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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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At least 289 records · Page 16

Measurement of three-dimensional inclusive muon-neutrino charged-current cross sections on argon with the MicroBooNE detector

We report the measurement of the triple-differential cross section d 3 σ/dE vis d cos(θ μ )dP μ for inclusive muon-neutrino charged-current scattering on argon. This measurement utilizes data from 6.4 x 10 20 protons on target of exposure collected using the MicroBooNE liquid argon time projection chamber located along the Fermilab Booster Neutrino Beam with a mean neutrino energy of approximately 0.8 GeV. The mapping from reconstructed kinematics to truth quantities is validated within uncertainties by comparing the distribution of reconstructed hadronic energy in data to that of the model prediction in different muon scattering angle bins after applying a conditional constraint from the muon momentum distribution in data. The success of this validation provides confidence that the energy transfer in the MicroBooNE detector is well-modeled within simulation uncertainties, enabling a reliable unfolding to a triple-differential cross section defined at the nominal neutrino flux over muon momentum, muon scattering angle, and visible neutrino energy. This validation not only supports accurate cross-section extraction, but also establishes a critical foundation for tuning interaction models used in future neutrino oscillation measurements. The unfolded measurement covers an extensive phase space, providing a wealth of information useful for future liquid argon time projection chamber experiments measuring neutrino oscillations. Comparisons against a number of commonly used model predictions are included and their performance in different parts of the available phase-space is discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

flat10MIP: an emissions-driven experiment to diagnose the climate response to positive, zero and negative CO2 emissions

Abstract. The proportionality between global mean temperature and cumulative emissions of CO2 predicted in Earth system models (ESMs) is the foundation of carbon budgeting frameworks. Deviations from this behavior could impact estimates of required net-zero timings and negative emissions requirements to meet the Paris Agreement climate targets. However, existing ESM diagnostic experiments do not allow for direct estimation of these deviations as a function of defined emissions pathways. Here, we perform a set of climate model diagnostic experiments for the assessment of transient climate response to cumulative CO2 emissions (TCRE), the Zero Emissions Commitment (ZEC), and climate reversibility metrics in an emissions-driven framework. The emissions-driven experiments provide consistent independent variables simplifying simulation, analysis and interpretation, with emissions rates more comparable to recent levels than existing protocols using model-specific compatible emissions from the CMIP DECK 1pctCO2 experiment, where emissions rates tend to increase during the experiment, such that at the time of CO2 doubling in year 70, emissions are much greater than present-day values. A base experiment, “esm-flat10”, has constant emissions of CO2 of 10 GtC per year (near-present-day values), and initial results show that the TCRE estimated in this experiment is about 0.1 K less than that obtained using 1pctCO2. A subset of ESMs exhibit land carbon sinks that saturate during this experiment. A branch experiment, esm-flat10-zec, illustrates that both positive and negative ZEC effects are less pronounced under esm-flat10 than under 1pctCO2 – the magnitude of ZEC50 in ESMs is, on average, reduced by 30 % compared with 1pctCO2 branch experiments. A final experiment, esm-flat10-cdr, assesses climate reversibility under negative emissions, where we find that peak warming may occur before or after net zero and that the asymmetry in temperature at a given level of cumulative emissions between the positive and negative emissions phases is well described by ZEC in most models. Further, we find that existing probabilistic simple climate model (SCM) ensembles tend to overestimate temperature reversibility compared with ESMs, highlighting the need for additional constraints. We propose a set of climate diagnostic indicators to quantify various aspects of climate reversibility. These experiments were suggested as potential candidates in CMIP7 and have since been adopted as “fast track” simulations.

Sanderson, Benjamin M↗

Performance Modeling of a Variable-Geometry Oscillating Surge Wave Energy Converter on a Raised Foundation: Preprint

This paper analyzes the power capture potential, structural loadings, and costs associated with an oscillating surge wave energy converter (OSWEC) operating on a raised foundation. The raised OSWEC offers opportunities for reduced installation costs, improved energy production, and greater flexibility of deployment when compared with bottom-fixed models. In this investigation, several different foundation geometries were simulated using WEC-Sim to estimate power capture and structural loads. In an effort to maximize power capture, several cases in which flat plates of varying size were attached to the top of the foundation, under and parallel with the OSWEC, were also simulated. These plates were found to enhance power capture by preventing the wave induced pressure from passing underneath the OSWEC, diverting this pressure towards the OSWEC instead. The OSWEC was simulated in the six Wave Energy Prize sea states, which were chosen as a representative sample of U.S. deployment sites. A first-order estimate of structural costs was calculated using the Wave Energy Prize ACE metric, with the foundation comprised predominantly of steel-reinforced concrete and the OSWEC comprised of A36 steel. Influence of foundation geometry on power capture, structural loadings, and ACE are topics of particular interest. This work has been inspired by advances in large scale additive manufacturing techniques that have the potential to dramatically reduce the cost of subsea foundations. These advancements may enable cost effective WEC systems to be deployed on raised foundations.

