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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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974 records · Page 27

An Overview of CMIP5 and CMIP6 Simulated Cloud Ice, Radiation Fields, Surface Wind Stress, Sea Surface Temperatures and Precipitation over Tropical and Subtropical Oceans

The potential links between ice water path (IWP), radiation, circulation, sea surface temperature (SST) and precipitation over the Pacific and Atlantic Oceans resulting from the falling ice radiative effects (FIREs) are examined from present day model outputs of CMIP5 and CMIP6. The latter is divided into two subsets with (SON6) and without FIREs (NOS6) as more models with FIREs are included in CMIP6 than in CMIP5. Improvement in floating cloud ice (~20 g m-2) is noticeable over convective regions in CMIP6 relative to CMIP5. The inclusion of FIREs in SON6 subset may contribute to reduce biases of overestimated outgoing longwave radiation and downward surface shortwave and overestimated reflected shortwave at the top of the atmosphere (TOA) by magnitudes of 4?8 W m-2 over convective regions against CERES, compared to NOS6 subset. The reduced biases in radiative fluxes in convective regions stabilize the atmosphere and lead to circulation, SST, cloud and precipitation changes over the trade-wind regions, as seen from improved radiative fluxes (4?15 W m-2), surface wind stress biases, SST (0.2?0.8 K) and precipitation (1 mm day-1) biases. The significant improvement from NOS6 to SON6 leads to improved multi-model means for CMIP6 relative to CMIP5 for radiation fields over the trade wind regions but the degradation over convective zones is attributed to NOS6 subset. The results suggest that other sources of uncertainty and deficiencies in climate models may play significant roles for reducing discrepancies although FIREs, via radiation-circulation coupling, may be one of the factors that help to reduce regional biases.

Jui-Lin F Li

Physics basis for the reference flat-top plasma scenario in the ST–E1 fusion power plant

As part of the U.S. Department of Energy’s Milestone-Based Fusion Energy Development Program, Tokamak Energy has completed the pre-concept design of the ST–E1 fusion power plant. ST–E1 is envisaged to operate in two phases: a pilot plant phase, targeting sustained net power production of 300 - 500 MWe for a duration >1 hr, followed by a commercial power plant phase targeting steady-state operations and a normalised overnight capital cost of ⩽12 000 $\$$/kWe. The design process adopted was highly iterative, integrating all major plant systems and progressing in a phased fidelity approach. At the pre-conceptual stage, the emphasis has been on exploring the design space, identifying the main system-level trade-offs, and making the key decisions that define the overall plant concept, rather than optimising a single operating point. This paper, part of a focused collection detailing the ST–E1 pre-concept design, addresses the development of a series of reference flat-top plasma operating points for the pilot plant phase. A modelling workflow was established to develop and assess candidate plasma design points and explore key dependencies. The workflow includes integrated core plasma modelling, magnetohydrodynamic (MHD) stability assessment, equilibrium generation, scrape-off-layer and exhaust modelling, heating & current drive design and optimisation, and turbulent transport modelling. Using this framework, the impact of several key parameters on the flat-top operating space was investigated, including the density limit, core radiation fraction and divertor power loading, level of external heating and curent drive power and assumed pedestal characteristics. The MHD stability, controllability and micro-stability characteristics of these plasmas were also analysed. These investigations informed the definition of a set of fully non-inductive, flat-top reference operating points that satisfy the high-level ST–E1 mission, including a low and high density case, a case that is stable to resistive wall modes and a case with reduced divertor power loading.

ST–E1

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,

Lunar Nuclear Reactor Neutron Fluence and Gamma Dose Estimates

NASA aims to deploy a fission reactor on the lunar surface by 2030 to generate 100 kWe of power for at least 10 years without maintenance or refueling. To assess system and subsystem survivability according to those requirements, a model of the reactor pallet was created in the radiation transport code MCNP to determine the neutron fluences and gamma doses that the materials and systems would be exposed to. The model was based on the 2025 government design. The model indicated that the control drum motors, Brayton cycle engines, and pipes and valves would be exposed to neutron fluences of 1×10 15 – 1×10 16 n/cm 2 per year and gamma doses ranging from 10 to 500 Mrad per year. The electronics box housing the instrumentation and control elements is expected to receive 1×10 14 – 1×10 15 n/cm 2 per year and gamma doses in the range of 1–5 Mrad per year. These doses necessitate that the control drum motors, Brayton cycle engines, valve components, control electronics, and other components be radiation-hardened (>10 16 n/cm 2 and >10 Mrad gamma dose) or additionally shielded to survive the 10-year lunar mission.

