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DOE OSTI2025

Understanding X-ray bursts via direct measurements of ( α , p ) reactions

X-ray bursts, which are thermonuclear explosions on neutron stars accreting mass from companion stars, are the most frequent stellar explosions. To understand the mechanisms behind these bursts, astrophysical models need to incorporate the reaction rates of key nuclear reactions occurring in these stellar environments. This, however, presents significant challenges due to the typically small cross sections of these reactions and the experimental complexities associated with the use of low-intensity radioactive beams. Consequently, most of these reaction rates remain unknown. However, recent advancements in radioactive ion beam facilities and experimental techniques have opened new opportunities to measure these crucial astrophysical reactions. Furthermore, this work explores these advances and highlights recent measurements relevant to X-ray bursts.

Avila, M. L. [Argonne National Laboratory (ANL), A↗

DOE OSTI2023

Probing mass orderings in presence of a very light sterile neutrino in a liquid argon detector

Results from experiments like LSND and MiniBooNE hint towards the possible presence of an extra eV scale sterile neutrino. The addition of such a neutrino will significantly impact the standard three flavor neutrino oscillations. In particular, it can give rise to additional degeneracies due to additional sterile parameters. For an eV scale sterile neutrino, the cosmological constraints dictate that the sterile state is heavier than the three active states. However, for lower masses of sterile neutrinos, the sterile state can be lighter than one and/or more of the three states. In such cases, the mass ordering of the sterile neutrinos also becomes unknown, along with the mass ordering of the active states. In this paper, we explore the mass ordering sensitivity in the presence of a sterile neutrino assuming the mass squared difference |Δ 41 | to be in the range 10 –4 –1 eV 2 . We study (i) how the ordering of the active states, i.e. the determination of the sign of Δ 31 gets affected by the presence of a sterile neutrino in the above mass range, (ii) the possible determination of the sign of Δ 41 for Δ 41 in the range 10 –4 –0.1 eV 2 . This analysis is done in the context of a liquid argon detector using beam neutrinos traveling a distance of 1300 km and atmospheric neutrinos that propagate through a distance ranging from 10 – 10000 km, allowing resonant matter effects. Apart from presenting separate results from these sources, we also do a combined study and probe the synergy between these two in giving an enhanced sensitivity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Dynamic characterization and performance evaluation of a 10-kW power take-off with mechanical motion rectifier for wave energy conversion

The power take-off (PTO) is a key component for wave energy converters. In this paper, a compact PTO with mechanical motion rectification rated at 10 kW is designed and prototyped, and characterized. A piecewise nonlinear dynamic model is established to describe its unique dynamic property. A linear hydraulic actuator is adopted in lab testing to drive the prototype and the unknown parameters of the dynamic model are identified. Further verification shows that the model can predict the dynamic performance of the PTO well. The test results show that the mechanical motion rectifier-based PTO can achieve overall energy transfer efficiency as high as 65% in regular waves even when the generator is working below the rated electric load and speed. In the irregular wave test, the PTO achieved the overall energy transfer efficiency of 54%, and the peak-to-average ratio acquired during the test is 12.5.

16 TIDAL AND WAVE POWER↗

DOE OSTI2021

Potential environmental effects of deepwater floating offshore wind energy facilities

Over the last few decades, the offshore wind energy industry has expanded its scope from turbines mounted on fixed platforms driven into the seafloor and standing in less than 50 meters of water, to floating turbines moored in 120 meters of water, to prospecting the development of floating turbines moored in ~1000 meters of water. Since there are few prototype turbines and mooring systems of these deepwater, floating offshore wind energy facilities (OWFs) currently deployed, their effects on the marine environment are largely unknown. Using the available scientific literature concerning appropriate analogs, this study provides the first synthesis of the potential environmental effects of deepwater, floating OWFs during operation, as well as potential mitigation measures to some of the risks. Potential effects we identify and evaluate include changes to atmospheric and oceanic dynamics, electromagnetic fields, habitat alterations, noise, structural impediments, and changes to water quality that could affect a variety of marine species across trophic levels. Our synthesis suggests that many of these potential effects could be mitigated to pose a low risk to the marine environment if developers adopt appropriate mitigation strategies and best-practice protocols. This review takes the necessary first steps in summarizing the available information on the potential environmental effects of deepwater, floating OWFs and can serve as a valuable reference document for marine scientists and engineers, the energy industry, permitting agencies and regulators of the energy industry, project developers, and concerned stakeholders such as coastal residents, conservationists, and fisheries.