50 EE - Wind and Water Power Program - Water (EE-4↗

First-Principles Modeling of the Repassivation of Corrosion Resistant Alloys: Part I. O and Cl Adsorption Energy

To understand the mechanism of repassivation, a key process that controls the performance of corrosion resistant alloys (CRAs), it is useful to obtain some fundamental parameters that describe the atomistic processes. Oxygen and chlorine adsorption energies were systematically calculated with density functional theory for Ni-22Cr alloys with seven different solute elements: Co, Cu, Fe, Mn, Mo, Ru and W. All elements other than Cu enhance both O and Cl adsorption to alloy surfaces. Cr has the strongest effect among these elements. Surface configurations that give stronger O adsorption also tend to give stronger Cl adsorption. While this makes it difficult to differentiate the effect of these solute elements on the oxidation/repassivation tendency of alloys, these fundamental properties provide the foundation for higher scale models that could be used to study the oxidation process during corrosion and potentially inform the design of CRAs. Bader charge analysis reveals a strong relationship between the adatom adsorption energy and the Bader charges of both O and Cl adatom. In conclusion, the work function of alloy surfaces is increased by O while decreased by Cl, suggesting that Cl adsorption can have an intrinsic negative impact on corrosion resistance by decreasing the barrier to electron transfer.

36 MATERIALS SCIENCE↗

Describing Point Defect Topology in 2D Energy Materials Through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science. ML is often not just a matter of straightforward application, and pretrained models proved ineffective in this case. Instead, we trained our own neural network (NN) and applied data augmentation techniques and fine-tuning to the training dataset. Since labeled microscopy data is often scarce, we developed training data from a previously published wide-frame MXene image, using customized Gaussian fitting to locate atomic positions. Our trained model was then applied to a large dataset of experimental images, enabling a statistical study of defect configurations across three samples prepared with different HF etchant concentrations (5%, 9.1%, and 12.5%), as shown in Fig. 1. This also allowed us to investigate local strain around vacancies, though we find that we are limited by the precision of measurements using high-angle annular dark field (HAADF) images, as shown in Fig. 2. This study demonstrates how ML enables large-scale, quantitative analysis of atomic defects - an otherwise infeasible task with traditional methods. While our NN was specialized for Ti3C2 MXenes, the pipeline we developed provides a foundation for future ML models tailored to other materials. Ultimately, we envision embedding the NN onto the microscope to give real-time feedback to the user. To make this a reality, continued work is necessary to fully understand the NN's capabilities and limitations. This study gets one step closer to our goals of automated experimentation moving away from traditional methods of manual labeling. As ML capabilities advance, we hope to continue adapting and applying these techniques in microscopy.

2D materials↗

Simulated effect of defect volume and location on very high cycle fatigue of laser beam powder bed fused AlSi10Mg

This study quantifies the interaction between volumetric defect location and size on the very high cycle fatigue (VHCF) of laser beam powder bed fused (LB-PBF) AlSi10Mg. Crystal plasticity finite element method (CPFEM) simulations were used to investigate the effects of defect location and size on the driving force for crack initiation. The CPFEM model was calibrated against uniaxial and cyclic experimental data of LB-PBF AlSi10Mg. Defect characteristics were informed by experimental data from the specimens produced in various geometries to create realistic representative volume elements (RVEs) with equivalent volume fractions of defects. By embedding defects of varying sizes and locations within the RVEs, fatigue indicator parameters (FIPs) were calculated to analyze the impact of defects’ characteristics on fatigue performance. Different combinations of defect volume and locations were generated for various microstructure instantiations, providing insight into extreme value fatigue responses. Larger defect volumes located on free surfaces consistently generated the highest FIPs, suggesting defect size and boundary proximity intensify stress concentration effects. RVEs with multiple smaller defects produced lower FIPs than those with single large critical defects. These findings underscore the critical role of defect characteristics on fatigue life, providing a foundation for future predictive modeling in fatigue-sensitive AM applications.

