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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sequential spectral line analysis for accurate density and temperature diagnosis of laboratory opacity measurements

The accuracy of iron opacity calculated in stellar interiors has been questioned since the discovery of the “solar problem” and the discrepancies between the measured and modeled iron opacity reported in 2015. Experimental opacity benchmarks require accurate temperature and density measurements, which were inferred by analyzing tracer magnesium spectra in those experiments. Could the observed discrepancy be explained by insufficient accuracy in the inferred temperature, density, and their uncertainties? Previous analyses may have yielded biased results due to three limitations: (1) simultaneous multi-line fitting, (2) approximations in line-shape models, and (3) exclusion of certain spectral lines due to insufficient background characterization. Notably, the first issue is a common concern for many inversion methods, including Bayesian inferences. We present a refined analysis method that overcomes these limitations, applied to three categories of iron opacity experiments (Anchor 1, 2, and 3). In particular, the sequential fitting method yields unbiased results with more realistic uncertainties by accounting for line inconsistencies in the parameter uncertainties. The average electron temperature and density values are 162 ± 6 eV and (7.0 ± 1.9) × 10 21 cm −3 for six Anchor 1 experiments, 189 ± 7 eV and (3.4 ± 0.3) × 10 22 cm −3 for 21 Anchor 2 experiments, and 201 ± 6 eV and (4.8 ± 1.1) × 10 22 cm −3 for nine Anchor 3 experiments. These results show ∼4% temperature and ∼20% density reproducibility over a decade, which also aligns with the inferred parameter uncertainties. In conclusion, the resulting temperature and density uncertainties lead to a quasi-continuum iron opacity variation of ±4%–7% for wavelengths below 9.5 Å, which is insufficient to explain the significant model-data discrepancies reported in 2015.

Absorption spectroscopy↗
DOE OSTI2025

The Langdon effect in laser plasmas: Absorption and conduction

A plasma heated by inverse bremsstrahlung absorption of laser light develops a non-Maxwellian electron distribution function, called the Langdon effect [A. B. Langdon, Phys. Rev. Lett. 44, 575 (1980)]. These non-Maxwellian distributions are sufficiently long-lived to impact the absorption processes itself as well as the transport of heat by electrons. The theory of the Langdon effect in a homogeneous plasma is reviewed to clarify some aspects of Langdon's derivation as well as to confirm that the widely used super-Gaussian approximation works fairly well to describe the shape of the distribution function and reduction of the absorption rate. The Langdon effect on thermal conduction in an inhomogeneous plasma is developed by considering perturbations in a homogeneous absorbing plasma, which develops a heat flux due to both temperature and density gradients. A practical theory of the heat flux is developed by fitting the results of Vlasov–Fokker–Planck simulations, which avoids several approximations that compromised the usefulness of past theoretical predictions, most critically, the effect of electron–electron collisions on the fluxes. The present fits parameterize the coefficients of the temperature gradient (thermal conductivity) and the density gradient for a plasma of any ionization state and for any laser intensity where the theory of the Langdon effect remains locally valid. It is expected that this generalized theory of heat flow in an absorbing plasma will improve the predictive capability of radiation-hydrodynamics simulations of laser-produced plasmas, especially those formed in inertial confinement fusion experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Improved loss functions for machine-learned atomic potentials

Machine learning (ML) has become an invaluable tool across a wide array of domains in science as researchers find new ways to leverage its predictive power. This is especially true in chemistry, where ML is used to fit chemical properties or desirable attributes to the local structure of molecules and materials. In the pursuit of greater accuracy, it is relatively simple to increase the size or complexity of such models, although this often requires simultaneously seeking larger datasets in order to both fit and interpret the larger number of parameters. However, it is equally important to assess the quality and relative importance of the data and how these factors impact the training process. We, therefore, investigate the impact of using different loss functions for training neural network potentials (NNPs), as the loss function defines the error and parameter gradients used to train the NNP. In particular, we test the mean-squared error and Huber loss functions and, using insight from these functions, derive a new loss function based on the Asinh function, which yields significant improvement in the accuracy and generality of NNPs. We show that by discounting/minimizing errors and anomalies in the optimization process, both the Huber and Asinh loss functions improve the training of NNPs, leading to a final potential with a greater effective dimensionality.

