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Determining Stellar Elemental Abundances from DESI Spectra with the Data-driven Payne

Abstract Stellar abundances for a large number of stars provide key information for the study of Galactic formation history. Large spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI) and LAMOST take median-to-low-resolution (R≲ 5000) spectra in the full optical wavelength range for millions of stars. However, the line-blending effect in these spectra causes great challenges for elemental abundance determination. Here we employDD-Payne, a data-driven method regularized by differential spectra from stellar physical models, to the DESI early data release spectra for stellar abundance determination. Our implementation delivers 15 labels, including effective temperatureT eff , surface gravity log g , microturbulence velocityv mic , and the abundances for 12 individual elements, namely C, N, O, Mg, Al, Si, Ca, Ti, Cr, Mn, Fe, and Ni. Given a spectral signal-to-noise ratio of 100 per pixel, the internal precisions of the label estimates are about 20 K forT eff , 0.05 dex for log g , and 0.05 dex for most elemental abundances. These results agree with the theoretical limits from the Crámer–Rao bound calculation within a factor of 2. The majority of the accreted halo stars contributed by the Gaia–Enceladus–Sausage are discernible from the disk and in situ halo populations in the resultant [Mg/Fe]–[Fe/H] and [Al/Fe]–[Fe/H] abundance spaces. We also provide distance and orbital parameters for the sample stars, which spread over a distance out to ∼100 kpc. The DESI sample has a significantly higher fraction of distant (or metal-poor) stars than the other existing spectroscopic surveys, making it a powerful data set for studying the Galactic outskirts. The catalog is publicly available.

Astronomy & Astrophysics

Comparing the fluorination of Pb+ and Po+: insights into p-block relativistic effects for superheavy elements

It is expected that the chemical properties of the heaviest of the superheavy elements (SHEs, = 113 – 118) do not align with what is suggested by their current positions on the periodic table. Specifically, the onset of significant relativistic effects, including increased spin–orbit splitting of the p-orbitals may lead to enhanced stability of low-oxidation states. Notably, it is predicted that flerovium ( = 114) may exhibit pseudo-noble gas behavior from a electron configuration that acts as an ‘inert pair’. Even though it is expected that the – splitting becomes pronounced toward the end of the p-block’s sixth row, there is currently limited experimental evidence to confirm its extent or impact. Here, the production of gas-phase lead ( = 82) and polonium ( = 84) fluoride cations (PbF and PoF ) were compared to elucidate differences in accessible oxidation states. The PoF and PbF species were produced and identified with the FIONA spectrometer at the Lawrence Berkeley National Laboratory 88-Inch Cylctron Facility. Polonium showed notably different fluorination chemistry than lead, producing PoF and PoF as primary products compared to lead’s PbF and PbF . The distribution of PoF products observed offer insights as to the role of spin–orbit splitting for polonium. Similar studies of superheavy elements would elucidate the accessibility of their low-oxidation states as well as to inform chemical predictions for eighth-row elements not yet discovered.

Pore, Jennifer L [Nuclear Science Division, Lawren

Collapse of magnetized white dwarfs as site of heavy-element formation and kilonova signal

We present the first end-to-end calculation connecting the accretion-induced collapse (AIC) of a magnetized, rapidly rotating white dwarf to observable kilonova signatures, combining two-dimensional (2D) general-relativistic neutrino-magnetohydrodynamic simulations, followed by radiation hydrodynamics with in-situ nuclear network and 2D Monte Carlo radiative transfer with spatially resolved heating rates. Unlike all previous unmagnetized AIC models – which predicted proton-rich, $^{56}$Ni-dominated ejecta – strong magnetic fields eject ${\approx }\, 0.2\, \mathrm{ M}_\odot$ of neutron-rich material ($\langle Y_e \rangle \sim 0.24$) on dynamical time-scales, before neutrino irradiation can raise the electron fraction, enabling strong r-process nucleosynthesis up to and beyond the third peak. The resulting kilonova is lanthanide-rich ($X_{\rm lan} \approx 8~{{\ \rm per\ cent}}$) and dominated by near-infrared emission. We compute synthetic light curves in the Large Synoptic Survey Telescope and J ames Webb Space Telescope bands and find striking agreement, without parameter tuning, between the observations of AT 2023vfi/GRB 230307A and our broadband light curves for polar viewing angles. These results establish magnetized AIC as a viable channel for heavy r-process element production and a compelling progenitor candidate for long-duration gamma-ray bursts with kilonova signatures.

