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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 397 records · Page 22

Potential energy surfaces for high-energy N + O 2 collisions

Potential energy surfaces for high-energy collisions between an oxygen molecule and a nitrogen atom are useful for modeling chemical dynamics in shock waves. In the present work, we present doublet, quartet, and sextet potential energy surfaces that are suitable for studying collisions of O 2 ( 3 Σ$^{–}_{g}$) with N( 4 S) in the electronically adiabatic approximation. Two sets of surfaces are developed, one using neural networks (NNs) with permutationally invariant polynomials (PIPs) and one with the least-squares many-body (MB) method, where a two-body part is an accurate diatomic potential and the three-body part is expressed with connected PIPs in mixed-exponential-Gaussian bond order variables (MEGs). We find, using the same dataset for both fits, that the fitting performance of the PIP-NN method is significantly better than that of the MB-PIP-MEG method, even though the MB-PIP-MEG fit uses a higher-order PIP than those used in previous MB-PIP-MEG fits of related systems (such as N 4 and N 2 O 2 ). However, the evaluation of the PIP-NN fit in trajectory calculations requires about 5 times more computer time than is required for the MB-PIP-MEG fit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Passive Low-Energy Nuclear-Recoil Detection with Color Centers

Crystal-damage events such as tracks and point defects have been used to record and detect radiation for a long time and recently they have been proposed as a means for dark-matter detection. Color centers can be read out optically and we propose a scheme based on selective plane illumination microscopy for micrometer-scale imaging of large volumes corresponding to kilogram mass detectors. This class of detectors would be passive and would operate at room temperature and we call this the passive low-energy optical color-center nuclear-recoil (PALEOCCENE) detection method. We apply these concepts to the detection of reactor neutrinos using coherent elastic neutrino nucleus scattering (CE ν NS). Crystal-damage formation energies are intrinsically on the order of 25 eV, resulting in similarly low nuclear-recoil thresholds. Furthermore, this would enable the observation of reactor-neutrino CE ν NS with detectors as small as 10 g. Additionally, a competitive search for spin-dependent dark-matter scattering down to a dark-matter mass of 0.3 GeV could be possible. Passive crystal detectors might also be attractive for nuclear-nonproliferation safeguards if used to monitor reactor power and to put limits on plutonium production. The passive nature and small footprint of the proposed detectors implies that these might fit well within accepted reactor-safeguards operations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Comparison of simulated neutrino emission models with data on Supernova 1987A

Here we compare models of supernova (SN) neutrino emission with the Kamiokande II data on SN 1987A using the Bayesian approach. These models are taken from simulations and are representative of current one-dimensional SN models. We find that models with a brief accretion phase of neutrino emission are the most favored. This result is not affected by varying the overall flux normalization or considering neutrino oscillations. We also check the compatibility of the best-fit models with the data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Deuterium Permeation Through a Self-Supported Palladium-Silver Membrane in Helium Gas Mixtures

Palladium membranes and membrane reactors can separate and purify tritium from impurities in the plasma exhaust processing system for the fusion energy fuel cycle. Membranes can also act as a continuous separation method to remove tritium from helium streams in the breeder blanket tritium extraction system, such as from the purge gas of solid breeders. To investigate the potential of these membranes for these applications, we performed a deuterium permeation campaign with a self-supported palladium-silver (Pd-25Ag wt%) tube of 0.15 m length, 76 µ m wall thickness, and 3.0 mm inner diameter. A gas mixture of 3.95% D 2 and a balance of He was delivered to the inside of the tube and D permeated radially outwards through the membrane into a vacuum chamber. Permeation experiments were conducted at 300 ° C, 350 ° C, 400° C, and 450°C, from 100 to 1000 sccm total flow rate, and with total pressures of 90, 150, 190, and 250 kPa. Further, deuterium permeation was consistently lower than predicted from diffusion-limited permeation models, thus we developed a transport model that included gas-phase mass transfer and surface reactions to model experimental results. The dissociation constant was optimized to fit the developed model to experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Electrochemical Characterization of Bromine Reduction to Tribromide in Individual Nitrobenzene-in-Water Emulsion Droplets