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

Robust quantification of the diamond nitrogen-vacancy center charge state via photoluminescence spectroscopy

Nitrogen vacancy (NV) centers in diamond are at the heart of many emerging quantum technologies, all of which require control over the NV charge state. Hence, methods for quantification of the relative photoluminescence intensities of the NV 0 and NV − charge states, i.e., a charge state ratio, are vital. Several approaches to quantify NV charge state ratios have been reported but are either limited to bulk-like NV diamond samples or yield qualitative results. We propose an NV charge state quantification protocol based on the determination of sample- and experimental setup-specific NV 0 and NV − reference spectra. The approach employs blue (400–470 nm) and green (480–570 nm) excitation to infer pure NV 0 and NV − spectra, which are then used to quantify NV charge state ratios in subsequent experiments via least squares fitting. We test our dual excitation protocol (DEP) for a bulk diamond NV sample and 20 and 100 nm nanodiamond particles and compare results with those obtained via other commonly used techniques such as zero-phonon line fitting and non-negative matrix factorization. We find that DEP can be employed across different samples and experimental setups and yields consistent and quantitative results for NV charge state ratios that are in agreement with our understanding of NV photophysics. By providing robust NV charge state quantification across sample types and measurement platforms, DEP will support the development of NV-based quantum technologies.

Color center laser spectroscopy↗
DOE OSTI2025

Bridging material models across scales: An integrated approach to equation of state and molecular dynamics modeling of copper

New uncertainty-aware equation of state (EOS) and electrical conductivity (EC) models for copper have been developed. The multiphase EOS/EC models are fit to experimental solid/liquid EC isobar measurements as well as density-functional theory molecular dynamics (DFT-MD) EC calculations in both expanded and compressed regimes (0.1–16 g/ cm 3 ⁠). The liquid and solid EOS phases were fit to available experimental data along with additional DFT-MD data over the same range as the EC. Leveraging the DFT-MD data, a corresponding machine-learned interatomic potential (MLIAP) for copper was trained using genetic-algorithm optimization. The copper MLIAP was constrained by EOS shock points at high compressions. The final EOS bounded MLIAP proves to be stable over a large density range (approximately 0.1–20 g/ cm 3 ) with good agreement to an isothermal compression curve, shock Hugoniot, and liquid speed of sound measurements at high pressures (100s of GPa).

Acoustic measurements and instrumentation↗
DOE OSTI2026

Enhanced coercivity in Fe5C2/SiO2 core/shell nanocrystals

Rod-shaped Fe5C2 and core/shell Fe5C2/SiO2 nanocrystals were synthesized via a solution-based chemical method. Structural analysis confirmed the monoclinic phase of Fe5C2 with space group C2/c. Zero-field-cooling (ZFC) and field-cooling (FC) magnetization curves revealed distinct magnetic behaviors: uncoated Fe5C2 exhibited a low-temperature FC plateau indicative of strong dipolar interactions, while Fe5C2/SiO2 showed a monotonic increase in FC magnetization, suggesting reduced dipolar interactions due to SiO2 surface passivation. Isothermal remanent magnetization (IRM) and DC demagnetization (DCD) measurements supported this trend, with δM plots confirming weaker dipolar interactions in the coated sample. Bloch’s law fitting of temperature-dependent saturation magnetization showed a smaller Bloch’s constant for pure Fe5C2 and a larger value for Fe5C2/SiO2, reflecting enhanced surface disorder and reduced exchange coupling in the latter. Notably, Fe5C2/SiO2 demonstrated increased coercivity, attributed to decreased dipolar interaction and elevated surface anisotropy. Kneller’s law fitting yielded higher blocking temperatures for Fe5C2 (476 K) than Fe5C2/SiO2 (456 K), highlighting the impact of dipolar interactions on magnetic relaxation. These findings illustrate how SiO2 coatings effectively modulate dipolar interactions and enhance coercivity in Fe5C2 nanocrystals.

