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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 541 records · Page 30

Ionic Pairs-Engineered Fluorinated Covalent Organic Frameworks Toward Direct Air Capture of CO 2

The covalent organic frameworks (COFs) possessing high crystallinity and capability to capture low-concentration CO 2 (400 ppm) from air are still underdeveloped. The challenge lies in simultaneously incorporating high-density active sites for CO 2 insertion and maintaining the ordered structure. Herein, a structure engineering approach is developed to afford an ionic pair-functionalized crystalline and stable fluorinated COF (F-COF) skeleton. The ordered structure of the F-COF is well maintained after the integration of abundant basic fluorinated alcoholate anions, as revealed by synchrotron X-ray scattering experiments. The breakthrough test demonstrates its attractive performance in capturing (400 ppm) CO 2 from gas mixtures via O$-$C bond formation, as indicated by the in situ spectroscopy and operando nuclear magnetic resonance spectroscopy using 13 C-labeled CO 2 sources. Both theoretical and experimental thermodynamic studies reveal the reaction enthalpy of ≈-40 kJ mol -1 between CO 2 and the COF scaffolds. This implies weaker interaction strength compared with state-of-the-art amine-derived sorbents, thus allowing complete CO 2 release with less energy input. The structure evolution study from synchrotron X-ray scattering and small-angle neutron scattering confirms the well-maintained crystalline patterns after CO 2 insertion. In conclusion, the as-developed proof-of-concept approach provides guidance on anchoring binding sites for direct air capture (DAC) of CO 2 in crystalline scaffolds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Novel machine-learning method for spin classification of neutron resonances

The performance of nuclear reactors and other nuclear systems depends on a precise understanding of the neutron interaction cross sections for materials used in these systems. These cross sections exhibit resonant structure whose shape is determined in part by the angular-momentum quantum numbers of the resonances. The correct assignment of the quantum numbers of neutron resonances is, therefore, paramount. In this project, we apply machine learning to automate the quantum number assignments using only the resonances' energies and widths and not relying on detailed transmission or capture measurements. The classifier used for quantum number assignment is trained using stochastically generated resonance sequences whose distributions mimic those of real data. Here we explore the use of several physics-motivated features for training our classifier. These features amount to out-of-distribution tests of a given resonance's widths and resonance-pair spacings. We pay special attention to situations where either capture widths cannot be trusted for classification purposes or where there is insufficient information to classify resonances by the total spin J. We demonstrate the efficacy of our classification approach using simulated and actual 52 Cr resonance data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Neutrino fast flavor instability in three dimensions for a neutron star merger

The flavor evolution of neutrinos in core collapse supernovae and neutron star mergers is a critically important unsolved problem in astrophysics. Following the electron flavor evolution of the neutrino system is essential for calculating the thermodynamics of compact objects as well as the chemical elements they produce. Accurately accounting for flavor transformation in these environments is challenging for a number of reasons, including the large number of neutrinos involved, the small spatial scale of the oscillation, and the nonlinearity of the system. We take a step in addressing these issues by presenting a method which describes the neutrino fields in terms of angular moments. We apply our moment method to neutron star merger conditions and show it simulates fast flavor neutrino transformation in a region where this phenomenon is expected to occur. By comparing with particle-in-cell calculations we show that the moment method is able to capture the three phases of growth, saturation, and decoherence, and correctly predicts the lengthscale of the fastest growing fluctuations in the neutrino field.