AlSi10Mg↗

Modular Hydronic Room Conditioning System (CRADA NFE-24-10120 Final Report)

This project presents the development and validation of high-fidelity numerical models for fin-tube heat exchangers to enable accurate performance prediction and informed design optimization. The modeling framework integrates detailed geometric specifications, thermophysical property data, and system-level constraints to simulate the heat exchanger’s behavior under a range of operating conditions. The model is calibrated using real-world product specifications and validated against experimental data collected from controlled cooling and heating tests. In cooling mode, the model captures the overall trends in capacity and outlet air temperature but tends to underpredict latent effects, especially at lower air flow rates. In heating mode, the simulation consistently overestimates both the thermal capacity and outlet air temperature, indicating the need for refinement in air-side heat transfer assumptions. Despite these deviations, the model provides a solid foundation for optimization, allowing key design variables to be tuned within physical and performance-based constraints. This research advances the ability to simulate, validate, and optimize fin-tube heat exchanger designs with greater confidence and efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Techno-Economic Analysis and Global Warming Potential of a Novel Offshore Macroalgae Biorefinery

The success of a large scale macroalgae-based biorefinery is dependent on the demonstration of favorable system economics and environmental sustainability. This study uses detailed process modeling to quantify the mass and energy flows through the various unit operations required for a novel free-floating macroalgae biorefinery concept. The modular process model served as the foundation for the techno-economic and global warming potential analyses used to quantify the sustainability of the proposed concept. This work includes detailed techno-economic results for a complete macroalgae cultivation and conversion system with multiple hatchery configurations and several emerging technologies. System optimization was achieved through the evaluation of various technology options for each unit operation. Technologies considered include traditional twine and textile substrate hatchery configurations, drone assisted seeding and biomass transport, mechanized line seeding and harvesting, adhesive spore mixtures that simplify seeding operations and improve hatchery energetics, and hydrothermal liquefaction to produce upgradable biocrude. Outputs from the system include renewable diesel (R100), naphtha, biochar, nitrogen and phosphorus fertilizers, and aqueous/solid waste streams. Three different system pathways were explored, yielding a biomass production cost ranging from $210 to $565 per dry metric ton and a minimum fuel selling price from $1.35 to $2.91 per liter of gasoline equivalent. Stochastic manipulation of the process model and sensitivity analyses support these results. The global warming potential analysis shows net greenhouse gas emissions ranging from 14 to 29 gCO2-eq MJ-1, supported by stochastic and sensitivity analyses. The recommendations from this work highlight critical areas for research and development investment such that a sustainable macroalgae cultivation and conversion system can be realized.

NOMAD seaweed cultivation, techno-economic analysi↗

Recrystallization driven softening and heating rate dependencies of FeCrAl nuclear fuel cladding during accident transients

A refined understanding of FeCrAl cladding behavior during rapid transients is critical for its potential deployment in light-water reactors. Current assessments focus on transient burst testing metrics such as balloon geometry, burst temperature, and hoop stress, often used as proxies for simpler conventional tensile properties. However, directly correlating isothermal tensile and creep data with accident transient scenarios remains a challenge, although it is essential for high fidelity model development. Recent modeling based on tensile tests up to 800 °C, conducted with both immediate loading and a 10-minute soak, showed that immediate loading better predicts experimental burst temperatures, indicating a thermal softening effect. Building upon this observation, the current study connects transient performance, microstructural evolution, and high-temperature tensile properties by leveraging results from C26M claddings burst tests performed at heating rates of 1–50 °C/s and hoop stresses from 25 to 100 MPa. At 25 MPa, rupture temperatures varied by only 6 °C, but at 100 MPa, the difference reached 116 °C, with faster heating yielding higher burst temperatures. Microstructural analysis identified recrystallization as the primary cause of heating rate-dependent softening, eliminating prior cold-working. In-situ thermomechanical data linked ballooning onset to localized instabilities, similar to ultimate tensile strength behavior in conventional tensile tests. High heating rates correlated with immediate loading tensile data, while lower rates matched soaked data. Furthermore, by linking burst performance to microstructural evolution and tensile properties, this work provides a foundation for more accurate modeling of FeCrAl claddings and potentially other Fe-based materials under accident conditions.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Deep learning-assisted modeling for χ (2) nonlinear optics

Modeling second-order (χ(2)) nonlinear optical processes remains computationally expensive due to the need to resolve fast field oscillations and simulate wave propagation using methods such as the split-step Fourier method (SSFM). This can become a bottleneck in real-time applications, such as high-repetition-rate laser systems requiring rapid feedback and control. We present a long short-term memory-based surrogate model trained on SSFM simulations generated from a start-to-end model of the photocathode drive laser at SLAC National Accelerator Laboratory’s Linac Coherent Light Source II. The model achieves over 250× speedup while maintaining high fidelity, enabling future real-time optimization and laying the foundation for data-integrated modeling frameworks and digital twins of laser systems.

Accelerator Physics (physics.acc-ph)↗

Overview of the MOSAiC expedition—Atmosphere

With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.

54 ENVIRONMENTAL SCIENCES↗

Performance Modeling of a Variable-Geometry Oscillating Surge Wave Energy Converter on a Raised Foundation

This paper analyzes the power capture potential, structural loadings, and costs associated with an oscillating surge wave energy converter (OSWEC) operating on a raised foundation. The raised OSWEC offers opportunities for reduced installation costs, improved energy production, and greater flexibility of deployment when compared with fixed-bottom models. In this investigation, we simulated several different foundation geometries using WEC-Sim to estimate power capture and structural loads. In an effort to maximize power capture, several cases in which flat plates of varying size were attached to the top of the foundation, under and parallel with the OSWEC, were also simulated. These plates were found to enhance power capture by preventing the wave-induced pressure from passing underneath the OSWEC, diverting this pressure toward the OSWEC instead. The OSWEC was simulated in the six Wave Energy Prize sea states, which were chosen as a representative sample of U.S. deployment sites. A first-order estimate of structural costs was calculated using the Wave Energy Prize ACE metric, with the foundation comprised predominantly of steel-reinforced concrete and the OSWEC comprised of A36 steel. Influence of foundation geometry on power capture, structural loadings, and ACE are topics of particular interest. This work has been inspired by advances in large-scale additive manufacturing techniques that have the potential to dramatically reduce the cost of subsea foundations. These advancements may enable cost-effective WEC systems to be deployed on raised foundations.

cost↗

Usage Pattern Analysis for the Summit Login Nodes

High performance computing (HPC) users interact with Summit through dedicated gateways, also known as login nodes. The performance and stability of these login nodes can have a significant impact on the user experience. In this study, the performance and stability of Summit’s five login nodes are evaluated by analyzing the log data from 2020 and 2021. The analysis focuses on the computing capability (CPU average load, users and tasks) and the storage performance, along with the associated job scheduler activity. The outcome of this study can serve as the foundation of a predictive modeling framework that enables the system admin of an HPC system to preemptively deploy countermeasures before the onset of a system failure.

Eiffert, Brett↗

Cosmology from random entanglement

We construct entangled microstates of a pair of holographic CFTs whose dual semiclassical description includes big bang-big crunch AdS cosmologies in spaces without boundaries. The cosmology is supported by inhomogeneous heavy matter and it partially purifies the bulk entanglement of two disconnected auxiliary AdS spacetimes. We show that the island formula for the fine grained entropy of one of the CFTs follows from a standard gravitational replica trick calculation. In generic settings, the cosmology is contained in the entanglement wedge of one of the two CFTs. We then investigate properties of the cosmology-to-boundary encoding map, and in particular, its non-isometric character. Restricting our attention to a specific class of states on the cosmology, we provide an explicit, and state-dependent, boundary representation of operators acting on the cosmology. Finally, under genericity assumptions, we argue for a non-isometric to approximately-isometric transition of the cosmology-to-boundary map for “simple” states on the cosmology as a function of the bulk entanglement, with tensor network toy models of our setup as a guide.

79 ASTRONOMY AND ASTROPHYSICS↗

Thermal and dynamic partition of dumbbell interstitials in complex concentrated alloys

Complex concentrated alloys (CCAs) are promising candidates for applications in extreme conditions, such as irradiation where interstitial mediated diffusion is important. In CCAs with N principal elements, $\frac{N(N+1)}{2}$ types of dumbbell interstitials exist. Currently, there is no way to predict the thermal partition (fractional concentration at equilibrium) and the dynamic partition (fractional time an interstitial spends during diffusion) of each type of dumbbell interstitial. To mitigate this issue, this work proposes a theoretical model for computing the equilibrium concentrations and thermal partition of dumbbell interstitials in CCAs and validates the model using grand canonical Monte Carlo simulations. Lattice kinetic Monte Carlo simulations show that the thermal partition is equivalent to the dynamic partition, and both are governed by composition and formation energies of dumbbells. As a result, the model proposed provides a foundation for understanding radiation enhanced diffusion and induced segregation in CCAs under irradiation.