Joshi, Pramanand [Department of Physics, Universit↗
DOE OSTI2025

High-density CRISPRi screens reveal diverse routes to improved acclimation in cyanobacteria

Cyanobacteria are the oldest form of photosynthetic life on Earth and contribute to primary production in nearly every habitat, from permafrost to hot springs. Despite longstanding interest in the acclimation of these microbes, it remains poorly understood and challenging to rewire. Here, this study uses a high-density, genome-wide CRISPR interference screen to examine the influence of gene-specific transcriptional variation on the growth of Synechococcus sp. PCC 7002 under environmental extremes. Surprisingly, many partial knockdowns enhanced fitness under cold monochromatic conditions. Transcriptional repression of genes for core subunits of the NDH-1 complex, which are important for photosynthesis and carbon uptake, improved growth rates under both red and blue light but at distinct, color-specific optima. Most genes with fitness-improving knockdowns were distinct to each light color, and dual-target transcriptional repression produced nonadditive effects. Findings reveal diverse routes to improved acclimation in cyanobacteria (e.g., attenuation of genes involved in CO 2 uptake, light harvesting, translation, and purine metabolism) and provide an approach for using gradients in sgRNA activity to pinpoint biochemically influential transcriptional changes in cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Acclimation to high and low diurnal light is flexible in Chlamydomonas reinhardtii

Chlamydomonas acclimates to repeated low (LL) or high light (HL) days by changing the abundance of photosynthetic complexes and the ultrastructure of its thylakoid membranes. These phenotypes persist through the night phases, suggesting a readiness for the daylight environment that is routinely experienced despite the intervening dark periods [S. Dupuis et al., Plant Cell 37, koaf086 (2025), 10.1093/plcell/koaf086]. Here, we investigate how prior acclimation impacts algal fitness upon a change in daylight intensity and how quickly Chlamydomonas can reprogram its photoprotective strategy in a diurnal context. We performed a systems analysis of synchronized populations acclimated to diurnal LL when subjected to HL days and of populations acclimated to diurnal HL when subjected to LL days. In the latter case, diurnal photoacclimation decreased fitness during the first day at a new light intensity: HL-acclimated cells barely increased in size over the first LL period, and they failed to complete a cell cycle. However, although LL-acclimated cells showed severe photodamage after 6 h of HL, they recovered chloroplast form and function later that afternoon and successfully divided at nightfall. These cells rapidly altered their thylakoid membrane ultrastructure, increased their photoprotective quenching capacity, and decreased their inventory of photosystem and antenna proteins by the end of the first HL day. Transcriptomic and proteomic analyses revealed rapid induction of thousands of genes, including those encoding proteases, chaperones, and other proteins involved in the chloroplast unfolded protein response. These results show that the alga is highly flexible and competent to rapidly acclimate to changes in diurnal light intensity.

Diel↗
DOE OSTI2020

Methodology for Generating Covariance Data of Thermal Neutron Scattering Cross Sections

This paper details and implements a framework for evaluating thermal neutron scattering cross sections that provide S(α,β) data and covariance data for hydrogen in light water. This methodology involves perturbing model parameters of molecular dynamics potentials and fitting the simulation results to experimental data. The framework is general and can be applied to any material or simulation method. The fit is made using the Unified Monte Carlo method to experimentally measure double-differential scattering cross sections of light water at the Spallation Neutron Source at Oak Ridge National Laboratory. Mean values and covariance data were generated for model parameters, phonon density of states, double-differential cross sections, and total scattering cross sections. These posterior parameter values were very similar to their prior values with a maximum relative error of 0.54%. This falls within in the Unified Monte Carlo–calculated uncertainties on the order of 2.7%. Additionally, posterior double-differential cross sections agree favorably with ENDF/B-VIII.0 cross sections. The new thermal scattering law was tested by comparing it against benchmarks from the International Criticality Safety Benchmark Evaluation Project Handbook, which showed a slight improvement over the ENDF/B-VIII.0 library. Additionally, the covariance matrix of the phonon density of states was validated to confirm that the spread of k eff from the density of states used to generate the covariance matrix was similar to the spread of k eff from the density of states of the sampled covariance matrix.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Comparative Evaluation of Spectral Methods for Robust Reactor Noise Estimation

