibration and to support broad applications such as evaluating vulnerabilities to droughts and floods. The dataset can be used to identify under what hydroclimate conditions parametric uncertainties demonstrate substantial effects on hydrological predictions and clarify where further investigations are needed to understand how land runoff uncertainties interact with other Earth system processes. Please refer to the included README.pdf for a description of the included files. Note that raw CLM5 model outputs for each forcing dataset are hosted on a Globus endpoint: https://app.globus.org/file-manager?destination_id=d22ef858-27b0-11ed-a910-fd3165076336.

Yan, Hongxiang↗