We report an electrochemical study of bromine reduction to tribromide in a single nitrobenzene (NB) droplet during a single collision event. The feasibility of this study is based on the favorable distribution of Br 2 in NB rather than in water, which was demonstrated by voltammetry at the NB/water interface. The NB-in-water emulsions containing the ionic liquids trihexyltetradecylphosphonium bis(trifluoromethylsulfonyl)amide (ILPA) as the supporting electrolyte and sodium dodecyl sulfate (SDS) as the surfactant were prepared by a high-power ultrasonication. Its single droplet as an attoliter reactor, colliding on a 25 μm Pt UME, was monitored by chronoamperometry. The spike-type current transients of Br 2 reduction can elucidate the size and size distribution of NB, and measure the diffusion in the droplet as analyzed by a bulk electrolysis model. The frequency of collisions can provide diffusion coefficient of the droplets to the UME. Moreover, the i-t decay behavior can be simulated, which fits well with the experimental one.

25 ENERGY STORAGE↗

Learning crystal field parameters using convolutional neural networks

We present a deep machine learning algorithm to extract crystal field (CF) Stevens parameters from thermodynamic data of rare-earth magnetic materials. The algorithm employs a two-dimensional convolutional neural network (CNN) that is trained on magnetization, magnetic susceptibility and specific heat data that is calculated theoretically within the single-ion approximation and further processed using a standard wavelet transformation. We apply the method to crystal fields of cubic, hexagonal and tetragonal symmetry and for both integer and half-integer total angular momentum values J J of the ground state multiplet. We evaluate its performance on both theoretically generated synthetic and previously published experimental data on CeAgSb _2 2 , PrAgSb _2 2 and PrMg _2 2 Cu _9 9 , and find that it can reliably and accurately extract the CF parameters for all site symmetries and values of J J considered. This demonstrates that CNNs provide an unbiased approach to extracting CF parameters that avoids tedious multi-parameter fitting procedures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Cosmology Intertwined III: $f \sigma_8$ and $S_8$

The standard $\Lambda$ Cold Dark Matter cosmological model provides a wonderful fit to current cosmological data, but a few tensions and anomalies became statistically significant with the latest data analyses. While these anomalies could be due to the presence of systematic errors in the experiments, they could also indicate the need for new physics beyond the standard model. In this Letter of Interest we focus on the tension of the Planck data with weak lensing measurements and redshift surveys, about the value of the matter energy density $\Omega_m$, and the amplitude or rate of the growth of structure ($\sigma_8,f\sigma_8$). We list a few interesting models for solving this tension, and we discuss the importance of trying to fit with a single model a full array of data and not just one parameter at a time.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Physical Security Model Development of an Electrochemical Facility

Nuclear facilities in the U.S. and around the world face increasing challenges in meeting evolving physical security requirements while keeping costs reasonable. The addition of security features after a facility has been designed and without attention to optimization (the approach of the past) can easily lead to cost overruns. Instead, security should be considered at the beginning of the design process in order to provide robust, yet efficient physical security designs. The purpose of this work is to demonstrate how modeling and simulation can be used to optimize the design of physical protection systems. A suite of tools, including Scribe3D and Blender, were used to model a generic electrochemical reprocessing facility. Physical protection elements such as sensors, portal monitors, barriers, and guard forces were added to the model based on best practices for physical security. Two theft scenarios (an outsider attack and insider diversion) as well as a sabotage scenario were examined in order to optimize the security design. Security metrics are presented. This work fits into a larger Virtual Facility Distributed Test Bed 2020 Milestone in the Material Protection, Accounting, and Control Technologies (MPACT) program through the Department of Energy (DOE). The purpose of the milestone is to demonstrate how a series of experimental and modeling capabilities across the DOE complex provide the capabilities to demonstrate complete Safeguards and Security by Design (SSBD) for nuclear facilities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Investigation of Mass Transfer and Sorption in CO 2 /Brine/Rock Systems via In Situ FT-IR