Radiation-Hardened Materials

Subscale Hardware-In-The-Loop Results for Hybrid Electric Turbofan Controls Use Cases

NASA is investigating hybrid electric turbine engine systems for commercial transport aircraft due to the potentially significant improvements hybrid electric technology offers in performance, fuel consumption, and operational and design flexibility. Recently, the technology has been tested at full scale in partnership with industry and advanced to Technology Readiness Level 4. This presentation will focus on a recent subscale hardware-in-the-loop test of an open source turbofan engine model developed by NASA. The Advanced Geared Turbofan 30,000 lbf – electrified (AGTF30-e) engine is used as a reference model to demonstrate control system design and use cases for an example mild hybrid electric system with no large-scale energy storage. This model is run in real-time in NASA’s Hybrid Propulsion Emulation Rig (HyPER) and is used to drive an emulation of the turbomachinery system using subscale electric machines. This dynamic scaled shaft emulation interacts with a subscale (<100 kW) hybrid system consisting of electric machines, motor controllers, and a programmable electronic load. Specific use cases demonstrated include the use of Turbine Electrified Energy Management to improve operation during transients, megawatt-scale power extraction from the AGTF30-e, and power transfer between engine spools. Results related to the effectiveness of hybrid systems are qualitatively compared to results from industry testing.

Hybrid

Validation of Accurate Cryogenic Fluid Vapor-Liquid Boundary Conditions Via Molecular Simulations

Vapor-liquid interfaces drive many important phenomena in cryogenic fluid management, including heat transfer, evaporation, and capillary flow. Design of cryogenic fluid systems, such as propellant storage, requires accurate predictions of fluid behavior, including evaporation rates. Many models have been proposed for heat and mass transfer at vapor liquid interfaces, but the accuracy of these models in the context of cryogenic fluids has not been performed. We use molecular dynamics simulations, which allow for nanometer scale resolution of fluid phenomena, to evaluate the accuracy of a variety of vapor-liquid boundary conditions at evaporating and condensing interfaces. We find that an anisotropic temperature distribution is a critical ingredient for accurate prediction of intensive evaporation and condensation.

Daniel Vigil

Getting Warmer: IceCube Nears Freeze Out

IceCube has recently detected a diffuse population of high-energy neutrinos arising from the Milky Way. We use this high-significance detection to place new limits on dark matter (DM) annihilation to neutrinos with two complementary approaches. The first method uses the background-subtracted Galactic longitude distribution of shower events to place a conservative bound on the DM annihilation cross section that does not rely on any assumed Galactic cosmic ray emission model; the resulting limits on the velocity-averaged annihilation cross section improve upon existing bounds by factors of a few. The second method uses the template-dependent neutrino energy spectra from the Inner Galaxy, inferred under different Galactic cosmic ray emission models. This complementary approach shows that the inferred Galactic neutrino intensities are already sensitive to DM contributions near the thermal-relic benchmark for a range of TeV-scale DM masses, though this comparison is more model-dependent. Our results demonstrate that measurements of diffuse Galactic neutrino emission can be used as a powerful probe of DM annihilation into neutrinos. Future observations with IceCube-Gen2 and KM3NeT will substantially extend this sensitivity, potentially allowing a decisive test of the thermal freeze-out mechanism with Galactic neutrino observations.

