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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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838 records · Page 29

Smart Charging of Fleet and Personal Electric Vehicles through Joint Vehicle-to-Grid Optimization

As electric vehicle (EV) adoption accelerates, vehicle-to-grid (V2G) strategies offer advantages over unmanaged charging (V0G) by enhancing grid stability, reducing fleet operation costs, and supporting integration of variable generation resources. This research develops a day-ahead optimization framework linked with agent-based simulations to evaluate coordinated V2G participation by fleet and personal EVs under 5 energy-pricing settings in Austin, Texas. Three scenarios (V0G, fleet-only V2G, and joint-V2G) are examined, considering real-time price and grid profiles, health-damage costs, and operational constraints for both fleet and personal EVs. Results show how V2G scenarios shift fleet EV charging to mid-day while enabling strategic battery-discharge during evening peaks, mitigating grid stress and lowering EV energy costs. V2G delivers close to 80% energy-cost savings for a 2000-EV fleet in Austin on grid-stressed days, with 55% lower charging pollutant outputs. Joint-V2G amplifies system-level benefits by complementing fleet discharge, but smart-charging equipment costs can offset those benefits.

Electric vehicle

Effect of the Nature of Both Cation and Anion Substitution on the Structural Symmetry of Li‐Rich 3 d ‐Metal Chalcogenide Electrodes

Abstract Li‐rich layered chalcogenides have recently led to better understanding of the anionic redox process and its associated high capacity while providing ways to overcome its practical limitations of voltage fade and irreversibility. This study reports on the feasibility of triggering anionic activity in Li 2 TiS 3 , through anionic substitution (Se for S) or cationic substitution (Fe for Ti). Herein, the chalcogenide chemical space is further explored to prepare mono‐substituted Li 1.7 Ti 0.85 Mn 0.45 Ch 3 (Ch = S/Se) and doubly substituted cationic and anionic phases (Li 1.7 Ti 0.85 Fe 0.45 S 3‐z Se z ) which crystallize either in the O3‐ or O1‐type structures depending upon substituents. All series show a bell‐shape capacity variation as function of the transition metal (TM) substitution degree with values up to 240 mAh g −1 . For specific compositions, a structural O3 to O1 phase transition is observed upon Li removal, which is not reversible upon Li re‐insertion due to kinetic limitations and negatively affects long‐term cycling performance. Density functional theory (DFT) calculations confirm the O3/O1 relative stability along the different series and point subtle electronic differences in the TM‐doping, rationalizing the structural and electrochemical behaviors of these phases upon cycling. These findings provide further insights into the link between structural and electronic stability, which is of key importance for designing chalcogenide‐based anionic redox compounds.

Chemistry

Understanding and Predicting the Spatially Resolved Adsorption Properties of Nanoporous Materials

Using knowledge from statistical thermodynamics and crystallography, we develop an image–image translation model, called SorbIIT, that uses three-dimensional grids of adsorbate–adsorbent interaction energies as input to predict the spatially resolved loading surface of nanoporous materials over a broad range of temperatures and pressures. SorbIIT consists of a closed-form differential model for loading-surface prediction and a U-Net to generate spatial differential distributions from the energy grids. SorbIIT is trained using the energy grids and adsorbate distributions (obtained from high-throughput simulations) of 50 synthesized and 70 hypothetical zeolites and applied for predicting the adsorption of carbon dioxide, hydrogen sulfide, n-butane, 2-methylpropane, krypton, and xenon in other zeolites from 256 to 400 K. In conclusion, employing a quadratic isotherm model for the local differentiation, SorbIIT yields mean R 2 values of 0.998 for total adsorption and 0.6904 for local adsorption with a resolution of 0.2 Å, and a value of 0.721 for the structural similarity of the local loading distribution.

Sun, Yangzesheng [Univ. of Minnesota, Minneapolis,

Observations of Offshore Low‐Level Jets Off the U.S. East Coast Reveal Systematic Biases in ERA5 and HRRR

Low-level jets (LLJs)—wind speed maxima typically occurring a few hundred meters above the surface—are common off the U.S. East Coast and influence many atmospheric processes with societal importance, including cloud formation, aviation safety, and search-and-rescue. However, their vertical structure and frequency remain poorly quantified due to limited offshore observations. This study presents new scanning Doppler LiDAR and infrared spectroradiometer data from the 2024 summer deployment of an offshore barge during the Wind Forecast Improvement Project 3. These coupled wind and temperature profiles provide unprecedented resolution to assess LLJ behavior and model performance. LLJs occurred in over 21% of observed profiles, with a weak diurnal preference for nighttime and early morning hours and maximum winds typically near 300 m. Both ERA5 and High-Resolution Rapid Refresh analysis underestimate jet wind speeds and misrepresent the boundary layer thermal structure. These results highlight persistent model biases and the critical need for high-resolution offshore observations.

