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172 records · Page 6

Nine lensed quasars and quasar pairs discovered through spatially extended variability in Pan-STARRS

We present the proof of concept of a method for finding strongly lensed quasars using their spatially extended photometric variability through difference imaging in cadenced imaging survey data. We applied the method to Pan-STARRS, starting with an initial selection of 14 107Gaiamultiplets with quasar-like infrared colours from WISE. We identified 229 candidates showing notable spatially extended variability during the Pan-STARRS survey period. These include 20 known lenses and an additional 12 promising candidates for which we obtained long-slit spectroscopy follow-up. This process resulted in the confirmation of four doubly lensed quasars, four unclassified quasar pairs, and one projected quasar pair. Only three are pairs of stars or quasar+star projections. The false-positive rate accordingly is 25%. The lens separations are between 0.81″ and 1.24″, and the source redshifts lie betweenz = 1.47 andz = 2.46. Three of the unclassified quasar pairs are promising dual-quasar candidates with separations ranging from 6.6 to 9.3 kpc. We expect that this technique is a particularly efficient way to select lensed variables in the upcomingRubin-LSST, which will be crucial given the expected limitations for spectroscopic follow-up.

Astronomy & Astrophysics

Hydrogen diffusion induced dislocation transformations in a nickel superalloy

The diffusion of hydrogen in metals and alloys induces embrittlement that can adversely affect the structural properties. We examine the adsorption and diffusion of hydrogen in Inconel-718 (IN-718), and scrutinize the ensuing effects on the dislocation behavior in the alloy to elucidate the fundamental mechanisms of hydrogen-microstructure interactions from classical molecular simulations. Hydrogen adsorption increases with time until the surface saturates, while hydrogen diffusion exhibits strong temperature dependence, with diffusion coefficients converging above 1300 K regardless of the initial hydrogen concentration in the alloy. The diffusion in IN-718 is significantly sluggish than in pure Ni, Fe, or Cr, and is strongly impacted by hydrogen concentrations, resulting in an order of magnitude higher diffusion coefficient for hydrogen (10-14 m2/s relative to 10-15 m2/s) at high concentrations, especially below 600 K. Hydrogen diffusion coefficient varies from 10-12 to 10-15 m2/s in IN-718 depending on temperature (500–1400 K). More critically, our results reveal that increasing hydrogen concentration induces microstructural changes in the alloy, transforming perfect dislocations into stair-rods and Shockley partials, with higher temperatures favoring the latter. The results are significant for hydrogen fuel applications to gain insights into the materials chemistry for designing safer and more efficient propulsion systems, particularly in high-performance environments related to controlled hydrogen combustion applications.

Banerjee, Tanumoy

Nanohybrid of Cu2O-Ti3C2Tx as a Silver-Free MXene Sorbent for Iodine Gas Capture from Nuclear Waste

The capture of volatile radioiodine from nuclear fuel reprocessing off-gas streams remains a critical challenge due to the high volatility, long half-life of 129I, and biological uptake of iodide from the environment. Although silver-based sorbents provide strong iodine chemisorption, their high cost and regulatory classification as mixed radioactive-hazardous waste motivate the development of alternative materials. Here, we report a silver-free Cu2O-Ti3C2Tx MXene hybrid for iodine gas capture at 150 °C. Structural and compositional analyses confirm the formation of Cu2O nanoparticles on Ti3C2Tx nanosheets and their subsequent conversion to thermodynamically stable CuI upon static iodine gas exposure, achieving an iodine mass loading of up to 1115 mg/g. These results demonstrate the potential of Cu2O-Ti3C2Tx MXene as a copper-based alternative to silver sorbents for elevated-temperature iodine gas capture.

iodine gas capture

Crack‐Free Single‐Crystalline LiNiO 2 for High Energy Density All‐Solid‐State Batteries