CO 2 geological storage in deep saline formations is considered a promising method to mitigate anthropogenic CO 2 emissions and, thereby, minimize changes to the Earth’s atmosphere. A fundamental understanding of CO 2 mass transfer and sorption phenomena in brine-saturated reservoir formations is necessary to understand the long-term fate of injected CO 2 as it is subjected to different (physical, dissolution, and mineral) trapping mechanisms. In this work, we investigate CO 2 sorption in brine-saturated and dry Mt. Simon sandstone samples via in-situ Fourier Transform infrared spectroscopy (FT-IR) at elevated pressures, ranging from 0.3 MPa to 8.3 MPa, at a temperature of 50 ⁰C. The FT-IR spectra of bulk-phase CO 2 were simultaneously recorded under the same conditions. For bulk-phase CO 2 , we observed, in agreement with past studies, a doublet peak at 2361 cm -1 and 2336 cm -1 and another peak (ν 2 bending mode) at 667 cm -1 . With increasing pressure, the position of the peak at 667 cm -1 remains invariant, however, when crossing into the supercritical region the doublet peak degenerates onto a single peak at 2336 cm -1 with a barely visible shoulder at 2361 cm -1 . The bulk CO 2 data provide a perfect fit for Beer’s law for the whole range of pressure conditions. For the dry sample, the IR spectrum is experimentally indistinguishable from the bulk CO 2 spectrum, signifying that if physical adsorption occurs to any significant extent, the adsorbed CO 2 molecules are not substantially more rotationally constrained than the dense bulk CO 2 molecules. For the brine-saturated sample, we observe a strong band centered at 2342 cm -1 and a small companion peak at 2360-2361 cm -1 that degenerates into a barely visible shoulder peak at the higher pressures. The 2342 cm -1 band has been previously observed by other investigators for CO 2 dissolved in bulk water/brine as well during its adsorption on a variety of other wet natural porous media. We observe no peaks corresponding to bicarbonate or carbonate bulk species, which correlates well with the prior literature on similar low-pH aqueous solutions. The integrated peak area for the CO 2 sorbed in the brine-saturated sample correlates linearly with its solubility in the same bulk brine, as measured separately via a PVT-cell approach. Here, this validates the accuracy of both techniques, and the potential of the FT-IR method to be used in the study of mass transfer and adsorption in such systems. To that effect, a simple mathematical model is presented to analyze the FT-IR data to determine the CO 2 effective diffusivity in the brine-saturated sandstone sample.

58 GEOSCIENCES↗

Physical Models from Physical Templates Using Biocompatible Liquid Crystal Elastomers as Morphologically Programmable Inks For 3D Printing

Advanced manufacturing has received considerable attention as a tool for the fabrication of cell scaffolds however, finding ideal biocompatible and biodegradable materials that fit the correct parameters for 3D printing and guide cells to align remain a challenge. Herein, a photocrosslinkable smectic-A (Sm-A) liquid crystal elastomer (LCE) designed for 3D printing is presented, that promotes cell proliferation but most importantly induces cell anisotropy. The LCE-based bio-ink allows the 3D duplication of a highly complex brain structure generated from an animal model. Vascular tissue models are generated from fluorescently stained mouse tissue spatially imaged using confocal microscopy and subsequently processed to create a digital 3D model suitable for printing. The 3D structure is reproduced using a Digital Light Processing (DLP) stereolithography (SLA) desktop 3D printer. Synchrotron Small-Angle X-ray Diffraction (SAXD) data reveal a strong alignment of the LCE layering within the struts of the printed 3D scaffold. The resultant anisotropy of the LCE struts is then shown to direct cell growth. This study offers a simple approach to produce model tissues built within hours that promote cellular alignment.

3D cell culture↗

High-power test results for a cylindrical-shell silicon carbide higher-order-mode damper