17 WIND ENERGY

Spin‐Polarized Interfaces Redirect CO 2 Reduction From CO to Formate

Achieving high product selectivity in electrocatalytic carbon dioxide reduction (CO 2 RR) remains a critical challenge due to competition between multiple proton-coupled electron-transfer pathways on catalyst surfaces. Meanwhile, chirality-induced spin selectivity (CISS), which enables spin-polarized electron transport through chiral interfaces, has recently emerged as a promising strategy to modulate interfacial electrochemical reactions. Although the CISS effect has been shown to enhance selectivity and efficiency in the spin-sensitive oxygen evolution reaction (OER), its role in regulating CO 2 RR pathways and in stabilizing intermediates remains largely unexplored. Here, chiral molecules (R- and S-1,1′-bi-2-naphthyl-2,2′-diyl hydrogen phosphate, BNP) were integrated with SnO 2 to construct chiral-modified catalysts (R-BNP/SnO 2 and S-BNP/SnO 2 ). Compared with bare SnO 2 and racemic BNP-modified SnO 2 (Rac-BNP/SnO 2 ), the chiral catalysts exhibited a pronounced shift in product selectivity from CO toward formate production. Importantly, in-situ attenuated total reflectance surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS) reveals that the chiral interface selectively stabilizes the O-bound *OCHO intermediate associated with the formate pathway and modulates interfacial water structure and hydrogen-bonding dynamics. These findings demonstrate that spin-polarized interfacial electron transfer can regulate CO 2 RR pathway selectivity by modulating the stabilization of key intermediates. More broadly, this work establishes chiral spin-selective interfaces as a new strategy for regulating competitive electrocatalytic reaction pathways.

14 SOLAR ENERGY

Minimal dark 𝑆⁢𝑈⁡(2) origin of a massless Dirac neutrino

We propose a gauge-symmetry origin of a rank-two Dirac neutrino mass matrix that enforces one exactly massless neutrino, while being consistent with the oscillation data, as well as cosmological constraints. The mechanism relies on a minimal dark 𝑆⁢𝑈⁢(2) 𝐷 gauge symmetry under which one right-handed neutrinolike Weyl fermion is charged, thereby forbidding its Standard Model Yukawa coupling. Quantum consistency then fixes the minimal dark-sector completion: Cancellation of the Witten anomaly requires a second fermionic 𝑆⁢𝑈⁢(2) 𝐷 doublet, while a discrete 𝑍 4 symmetry that forbids Majorana masses allows the two dark doublets to form a vectorlike pair. This anomaly-free completion gives rise to a secluded, confining dark sector that can contain a potential dark matter candidate, linking the protected neutrino texture to dark infrared dynamics.

confinement

PowerModelsGAT-AI: Physics-Informed Graph Attention for Multi-System Power Flow With Continual Learning

Solving the alternating current power flow equations in real time is essential for secure grid operation, yet classical Newton–Raphson solvers can be slow under stressed conditions. Existing graph neural networks for power flow are typically trained on a single system and often degrade on different systems. We present PowerModelsGAT-AI, a physics-informed graph attention network that predicts bus voltages and generator injections. The model uses bus-type-aware masking to handle different bus types and balances multiple loss terms, including a power-mismatch penalty, using learned weights. We evaluate the model on 14 benchmark systems (4 to 6,470 buses) and train a unified model on 13 of these under contingency conditions with up to two branch outages, achieving an average normalized mean absolute error of 0.89% for voltage magnitudes and R 2 >0.99 for voltage angles. We also show continual learning: when adapting a base model to a new 1,354-bus system, standard fine-tuning causes severe forgetting with error increases exceeding 1000% on base systems, while our experience replay and elastic weight consolidation strategy keeps error increases below 2% and in some cases improves base-system performance. Interpretability analysis shows that learned attention weights correlate with physical branch parameters (susceptance: r=0.38 ; thermal limits: r=0.22 ), and feature importance analysis supports that the model captures established power flow relationships.