Mukhopadhyay, Mainak [Fermilab; Chicago U., KICP;

NASA Space Launch System Artemis I & II Post Flight Ascent Aerothermal Environments Overview

Since 2011 the Aerosciences Branch/EV33 at NASA Marshall Space Flight Center has been involved with the development of ascent external aerothermal environments for the NASA Space Launch System (SLS) Block 1 launch vehicle for the purposes of supporting thermal analysis and the design of thermal protection systems. The SLS Block 1 Artemis I and II launch vehicles successfully launched from Pad39B at NASA Kennedy Space Center on November 16th, 2022 and April 1st, 2026, respectively. Over 70 aerothermal islands, consisting of over 265 operational instruments captured aerodynamic heating and plume induced environments throughout the launch vehicles. Gauges consisted of calorimeters, radiometers, gas temperature probes, pressure transducers, bi-directional pressure probes and thermocouples. Prior to launch, aerothermal design environment models were generated to predict ascent aerodynamic heating and plume induced environments over a design space that covered a range of vehicle trajectories that varied atmospheric, vehicle performance, and off-nominal, engine-out conditions. Post flight reconstruction models were developed for each flight island using the Day-of-Launch (DOL) Best Equivalent Trajectory (BET) that provided freestream conditions and propulsion system boundary conditions. This paper discusses a summary of the ascent aerothermal environments observed during the flights and the respective modelling approaches and the performance of them through comparisons of flight data and predictions.

aerothermodynamics

Petermann Glacier on the Brink: Progress, Challenges and Insights

Petermann Glacier, the largest marine-terminating glacier in northern Greenland based on catchment area and ice discharge, plays a key role in regulating ice discharge from the Greenland Ice Sheet into the Arctic Ocean. With an upstream catchment connected to the ice sheet interior via a deep subglacial canyon, its future stability has major implications for sea level rise. In this review, we synthesize recent advances in understanding Petermann’s dynamics across three critical interfaces: the ice–ocean, ice–atmosphere, and ice–bed boundaries. At the surface, observations show that reanalysis products underestimate air temperatures and melt, while regional climate models diverge significantly in their estimates of surface mass balance, underscoring the need for improved in situ data and models. At the ocean boundary, enhanced basal melting driven by both subglacial runoff and Atlantic water intrusions is identified as the dominant driver of recent mass loss of Petermann Glacier, with continued warming posing a serious threat to the stability of the floating tongue. At the bed, new geophysical synthesis reveals complex geology, likely spatial variability in geothermal heat flux, and the influence of the megacanyon on seasonal hydrology and velocity fluctuations. Petermann’s mass balance has been negative in recent decades without corresponding flow acceleration. However, the glacier has undergone significant calving events, and the current rifting that began in September 2025 highlights its vulnerability. This upcoming calving event underscores the timeliness of this review, as it will put Petermann Glacier’s terminus at its most retreated position since records began in 1923. The anticipated retreat of the ice tongue also reduces buttressing and brings the terminus closer to the grounding zone, and modeling studies suggest that calving within 12 km of the grounding zone could potentially trigger dynamic retreat, accelerating ice discharge, and a doubling of flow speeds. We conclude that improved observations, sustained monitoring of oceanographic and atmospheric properties, and high-resolution modeling are critical to constraining projections of Petermann Glacier’s future and its role in the stability of the Greenland Ice Sheet.

Dominik Fahrner

The impact of aerosol mixing state on immersion freezing: insights from classical nucleation theory and particle-resolved simulations

Immersion freezing, initiated by ice-nucleating particles (INPs) in supercooled aqueous droplets, plays an important role in the formation of ice crystals within clouds. The efficiency of immersion freezing depends strongly on INP composition and, crucially, on the mixing state – how chemical species are distributed across the particle population. Here, we quantify the impact of aerosol mixing state on immersion freezing using a combined theoretical and particle-resolved modeling approach. We derive analytical expressions for the frozen fraction of internally and externally mixed INP populations based on classical nucleation theory, showing that the frozen fraction is sensitive to whether ice-active species are present in all particles or only in a subset of the population. We introduce a multi-species immersion freezing scheme into the particle-resolved model PartMC, using the water activity-based immersion freezing model (ABIFM) to compute freezing probabilities for mixed-composition particles. To improve computational efficiency, we implement a Binned Tau-Leaping algorithm and demonstrate an order-of-magnitude speedup with minimal accuracy loss. Simulations reproduce the analytical trends in limiting cases and extend the analysis to more general aerosol populations, where mixing state continues to exert a substantial control on frozen fraction. Sensitivity analyses across particle size, species type, and cooling condition reveal that the mixing state effect is most pronounced when small amounts of highly efficient INPs are mixed with less efficient materials. These findings underscore the need to represent aerosol mixing state explicitly in models of heterogeneous ice nucleation to reduce uncertainty in cloud-phase partitioning.