79 ASTRONOMY AND ASTROPHYSICS↗

Structural properties of aqueous grown polydopamine thin films determined by neutron reflectometry

Here, in this work, neutron reflectometry (NR) studies of the bio-mimetic polymer, polydopamine (PDA), deposited from differing initial concentrations of precursor material dopamine hydrochloride for a range of polymerization times, is reported. PDA can form a complex and highly versatile polymer film, with many structure studies having been performed previously, but a comprehensive structural determination of PDA by NR is lacking in the literature. It was found that simple box models were incapable of fully explaining the observed data, necessitating the use of a composite model consisting of the weighted average of both the 1 and 2 box models to fully capture the heterogeneous nature of the PDA film structure. Confocal laser scanning microscopy (CLSM) and atomic force microscopy (AFM) were performed to capture the surface structure and relative mechanical difference between the separate domains of the PDA. The CLSM results provide evidence that the PDA domains are larger than the coherent scattering length of a neutron used in these measurements, 10μm, supporting the need for a composite model. The AFM measurements show complex structure below the coherence length provide physical justification for the two box model. It was determined that film structure and quality are both heavily impacted by the initial concentration of dopamine hydrochloride and the polymerization time, giving confidence to the highly customizable nature of PDA as an adhesion promoting interface treatment in composite systems, such as plastic bonded explosives (PBX).

36 MATERIALS SCIENCE↗

Machine learning methods for fission product identification from Bragg curves

A fission time projection chamber (fission-TPC) was developed to provide precise neutron-induced fission measurements for several major actinides. As fission fragments lose energy in one of the gas volumes of the fission-TPC, energy loss information is captured and may be used to determine fission product yields as the stopping power of an ion is dependent on the atomic number. The work presented here demonstrates the ability to apply machine learning techniques for Bragg curve classification. A set of one million energy loss curves for 24 different fission-fragment elements was generated using common stopping power software. A ResNet architecture optimized for 1D data was used to train, test, and validate a model for light and heavy fission fragments using the simulated data. The resultant classification accuracy for the light and heavy fragments indicates that this could be a viable method for elemental classification of data from the fission-TPC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Space to Air High-Altitude Region Adjoint Neutron Transport

Neutrons from an atmospheric nuclear explosion can be detected by sensors in orbit. Current tools for characterizing the neutron energy spectrum assume a known source and use forward transport to recreate the detector response. In realistic scenarios the true source is unknown, making this an inefficient, iterative approach. In contrast, the adjoint approach directly solves for the source spectrum, enabling source reconstruction. The time–energy fluence at the satellite and adjoint transport equation allow a Monte Carlo method to characterize the neutron source’s energy spectrum directly in a new model: the Space to High-Altitude Region Adjoint (SAHARA) model. A new adjoint source event estimator was developed in SAHARA to find feasible solutions to the neutron transport problem given the constraints of the adjoint environment. This work explores SAHARA’s development and performance for mono-energetic and continuous neutron energy sources. In general, the identified spectra were shifted towards energies approximately 5% lower than the true source spectra, but SAHARA was able to capture the correct spectral shapes. Continuous energy sources, including real-world sources Fat Man and Little Boy, resulted in identifiable spectra that could have been produced by the same distribution as the true sources as demonstrated by two-dimensional (2D) Kolmogorov–Smirnov tests.

LaMere, Zachary W.↗

TRANSFER LEARNING FOR FIELD EMISSION MITIGATION IN CEBAF SRF CAVITIES

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab operates hundreds of super-conducting radio frequency (SRF) cavities in its two linear accelerators (linacs). Field emission (FE) is an ongoing operational challenge in higher gradient SRF cavities. FE generates high levels of neutron and gamma radiation leading to damaged accelerator hardware and a radiation hazard environment. During machine development periods, we performed gradient scans to record data capturing the relationship between cavity gradients and radiation levels measured throughout the linacs. However, the field emission environment at CEBAF varies considerably over time as the configuration of the radio frequency (RF) gradients changes and due to the changing behaviour of field emitters. An artificial intelligence/machine learning (AI/ML) approach with transfer learning could be a valuable tool to mitigate FE and lower the radiation levels. In this work, we mainly focus on leveraging the RF trip data gathered during CEBAF operations. We develop a transfer learning-based surrogate model for radiation detector readings given RF cavity gradients to track the CEBAF?s changing configuration and environment. Then, we could use the developed model as an optimization process for redistributing the RF gradients within a linac to minimize radiation levels.