24 POWER TRANSMISSION AND DISTRIBUTION

Utility Experience with Inverter Based Resource Impacts on Transmission Protection

High penetration of inverter-based resources (IBR) can adversely affect the transmission protection schemes in the area. With the proliferation of IBRs, utilities are finding out that conventional protection schemes are not adequately equipped to protect the electric systems because the existing system has been designed based on the fault current response of conventional rotating-machine-based generators. In several cases, the available literature does not provide any clear solution for the issues when the protection scheme does not operate properly near IBRs. This report identifies various protection challenges due to IBRs that industry is facing, from the utility perspective. It includes a broad review of all challenges that system protection has experienced so far with high penetration of IBRs. Key issues have been identified based on a survey of different utility protection engineers. Finally, fault event recordings are shown to demonstrate some actual cases of mis-operations of relays near IBRs.

24 POWER TRANSMISSION AND DISTRIBUTION

Dark Energy Survey year 6 results: Magnification modeling and its impact on galaxy clustering and galaxy-galaxy lensing cosmology

Gravitational lensing magnification alters the observed spatial distribution of galaxies and must be accounted for to prevent biases in cosmological probes of the large-scale structure. We investigate its effects on the Dark Energy Survey Year 6 galaxy clustering and galaxy-galaxy lensing analyses using the fiducial lens (position tracer) sample M ag L im++. Magnification bias is parameterized by a coefficient that describes the response of the number of selected objects per unlensed area element to a change in the lensing convergence. We quantify this coefficient using the BALROG synthetic source injection catalog to account for the complexity of the selection function, and compare these results with simplified estimates. The resulting values of the magnification coefficients for each redshift bin are [3.16 ± 0.08, 2.76 ± 0.21, 4.09 ± 0.15, 4.42 ± 0.16, 4.90 ± 0.29, 4.83 ± 0.25]. Relative to Year 3, this analysis provides more precise and accurate magnification bias estimates through a larger BALROG area and reweighting to better match the data properties. Here, the cosmological results are robust when tested against various magnification parameter prior choices and also when adding cross-clustering between lens redshift bins. Neglecting magnification, however, introduces significant systematic shifts: relative to the fiducial analysis with Gaussian priors centered on the BALROG -derived estimates, we observe shifts of 1.37σ in S 8 and -0.84σ in Ω m (with cosmic shear included: -0.61σ in S 8 and -0.71σ in Ω m ), in agreement with findings from simulated data, demonstrating that magnification must be modeled to avoid biases. Freeing the magnification bias in lens bin 2 leads to unphysical negative values, further justifying its exclusion from the fiducial Year 6 analysis.

Cosmological parameters

Structure of Self-Generated Magnetic Fields in Laser-Solid Interaction from Proton Tomography

Self-generated magnetic fields in laser-solid interactions are experimentally characterized to reveal the 3D location and local field strength, rather than path-integrated quantities, using multi-view proton radiography and tomographic inversion. We infer magnetic fields that extend several millimeters off the target into the hot, rarefied corona, sufficient to strongly magnetize the plasma (Ω e τ e ≫ 1). The data are compared to MHD simulations incorporating recent improvements in modeling magnetic field generation and transport; the volume-averaged coronal field strength and magnetic flux agree to within 25% using a model with magnetic re-localization of transport, although the near-target morphology is not reproduced. This work demonstrates tomographic proton radiography as a valuable tool for investigating magnetic fields in laser-produced plasmas.

High-energy-density plasmas

Material efficiency technologies in the food and beverage industry

The U.S. food and beverage (F&B) sector is a major contributor to manufacturing gross domestic product and supports substantial employment and economic activity, while exerting significant pressures on land and water resources. At the same time, the industry faces growing expectations to balance its resource-intensive operations without compromising cost competitiveness. Material inefficiencies across the F&B value chain, particularly in raw material use and product loss/waste, lead to substantial financial losses and resource depletion. Thus, the F&B sector requires adoption of solutions and measures to avoid food wastage, reduce raw material consumption and valorize waste to high-value added products. This work presents a comprehensive understanding of the various technology solutions available for the F&B sector. The following two research questions are addressed: “What are the mid-to-high Technology Readiness Level technologies or measures to reduce material use and enable waste valorization in the F&B sector? What are the barriers to their commercial deployment? Additionally, what targeted research and development efforts are needed to overcome these barriers and accelerate their scale-up?” The findings are intended to support evidence-based decision-making, guide strategic investment, and help stakeholders strengthen resilience and competitiveness across the F&B sector.