The next high-current Electron-Ion Collider (EIC) is a new accelerator to be built at Brookhaven National Laboratory in collaboration with Thomas Jefferson National Accelerator Facility. In the EIC Electron Storage Ring (ESR), there will be beam currents of up to 2.5 A, which will excite massive higher-order-mode (HOM) power in the 17 single-cell 591 MHz superconducting radio-frequency (SRF) cavities. Damping the HOM power in the ESR SRF cavities is a challenge. A room temperature cylindrical shell shape silicon carbide (SiC) beamline HOM absorber (BLA) was chosen as the baseline design, due to its broadband and high-power capability, and previous demonstrations at other accelerator facilities, albeit at much lower power. Because the EIC BLA HOM power dissipation is significantly greater than the previous applications, it is imperative to carry out high-power testing to determine the maximum device performance levels achievable for thermal transport, rf breakdown, and mechanical stress, prior to finalizing the design. A SiC HOM absorber with a state-of-the-art geometry size was prototyped to verify the shrink-fit technique, test outgassing rate, and high-power handling capability. This paper presents the HOM damper’s prototyping and test results. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Two-Pole Nature of the Λ ( 1405 ) Resonance from Lattice QCD

This Letter presents the first lattice QCD computation of the coupled channel π Σ − K ¯ N scattering amplitudes at energies near 1405 MeV. These amplitudes contain the resonance Λ ( 1405 ) with strangeness S = − 1 and isospin, spin, and parity quantum numbers I ( J P ) = 0 ( 1 / 2 − ) . However, whether there is a single resonance or two nearby resonance poles in this region is controversial theoretically and experimentally. Using single-baryon and meson-baryon operators to extract the finite-volume stationary-state energies to obtain the scattering amplitudes at slightly unphysical quark masses corresponding to m π ≈ 200 MeV and m K ≈ 487 MeV , this study finds the amplitudes exhibit a virtual bound state below the π Σ threshold in addition to the established resonance pole just below the K ¯ N threshold. Several parametrizations of the two-channel K matrix are employed to fit the lattice QCD results, all of which support the two-pole picture suggested by SU(3) chiral symmetry and unitarity. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Expanding Activity Allocation Models to Daily Activities: Tracking Simulated Agent Trips to Exercise Locations in Clarksville, TN

Exercise facilities have been proven to have numerous physical, mental, and psychological benefits, yet exercise facilities are still inaccessible to a large portion of the population. This study serves to explore the accessibility of fitness centres through geographical, demographic, and temporal lenses through an expansion of the UrbanPop framework that seeks to allocate simulated agents to fitness centres in the Clarksville metro to explore the effects of travel distances on different demographics throughout the week. Findings indicate that senior and retired demographics consistently travel longer distances to exercise in the larger Clarksville area, likely due to tendencies to live further from the center of the metropolitan area. Furthermore, all demographics tend to travel further distances to exercise on the weekends rather than the weekdays, indicating that travel distance can affect likelihood of agents to travel, especially on weekdays when many agents are in the workforce or participating in schooling.

99 GENERAL AND MISCELLANEOUS↗

A mathematical approach to survey electrochemical impedance spectroscopy for aging in lithium-ion batteries

Electrochemical impedance spectroscopy (EIS) is a valuable technique to detect the health status and aging phenomena in lithium-ion batteries (LiB). Equivalent circuit modeling (ECM) is conventionally used when interpreting EIS data and gaining physical insights into the aging mechanisms. However, performing ECM is resource intensive and expert-level of knowledge is usually required to select suitable models and fitting parameters. This article presents a quick and user-friendly data analysis algorithm as an alternative to ECM by mathematically fitting geometric features in Nyquist plots and obtaining the growth trends of the features. The evolving trends in the Nyquist plots, such as chord lengths of the arcs and interception points, are consistent with the growth of resistance components obtained using ECM with R 2 values from 0.67 to 0.99, and therefore can be used as indicators of battery aging. Our results show that the quick-fitting approach is suitable for analyzing a series of EIS data acquired during battery cycling and identifying the underlying aging mechanisms.

Chen, Bor-Rong↗

Analytical Modeling of Exoplanet Transit Spectroscopy with Dimensional Analysis and Symbolic Regression

Abstract The physical characteristics and atmospheric chemical composition of newly discovered exoplanets are often inferred from their transit spectra, which are obtained from complex numerical models of radiative transfer. Alternatively, simple analytical expressions provide insightful physical intuition into the relevant atmospheric processes. The deep-learning revolution has opened the door for deriving such analytical results directly with a computer algorithm fitting to the data. As a proof of concept, we successfully demonstrate the use of symbolic regression on synthetic data for the transit radii of generic hot-Jupiter exoplanets to derive a corresponding analytical formula. As a preprocessing step, we use dimensional analysis to identify the relevant dimensionless combinations of variables and reduce the number of independent inputs, which improves the performance of the symbolic regression. The dimensional analysis also allowed us to mathematically derive and properly parameterize the most general family of degeneracies among the input atmospheric parameters that affect the characterization of an exoplanet atmosphere through transit spectroscopy.