Abstract Single‐crystalline layered oxide (LiNi 1‐ x ‐ y Mn x Co y O 2 ) cathodes have been found to exhibit exceptional electrochemical properties when coupled with various inorganic solid electrolytes (ISEs) in all‐solid‐state batteries (ASSBs). Their advantages stem from the robust morphological integrity with the absence of grain boundaries and the high electrochemical oxidative stability. Here, ASSBs featuring single‐crystalline LiNiO 2 (LNO) with the highest Ni content are reported, offering a high theoretical specific capacity of 275 mAh g ‐1 alongside a high average discharge voltage (3.7 V vs Li + /Li). Through a careful investigation, it is demonstrated that micron‐sized single‐crystalline LNO (µSC‐LNO) composite cathodes with a halide ISE exhibit a high initial discharge capacity of 205 mAh g ‐1 with an outstanding cycle performance over 200 cycles in room‐temperature ASSBs. The significance of engineering parameters is emphasized, such as particle size and specific density, in promoting a homogeneous and fast Li + transport within the composite cathodes. Furthermore, the formation of undesirable interphase between the halide ISE in the cathode and sulfide ISE separator is elucidated, which may be a critical factor impeding long‐term cyclability of ASSBs. This work provides insights into the design of composite cathodes for high‐energy‐density ASSBs.

Chemistry

Purpose, Design, and Analysis of the NSTX-U Centerstack Casing Lateral Support Shims

The National Spherical Torus Experiment Upgrade (NSTX-U) centerstack casing surrounds the central magnet core of NSTXU. It provides the inner vacuum boundary of the plasma chamber and supports the radially inboard plasma facing components lining the plasma chamber. The casing is supported like a cantilever, fixed at the lower flange by a connection to the TF Bundle through a G-10 ring. It is flexibly supported at the top by bellows, and insulated shims intended to react the largest part of the inventory of the disruption loads at the upper support, thereby protecting the upper and lower connections from excessive loads. A large part of the qualification of the casing and tiles requires addressing and quantifying disruption loads. These have been estimated based on extensions of the behavior of NSTX during its run period roughly 15 years ago. Structural qualification of the Upgrade used these estimates of the loading as input to calculations to demonstrate adequacy for a “most probable” disruption. The estimates are included in a requirements document to guide conservative design of all components loaded by disruptions. However, the changes made for the upgrade made the extrapolation of disruption behavior uncertain. Disruptions include axisymmetric loading from axisymmetric currents induced in the vessel shells. In addition, more complex currents called Halo currents are a result of plasma poloidal currents impinging on the casing. The halo currents add another layer of uncertain behavior and net lateral loading to the casing. As a result, NSTX-U is equipped with a number of instruments intended to assess the nature and severity of disruptions. The casing shims are required for lateral support of the casing, but these have also been converted to load cells to provide another measure of the magnitude of symmetric and asymmetric loading. Some of the logic in the development of the requirements document are presented. Electromagnetic analysis of axisymmetric and halo loading is described. Global simulations of the casing transient dynamic response, and local analysis and testing of the shim/load cell are included. The shim load cells and other instrumentation will be an important guide in planning NSTX-U experiments beyond its next run period expected in late 2026 or early 2027.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Technoeconomic Analysis Round Robin of a Retrofit of the Ivanpah Concentrating Solar Plant with a Molten-Salt System with Thermal Energy Storage

While the fidelity of technoeconomic analysis (TEA) models for concentrating solar thermal systems has improved in recent years, there is a lack of consensus on the specific inputs used to forecast performance of a newly built tower system due to a lack of validations and post-mortems available to the public. This effort is a joint initiative between multiple international organizations to validate and compare their TEA models. The specific case study is a proposed retrofit of one unit of the Ivanpah Solar Energy Generating System to include molten-salt storage, replacing the steam generation system with a molten-salt receiver, salt-to-steam heat exchanger train, and new balance of plant while keeping the existing steam turbine, solar field, and interconnection in place, using plant data for calibration. This manuscript discusses several of the agreed-upon assumptions for this study as well as a preliminary analysis from prior work that motivates the study.