Nain, Preeti [ORNL] (ORCID:0000000258358959)

Nuclear Structure and Decay Data for A=35 Isobars

Here, this work presents a comprehensive and critical evaluation of experimental nuclear spectroscopic data from reactions and decays for all 11 known nuclides with mass number 35 (Ne, Na, Mg, Al, Si, P, S, Cl, Ar, K, Ca). Recommended values are produced for level energies, spins and parities, half-lives, and radiation properties including energies, branching ratios, and multipolarities of γ rays, as well as characteristics of β radiation decays, based on a rigorous assessment of all available experimental data. Discrepancies among existing results are carefully addressed. This work supersedes earlier full evaluations of A=35 published by 2011Ch48, 1990En08 (also 1998En04 update) and 1978En02.

Sun, Lijie [Michigan State University, East Lansin

Black-hole powered quantum coherent amplifier

Abstract Atoms falling into a black hole (BH) through a cavity are shown to enable coherent amplification of light quanta powered by the BH-gravitational vacuum energy. This process can harness the BH energy towards useful purposes, such as propelling a spaceship trapped by the BH. The process can occur via transient amplification of a signal field by falling atoms that are partly excited by Hawking radiation reflected by an orbiting mirror. In the steady-state regime of thermally equilibrated atoms that weakly couple to the field, this amplifier constitutes a BH-powered quantum heat engine. The envisaged effects substantiate the thermodynamic approach to BH acceleration radiation.

Physics

Characterizing the γ-Ray Emission from FR0 Radio Galaxies

Abstract FR0 galaxies constitute the most abundant jet population in the local Universe. With their compact jet structure, they are broadband photon emitters and have been proposed as multimessenger sources. Recently, these sources have been detected for the first time inγrays. Using a revised FR0 catalog, we confirm that the FR0 population as a whole areγ-ray emitters, and we also identify two significant sources. For the first time, we find a correlation between the 5 GHz core radio luminosity andγ-ray luminosity in the 1–800 GeV band, having a 4.8σstatistical significance. This is clear evidence that the jet emission mechanism is similar in nature for FR0s and the well-studied canonical FR (FRI and FRII) radio galaxies. Furthermore, we perform broadband spectral energy distribution modeling for the significantly detected sources as well as the subthreshold source population using a one-zone synchrotron self-Compton model. Within the maximum jet power budget, our modeling shows that the detectedγrays from the jet can be explained as inverse Compton photons. To explain the multiwavelength observations for these galaxies, the modeling results stipulate a low bulk Lorentz factor and a jet composition far from equipartition, with the particle energy density dominating over the magnetic field energy density.

Astronomy & Astrophysics

Additively manufactured refractory high-entropy alloys with superior radiation resistance

Refractory high-entropy alloys (RHEAs) are promising candidates for next-generation nuclear and high-temperature applications. Among many approaches to manufacture RHEAs, additive manufacturing (AM) represents the most recent and advanced metal manufacturing method which allows near-net-shape manufacturing to reduce material waste and post-processing time. However, performance of AM RHEAs under complex irradiation conditions remains largely unexplored. Here, in this study, we demonstrate for the first time the response of directed energy deposition (DED) AM quaternary RHEAs (HfTaVW, CrTaVW) subjected to sequential dual-beam ion irradiation, consisting of helium pre-implantation followed by high-dose heavy ion bombardment. Compositions of DED AM RHEAs were selected using Monte Carlo (MC) simulations based on a cluster expansion (CE) Hamiltonian parameterized by density functional theory (DFT). Post-irradiation microstructural characterization revealed that the AM RHEA maintained remarkable stability, with suppressed helium bubble growth and reduced defect accumulation compared to conventional alloys. Even at high doses (∼100 dpa), the alloy exhibited no void swelling, a low density of dislocation loops, and no evidence of severe degradation. These results highlight the intrinsic ability of AM-derived microstructures and multicomponent chemistry to synergistically mitigate irradiation effects. Our findings establish AM RHEAs as a class of materials with superior resistance to radiation damage under conditions relevant to advanced fusion and fission environments and demonstrate the importance of sequential ion beam studies in evaluating their long-term performance.