Farr, Hayley K.↗

DOE OSTI2023

Residential segregation and outdoor urban moist heat stress disparities in the United States

The combined impact of urbanization-induced warming and drying on large-scale heat stress disparities remains unknown, with multicity studies using satellite-derived land surface temperature as a proxy for these disparities. Here, using high-resolution urban-resolving numerical model simulations for 2014–2018, we find pervasive disparities in all-sky average maximum summertime air temperature and moist heat stress metrics across US cities, with higher outdoor heat stress exposure in poorer and primarily non-white census tracts. Ninety-four percent of the US urban population (228 million) live in cities where heat stress burdens the poor, with heat stress inequities between white and non-white populations strongly associated with residential segregation. Similarly, historically redlined neighborhoods show higher heat stress than their non-redlined counterparts, demonstrating how historical segregation relates to present-day environmental inequalities. Our results provide quantitative estimates of physiologically relevant heat stress disparities at the US national scale and highlight potential biases when using satellites as a proxy for these.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Spatially calibrating polycyclic aromatic hydrocarbons (PAHs) as proxies of area burned by vegetation fires: Insights from comparisons of historical data and sedimentary PAH fluxes

Many regions worldwide have experienced increasing wildfire activity in recent years and climate changes are predicted to result in more frequent and severe fires. Reconstruction of past fire activity offers paleoenvironmental context for modern and future burning. Pyrogenic polycyclic aromatic hydrocarbons (PAHs) have been increasingly used as a molecular biomarker for fire occurrence in the paleorecord and offer opportunity for nuanced reconstructions of fire characteristics. A suite of PAHs are produced during combustion, and the emission amount and assemblage is influenced by many variables including fuel type, fire temperature, and oxygen availability. Despite recent advances in understanding the controls and taphonomy of these biomass burning markers, the spatial scale of this proxy is unknown. In this paper, measurements of PAH fluxes preserved in a lake sediment archive from the Sierra Nevada, California were compared with a historical geographic information system dataset of area burned up to 150 km distance from the lake to determine the spatial scales for which these biomarkers are reliable proxies of burning. Comparisons of PAH fluxes with charcoal accumulation rates in the same sediments suggest that pyrogenic particulate transport modulates low to mid-molecular weight PAHs via adsorption. Overall, the results indicate that PAH records integrate a combination of spatial signals of area burned and measurement of individual PAHs may enable cross-scale paleofire reconstructions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Expression and characterization of spore coat Cot$\mathrm{H}$ kinases from the cellulosomes of anaerobic fungi ( Neocallimastigomycetes )

Anaerobic fungi (Neocallimastigomycetes) found in the guts of herbivores are biomass deconstruction specialists with a remarkable ability to extract sugars from recalcitrant plant material. Anaerobic fungi, as well as many species of anaerobic bacteria, deploy multi-enzyme complexes called cellulosomes, which modularly tether together hydrolytic enzymes, to accelerate biomass hydrolysis. While the majority of genomically encoded cellulosomal genes in Neocallimastigomycetes are biomass degrading enzymes, the second largest family of cellulosomal genes encode spore coat CotH domains, whose contribution to fungal cellulosome and/or cellular function is unknown. Structural bioinformatics of CotH proteins from the anaerobic fungus Piromyces finnis shows anaerobic fungal CotH domains conserve key ATP and Mg 2+ binding motifs from bacterial Bacillus CotH proteins known to act as protein kinases. Experimental characterization further demonstrates ATP hydrolysis activity in the presence and absence of substrate from two cellulosomal P. finnis CotH proteins when recombinantly produced in E. coli. These results present foundational evidence for CotH activity in anaerobic fungi and provide a path towards elucidating the functional contribution of this protein family to fungal cellulosome assembly and activity.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