Ahammed, K.↗

TRANSFER LEARNING FOR FIELD EMISSION MITIGATION IN CEBAF SRF CAVITIES

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab operates hundreds of super-conducting radio frequency (SRF) cavities in its two linear accelerators (linacs). Field emission (FE) is an ongoing operational challenge in higher gradient SRF cavities. FE generates high levels of neutron and gamma radiation leading to damaged accelerator hardware and a radiation hazard environment. During machine development periods, we performed gradient scans to record data capturing the relationship between cavity gradients and radiation levels measured throughout the linacs. However, the field emission environment at CEBAF varies considerably over time as the configuration of the radio frequency (RF) gradients changes and due to the changing behaviour of field emitters. An artificial intelligence/machine learning (AI/ML) approach with transfer learning could be a valuable tool to mitigate FE and lower the radiation levels. In this work, we mainly focus on leveraging the RF trip data gathered during CEBAF operations. We develop a transfer learning-based surrogate model for radiation detector readings given RF cavity gradients to track the CEBAF?s changing configuration and environment. Then, we could use the developed model as an optimization process for redistributing the RF gradients within a linac to minimize radiation levels.

Ahammed, K.↗

Highly-detailed neutronic and thermal-hydraulic coupled calculations for OPAL reactor using diverse codes and approaches

The industry-standard approach for designing and operating research reactors cores relies on well-established methodologies that consider uncoupled neutronic calculations and a subchannel analysis of the Thermal-Hydraulic (TH) associated problem. Advancements in computing power and codes allow detailed Multiphysics approaches to be implemented, thereby reducing conservatism. In this study, a comparative analysis of results from diverse detailed neutronic-TH coupled core approaches is developed. To address a realistic application case, the comparison is made for a reported critical configuration from the Open Pool Australian Lightwater research reactor (OPAL) at Hot Full Power (HFP) and low burnup. Both cell-core and stochastic methodologies for neutronics are evaluated, whereas two different subchannel codes are considered for TH. In conclusion, the convergence of the coupled schemes, and the consistency of the main parameters are discussed, showing the compatibility of the alternative methods and their ability to offer critical insights not captured by standard practices.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Dark kinetic heating of exoplanets and brown dwarfs

Dark kinetic heating of neutron stars has been previously studied as a promising dark matter detection avenue. Kinetic heating occurs when dark matter is sped up to relativistic speeds in the gravitational well of high-escape velocity objects, and deposits kinetic energy after becoming captured by the object, thereby increasing its temperature. We show that dark kinetic heating can be significant even in objects with low-escape velocities, such as exoplanets and brown dwarfs, increasing the discovery potential of such searches. This can occur if there is a long-range dark force, creating a “dark escape velocity”, leading to heating rates substantially larger than those expected from neutron stars. We consequently set constraints on dark sector parameters using Wide-field Infrared Survey Explorer and JWST data on Super-Jupiter WISE 0855-0714, and map out future sensitivity to the dark matter scattering cross section below 10 −40 cm 2 . We compare dark kinetic heating rates of other lower escape velocity objects such as the Earth, Sun, and white dwarfs, finding complementary kinetic heating signals are possible depending on particle physics parameters.

Astrophysics↗

Phase transition phenomenology with nonparametric representations of the neutron star equation of state