54 ENVIRONMENTAL SCIENCES

Nickel-cadmium Battery Cell Reversal from Resistive Network Effects

During the individual cell short-down procedures often used for storing or reconditioning nickel-cadmium (Ni-Cd) batteries, it is possible for significant reversal of the lowest capacity cells to occur. The reversal is caused by the finite resistance of the common current-carrying leads in the resistive network that is generally used during short-down. A model is developed to evaluate the extent of such a reversal in any specific battery, and the model is verified by means of data from the short-down of a f-cell, 3.5-Ah battery. Computer simulations of short-down on a variety of battery configurations indicate the desirability of controlling capacity imbalances arising from cell configuration and battery management, limiting variability in the short-down resistors, minimizing lead resistances, and optimizing lead configurations.

Zimmerman, A. H.

Computational simulation of asymmetric phase transformation in cracked Li₇La₃Zr₂O₁₂: Variant selection and chemo-mechanical implications

Coupling between microcracks and phase transformation in ion-conducting ceramics can jointly affect mechanical responses and ion transport. In this work we investigate the cubic-to-tetragonal phase transformation in Li₇La₃Zr₂O₁₂ in the presence of a microcrack under hydrostatic loading and quantify its implications for crack-tip stress concentration and Li-ion transport using phase-field and molecular dynamics simulations. The phase transformation exhibits a strong asymmetry between hydrostatic tension and compression. Under tension, the crack edge nucleates one tetragonal variant that amplifies the crack-tip stress intensity and promotes crack opening. Under compression, the crack tip nucleates a different tetragonal variant that enhances the stress-induced crack-closure tendency. Effective Li diffusivity analysis shows faster transport degradation under compression due to accelerated transformation kinetics, exposing a trade-off between mechanical stability and ionic conductivity. These results highlight the intertwined nature of cracking, phase transformation, and ionic transport in ion-conducting oxides and provide mechanistic insights into chemo-mechanical degradation of solid electrolytes.

36 MATERIALS SCIENCE

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

Collective excitations and low-energy ionization signatures of relativistic particles in silicon detectors

Abstract Solid-state detectors with a low energy threshold have several applications, including searches of non-relativistic halo dark-matter particles with sub-GeV masses. When searching for relativistic, beyond-the-Standard-Model particles with enhanced cross sections for small energy transfers, a small detector with a low energy threshold may have better sensitivity than a larger detector with a higher energy threshold. In this paper, we calculate the low-energy ionization spectrum from high-velocity particles scattering in a dielectric material. We consider the full material response including the excitation of bulk plasmons. We generalize the energy-loss function to relativistic kinematics, and benchmark existing tools used for halo dark-matter scattering against electron energy-loss spectroscopy data. Compared to calculations commonly used in the literature, such as the Photo-Absorption-Ionization model or the free-electron model, including collective effects shifts the recoil ionization spectrum towards higher energies, typically peaking around 4–6 electron-hole pairs. We apply our results to the three benchmark examples: millicharged particles produced in a beam, neutrinos with a magnetic dipole moment produced in a reactor, and upscattered dark-matter particles. Our results show that the proper inclusion of collective effects typically enhances a detector’s sensitivity to these particles, since detector backgrounds, such as dark counts, peak at lower energies.

Physics

Heat Flow and Thermal History of the Moon

An analysis was made of current heat flow data and thermal models of lunar evolution which satisfy the diverse information that has accumulated on internal processes.