36 MATERIALS SCIENCE

The Role of Nuclear Data Sensitivities in Prompt α-Eigenvalue Predictions of Delayed Critical Benchmarks

Alpha (α) eigenvalues, which describe the logarithmic time derivative of the neutron population in a multiplying system, are integral to time-dependent behavior and diagnostic applications. However, uncertainties in the evaluated nuclear data can significantly impact the accuracy of transport simulations for such quantities. This work explores the use of machine learning models to predict two key outputs, α-eigenvalues and keff bias, using input features derived from α-eigenvalue sensitivities to nuclear data. The criticality safety benchmark models used in this study come from the International Handbook of Evaluated Criticality Safety Benchmark Experiments. Three models, random forest, XGBoost, and NGBoost, are trained on both energy-resolved and energy-summed α sensitivities. For the α-eigenvalue bias prediction, NGBoost achieved the highest R 2 (0.9476) using energy-resolved features, while XGBoost performed best using summed sensitivities. In contrast, when predicting the keff bias, all the models showed moderate predictive capability (best R 2 ≈ 0.72), as the mapping from the static α-sensitivities to the static keff bias was less direct. SHAP (SHapley Additive exPlanations) analysis was used to interpret the model predictions. Across both prediction tasks, the features associated with neutron capture [H-1 (n, γ)], uranium scattering reactions (such as 235 U elastic/inelastic), and actinide capture/fission reactions (such as 239 Pu and 234 U) were consistently identified as the most impactful. This highlights the key role of specific nuclear reactions and energy ranges in shaping both time-dependent and steady-state criticality behavior. These results demonstrated that α-sensitivities, despite being computed for time-dependent metrics, can provide valuable insights for predicting both α-eigenvalues and the keff bias. Moreover, machine learning models offer a promising pathway for uncovering important nuclear data dependencies and guiding future data evaluation efforts.

Nuclear data

Mechanically Accelerated Depolymerization of Entangled Linear Polymer Melts

Mechanical forces can enhance the chemical depolymerization of synthetic polymers when shear flow accelerates chain scission. To quantify the extent of mechanically-accelerated scission, the effect of simple shear flow (duration and strength) with low Weissenberg and Deborah numbers was investigated by considering the impact of applied work in both simple shear and shear dominated mixed flows. Hydrogenated polyisoprene was chosen as a model linear, entangled system. The conditions (strain amplitude, frequency, and shearing time) necessary to increase chain scission were assessed in the rubbery melt. Shear flow accelerated chain scission at higher temperatures, suggesting an activated process. Isothermal scission versus work curves were superposed by applying shift factors a T,S , whose Arrhenius-like temperature dependence gave an apparent activation energy for chain scission of ~ 110 kJ/mol, which is likely a combination of the activation energy of viscosity and bond energy. This work provides a base for quantifying the impact of shear on depolymerization of polymer melts and highlight the connection between viscous dissipation and scission chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Reduced instability growth and improved radiation trapping with optimized shock timing in double-shell inertial confinement fusion capsules

The double shell is a volume-burn inertial confinement fusion concept consisting of two concentric shells: a low-Z outer shell that collides with and transfers momentum to a high-Z inner shell which compresses and heats the thermonuclear fuel. The increased number of capsule interfaces and severe hydrodynamic instability of the high-density pusher during its acceleration phase provide challenges to the success of the double shell. Two-dimensional radiation-hydrodynamics simulations predict the hydrodynamic instability growth on the outer surface of the pusher can be greatly reduced through appropriate timing of two shocks that cross this interface. One of these shocks, unique to multi-shell designs, arises from radiation-driven ablation of the inner shell ahead of the main shock, the second shock of concern. The shock timing is optimized by increasing the thickness of a low-Z tamper layer exterior to the pusher, resulting in only minimal changes to the implosion timing. Reducing the instability growth on the outer surface of the high-Z pusher can dramatically decrease the modulations that feedthrough to the pusher inner surface, improving the efficacy of radiation trapping in the thermonuclear fuel and increasing the predicted thermonuclear yield by ≳20×.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY