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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Fuel–shell mix and yield degradation in kinetic shock-driven inertial confinement fusion implosions

Fuel–shell mix in kinetic plasma conditions is probed using nuclear and x-ray self-emission in shock-driven, D 3 He-gas-filled inertial confinement fusion implosions. As initial gas fill density decreases, measured nuclear yields and ion temperatures are lower than expected as compared to radiation-hydrodynamic simulations. Spatially and temporally resolved x-ray emissions indicate significant mixing at the fuel–shell interface in implosions with low initial gas fill density. In conclusion, this observed fuel–shell mix introduces a substantial amount of shell ions into the center of the implosion prior to and during shock flash and is the key mechanism needed in the kinetic-ion simulations to match experimental nuclear yields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Long Range Plan: Dense matter theory for heavy-ion collisions and neutron stars

Since the release of the 2015 Long Range Plan in Nuclear Physics, major events have occurred that reshaped our understanding of quantum chromodynamics (QCD) and nuclear matter at large densities, in and out of equilibrium. The US nuclear community has an opportunity to capitalize on advances in astrophysical observations and nuclear experiments and engage in an interdisciplinary effort in the theory of dense baryonic matter that connects low- and high-energy nuclear physics, astrophysics, gravitational waves physics, and data science. This is a white paper prepared by a group of nuclear physicists during the 2023 LRP process.

Lovato, Alessandro↗
DOE OSTI2025

Bayesian model mixing with multireference energy density functional

Reliably predicting nuclear properties across the entire chart of isotopes is important for applications ranging from nuclear astrophysics to superheavy science to nuclear technology. To this day, however, all the theoretical models that can scale at the level of the chart of isotopes remain semiphenomenological. Because they are fitted locally, their predictive power can vary significantly; different versions of the same theory provide different predictions. Bayesian model mixing takes advantage of such imperfect models to build a local mixture of a set of models to make improved predictions. Earlier attempts to use Bayesian model mixing for mass table calculations relied on models treated at single-reference energy density functional level, which fail to capture some of the correlations caused by configuration mixing or the restoration of broken symmetries. In this study we have applied Bayesian model mixing techniques within a multireference energy density functional (MR-EDF) framework. We considered predictions of two-particle separation energies from particle number projection or angular momentum projection with four different energy density functionals—a total of eight different MR-EDF models. We used a hierarchical Bayesian stacking framework with a Dirichlet prior distribution over weights together with an inverse log-ratio transform to enable positive correlations between different models. We found that Bayesian model mixing provides significantly improved predictions compared to the participating models. Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Application of the Redlich-Kister expansion for estimating the density of molten fluoride psuedo-ternary salt systems of nuclear industry interest

The development of next-generation molten salt reactors relies on accurate knowledge of the thermophysical properties of the candidate coolant and fueled molten salts. These thermophysical properties include density, viscosity, thermal conductivity, and heat capacity. Because of difficulties in measuring thermophysical properties of molten salts, there are many gaps in the current state of thermophysical property knowledge of these salts, particularly those that contain actinides or beryllium. Therefore, leveraging modeling techniques to estimate unknown molten salt thermophysical properties and guide future experimental measurements has high value for the nuclear industry. Here, the densities of molten fluoride pseudo-ternary salt systems, which are of interest to the nuclear industry, were estimated using Redlich-Kister expansion and Muggianu interpolation techniques. The pseudo-ternary systems considered for estimation in this study were NaF-LiF-ZrF 4 , LiF-BeF 2 -ZrF 4 , LiF-BeF 2 -ThF 4 , NaF-LiF-BeF 2 , NaF-KF-BeF 2 , NaF-ZrF 4 -UF 4 , and NaF-BeF 2 -UF 4 . This Redlich-Kister estimation approach accounts for nonideal mixing behavior based on pseudo-binary subsystem interaction parameters determined from experimentally measured pseudo-binary system density data sets. The Redlich-Kister estimation was compared with the method of additive molar volumes, which assumes ideal mixing. Additionally, the Redlich-Kister approach was used to determine previously unknown binary and ternary interaction parameters based on experimentally measured density data sets for select pseudo-ternary salt systems. The results of this study show improvement in density estimation using the Redlich-Kister approach for all systems considered compared with estimation by additive molar volumes. Furthermore, this analysis allowed for the estimation of nonideal density behavior in experimentally unstudied ZrF 4 -UF 4 and BeF 2 -UF 4 , as well as the quantification of ternary interaction in NaF-LiF-ZrF 4 , NaF-BeF 2 -UF 4 , and NaF-ZrF 4 -UF 4 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Hydrogen density mapping in biomolecular crystals through dynamic nuclear polarization

Many fundamental biological processes, including those in photosynthetic reaction centers and enzyme active sites, involve charge and energy transfer, bond cleavage, protonation and hydrogen bonding. Because H atoms play such central roles in these reactions, accurately determining their positions is essential. Yet, conventional X-ray crystallography primarily resolves the heavy atoms in biological structures and provides limited insight into hydrogen, even at atomic resolution. Neutron macromolecular crystallography (NMC) overcomes this limitation by offering exceptional sensitivity to hydrogen and deuterium. Here, we present a theoretical framework for the development of dynamic nuclear polarization NMC (DNP-NMC) techniques, which exploit the alignment of neutron and proton nuclear spins to enhance and tune the hydrogen signal contribution. The DNP-NMC approach advances the resolution of H atoms within biomolecular crystals, whether bound to protein residues or present in solvent. The method establishes key relationships for the coherent structure factor of polarized neutron scattering from hydrogenous matter. It theoretically achieves full accuracy in phase reconstruction and offers a path to improve neutron structure determination, achieving accuracies exceeding ≳80% by incorporating titration states. Using a variant of the hybrid input/output phase-retrieval algorithm, it allows recovery of the hydrogen density with ≳90% phase accuracy. In conclusion, we further discuss sources of experimental uncertainty for the upcoming DNP-enabled, quasi-Laue IMAGINE-X experiment at Oak Ridge National Laboratory's High Flux Isotope Reactor.

dynamic nuclear polarization↗
DOE OSTI2024

Universal reduced basis for the calibration of covariant energy density functionals

The reduced basis method is used to construct a “universal” basis of Dirac orbitals that may be applicable throughout the nuclear chart to calibrate covariant energy density functionals. Relative to the successful development of a reduced basis emulator for the nonrelativistic Schrödinger equation, the Dirac equation adds an extra layer of complexity due to the existence of negative energy states, which complicates building an efficient reduced basis. However, once this problem is mitigated, the resulting reduced basis is able to accurately and efficiently reproduce the high-fidelity model at a fraction of the computational cost. We are confident that the resulting reduced basis will serve as a foundational element in developing rapid and accurate emulators. In turn, these emulators will play a critical role in the Bayesian optimization of covariant energy density functionals.

Bayesian methods↗
DOE OSTI2022

High-energy-density plasma in femtosecond-laser-irradiated nanowire-array targets for nuclear reactions

In this work, the high-energy-density plasmas (HEDP) evolved from joule-class-femtosecond-laser-irradiated nanowire-array (NWA) targets were numerically and experimentally studied. The results of particle-in-cell simulations indicate that ions accelerated in the sheath field around the surfaces of the nanowires are eventually confined in a plasma, contributing most to the high energy densities. The protons emitted from the front surfaces of the NWA targets provide rich information about the interactions that occur. We give the electron and ion energy densities for broad target parameter ranges. The ion energy densities from NWA targets were found to be an order of magnitude higher than those from planar targets, and the volume of the HEDP was several-fold greater. At optimal target parameters, 8% of the laser energy can be converted to confined protons, and this results in ion energy densities at the GJ/cm 3 level. In the experiments, the measured energy of the emitted protons reached 4 MeV, and the changes in energy with the NWA’s parameters were found to fit the simulation results well. Experimental measurements of neutrons from 2 H(d,n) 3 He fusion with a yield of (24 ± 18) × 10 6 /J from deuterated polyethylene NWA targets also confirmed these results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Leveraging differentiable programming in the inverse problem of neutron stars

Neutron stars (NSs) probe the high-density regime of the nuclear equation of state (EOS). However, inferring the EOS from observations of NSs is a computationally challenging task. Here, in this work, we efficiently solve this inverse problem by leveraging differential programming in two ways. First, we enable full Bayesian inference in under one hour of wall time on a GPU by using gradient-based samplers, without requiring pretrained machine learning emulators. Moreover, we demonstrate efficient scaling to high-dimensional parameter spaces. Second, we introduce a novel gradient-based optimization scheme that recovers the EOS of a given NS mass-radius curve. We demonstrate how our framework can reveal consistencies or tensions between nuclear physics and astrophysics. First, we show how the breakdown density of a metamodel description of the EOS can be determined from NS observations. Second, we demonstrate how degeneracies in EOS modeling using nuclear empirical parameters can influence the inverse problem during gradient-based optimization. Looking ahead, our approach opens up new theoretical studies of the relation between NS properties and the EOS, while effectively tackling the data analysis challenges brought by future detectors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1994

Gamma-ray and millimeter-wave emissions from the 1991 June X-class solar flares

We have studied the spectacular 1991 June X-class flares using gamma-ray data from the Charged Particle Detectors (CPDs) of the Burst and Transient Source Experiment (BATSE) on the Compton Gamma Ray Observatory (CGRO) and 80 GHz millimeter data from Nobeyama, Japan. The CPDs were the only CGRO instrument that did not saturate during the extremely intense 1991 June 4 flare. We have shown that for this flare the CPDs respond to MeV photons, most of which are due to bremsstrahlung produced by relativistic electrons at the Sun. We have further shown that the gamma-ray and millimeter observations agree numerically if the 80 GHz radiation is gyrosynchrotron radiation produced by trapped electrons and the gamma rays are thick-target bremsstrahlung due to electrons precipitating out of the trap. The requirement that the trapping time obtained from the numerical comparison be consistent with the observed time profiles implies a magnetic field between about 200 and 300 G and an electron spectral index between about 3 to 5. By comparing the CPD observations with both the 80 GHz data and nuclear line data from the Energetic Gamma Ray Experiment Telescope (EGRET) and the Oriented Scintillation Spectroscopy Experiment (OSSE) on CGRO for the flares of June 4, 6, 9, and 11, we found that the ratio of the CPD counts to both the millimeter flux densities and the nuclear line fluences decreases with decreasing flare heliocentric angle. All of these flares were produced in the same active region. We interpreted this result in terms of a loop model in which the gyrosynchrotron emission is produced in the coronal portion of the loop where the electrons are kept isotropic by pitch angle scattering due to plasma turbulence, while the bremsstrahlung is produced by precipitating electrons that interact anisotropically. We found that the trapping time in the coronal portion is time dependent, reaching a minimum of about 10 s at the peak of the CPD count rate. We suggested the damping of the turbulence as a possible reason for the variation of the trapping time. turbulence as a possible reason for the variation of the trapping time.

Ramaty, Reuven↗
DOE OSTI2025

General features of the stellar matter equation of state from microscopic theory, new maximum-mass constraints, and causality

The profile of a neutron star probes a very large range of densities, from the density of iron up to several times the density of saturated nuclear matter, and thus no theory of hadrons can be considered reliable if extended to those regions. We emphasize the importance of taking contemporary ab initio theories of nuclear and neutron matter as the baseline for any extension method, which will unavoidably involve some degree of phenomenology. We discuss how microscopic theory, on the one end, with causality and maximum-mass constraints, on the other, set strong boundaries to the high-density equation of state. We present our latest neutron star predictions where we combine polytropic extensions and parametrizations guided by speed of sound considerations. The predictions we show include our baseline neutron star cooling curves.

chiral effective field theory↗
DOE OSTI2021

Challenges and opportunities to alloyed and composite fuel architectures to mitigate high uranium density fuel oxidation: Uranium mononitride

We see the challenges and opportunities to alloyed and composite fuel architectures designed and intended to mitigate oxidation of the fuel during a cladding breech of a water-cooled reactor are discussed in three review manuscripts developed in parallel, with the presented article focused on the oxidation performance of uranium mononitride. Several high uranium density fuels are under consideration for deployment as accident tolerant and/or advanced technology nuclear reactor fuels, including one on each: UN, U 3 Si 2 , UC and UB 2 . Presented here is the research motivation for the incorporation of additives, dopants, or composite fuel architectures to improve the oxidation/corrosion behavior of high uranium density nuclear fuels for use in LWRs. Furthermore, this review covers the literature on the degradation modes, thermodynamics, and oxidation performance of pure UN and UN-compounds as well as reported alloyed and composite architectures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1982

Harmonic well matter densities and Pauli correlation effects in heavy-ion collisions

A generalized optical model heavy ion reaction theory is extended to include correlation effects between projectile and target constituents according to the Pauli exclusion principle. These correlation effects are significant for accurately predicting cross sections for projectile nucleus abrasions, but are relatively unimportant for determining total and absorption cross sections for heavy ion collisions. For lighter nuclei, predictive capabilities were also improved by developing an analytic method for extracting their nuclear single particle density distributions from experimentally measured harmonic well charge density distributions. This improved theory is compared with previous theoretical predictions and recent experimental results.

Townsend, L. W.↗
DOE OSTI2023

Density Measurements of Plutonium Bearing Salts via Neutron Beam Dilatometry (Final Report for Gateway for Accelerated Innovation in Nuclear (GAIN) Voucher NE-21-25117)

A novel neutron radiographic technique was developed and implemented to measure the change in volume as a function of temperature of select plutonium-containing liquid chloride mixtures from melt to 1250 K. These measurements were performed at Los Alamos National Laboratory by members of the molten salt research group under support from Gateway for Accelerated Innovation in Nuclear (GAIN) voucher NE-21-25117: “Density Measurements of Plutonium Bearing Salts via Neutron Beam Dilatometry”.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Comparing different density-matrix expansions for long-range pion exchange

Empirical energy density functionals (EDFs) are generally successful in describing nuclear properties across the table of nuclides. But their limitations motivate using the density-matrix expansion (DME) to embed long-range pion interactions into a Skyrme functional. Recent results on the impact of the pion were both encouraging and puzzling, necessitating a careful re-examination of the DME implementation. In this study, we take the first steps, focusing on two-body scalar terms in the DME. Exchange energies with long-range one-pion contributions are well approximated by all DME implementations considered, with preference for variants that do not truncate at two derivatives in every EDF term. The use of the DME for chiral pion contributions is therefore supported by this investigation. For scalar-isovector energies it is important to treat neutrons and protons separately. The results are found to apply under broad conditions, although self-consistency is not yet tested.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Analytic Nuclear Gradients for Complete Active Space Linearized Pair-Density Functional Theory

Accurately modeling photochemical reactions is difficult due to the presence of conical intersections and locally avoided crossings, as well as the inherently multiconfigurational character of excited states. As such, one needs a multistate method that incorporates state interaction in order to accurately model the potential energy surface at all nuclear coordinates. The recently developed linearized pair-density functional theory (L-PDFT) is a multistate extension of multiconfiguration PDFT, and it has been shown to be a cost-effective post-MCSCF method (as compared to more traditional and expensive multireference many-body perturbation methods or multireference configuration interaction methods) that can accurately model potential energy surfaces in regions of strong nuclear–electronic coupling in addition to accurately predicting Franck–Condon vertical excitations. Here, in this paper, we report the derivation of analytic gradients for L-PDFT and their implementation in the PySCF-forge software, and we illustrate the utility of these gradients for predicting ground- and excited-state equilibrium geometries and adiabatic excitation energies for formaldehyde, s-trans-butadiene, phenol, and cytosine.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Controlling extrapolations of nuclear properties with feature selection

Predictions of nuclear properties far from measured data are inherently inaccurate because of uncertainties in our knowledge of nuclear forces and in our treatment of quantum many-body effects in strongly-interacting systems. While the model bias can be directly calculated when experimental data is available, only an estimate can be made in the absence of such measurements. Current approaches to compute the estimated bias quickly lose predictive power when their input variables are taken far from the training region, resulting in uncontrolled uncertainties in applications such as nucleosynthesis simulations. In this letter, we present a novel technique to identify the input variables of machine learning algorithms that can provide robust estimates of model bias. Our process is based on selecting input variables, or features, based on their probability distribution functions across the entire nuclear chart. We illustrate our approach on the problem of quantifying the model bias in nuclear binding energies calculated with Density Functional Theory (DFT). We prove that building model biases with only Z and N as features leads to highly unreliable extrapolations. Conversely, we show that proper feature selection can systematically improve theoretical predictions without increasing uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