79 ASTRONOMY AND ASTROPHYSICS↗

Effects of interaction strength of associating groups on linear and star polymer dynamics

A small number of associating groups incorporated onto a polymer backbone have dramatic effects on the mobility and viscoelastic response of the macromolecules in melts. These associating groups assemble, driving the formation of clusters, whose lifetime affects the properties of the polymers. In this study, we probe the effects of the interaction strength on the structure and dynamics of two topologies, linear and star polymer melts, and further investigate blends of associative and non-associating polymers using molecular dynamics simulations. Polymer chains of approximately one entanglement length are described by a bead–spring model, and the associating groups are incorporated in the form of interacting beads with an interaction strength between them that is varied from 1 to 20 k B T. We find that, for all melts and blends, interaction of a few k B T between the associating groups drives cluster formation, where the size of the clusters increases with increasing interaction strength. These clusters act as physical crosslinkers, which slow the chain mobility. Blends of chains with and without associating groups macroscopically phase separate for interaction strength between the associating groups of a few k B T and above. For weakly interacting associating groups, the static structure function S(q) is well fit by functional form predicted by the random phase approximation where a clear deviation occurs as phase segregation takes place, providing a quantitative assessment of phase segregation.

36 MATERIALS SCIENCE↗

The star-formation history in the last 10 billion years from CIB cross-correlations

ABSTRACT The cosmic infrared background (CIB) traces the emission of star-forming galaxies throughout all cosmic epochs. Breaking down the contribution from galaxies at different redshifts to the observed CIB maps would allow us to probe the history of star formation. In this paper, we cross-correlate maps of the CIB with galaxy samples covering the range z ≲ 2 to measure the bias-weighted star-formation rate (SFR) density 〈bρSFR〉 as a function of time in a model independent way. This quantity is complementary to direct measurements of the SFR density ρSFR, giving a higher weight to more massive haloes, and thus provides additional information to constrain the physical properties of star formation. Using cross-correlations of the CIB with galaxies from the DESI Legacy Survey and the extended Baryon Oscillation Spectroscopic Survey, we obtain high signal-to-noise ratio measurements of 〈bρSFR〉, which we then use to place constraints on halo-based models of the star-formation history. We fit halo-based SFR models to our data and compare the recovered ρSFR with direct measurements of this quantity. We find a qualitatively good agreement between both independent data sets, although the details depend on the specific halo model assumed. This constitutes a useful robustness test for the physical interpretation of the CIB, and reinforces the role of CIB maps as valuable astrophysical probes of the large-scale structure. We report our measurements of 〈bρSFR〉 as well as a thorough account of their statistical uncertainties, which can be used to constrain star-formation models in combination with other data.

Astronomy & Astrophysics↗

Enhanced analysis of experimental x-ray spectra through deep learning

X-ray spectroscopic data from high-energy-density laser-produced plasmas has long required thorough, time-consuming analysis to extract meaningful source conditions. There are often confounding factors due to rapidly evolving states and finite spatial gradients (e.g., the existence of multi-temperature, multi-density, multi-ionization states, etc.) that make spectral measurements and analysis difficult. Here, in this paper, we demonstrate how deep learning can be applied to enhance x-ray spectral data analysis in both speed and intricacy. Neural networks (NNs) are trained on ensemble atomic physics simulations so that they can subsequently construct a model capable of extracting plasma parameters directly from experimental spectra. Through deep learning, the models can extract temperature distributions as opposed to single or dual temperature/density fits from standard trial-and-error atomic modeling at a significantly reduced computational cost compared to traditional trial-and-error methods. These NNs are envisioned to be deployed with high repetition rate x-ray spectrometers in order to provide detailed real-time analysis of experimental spectra.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