Reactor noise analysis provides a noninvasive means to determine neutron kinetic parameters from stochastic fluctuations in detector signals. However, standard cross-power spectral density (CPSD) analyses can be sensitive to numerical processing choices, which may introduce processing-dependent systematic shifts in estimates of the prompt neutron decay constant (α) and limit reproducibility. This study uses a hybrid multitaper–Welch spectral estimator to analyze subcritical noise measurements from a fast-spectrum critical assembly. The decay constant α was extracted using three frequency-domain methods: the CPSD, the magnitude-squared coherence (MSC), and the generalized magnitude-squared coherence (GMSC). These coherence-based estimators normalize detector auto-spectral structure and are expected to reduce the sensitivity of fitted α values to processing parameters. A Sobol global sensitivity analysis identified which numerical inputs most strongly influence the fitted values of α. All estimators produced a linear dependence of α on inverse count rate, with delayed-critical extrapolations near 1.7 × 10 4 s −1 , in agreement within 8% of MCNP6.3 KOPTS benchmark calculations. Sensitivity results show that while the CPSD depends on both time-bin width and taper selection, the MSC and GMSC are dominated by time-bin width alone, indicating reduced parameter coupling and greater robustness to processing variability. These findings demonstrate the feasibility and practical value of coherence-based spectral estimators for extracting α from reactor noise and support their broader application to multi-detector and irregular datasets in subcritical system characterization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Deeper snow increases the net soil organic carbon accrual rate in moist acidic tussock tundra: 210Pb evidence from Arctic Alaska

The net change in the carbon inventory of arctic tundra remains uncertain as global warming leads to shifts in arctic water and carbon cycles. To better understand the response of arctic tundra carbon to changes in winter precipitation amount, we investigated soil depth profiles of carbon concentration and radionuclide activities ( 7 Be, 137 Cs, 210 Pb, and 241 Am) in the active layer of a twenty-two-year winter snow depth manipulation experiment in moist acidic tussock tundra at Toolik Lake, Alaska. Depth correlations of cumulative carbon dry mass (g cm -2 ) vs. unsupported 210 Pb activity (mBq g -1 ) were examined using a modified constant rate of supply (CRS) model. Results were best fit by two-slope CRS models indicating an apparent step temporal increase in the accumulation rate of soil organic carbon. Most of the best-fit model chronologies indicated that the increase in carbon accumulation rate apparently began and persisted after snow fence construction in 1994. The inhomogeneous nature of permafrost soils and their relatively low net carbon accumulation rates make it challenging to establish robust chronologic records. Nonetheless, the data obtained in this study support a decadal-scale increase in net soil organic carbon accumulation rate in the active layer of arctic moist acidic tussock tundra under conditions of increased winter precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Techno-Economic Analysis of Gas-Liquid Contactors for Tritium Extraction from Lead-Lithium

To enable a sustainable fuel cycle, any deuterium-tritium fusion reactor must breed its tritium fuel onsite. Lead-lithium (PbLi), a eutectic metal, is a leading liquid breeder material for tritium generation. One challenge with PbLi blanket technology is the extraction of tritium from the molten eutectic. Three technologies are the focus of worldwide research: the vacuum permeator, the vacuum sieve tray, and the gas-liquid contactor (GLC). The present work offers a methodology for designing, sizing, optimizing, and costing a trickle-bed GLC. Here, we analyzed tritium extraction from PbLi using MELODIE experimental data by applying traditional packed bed mass transfer efficiency models along with supplementary models, like film theory. Our analysis revealed that traditional packed bed mass transfer efficiency models do not fit the MELODIE loop experimental data. Moreover, uncertainty in PbLi solubility resulted in a 325-fold increase in required gas flow rates when comparing identical packing heights. The film theory liquid mass transfer coefficient, Delt-Olujic wettability model, and Reiter tritium solubility values fit the MELODIE data best and were used both in the design and to conduct the economic analysis. Techno-economic analysis of the GLC was performed to evaluate three design sizes, all achieving a minimum extraction efficiency of 90 [%] for a total tritium extraction of 31 [kg/yr].