First measurement in the Gamow window of a reaction for the γ-process in inverse kinematics: 76 Se(α,γ) 80 Kr

The p-nuclei are the few stable nuclei heavier than iron on the neutron-deficient side of the valley of stability that cannot be produced through astrophysical neutron-capture reactions. The limited experimental data on reactions through which the p-nuclei might be produced leaves the origin of their production largely unknown. This work presents the first cross section measurements of the 76 Se(α,γ) 80 Kr reaction. The rate of the time reversed reaction, 80 Kr(γ,α) 76 Se, is one of the most uncertain of possible reactions which can occur at the 80 Kr branching point on the ,-process photo-disintegration pathway. The reaction flow through 80 Kr will directly affect the final abundance of the p nuclide 78 Kr. Experimental cross sections at two astrophysically relevant energies are reported and compared to cross sections calculated using Hauser-Feshbach codes TALYS, NON-SMOKER, and SMARAGD. The success of these first (α,γ) cross section measurements performed in inverse kinematics in the energy region of the γ-process opens the door for future studies of reactions on radioactive γ-process nuclides.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Measurement of nuclear interaction cross sections towards neutron-skin thickness determination

The accuracy of reaction theories used to extract properties of exotic nuclei from scattering experiments is often unknown or not quantified, but of utmost importance when, e.g., constraining the equation of state of asymmetric nuclear matter from observables as the neutron-skin thickness. In order to test the Glauber multiple-scattering model, the total interaction cross section of 12 C on carbon targets was measured at initial beam energies of 400, 550, 650, 800, and 1000 MeV/nucleon. The measurements were performed during the first experiment of the newly constructed R 3 B (Reaction with Relativistic Radioactive Beams) experiment after the start of FAIR Phase-0 at the GSI/FAIR facility with beam energies of 400, 550, 650, 800, and 1000 MeV/nucleon. The combination of the large-acceptance dipole magnet GLAD and a newly designed and highly efficient Time-of-Flight detector enabled a precise transmission measurement with several target thicknesses for each initial beam energy with an experimental uncertainty of ±0.4%. A comparison with the Glauber model revealed a discrepancy of around 3.1% at higher beam energies, which will serve as a crucial baseline for the model-dependent uncertainty in future fragmentation experiments.

Astronomy & Astrophysics↗

DOE OSTI2024

Suppressed electric quadrupole collectivity in 49 Ti

Single-step Coulomb excitation of 46,48,49,50 Ti is presented. A complete set of E2 matrix elements for the quintuplet of states in 49 Ti, centred on the core excitation, was measured for the first time. A total of nine E2 matrix elements are reported, four of which were previously unknown. $^{49}_{22}$Ti 27 shows a 20% quenching in electric quadrupole transition strength as compared to its semi-magic $^{50}_{22}$Ti 28 neighbour. This 20% quenching, while empirically unprecedented, can be explained with a remarkably simple two-state mixing model, which is also consistent with other ground-state properties such as the magnetic dipole moment and electric quadrupole moment. A connection to nucleon transfer data and the quenching of single-particle strength is also demonstrated. The simplicity of the 49 Ti- 50 Ti pair (i.e., approximate single-j 0 7/2 valence space and isolation of yrast states from non-yrast states) provides a unique opportunity to disentangle otherwise competing effects in the ground-state properties of atomic nuclei, the emergence of collectivity, and the role of proton-neutron interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Transverse single-spin asymmetries in $γ$ SIDIS as a direct probe of quark-gluon-quark longitudinal momentum structure