Astrophysical observations of neutron stars probe the structure of dense nuclear matter and have the potential to reveal phase transitions at high densities. Most recent analyses are based on parametrized models of the equation of state with a finite number of parameters and occasionally include extra parameters intended to capture phase-transition phenomenology. However, such models restrict the types of behavior allowed and may not match the true equation of state. We introduce a complementary approach that extracts phase transitions directly from the equation of state without relying on, and thus being restricted by, an underlying parametrization. We then constrain the presence of phase transitions in neutron stars with astrophysical data. Current pulsar mass, tidal deformability, and mass-radius measurements disfavor only the strongest of possible phase transitions (latent energy per particle ≳ 100 MeV). Weaker phase transitions are consistent with observations. Here we further investigate the prospects for measuring phase transitions with future gravitational-wave observations and find that catalogs of O (100) events will (at best) yield Bayes factors of ~ 10 : 1 in favor of phase transitions even when the true equation of state contains very strong phase transitions. Our results reinforce the idea that neutron star observations will primarily constrain trends in macroscopic properties rather than detailed microscopic behavior. Fine-tuned equation of state models will likely remain unconstrained in the near future.

79 ASTRONOMY AND ASTROPHYSICS↗

Low-temperature spin dynamics in the TmFeO 3 orthoferrite with a non-Kramers ion

We investigate the magnetic dynamics of the orthorhombic perovskite TmFeO 3 at low temperatures, below the spin reorientation transition at TSR≈80 K, by means of time-of-flight neutron spectroscopy. We find that the magnetic excitation spectrum combines two emergent collective modes associated with different magnetic sublattices. The Fe subsystem orders below TN~632 K into a canted antiferromagnetic structure and exhibits sharp, high-energy magnon excitations. We describe them using linear spin-wave theory, and reveal a pronounced anisotropy between in- and out-of-plane exchange interactions, which was mainly neglected in previous reports on the spin dynamics in orthoferrites. At lower energies, we find two crystalline electrical field (CEF) excitations of Tm3+ ions at energies of ~2 and 5 meV. In contrast to the sister compound YbFeO 3 , where the Yb 3+ ions form quasi-one-dimensional chains along the c axis, the Tm excitations show dispersion along both directions in the (0KL) scattering plane. Analysis of the neutron scattering polarization factor reveals a longitudinal polarization of the 2 meV excitation. To evaluate the effect of the CEF on the Tm 3+ ions, we perform point-charge model calculations, and their results quantitatively capture the main features of Tm single-ion physics, such as energies, intensities, and polarization of the CEF transitions, and the type of magnetic anisotropy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Suppression of Composition g -modes in Chemically Equilibrating Warm Neutron Stars

We investigate the impact of chemical equilibration and the resulting bulk viscosity on nonradial oscillation modes of warm neutron stars at temperatures up to T ≈ 5 MeV, relevant for protoneutron stars and neutron star postmerger remnants. In this regime, the relaxation rate of weak interactions becomes comparable to the characteristic frequencies of composition g-modes in the core, resulting in resonant damping. To capture this effect, we introduce the dynamical sound speed, a complex, frequency-dependent generalization of the adiabatic sound speed that encodes both the restoring force and the dissipative effects of bulk compression. Using realistic weak reaction rates and three representative equations of state, we compute the complex frequencies of composition g-modes with finite-temperature profiles. We find that bulk viscous damping becomes increasingly significant with temperature and can completely suppress composition g-modes. In contrast, the f-mode remains largely unaffected by bulk viscosity due to its nearly divergence-free character. Our results highlight the sensitivity of g-mode behavior to thermal structure, weak reaction rates, and the equation of state, and establish the dynamical sound speed as a valuable descriptor characterizing oscillation properties in dissipative neutron star matter.

Neutron stars↗

Irradiation creep model for α-Fe: Dislocation climb in the presence of stress fields (Final Report)

Irradiation creep is known to be an important process for structural materials in nuclear environments, potentially leading to creep failure at temperatures where thermal creep is generally negligible. While there is a great deal of data for irradiation creep in steels and zirconium alloys in light water reactor conditions, much less is known for first wall materials under fusion energy conditions. Lacking suitable fusion neutron sources for detailed experimentation, modeling, and simulation can help bridge the dose-rate and spectral-effects gap and produce quantifiable expectations for creep deformation of first wall materials under standard fusion conditions. In this work, we present a comprehensive model for irradiation creep created from merging a crystal plasticity representation of the dislocation microstructure and a defect evolution simulator that accounts for the entire cluster dimensionality space. Both approaches are linked by way of a climb velocity that captures dislocation-biased defect absorption and a dislocation strengthening term that reflects the accumulation of defect clusters in the system. We carry out our study in Fe under first wall fusion reactor conditions, characterized by a fusion neutron spectrum at temperatures between 300 and 800°K.