MHD

Emissivity measurements of CuCrZr alloy

The Facility for Rare Isotope Beams (FRIB) heavy-ion accelerator, in user operation since 2022, produces rare isotope beams via interactions of high-intensity stable ion beams with a graphite production target. Approximately 20–40% of the primary beam power is deposited in the target, while the remaining 60–80% is absorbed by the beam dump. The minichannel beam dump (MCBD), currently operated at 20 kW and designed for operation up to 50 kW, uses CuCrZr alloy absorber plates. Thermal validation and thermal cycling tests of the MCBD were conducted at the Applied Research Laboratory (ARL) at Pennsylvania State University. Temperature measurements were obtained from an infrared (IR) camera. Since accurate temperature determination requires reliable emissivity values, the emissivity of CuCrZr was measured using the IR camera validated against thermocouple reference temperatures up to approximately 650 °C. The measurements were conducted under a vacuum level of approximately 10 -5 torr to minimize emissivity variations due to surface oxidation. The emissivity of CuCrZr was determined to be 0.057 ± 0.009 using a constant fit to the measured data over the surface temperature range from 100–650 °C.

Accelerator Subsystems and Technologies

X-ray tomography of damage dynamics in advanced materials using a laser wakefield accelerator

Additively manufactured (AM) metals offer the potential for customizable, cost-effective components, but qualification and certification are crucial. Key to this process is understanding pore dynamics under stress, typically analyzed using micro-computed tomography. This study introduces laboratory-scale “betatron” x-rays from laser wakefield acceleration as a high-throughput alternative for x-ray tomography of advanced materials, such as AM AlSi10Mg alloys. Coupled with 3D finite element modeling, this method provides detailed insights into stress-porosity interactions. The approach delivers high-resolution scans, revealing that pore shape and local triaxiality significantly influence fracture dynamics, supporting advanced material characterization. This work also demonstrates the potential and versatility of laser-betatron x-ray μCT for generating large datasets to accelerate our understanding of the stochastic, process-specific nature of pore formation in AM alloys.

Senthilkumaran, Vigneshvar

First measurement of polarized spin-density matrix elements and differential cross sections dσ/dt in ω photoproduction off the proton for 2.7 < Eγ < 5.2 GeV using CLAS at Jefferson Lab

We report on the differential cross sections dσ/dt, the unpolarized spin-density matrix elements ρ 00 0 , ρ 1 − 1 0 , Re ρ 10 0 , and the first extraction of the polarized elements Im ρ 10 3 , Im ρ 1 − 1 3 for the reaction γp → pω using the CLAS spectrometer at Jefferson Laboratory. The ω mesons were detected in their dominant charged decay mode, ω → π + π − π 0 , and all t-dependent results are presented in a fine binning for incident photon energies between 2.73 and 5.16 GeV (corresponding to the center-of-mass energy range W ∈ [ 2.45, 3.25 ] GeV). All matrix elements are first measurements for − t > 0.6 GeV2. Moreover, differential cross sections dσ/d(cos Θ c . m . ω ) and the corresponding angle-dependent unpolarized spin-density matrix elements in the Adair frame are presented for the incident photon energy range 1.56–3.80 GeV (corresponding to W ∈ [ 1.95, 2.83 ] GeV). These new ω photoproduction data are consistent with earlier CLAS results but extend the energy range well beyond the nucleon resonance region into the Regge regime. The comparison with Regge-theory-based model predictions shows that the new data impose more stringent constraints on our understanding of ω photoproduction.

Hu, T.

SAVY-4000 Finite-Element Drop Test Analysis

PFE Auxiliary Systems conducted drop testing on SAVY-4000 containers to evaluate structural response under 12-foot drop conditions. In support of that effort, a finite-element modeling capability was developed to simulate drop response across multiple container sizes and impact orientations. The purpose of this work was to provide a consistent analysis framework that could support interpretation of testing, compare response trends across multiple configurations, and generate quantities of interest for later comparison with experimental data. More broadly, the analysis and testing were intended to assess whether the containers continued to perform their primary function after a 12-foot drop, namely maintaining structural integrity and containment of the contents. The modeling approach combined an implicit preload analysis with an explicit drop simulation so that each drop event began from a mechanically realistic assembled condition, including compression of the silicone O-ring. Separate models were developed for 2-quart, 5-quart, 12-quart, and 10-gallon containers. The results were evaluated in terms of strain-gauge response, collar-lid gap behavior, and accumulated plastic strain. In addition, parametric studies were performed on the 2-quart container to assess sensitivity to O-ring stiffness, friction, canister thickness, geometry tolerance, and mesh density. The simulations showed that predicted drop responses depended strongly on both container size and drop orientation. Gap metrics identified cases in which the predicted collar-lid opening exceeded the nominal O-ring cross-section threshold, while plastic strain metrics identified localized regions of elevated permanent deformation. Parametric studies showed that the predicted response was especially sensitive to the assumed O-ring stiffness and contact friction, while the geometry tolerance study produced smaller changes in the cases examined. The main value of this work was that it established a repeatable modeling and simulation workflow to support drop-test implementation, evaluate effects of future configuration changes, and understand modeling assumptions that most influenced predicted response. At the current stage, the results were viewed as preliminary model predictions rather than validated predictions. The next step would be to compare drop-test data to the model so that predictive values of the workflow could be refined and used with greater confidence to assess whether the containers maintained structural integrity and containment of the contents after a 12-foot drop.