Transverse single-spin asymmetries in the semi-inclusive deep-inelastic production of isolated photons ($\gamma$SIDIS), $A_{UT}^{\gamma {\rm SIDIS}}$, provide an unprecedented opportunity to extract the quark-gluon-quark correlators $F_{FT}(x,x')$ and $G_{FT}(x,x')$ point-by-point in their full support $x,x'$. We utilize realistic models for these functions, based on input from the Sivers transverse momentum dependent parton distribution function and imposing constraints from the $d_2$ matrix element calculated in lattice QCD, in order to provide numerical estimates for $A_{UT}^{\gamma {\rm SIDIS}}$ at the Electron-Ion Collider (EIC). We thoroughly explore the EIC phase space in order to isolate in which regions the asymmetry can be sizable, finding it can be as much as $10\%$ or larger for certain kinematics. Given that $F_{FT}(x,x')$ and $G_{FT}(x,x')$ are basically unknown, $A_{UT}^{\gamma {\rm SIDIS}}$ will be an important future measurement to learn about multi-parton correlations in the nucleon.

Electron-Ion Collider↗

DOE OSTI2021

Data trustworthiness signatures for nuclear reactor dynamics simulation

With the increased reliance on digitization in industrial control systems, the need for effective monitoring techniques has risen dramatically. Specifically, there is now a growing concern about the so-called false data injection (FDI) attacks. These attacks aim to alter the raw sensors’ data to cause malicious outcomes. Any serious FDI algorithm is based on an intimate knowledge of the system and its associated physics models, which renders conventional outlier/anomaly detection techniques almost obsolete in the face of such attacks. Thus, a critical need has emerged to develop a new class of defense methods that are capable of detecting FDI attacks under the assumption that the attacker has a strong familiarity with the system and its physics modeling. This class of defense methods are denoted by model-based defenses which are premised on the assumption that the attacker, while having a good understanding of the system, does not have full privileged access to all proprietary data and historical records of operation. However, (s)he is assumed to be capable of learning system behavior using self-learning techniques during an initial lie-in-wait period. To defend against this scenario, we propose a new model-based randomized window algorithm that searches time-series data for signatures that can serve as classifiers between normal and FDI scenarios. The classifiers are based on the correlations between the dominant degrees of freedom (DOFs) and the less-dominant DOFs (expected to be very sensitive to the system details that are unknown to the attacker). For demonstration, RELAP5 models are employed to calculate representative nuclear reactor behavior during a number of transient scenarios. Finally, falsified data are injected into the RELAP5-simulated behavior, and the proposed signature-identification algorithm is employed to detect the injected data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

GeN-ROM—An OpenFOAM®-based multiphysics reduced-order modeling framework for the analysis of Molten Salt Reactors

This work presents a projection-based multiphysics Model Order Reduction (MOR) framework for the analysis of nuclear systems and its application to parametric simulations of Molten Salt Reactors (MSR). The framework, named GeN-ROM, is developed using OpenFOAM® and employs a Proper Orthogonal Decomposition aided Reduced-Basis technique (POD-RB). It can be used to reduce steady-state and transient multiphysics problems involving parametric fluid dynamics, heat exchange, and neutronics phenomena. For the treatment of structural elements in the hydraulic systems, a porous medium approach has been adopted. The reduction process is data-driven and snapshot information is extracted via POD to learn the solution manifold and to build global spatial basis functions. At the data collection phase, GeN-ROM makes use of the solvers available in GeN-Foam, a similarly OpenFOAM®-based multiphysics framework developed for the analysis of nuclear reactors. The global bases are used both to approximate the solution fields and to project the full-order equations onto lower-dimensional subspaces, thus considerably reducing the number of unknowns in a numerical system. This reduction leads to significant computational speedups, which is ideal for multi-query applications such as uncertainty quantification or design optimization. The developed tool has been tested using a 2D multiphysics model of the Molten Salt Fast Reactor (MSFR) with steady-state and transient scenarios, with speedups on the order of 10 – 10 5 .