14 SOLAR ENERGY

Polynomial-time preparation of low-temperature Gibbs states for two-dimensional toric code

In this work, we propose a polynomial-time algorithm for preparing the Gibbs state of the two-dimensional toric code Hamiltonian at any temperature, starting from any initial state, significantly improving upon prior estimates that suggested exponential scaling with inverse temperature. We prove that fast mixing at low temperature for the two-dimensional toric code can be achieved by augmenting local jump operators with simple global jump operators, which enable efficient transitions between logical sectors. To establish tight lower bounds on the spectral gap, we introduce a new reduction method that eventually maps the problem to estimating the spectral gap of a perturbed graph Laplacian on a stair graph. Our proof also shows that the Lindblad dynamics with a digitally implemented low-temperature local Davies generator is able to efficiently drive the quantum state toward the ground state manifold.

97 MATHEMATICS AND COMPUTING

Light-triggered electrochemical biosensor using singlet oxygen for self-powered operation and glucose detection

This study introduces a light-activated sensing strategy that integrates photosensitization with electrochemical detection. The sensor employs Eosin Y, a photosensitizer that generates singlet oxygen ( 1 O 2 ) via type II photosensitization. Immobilized within a thin polymer matrix on a carbon working electrode, Eosin Y produces 1 O 2 , under green light (520 nm) illumination, initiating a redox process that yields a measurable current. To incorporate biosensing capabilities and enable self-powered operation, this 1 O 2 – mediated process was coupled with glucose oxidase (GOx) to construct a fully operational glucose biosensor. The addition of glucose reverses the current flow by causing GOx to compete for electrons, with the resulting current magnitude correlating with glucose concentration providing a sensitive measure of glucose. The biosensor, as proof-of-principle, demonstrated excellent performance over a range of glucose concentrations (0–73 mM), achieving a detection limit (LOD) of 2.8 mM for steady state photocurrent under oxygen-saturated conditions. This platform leverages light and 1 O 2 as stimuli for tunable, on-demand signal control, offering a novel approach for adaptive, real-time biosensing technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Robust negativity in the quantum-to-classical transition of Kerr dynamics

Here, we quantify the quantum-to-classical transition of the single-mode Kerr nonlinear dynamics in the presence of loss. We establish three timescales that govern the dynamics, each with distinct characteristics. For times short compared with the Ehrenfest time, the evolution is classical, characterized by Gaussian dynamics. For sufficiently long times, as we increase the initial photon number, unitary Kerr evolution would generate macroscopic superpositions of coherent states (so-called kitten states). However, this is severely restricted in the presence of small photon loss, and the expectation values of observables coincide with their classical values. The intermediate timescale, however, shows resilient quantum behavior in the macroscopic limit. We show that in the mean-field non-Gaussian regime, the Kerr Hamiltonian (with small photon loss) generates a significant amount of Wigner-negativity, and classical flow is recovered only if the loss rate grows with system size. Our results broaden the usual understanding of quantum-to-classical transitions and demonstrate the potential for creating robust nonclassical resources for continuous-variable quantum information processing in the presence of loss.

Raza, Mohsin [University of New Mexico, Albuquerqu

Quantum Filtering and Analysis of Multiplicities in Eigenvalue Spectra

Fine-grained spectral properties of quantum Hamiltonians, including both eigenvalues and their multiplicities, provide useful information for characterizing many-body quantum systems as well as for understanding phenomena such as topological order. Extracting such information with small additive error is #BQP-complete in the worst case. In this work, we introduce QFAMES (quantum filtering and analysis of multiplicities in eigenvalue spectra), a quantum algorithm that efficiently identifies clusters of closely spaced dominant eigenvalues and determines their multiplicities under physically motivated assumptions, which allows us to bypass worst-case complexity barriers. QFAMES also enables the estimation of observable expectation values within targeted energy clusters, providing a powerful tool for studying quantum phase transitions and other physical properties. We validate the effectiveness of QFAMES through numerical demonstrations, including its applications to characterizing quantum phases in the transverse-field Ising model and estimating the ground-state degeneracy of a topologically ordered phase in the two-dimensional toric code model. We also generalize QFAMES to the setting of mixed initial states. Our approach offers rigorous theoretical guarantees and significant advantages over existing subspace-based quantum spectral analysis methods, particularly in terms of the sample complexity and the ability to resolve degeneracies.