Fusion Fuel Cycle↗
DOE OSTI2022

Traffic safety analysis and model updating for freeways using Bayesian method

Freeway crash prediction models are the basic of traffic safety research, yet crash occurrence and the influencing factors change over time. In order to make sure the implemented safety models fit the current traffic environment, this study conducts a comparative analysis of 2017 and 2020 datasets collected from freeways in Suzhou, China. Herein, considering the spatial correlation among analysis units and the hierarchical data structure, a Bayesian conditional autoregressive negative binomial (CAR-NB) model and a Bayesian hierarchical CAR-NB (HCAR-NB) model were used to explore the safety influencing factors, and a traditional NB model was developed for further comparison. To update the HCAR-NB model from 2017 to 2020, Bayesian inference with informative priors was used to improve its goodness of fit and efficiency. Preliminary results showed that 1) the HCAR-NB model outperformed the NB model and CAR-NB model in prediction accuracy, and 2) the number of crashes was significantly correlated with average speed, speed variance, road segment length, number of lanes, and presence of ramps. The potential for safety improvement (PSI) method was applied to the modeling results to identify hotspots for the two years. The results confirmed that the hotspots spatiotemporally shifted among the freeways. The proposed crash prediction model and updating method are expected to assist implementation of informed countermeasures for freeway safety improvement.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Reassessing Hybrid Vigor or Hybrid Dysfunction Using Physiological Trade-Offs in an Endangered Salamander System

Fitness of interspecific hybrids can be higher or lower than that of their parental genotypes, with major ramifications for evolution and conservation. A recent study found that hybrid tiger salamanders had higher metabolic rates than their parental forms. Specifically, the ratio of resting metabolic rate to water loss, which was used as a measure of performance, was greater in hybrids. Recent genetic research showed that over half of the experimental subjects in that study were genetically pure California tiger salamanders (Ambystoma californiense) misclassified as hybrids. We reanalyzed the data using the corrected identification of hybrids and parentals. As expected, updating the classification revealed even stronger evidence for differences between hybrids and parentals. Hybrids had higher resting metabolic rates and greater water loss than parentals. The ratio of resting metabolic rate to water loss was also higher in hybrids. However, we suggest that this ratio might not be a positive measure of salamander performance. Higher metabolic rate means higher energy expenditure, and higher water loss suggests increased risk of desiccation. Both are major challenges for terrestrial amphibians, especially salamanders, which are hypothesized to be low-energy, low-water-loss specialists. Under this hypothesis, the ratio of energy expenditure to water loss is a ratio of two costs rather than a ratio of benefit to cost. While our analyses corroborate and strengthen the previous statistical results, we suggest that high resting metabolic rate is better interpreted as hybrid dysfunction, not vigor. Here, both hypotheses are speculative, and specific research on the fitness effects of these physiological differences is needed to resolve this important ecological question.