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Crystalline phase transitions and water-soluble complexes of copper(Ⅰ) 2-hydroxyethanethiolate

We report the coordination polymer copper(I) 2-hydroxyethanethiolate, (CuSCH 2 CH 2 OH) n , though insoluble in all common solvents, dissolved readily in basic aqueous solutions of the thiolate anion (HOCH 2 CH 2 S – ) of 2-mercaptoethanol to form a single species: the tetranuclear cluster [Cu 4 (μ-SCH 2 CH 2 OH) 6 ] 2– . From this solution were grown X-ray quality single crystals of copper(I) 2-hydroxyethanethiolate. This compound underwent a hitherto unknown crystal phase transition at ca. 6 °C, from point group P2 1 2 1 2 1 to Pna2 1 , with noticeable changes in the geometry of the Cu-S layer and in the orientation of the alkylthiolate side chains. When the bulky base tetrabutylammonium hydroxide was employed in the aqueous thiolate solution used to dissolve (CuSCH 2 CH 2 OH) n , the water-soluble polynuclear copper(I) complex bis(tetrabutylammonium) hexakis(μ-2-hydroxyethanethiolato) tetracuprate(I), [(C 4 H 9 ) 4 N] 2 [Cu 4 (μ-SCH 2 CH 2 OH) 6 ], could be isolated as X-ray quality crystals. Structural characterization of this complex revealed a tetrahedral arrangement of copper(I) centers with thiolates bridging the edges of the tetrahedra. On standing, this complex degraded to a larger polynuclear Cu(I) sulfide cluster.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Extended use of face masks during the COVID-19 pandemic - Thermal conditioning and spray-on surface disinfection

The current COVID-19 pandemic has resulted in globally constrained supplies for face masks and personal protective equipment (PPE). Production capacity is limited in many countries and the future course of the pandemic will likely continue with shortages for high quality masks and PPE in the foreseeable future. Therefore, expectations are that mask reuse, extended wear and similar approaches will enhance the availability of personal protective measures. Repeated thermal disinfection could be an important option and likely easier implemented in some situations, at least on the small scale, than UV illumination, irradiation or hydrogen peroxide vapor exposure. In this paper, an overview on thermal responses and ongoing filtration performance of multiple face mask types is provided. Most masks have adequate material properties to survive a few cycles (i.e. 30 min disinfection steps) of thermal exposure in the 75°C regime. Some are more easily affected, as seen by the fusing of plastic liner or warping, given that preferred conditioning temperatures are near the softening point for some of the plastics and fibers used in these masks. Hence adequate temperature control is equally important. As guidance, disinfectants sprayed via dilute solutions maintain a surface presence over extended time at 25 and 37°C. Some spray-on alcohol-based solutions containing disinfectants were gently applied to the top surface of masks. Neither moderate thermal aging (less than 24 h at 80 and 95°C) nor gentle application of surface disinfectant sprays resulted in measurable loss of mask filter performance. Subject to bio-medical concurrence (additional checks for virus kill efficiency) and the use of low risk non-toxic disinfectants, such strategies, either individually or combined, by offering additional anti-viral properties or short term refreshing, may complement reuse options of professional masks or the now ubiquitous custom-made face masks with their often unknown filtration effectiveness.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Hygrothermal aging effects on polyimide and acrylate-based adhesive materials in high-performance flat-flex cable assemblies

Flat-flex assemblies are widely used across a diverse range of technologies, including consumer electronics, automotive systems, aerospace and defense applications, and medical devices, due to their compact form factor and flexibility. However, environmental stressors like temperature and humidity are known to degrade performance over time, though the main mechanisms for degradation remain unknown. Here, in this work, we examined the aging behavior of copper/polyimide/adhesive laminate systems under varying temperature and humidity conditions, focusing on material degradation and its effects on mechanical and dielectric properties. Results show that peel strength and breakdown voltage decrease with exposure time, temperature, and humidity; spectroscopic characterization revealed that the adhesive, and not the polyimide, is the weak link in the material stack-up. The adhesive, identified as a butyl acrylate-acrylonitrile (BA-AN) copolymer, exhibited age-related spectral changes that correlated with exposure severity and duration. Hydrolysis at BA ester and AN nitrile groups was identified as the primary degradation mechanism, producing amides, acids, and alcohols. We developed a mechanistic model that connects kinetic parameters for BA-AN spectral band decay to peel strength and breakdown voltage, and implicates hydrolysis at the AN moiety, not BA, in performance decrements. Modeling predictions at ambient conditions indicate faster decline in peel strength than dielectric strength at early times, followed by plateauing of both properties at longer times. These findings provide critical insights into laminate aging mechanisms and highlight the importance of addressing BA-AN degradation to improve the long-term reliability of these systems in high-humidity environments.