97 MATHEMATICS AND COMPUTING

Synthesis and application of thermally responsive nanofiber coatings for overtemperature monitoring

This study presents a one-pot synthesis route to organometallic nanofibers based on copper thiolate, exhibiting distinctive chemical and physical characteristics. Electron microscopy analysis of morphology and composition revealed 2-10 μm-long, 50-90 nm-diameter hollow and non-hollow fibers composed of copper, sulfur, oxygen, hydrocarbon, and chlorine. Thermogravimetric analysis showed a pronounced mass loss within 120°C-135°C. To elucidate the thermal responsive pathways, the nanofibers were characterized before and after heating. X-ray photoelectron spectroscopy indicates that an initially mixed Cu(I)/Cu(II) oxidation states transition to predominantly Cu(I) upon heating. A layer of nanofiber was coated on battery pouch foil and evaluated as a candidate thermally sensitive coating. At elevated temperature (100-130°C), nanofiber coating released volatile organic compounds, sulfide and sulfur dioxide as detected using multiple gas sensors. This thermally responsive gas release/sensing approach provides a potential large-area temperature monitoring strategy, which is particularly relevant where direct temperature measurements of individual batteries is impractical. The results established proof of concept for nanofiber-coated battery pouch foil as overtemperature warning platform that can provide alerts when surface temperatures exceed a critical threshold. More broadly, the ability to form interconnected fiber networks positions copper thiolate nanofiber coatings as promising materials for advanced applications.

Ihala Gamaralalage, Chanaka [ORNL] (ORCID:00000002

Large Language Model for Validation, Optical Calibration, and Learning (VOCAL) Distributed Temperature Sensing Interface

Distributed temperature sensing (DTS) using fiber optic sensors (FOS) offers a promising method for temperature measurements in advanced reactors, such as sodium fast reactors and molten salt cooled reactors. To support the calibration and validation of DTS measurements, Argonne National Laboratory developed the Validation, Optical Calibration, and Learning (VOCAL) software package. This report describes the integration of a local large language model (LLM) with a retrieval-augmented generation (RAG) system into the VOCAL interface to serve as an interactive user assistant. The LLM framework enhances the VOCAL platform’s accessibility to users by explaining interface components, clarifying inputs and outputs, and answering user queries dynamically in real-time. The accuracy of the LLM assistant performance was evaluated with 20 queries regarding the interface and its parameters using experimental data from the Thermal Hydraulic Experimental Test Article (THETA) facility. Results demonstrate that the LLM achieved a 95% accuracy rate, with a BERTScore of 0.8816 and SBERT value of 0.7417. Furthermore, validation of the RAG system within the LLM framework showed optimal accuracy with k-values between 1 and 2 using the k-refinement convergence test. The prompt perturbation analysis demonstrated good initial consistency for the RAG system, exhibiting the highest accuracy under punctuation variations and the greatest sensitivity under query reordering. Notably, the model’s errors were limited to data retrieval failures rather than factual hallucinations, reinforcing its baseline reliability. The integration of LLM provides a highly accurate, userfriendly enhancement to the VOCAL platform without disrupting its core computational capabilities for FOS calibration and validation.