36 MATERIALS SCIENCE↗

140,142 Ce Neutron Cross Section Resolved Resonance Region Evaluation [Slides]

ORNL has completed new RRR evaluations for 140,142 Ce. A lack of integral measurements made validation difficult, but the difference from Kadonis values suggests that more investigation of capture cross section is warranted. The complete file (with updated File2 and File32) has been submitted to NNDC repository for inclusion in next release of ENDF. A sponsor report publication is in progress.

07 ISOTOPE AND RADIATION SOURCES↗

Towards understanding the magnetic properties of the breathing pyrochlore compound Ba3Yb2Zn5O11through single-crystal studies

Abstract Ba 3 Yb 2 Zn 5 O 11 is exceptional among breathing pyrochlore compounds for being in the nearly-decoupled limit where inter-tetrahedron interactions are weak, hosting isolated clusters or molecular magnet-like tetrahedra of magnetic ytterbium (Yb 3+ ) ions. In this work, we present the study carried out on single-crystal samples of the breathing pyrochlore Ba 3 Yb 2 Zn 5 O 11 , using a variety of magnetometry and neutron scattering techniques along with theoretical modeling. We employ inelastic neutron scattering to investigate the magnetic dynamics as a function of applied field (with respect to both magnitude and direction) down to a temperature of 70 mK, where inelastic scattering reveals dispersionless bands of excitations as found in earlier powder sample studies, in good agreement with a single-tetrahedron model. However, diffuse neutron scattering at zero field and dc-susceptibility at finite field exhibit features suggesting the presence of excitations at low-energy that are not captured by the single tetrahedron model. Analysis of the local structure down to 2 K via pair distribution function analysis finds no evidence of structural disorder. We conclude that effects beyond the single tetrahedron model are important in describing the low-energy, low-temperature physics of Ba 3 Yb 2 Zn 5 O 11 , but their nature remains undetermined.

36 MATERIALS SCIENCE↗

Signatures of muonic activation in the Majorana Demonstrator

Experiments searching for very rare processes such as neutrinoless double-beta decay require a detailed understanding of all sources of background. Signals from radioactive impurities present in construction and detector materials can be suppressed using a number of well-understood techniques. Background from in situ cosmogenic interactions can be reduced by siting an experiment deep underground. However, the next generation of such experiments have unprecedented sensitivity goals of 10 28 years half-life with background rates of 10 -5 cts/(keV kg yr) in the region of interest. To achieve these goals, the remaining cosmogenic background must be well understood. In the work presented here, Majorana Demonstrator data are used to search for decay signatures of metastable germanium isotopes. Contributions to the region of interest in energy and time are estimated using simulations and compared to Demonstrator data. Correlated time-delayed signals are used to identify decay signatures of isotopes produced in the germanium detectors. A good agreement between expected and measured rate is found and different simulation frameworks are used to estimate the uncertainties of the predictions. The simulation campaign is then extended to characterize the background for the LEGEND experiment, a proposed tonne-scale effort searching for neutrinoless double-beta decay in 76 Ge .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Multigroup Scattering in Monte Carlo Radiation Transport Codes [Slides]

Legendre truncations to multigroup scattering distributions are not amenable to Monte Carlo sampling due to negative values. We have implemented two moment-preserving methods in MGMC that capture the shape of the truncation, are non-negative over [-1, 1], and can be efficiently sampled on CPUs and GPUs. MGMC can now simulate neutrons with anisotropic scattering mechanics and MGMC shows good agreement with LANL production codes PARTISN.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