organic↗

DOE OSTI2021

Towards grounding nuclear physics in QCD

Exascale computing could soon enable a predictive theory of nuclear structure and reactions rooted in the Standard Model, with quantifiable and systematically improvable uncertainties. Such a predictive theory will help exploit experiments that use nucleons and nuclei as laboratories for testing the Standard Model and its limitations. Examples include direct dark matter detection, neutrinoless double beta decay, and searches for permanent electric dipole moments of the neutron and atoms. It will also help connect QCD to the properties of cold neutron stars and hot supernova cores. We discuss how a quantitative bridge between QCD and the properties of nuclei and nuclear matter will require a synthesis of lattice QCD (especially as applied to two- and three- nucleon interactions), effective field theory, and ab initio methods for solving the nuclear many-body problem. While there are significant challenges that must be addressed in developing this triad of theoretical tools, the rapid advance of computing is accelerating progress. In particular, we focus this review on the anticipated advances from lattice QCD and how these advances will impact few-body effective theories of nuclear physics by providing critical input, such as constraints on unknown low-energy constants of the effective (field) theories. We also review particular challenges that must be overcome for the successful application of lattice QCD for low-energy nuclear physics. We describe progress in developing few-body effective (field) theories of nuclear physics, with an emphasis on HOBET, a non-relativistic effective theory of nuclear physics, which is less common in the literature. We use the examples of neutrinoless double beta decay and the nuclear-matter equation of state to illustrate how the coupling of lattice QCD to effective theory might impact our understanding of symmetries and exotic astrophysical environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Robust scalable initialization for Bayesian variational inference with multi-modal Laplace approximations

Predictive modeling typically relies on Bayesian model calibration to provide uncertainty quantification. Variational inference utilizing fully independent (“mean-field”) Gaussian distributions are often used as approximate probability density functions. This simplification is attractive since the number of variational parameters grows only linearly with the number of unknown model parameters. However, the resulting diagonal covariance structure and unimodal behavior can be too restrictive to provide useful approximations of intractable Bayesian posteriors that exhibit highly non-Gaussian behavior, including multimodality. High-fidelity surrogate posteriors for these problems can be obtained by considering the family of Gaussian mixtures. Gaussian mixtures are capable of capturing multiple modes and approximating any distribution to an arbitrary degree of accuracy, while maintaining some analytical tractability. Unfortunately, variational inference using Gaussian mixtures with full-covariance structures suffers from a quadratic growth in variational parameters with the number of model parameters. The existence of multiple local minima due to strong nonconvex trends in the loss functions often associated with variational inference present additional complications, These challenges motivate the need for robust initialization procedures to improve the performance and computational scalability of variational inference with mixture models. In this work, we propose a method for constructing an initial Gaussian mixture model approximation that can be used to warm-start the iterative solvers for variational inference. The procedure begins with a global optimization stage in model parameter space. In this step, local gradient-based optimization, globalized through multistart, is used to determine a set of local maxima, which we take to approximate the mixture component centers. Around each mode, a local Gaussian approximation is constructed via the Laplace approximation. Finally, the mixture weights are determined through constrained least squares regression. The robustness and scalability of the proposed methodology is demonstrated through application to an ensemble of synthetic tests using high-dimensional, multimodal probability density functions. Here, the practical aspects of the approach are demonstrated with inversion problems in structural dynamics.

97 MATHEMATICS AND COMPUTING↗