Hong, Evan

Fracture Analysis of Cohesive Zone Models for Modeling Residual Stress Induced Delamination in Composite Structures

A fracture study of coupon-scale composite cylinders with embedded defects was conducted with an objective to assess and validate a modeling approach using two available cohesive material models. The study included experimental and simulation evaluations of initiation of crack growth and progression. Interrupted thermal experiments used acoustic emissions monitoring to identify the onset of crack progression during each cooling interval and ultrasonic scanning provided images of defect growth. Verification, validation, and uncertainty quantification (VVUQ) processes were performed in the assessment of the simulation predicted temperature at which crack propagation begins (quantity of interest). The Sobol sensitivity analysis identified the hoop direction elastic modulus in the carbon fiber reinforced polymer (CFRP) plies as the most influential parameter for simulations using both cohesive models, accounting for at least 70% of the variation in the temperature at crack propagation. The UQ temperature range for the Tvergaard-Hutchinson model was higher (more conservative) than the experimental acoustic measurement indicators of crack progression, while the temperature range for the Thouless-Parmigiani model enveloped the experimental data points for the primary defect size of 0.75 x 1 in. The simulations could not capture the stable crack growth indicated in the experiments. This is likely due to the models’ inability to represent anisotropic fracture toughness attributed to the structure of the orthotropic fiber weave in a woven composite laminate.

42 ENGINEERING

Synthesis and investigation into explosive sensitivity for a series of new picramide explosives

Tailoring the molecular properties that govern energetic material sensitivity is essential to improve safety and help develop new energetic materials. Despite this need, understanding the complex chemistry and physics of explosive initiation and propagation is still a challenge. Recent work by our group has reinforced the view that explosive sensitivity under sub-shock conditions is connected to the strength of the weakest covalent bond in the molecule, that is, its “trigger linkage.” These correlations have been observed with different classes of energetic molecules and indicate that “trigger linkage” bond breaking, and heat of explosion are good indicators for the sensitivity trends. Herein we report the synthesis of aliphatic energetic materials with ethane, propane and neopentane backbones. Experimental and computational studies show that the trigger linkage model, based on results from quantum molecular dynamics simulations, correctly predicts trends observed in the impact sensitivity of the molecules. However, while the model predicts the impact sensitivities of the ethane series, the neopentane series has higher impact sensitivities than predicted, which is presumably influenced by crystal packing effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Sensitivity Analysis of Numerical Modeling Input Parameters on Wind Turbine Loads in Deterministic Transient Load Cases

Aero-hydro-elastic-servo numerical models used to design and analyze wind turbines are based on thousands of variable input parameters that dictate the inflow, aerodynamic, structural, and control characteristics of the system as well as sea state, hydrodynamic, and mooring characteristics for fixed-bottom and floating offshore wind turbines. Each of these parameters has some level of uncertainty, which can significantly impact the predicted loads. Understanding the uncertainty in the inputs is critical to understanding the uncertainty in the outputs. This work demonstrates a screening technique to identify which parameters ultimate loads are most sensitive to so that more focus can be given to quantifying the possible range of those parameters. This technique has been demonstrated previously for different turbine and load case types and is extended here for a floating offshore wind turbine in design load cases with transient events both in the inflow and operations. Each load case features a deterministic gust, including variations in wind speed, direction, and shear. Load cases are considered with an operating turbine as well as with prescribed fault, startup, and shutdown procedures. The study found that key input parameters with a large impact on loads include the length of the gust, the magnitude of direction change and speed in the gust, the initial wind speed, and the shape of the gust profile.

17 WIND ENERGY

A Full-Induction Magnetohydrodynamics Solver for Liquid Metal Fusion Blankets in Vertex-CFD