42 ENGINEERING

Three-dimensional nucleation and growth of deformation twins in magnesium

At two-thirds the weight of aluminum, magnesium alloys have the potential to reduce the fuel consumption of transportation vehicles. These advancements depend on our ability to optimize the desirable versus undesirable effects of deformation twins, which are three-dimensional (3D) microstructural domains that form under mechanical stresses. Previously only characterized through surface or thin-film measurements, we here present 3D in situ characterization of deformation twinning inside an embedded grain over mesoscopic fields of view using dark-field x-ray microscopy supported by crystal plasticity finite element analysis. The results revealed the role of triple junctions on twin nucleation and the sequence and irregularity of twin growth and showed that twin-grain junctions, twin-twin junctions, and twin boundaries were the sites of localized dislocation accumulation.

Lee, Sangwon [Univ. of Michigan, Ann Arbor, MI (Un

Four Years of Type Ia Supernovae Observed by TESS: Early-time Light-curve Shapes and Constraints on Companion Interaction Models

Abstract We present 307 type Ia supernova (SN) light curves from the first 4 yr of the Transiting Exoplanet Survey Satellite mission. We use this sample to characterize the shapes of the early-time light curves, measure the rise times from first light to peak, and search for companion star interactions. Using simulations, we show that light curves must have noise <10% of the peak flux to avoid biases in the early-time light-curve shape, restricting our quantitative analysis to 74 light curves. We find that the mean power-law index t β 1 of the early-time light curves isβ 1 = 1.93 ± 0.57, and the mean rise time to peak is 15.7 ± 3.5 days. The underlying population distribution forβ 1 may instead consist of a Gaussian component with mean 2.29, width 0.34, and a long tail extending to values less than 1.0. We find that the data can rarely distinguish between models with and without companion interaction models. Nevertheless, we find three high-quality light curves that tentatively prefer the addition of a companion interaction model, but the statistical evidence for the companion interactions is not robust. We also find two SNe that disfavor the addition of a companion interaction model to a curved power-law model. Taking the 74 SNe together, we calculate 3σupper limits on the presence of companion signatures to control for orientation effects that can hide companions in individual light curves. Our results rule out common progenitor systems with companions having Roche lobe radii >31R ⊙ (separations >5.7 × 10 12 cm, 99.9% confidence level) and disfavor companions having Roche lobe radii >10R ⊙ (separations >1.9 × 10 12 cm, 95% confidence level). Lastly, we discuss the implications of our results for the intrinsic fraction of single degenerate progenitor systems.

Astronomy & Astrophysics

Systematic Construction of Time-Dependent Hamiltonians for Microwave-Driven Josephson Circuits

Time-dependent electromagnetic drives are fundamental for controlling complex quantum systems, including superconducting Josephson circuits. In these devices, accurate time-dependent Hamiltonian models are imperative for predicting their dynamics and designing high-fidelity quantum operations. Existing numerical methods, such as black-box quantization (BBQ) and energy-participation ratio (EPR), excel at modeling the static Hamiltonians of Josephson circuits. However, these techniques do not fully capture the behavior of driven circuits stimulated by external microwave drives, nor do they include a generalized approach to account for the inevitable noise and dissipation that enter through microwave ports. Here, we introduce numerical techniques that leverage classical microwave simulations, efficiently executable in finite-element solvers, to obtain the time-dependent Hamiltonian of microwave-driven superconducting circuits with arbitrary geometries under charge, flux, or mixed electromagnetic modulation. Importantly, our techniques do not rely on a lumped-element description of the superconducting circuit, in contrast to previous approaches to tackling this problem. We demonstrate the versatility of our approach by characterizing the driven properties of realistic circuit devices in complex electromagnetic environments, including coherent dynamics due to charge and flux modulation, as well as drive-induced relaxation and dephasing. Our techniques offer a powerful toolbox for optimizing circuit designs and advancing practical applications in superconducting quantum computing.

Lu, Yao [Yale U.; Yale U. (main); Fermilab] (ORCID

Passive Confirmation of the Presence Of High-Explosive Material Via Neutron Transmission Spectroscopy

The goal of this project was to explore a novel approach for identifying presence and potential types of high explosives (HE) in treaty-controlled items with passive neutron sources by using passive neutron transmission spectroscopy. We predominantly look to measure relative elemental abundance of Carbon, Hydrogen, Oxygen, and Nitrogen (CHON) since most relevant materials are certain mix of these elements, as shown in Table 1. Previously, most studies exploring potential identification of CHON elemental content of targets in the vicinity of passive neutron source were focused solely on gamma spectroscopy using high resolution gamma detectors. Using neutron transmission spectroscopy with pulse-shape discrimination (PSD) capable organic scintillators is not only a novel idea in of itself, but arguably necessary for accurate identification of the CHON elemental content of an interrogated target. While high resolution gamma spectroscopy in principle can determine a presence of hydrogen and nitrogen, it is effectively blind to a quantitatively measuring areal densities of C, O. The initially proposed approach, described in detail in the project proposal, was to leverage previous Monte Carlo study on neutron transmission spectroscopy using slab shaped target interrogated with well-collimated (“pencil”) neutron beam. In this study, a simulated test CO 2 target was interrogated by a pencil neutron beam and transmitted neutron spectra were measured using PSD capable organic scintillator using MLEM based unfolding technique. To establish relative elemental content of carbon and oxygen, the unfolded neutron spectrum was fit with a parametrized combination of their respective elemental spectral templates. The individual spectral template was calculated by convoluting ENDF neutron crosssection with the known resolution of the PSD detector used in the study. This approach in the studied configuration successfully quantitatively established relative elemental composition of carbon and oxygen.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

Cation-Diffusive Carbon Interlayers Stabilize Na Metal and Double the Current in Na-S Redox-Flow Batteries for Grid-Scale Energy Storage

The sodium-sulfur nonaqueous redox-flow batteries (Na-S NARFBs) using earth-abundant elements are highly attractive due to the low material cost and improved energy density for grid-scale energy storage. However, the low current performance, poor Na0/Na+ redox kinetics, and Na dendrite growth pose severe challenges. We introduce cation-diffusive layers (CDLs): thin and Na+ affinitive interlayers at the Na anode that direct Na+ transport and stabilize Na deposition. Benchmarking three archetypal materials—carbon paper (CP), glass microfiber paper (GF), and foam—across Na-Na and Na-Cu, and Na-S cells identifies CP as the optimum. CP reduces symmetric cell overpotential by more than 70%, achieves 98% Na plating-stripping efficiency, and doubles the Na-S cell current density from 0.5 to 1.0 mA cm−2 without sacrificing capacity or efficiency. Ex situ electrochemical and SEM/XPS analysis, combined with molecular dynamics (MD) studies, reveal that electron-rich carbon fibers disperse supporting salt aggregates, enrich near-surface Na+ density, and create ion transport pathways for fast Na0/Na+ exchange while mitigating membrane degradation. Because of the ion-centric mechanism, CDLs can be generalized to other metal-anode designs. Further, this work establishes CDL design rules—cationic affinity and appropriate micro/nanostructure—as a simple, scalable route to high-current, durable metal-anode flow batteries.

Wu, Wenda [ORNL] (ORCID:000900033307687X)

Toward Fully Soft and Multifunctional Shape Sensing via Optical Waveguide Arrays

For soft bodies, surface deformation and pressure provide proprioceptive and exteroceptive information, including body configuration, body compliance, and external forces. We develop a sheet sensor with a fully soft sensing surface that provides surface shape reconstruction using optical waveguide arrays. The waveguides are fabricated to achieve a tunable linear response to bi‐directional bending curvature, and the waveguide arrays are configured to differentiate between ambiguous shapes. We characterize the waveguide performance, relating curvature sensitivity to the core's surface roughness. Synergy of waveguide responses reduces the number of sensing elements required and achieves damage resilience. Using waveguide sensitivity to pressure, we also demonstrate feasibility for exteroception. We demonstrate the multifunctional sensing capability by wrapping the sheet around an upper arm, showcasing joint motion and external force sensing. Integrated into or applied onto surfaces of robotic or living systems, this design can be implemented in applications such as virtual reality, teleoperation, physical therapy, and soft robotics.