Ye A Lyubimova

LAI Assimilation Schedules to Constrain Uncertain Cultivars and Soils in CERES-Maize

In anticipation of large-domain crop model applications where precise local configuration and calibration is not possible, we describe benefits and potential drawbacks of employing a crop pest module to achieve leaf area index (LAI) assimilation into a high performing CERES-Maize crop model configuration at a field experiment site in Perry, Iowa. Simulation experiments explore the use of MODIS satellite-derived LAI to constrain and adjust LAI to counter imprecise cultivar and soil configurations often occurring in the absence of high-quality local information. Simulations using single-day, window, and continuous LAI replacement across 5 cultivars and 2 soil calibration approaches for nine corn rotation years from 2004 to 2020 led to different yield outcomes and reverberations throughout the field environment. Evaluating variance and mean bias, results indicate minimal interventions in early vegetative and grain-filling stages were more beneficial than use of continuous LAI adjustments, as they minimized disruptions to the internal resource balances governing plant stresses and grain production. LAI adjustment was particularly helpful in constraining growth related to uncertain thermal unit requirements and leaf tip appearance rates (P1 and PHINT cultivar parameters, respectively). Findings underscore the need to assimilate additional state variables to ensure internal biophysical coherence. This approach shows promise for applications spanning wider domains with prediction time pressure where detailed configuration, more complex assimilation methods, or recalibration of crop model parameters may not be practical.

Phenology

Phonon screening and dissociation of excitons at finite temperatures from first principles

The properties of excitons, or correlated electron–hole pairs, are of paramount importance to optoelectronic applications of materials. A central component of exciton physics is the electron–hole interaction, which is commonly treated as screened solely by electrons within a material. However, nuclear motion can screen this Coulomb interaction as well, with several recent studies developing model approaches for approximating the phonon screening of excitonic properties. While these model approaches tend to improve agreement with experiment, they rely on several approximations that restrict their applicability to a wide range of materials, and thus far they have neglected the effect of finite temperatures. Here, we develop a fully first-principles, parameter-free approach to compute the temperature-dependent effects of phonon screening within the ab initio GW -Bethe–Salpeter equation framework. We recover previously proposed models of phonon screening as well-defined limits of our general framework, and discuss their validity by comparing them against our first-principles results. We develop an efficient computational workflow and apply it to a diverse set of semiconductors, specifically AlN, CdS, GaN, MgO, and SrTiO 3 . We demonstrate under different physical scenarios how excitons may be screened by multiple polar optical or acoustic phonons, how their binding energies can exhibit strong temperature dependence, and the ultrafast timescales on which they dissociate into free electron–hole pairs.

Science & Technology - Other Topics

A novel digital lifecycle for Material‐Process‐Microstructure‐Performance relationships of thermoplastic olefins foams manufactured via supercritical fluid assisted foam injection molding

Abstract This research significantly enhances the applicability of thermoplastic olefins (TPOs) in the automotive industry using supercritical N 2 as a physical foaming agent, effectively addressing the limitations of traditional chemical agents. It merges experimental results with simulations to establish detailed material‐process‐microstructure‐performance (MP2) relationships, targeting 5–20% weight reductions. This innovative approach labeled digital lifecycle (DLC) helps accurately predict tensile, flexural, and impact properties based on the foam microstructure, along with experimentally demonstrating improved paintability. The study combines process simulations with finite element models to develop a comprehensive digital model for accurately predicting mechanical properties. Our findings demonstrate a strong correlation between simulated and experimental data, with about a 5% error across various weight reduction targets, marking significant improvements over existing analytical models. This research highlights the efficacy of physical foaming agents in TPO enhancement and emphasizes the importance of integrating experimental and simulation methods to capture the underlying foaming mechanism to establish material‐process‐microstructure‐performance (MP2) relationships. Highlights Establishes a material‐process‐microstructure‐performance (MP2) for TPO foams Sustainably produces TPO foams using supercritical (ScF) N 2 with 20% lightweighting Shows enhanced paintability for TPO foam improved surface aesthetics Digital lifecycle (DLC) that predicts both foam microstructure and properties DLC maps process effects & microstructure onto FEA mesh for precise prediction

Engineering