Multiphysics modeling of liquid metal fusion blankets, which produce tritium and convert energy of neutrons created via fusion reactions into heat, is crucial for predicting performance, ensuring structural integrity, and optimizing energy production. While traditional blanket modeling of liquid metal flows during normal steady operating conditions commonly employs the inductionless approximation of the magnetohydrodynamics (MHD) equations, transient scenarios, when the plasma-confining magnetic field varies on millisecond time scales, require a full-induction MHD approach that dynamically evolves the magnetic field via the time-dependent induction equation. This paper presents the formulation, implementation, and initial verification of a full-induction MHD solver integrated within the open-source Vertex-CFD framework, which aims to achieve tight multiphysics coupling, a flexible software design enabling easy extension and addition of physics models, and performance portability across computing platforms. The solver utilizes finite element spatial discretization, implicit Runge–Kutta time integration, and an inexact Newton method to solve the resulting discrete nonlinear system, leveraging Trilinos packages for efficient computation. Verification against selected benchmark problems demonstrates accuracy and robustness of the solver. Furthermore, when the solver is applied to an idealized blanket model in 2.5D and full 3D, results obtained with Vertex-CFD are in good agreement with recently published quasi-2D simulations. These findings establish a computational foundation for future simulations of transient MHD phenomena in liquid metal blankets with Vertex-CFD, and open avenues for future extensions and performance optimizations.

Endeve, Eirik [ORNL] (ORCID:0000000312519507)

Cross-scale interaction between microturbulence and meso-scale reversed shear Alfvén eigenmodes in DIII-D plasmas

Abstract This paper reports global nonlinear gyrokinetic simulations that couple meso-scale reversed shear Alfvén eigenmodes (RSAEs) driven by energetic particles (EPs) and ion temperature gradient (ITG) microturbulence driven by thermal plasma, using equilibrium and profiles from DIII-D discharge #159243. In simulations focusing only on the ITG, electrostatic ITG drives a huge thermal ion heat transport, which is reduced by a factor of 10 to a level close to the experimental value in electromagnetic simulation due to finite β effect. In the simulations coupling the RSAE and ITG, ITG can scatter the resonant EP nonlinearly trapped by the RSAE and damp the zonal flows generated by the RSAE. The regulation of the RSAE by the ITG greatly reduces the initial saturation amplitude of the RSAE but increases the RSAE amplitude and associated EP transport to experimental levels in the quasi-steady state. The RSAE effects on the ITG, specifically the stronger zonal flows generated by the RSAE and the RSAE frequency modulation of the ITG-induced thermal ion heat transport, in turn, leads to a reduction of the thermal ion heat transport by more than a factor of 2 . For a stronger background ITG, the regulation of the RSAE by the ITG is stronger, while the RSAE effects on the ITG are weaker. This work highlights the importance of cross-scale coupling in the dynamics of the AE turbulence and EP transport.

Physics

Research and Development on Advanced Electrochemical Energy Storage Devices Enabling a Spectrum of Electrified Vehicles

The USABC Advanced Battery development plan had the following three focus areas: 1. Existing technology validation, implementation, and cost reduction 2. Identification of the next viable technology with emphasis on the potential to meet USABC cost and energy density goals. 3. Support high-risk, high-reward battery technology R&D The primary aim of this project was focused on the barriers that most impede wider public adoption of electrification in vehicles-cost, energy density, low-temp performance, calendar life, and improvements in abuse tolerance. The specific objectives are as follows: Cost Reduction: drive to significantly reduce battery cost to be in-line with the $\$$100/kWh or less (by the end of calendar year 2020) DOE cost goals. Additionally, goals of $\$$75/KWh were set for 2023 aligned with fast charge and some offset of energy density. Energy Density Increase: focus on improving the cell-level specific energy and energy densities to >350 watt hours per kilogram (Wh/kg) and >750Wh/L. Low Temperature Performance Increase: strive toward developments that improve the discharge power and eliminate or dramatically reduce the life limiting lithium plating associated with regenerative braking at low temperatures, during the program. Calendar Life Increase: drive to achieve a 15-year calendar life. Abuse Tolerance Improvement: strive to develop improvements in Li-ion abuse tolerance and/or development of electrochemical energy storage technologies with inherently better response to abuse circumstances. Emerging Areas: initiate new programs that address emerging technologies that arise during the contract period.

25 ENERGY STORAGE