36 MATERIALS SCIENCE↗

Cylinders and jets in crossflow: Wake formations as a result of varying geometric proximities

The combined flow physics of several canonical flow configurations is experimentally studied. Here, we analyze an array of jets issuing into a crossflow, then immediately navigating past an array of cylinders. This is achieved with a 2 × 3 triangular pattern of jets and symmetric cylinders at three jets to crossflow velocity ratios, enabling near-complete optical access of each jet, with velocities measured by time-resolved particle image velocimetry. Jet trajectories reveal that each configuration adheres to a power-law trend and that greater penetration is achieved by the downstream and confined jets compared to the more conventional upstream one. Recirculation regions of the upstream and downstream jets are nearly independent, with the confined jet encompassing regions of overlap with both. Turbulent statistics reveal the influence of geometric placement and velocity ratio on the time-averaged velocity, anisotropy, and Reynolds stresses incurred by each jet. Galilean decomposition utilizes a supplemental crossflow-only velocity field to delineate the influence of each jet's low- and high-pressure regions on the otherwise uniform stream. Proper orthogonal decomposition suggests that increased jet penetration decreases the number of modes required for truncation in the investigated spanwise plane. Vortex identification algorithms are applied to the reconstructed flow fields, reaffirming that with increasing velocity ratio, the jets generate vortices of their own in similar statistical formations as the cylinders. This investigation provides a foundation to aid future modeling efforts toward characterizing flow physics of importance in designing and passively controlling transverse jets with varying blockage proximities in a crossflow.

Kristo, Paul J. (ORCID:0000000225605175)↗

Mechanical characterization of Bi-2212 composite winding pack samples for high-field superconducting magnet design

Bi₂Sr₂CaCu₂O8−x (Bi-2212) multi-filament round wire is a high-temperature superconductor (HTS) capable of carrying high transport currents, which makes it suitable for high-field magnet applications. However, its weak Ag–Mg sheath leaves it vulnerable to mechanical stress, posing challenges for high-field magnet design. To better understand and improve mechanical stress management in Bi-2212 winding packs, we conducted an experimental study evaluating the axial stress–strain behavior of five winding pack configurations with varying insulation materials, reinforcement strategies, and construction quality. Using uniaxial tensile testing at 77 K, we measured Young’s modulus and Poisson’s ratio for each composition. Our results show that pure alumina braid insulation and co-wind reinforcements significantly enhance stiffness compared to aluminosilicate braids, with more than 2.5 times increased winding pack Young’s modulus. Rule of mixtures analysis further quantified the contribution of non-wire composite components to overall stiffness. These findings highlight the critical role of insulation material selection and reinforcement design in optimizing Bi-2212 coil performance under stress, providing a foundation for improved mechanical models and more reliable high-field HTS magnet designs.

Bi-2212 magnet↗

Hemispherical power asymmetry in intensity and polarization for Planck PR4 data

Abstract One of the foundations of the Standard Model of Cosmology is statistical isotropy, which can be tested, among other probes, through the study of the Cosmic Microwave Background (CMB). However, a hemispherical power asymmetry on large scales has been reported for WMAP and Planck data by different works.The statistical significance is above 3σfor temperature, suggesting a directional dependence of the local power spectrum, and thus a feature beyond the ΛCDM model. With the third release of the Planck data (PR3), a new analysis was performed including the E-mode polarization maps, finding an asymmetry at a modest level of significance. In this work, we perform an asymmetry analysis in intensity and polarization maps for the latest Planck processing pipeline (PR4). We obtain similar results to those obtained with PR3, with a slightly lower significance (2.8% for the Sevem method)for the amplitude of the E-mode local variance dipole as well as a significant variability with the considered mask.In addition, a hint of a possible T-E alignment between the asymmetry axes is found at the level of ∼ 5%. For the analysis, we have implemented an alternative inpainting approach in order to get an accurate reconstruction of the E-modes. More sensitive all-sky CMB polarization data, such as those expected from the future LiteBIRD experiment, are needed to reach a more robust conclusion on the possible existence of deviations from statistical isotropy in the form of a hemispherical power asymmetry.

Astronomy & Astrophysics↗