Yu, Qifan [Department of Mechanical Engineering Ma

Uncertainty quantification for competing failure mechanisms in unidirectionally reinforced carbon–carbon composites

Microstructure-informed finite element models play a key role in the carbon–carbon composite design process. Variability in manufacturing process parameters and experimental limitations introduce model parameter uncertainty. This study quantifies the effect of model parameter uncertainty on transverse tensile fracture behavior and proposes a methodology to predict the failure mode based on competing microscale damage mechanisms. Finite element simulations incorporate fiber–matrix interface debonding with cohesive zones and matrix damage with a smeared crack band approach in a unidirectional carbon–carbon composite. Results from a variance-based global sensitivity analysis identifies interfacial and matrix damage parameters as the primary source of variability in fracture behavior. Sobol’ indices indicate that matrix and cohesive zone strengths contribute 94% of the variance in the effective ultimate stress. A local analysis elucidates the relationship between these constituent strength parameters and failure mode by estimating the probability of cohesive, matrix, and mixed-mode dominated failure. Based on the results for 4000 simulations, 93% exhibit mixed-mode or interfacial dominated failure, which underscores the crucial role of fiber–matrix interface debonding in the transverse tensile failure of carbon–carbon composites. These uncertainty quantification results facilitate more efficient model calibration and provide a framework for microstructure-informed failure predictions in the face of manufacturing-induced uncertainty.

36 MATERIALS SCIENCE

Investigating permafrost carbon dynamics in Alaska with artificial intelligence

Abstract Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land–atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integratesin-situmeasurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics—active layer thickness (ALT), carbon dioxide flux (CO 2 ), and methane flux (CH 4 )—with high precision and minimal loss (i.e. ALT RMSE : 1.327 cm [1969–2022]; CO 2 RMSE : 0.697µmolCO 2 m −2 s −1 [2003–2021]; CH 4 RMSE : 0.715 nmolCH 4 m −2 s −1 [2011–2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.

Environmental Sciences & Ecology

Statistical Study of Energy Dissipation in Magnetic Structures During Turbulent Reconnection in the Earth's Magnetotail

Magnetic reconnection is a ubiquitous plasma phenomenon that plays a critical role in particle heating and energization. During reconnection, the topology of magnetic field rearranges, depositing energy into the surrounding plasma through bulk flow, thermal heating, or non-thermal particle acceleration. While the pathways of this transformation from magnetic energy into kinetic have been studied extensively in recent years through theoretical or case-by-case observations, comprehensive statistical studies remain limited. In this paper, we present a statistical investigation using data from the Magnetospheric Multiscale (MMS) mission, and detail the particle energization mechanisms in magnetic structures found near reconnecting regions in turbulent Earth's magnetotail. We find that electrons with motion perpendicular to the magnetic field dominate $\vec{j}$ ⋅ $\vec{E}$ dissipation. In contrast to the conventional picture of unidirectional energy transfer to particles by laminar two-dimensional (2D) reconnection, we find that energy exchange within magnetic structures during turbulent reconnection tends to be bidirectional with only a small positive bias from electromagnetic fields to particles. Specific electron energization mechanisms are quantified, including those due to parallel electric field, Fermi energization from curvature drift, betatron heating from magnetic field inhomogeneity, and polarization drift.

Wang, Rachel [Princeton University, NJ (United Sta

Selective depolymerization of polyolefin copolymer via high-entropy alloy catalyzed pyrolysis in a double-layered ultrafast heating reactor

Chemical recycling of polyolefin copolymers (PCPs) is essential for mitigating plastic pollution, yet achieving selective depolymerization into C 2 –C 3 monomers at high productivity remains challenging. Here, we introduce a double-layered ultrafast heating reactor (DUHR) that integrates Joule heating with a high-entropy alloy (HEA) catalyst composed of near-equimolar Co, Cu, Fe, Mn, and Ni. We achieve highly selective depolymerization of PCP into ethylene and propylene, yielding a 70% non-condensable fraction. Significant aromatic fractions form via radical-driven pathways—a behavior distinct from conventional externally heated pyrolyzers—highlighting DUHR's ability to generate reactive species and modulate reaction pathways. Furthermore, these findings demonstrate an effective strategy for chemical recycling of real-world plastic waste for polyolefin circularity and sustainable resource recovery.

Chemical recycling