Ambystoma californiense↗
DOE OSTI2021

Mapping dynamical ejecta and disk masses from numerical relativity simulations of neutron star mergers

Abstract We present fitting formulae for the dynamical ejecta properties and remnant disk masses from the largest to date sample of numerical relativity simulations. The considered data include some of the latest simulations with microphysical nuclear equations of state (EOS) and neutrino transport as well as other results with polytropic EOS available in the literature. Our analysis indicates that the broad features of the dynamical ejecta and disk properties can be captured by fitting expressions, that depend on mass ratio and reduced tidal parameter. The comparative analysis of literature data shows that microphysics and neutrino absorption have a significant impact on the dynamical ejecta properties. Microphysical nuclear EOS lead to average velocities smaller than polytropic EOS, while including neutrino absorption results in larger average ejecta masses and electron fractions. Hence, microphysics and neutrino transport are necessary to obtain quantitative models of the ejecta in terms of the binary parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Resonant x-ray emission across the L 3 edge of uranium compounds

A narrow bandwidth x-ray beamline and a multi-crystal von Hamos spectrometer were used to record x-ray absorption and x-ray emission (XES) across the uranium L 3 edge of UO 2 , UO 3 , Cs 2 UO 2 Cl 4 , and Cs 2 UCl 6 . Measurements were made over 17150–17250 eV with an instrumental resolution of ∼2 eV. This resolution allowed the use of Lorentzian peak fits to the L 3 N 4 and L 3 N 5 characteristic x-ray fluorescence lines that have ∼12–13 eV lifetime widths. The fluorescence yields of the four compounds display strong white lines near threshold and multiple scattering features at higher energies. The XES spectra were fit with three Lorentzians, two for the L 3 N 4 and L 3 N 5 lines and one for inelastic scattering by 2p–6d excitations and 4d–6d final states. The intensities of the white lines were largely due to the inelastic scattering component. To support the measurements, relativistic equation-of-motion coupled-cluster and restricted active space configuration interaction calculations were performed for uranium core-excitation energies in Cs 2 UO 2 Cl 4 and Cs 2 UCl 6 . These calculations with rigorous treatments of relativistic effects are shown to provide accurate uranium L 3 -edge binding energies, L 3 N 5 emission energies, as well as the energy losses in the inelastic scattering process. The measured and calculated results show variations between compounds with U(IV) oxidation states that contain 6d 0 5f 2 electrons in their ground configurations (UO 2 and Cs 2 UCl 6 ) compared with U(VI) compounds (UO 3 and Cs 2 UO 2 Cl 4 ) with empty 5f and 6d configurations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Has AMS-02 observed two-component dark matter?

There is convincing observational evidence for an increasing cosmic-ray positron-to-electron ratio at energies larger than ~10 GeV, at odds with expectations from secondary positron production. The most recent AMS-02 data exhibit an interesting spectral feature consisting of a bump at an energy around 300 GeV followed by a drop around ~800 GeV. A possible explanation for the most recent data is that the excess positron flux originates from decaying dark matter. Here, we show that models consisting of two dark matter particle species contributing equally to the global cosmological dark matter density provide good fits to the data. The favored models, with a best-fit with χ 2 / d . o . f ~ 2, consist of a first species weighing 750 GeV decaying with a lifetime τ χ ~ 10 26 s to τ lepton pairs (or to a pair of vector bosons subsequently decaying to a τ pair each), and a second species with a mass around 2.3 TeV decaying to μ lepton pairs. We provide a few possible concrete realizations for this scenario.

Physics↗
DOE OSTI2022

Coalescence, the thermal model and multi-fragmentation: the energy and volume dependence of light nuclei production in heavy ion collisions

Here, we present results of a phase space coalescence approach within the UrQMD transport and -hybrid model for a very wide range of beam energies from SIS to LHC. The coalescence model is able to qualitatively describe the whole range of experimental data with a fixed set of parameters. Some systematic deviations are observed for very low beam energies where the role of feed down from heavier nuclei and multi-fragmentation becomes relevant. The coalescence results are mostly very close to the thermal model fits. However, both the coalescence approach as well as thermal fits are struggling to simultaneously describe the triton multiplicities measured with the STAR and ALICE experiment. The double ratio of tp/d 2 , in the coalescence approach, is found to be essentially energy and centrality independent for collisions of heavy nuclei at beam energies of E lab > 10A GeV. On the other hand the clear scaling of the d/p 2 and t/p 3 ratios with the systems volume is broken for peripheral collisions, where a canonical treatment and finite size effects become more important.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