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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Characterizing the combined impact of nucleation-driven precipitation and secondary passivation on carbon mineralization

The evolution of mineral reactive surface area is one of the primary phenomena controlling the progression and extent of mineral carbonation. The CO 2 mineralization begins with nucleation of crystals that provide initial surface area for subsequent growth of the mineral. However, many reactive transport models (RTMs) for CO 2 mineralization do not include the nucleation process. The few RTMs that do include it are yet to be validated against experimental data. Similarly, many RTMs ignore passivating effects of the secondary mineral, which coats the surface of the dissolving mineral, slow down the reaction process, and reduce the total extent of carbonation. Furthermore, the combined impact of nucleation and passivation on carbon mineralization is yet to be properly characterized. In this study, we consider the coupled effects of passivation and nucleation on the mineralization extent. The nucleation-driven precipitation model relies on the formation of nuclei to provide a surface area for crystal growth, while a new model is proposed to account for passivation effects. Our analysis shows that (i) omission of nucleation leads to overestimation of extent of mineralization, and (ii) omission of passivation leads to overestimation of host rock reactivity. The model was evaluated via comparison with CO 2 mineralization data from the literature and models that ignore these processes. We observed that including nucleation and passivation lead to closer predictions of the CO 2 mineralization extent. Therefore, this study highlights the importance of including the coupled nucleation-driven precipitation and secondary passivation in RTMs. Here, the findings from the study can be applied in various scientific and engineering applications such as petroleum production, cement carbonation, CO 2 sequestration, chemical weathering, and concrete degradation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Operando FTIR investigation of salt dynamics in Li-ion batteries during fast charging

Li-ion batteries, when charged at fast-charging rates ($>$2C), suffer from reduced lifetimes and can undergo catastrophic failure. During high-rate charging, Li-ions are unable to rapidly transport through high-loading electrodes ($>$4 mAh cm −2 ). This results in unequal charge distributions, potentials, and utilization of the active material, which can lead to Li plating. Li-ion concentration polarization, in which Li-ions deplete in the anode and accumulate in the cathode during charging, precedes Li plating. An operando FTIR-ATR graphite/NMC cell developed in this research captured Li-ion concentration polarization in real-time. During fast charging, decreases in Li-ion concentration ($>$95%) were measured at the back of the anode. This is the first verification of complete Li-ion depletion within the anode at high C-rates. The measurements also showed graphite stage transition. A P2D model was developed for comparison to the operando measurements. The measurements agreed with the model in some cases, but disparities existed at high C-rates and loadings. In the experiment, the Li-ion concentration often failed to recover to 1.2 M until several hours after charging, whereas the model Li-ion concentration rapidly recovered. The contrast between the model and experiment results indicates that further investigation is required to improve understanding of Li-ion concentration dynamics during fast charging.

25 - ENERGY STORAGE↗
DOE OSTI2026

Dwarf Galaxies at Cosmic Noon: New JWST Constraints on Satellite Models and Subhalo Tidal Evolution

The advent of JWST has revolutionized the study of faint satellite galaxies at z ≳ 1, enabling statistical constraints on galaxy evolution and the galaxy–halo connection in a previously unexplored mass and redshift regime. We compare satellite abundances at 1 < z < 3.5 from recent JWST observations with predictions from cosmological dark-matter-only zoom-in simulations. We identify and quantify several sources of biases that can impact theoretical satellite counts, finding that assumptions about subhalo tidal evolution introduce the largest uncertainty in predictions for the satellite mass function. Using a flexible galaxy disruption model, we explore a range of disruption scenarios, spanning hydrodynamically motivated and idealized prescriptions, to bracket plausible physical outcomes. We show that varying galaxy durability can change the predicted satellite mass functions by a factor of ∼3.5. The JWST data and our fiducial model are consistent within 1σ–2σ across the full redshift (1 < z < 3.5) and stellar mass (M⋆ > 10 7 M ⊙ ) range probed. We find evidence that subhalos are at least as long-lived as predicted by hydrodynamic simulations. Our framework will enable robust constraints on the tidal evolution of subhalos with future observations. This work presents the first direct comparison between cosmological models and observations of the high-redshift satellite population in this low-mass regime. These results showcase JWST’s emerging power to test structure formation in the first half of the Universe in a new domain and to constrain the physical processes driving the evolution of low-mass galaxies across cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Neutrinos and Gamma Rays from Seyfert Galaxies Constrain the Properties of Coronal Turbulence

The TeV neutrino signal observed by IceCube from the active galactic nucleus NGC 1068 can probe its innermost coronal regions. If these neutrinos originate from hadrons accelerated within a magnetized turbulent corona, their intensity and spectrum depend on the turbulent magnetic field strength and turbulence coherence scale. The gamma rays accompanying neutrino production are absorbed in this optically thick environment, in a way that depends sensitively on the size of the corona. By a joint fit of the IceCube and Fermi-LAT observations, we translate the multimessenger signal from NGC 1068 and the tentative signal from NGC 7469 into quantitative constraints on coronal properties. NGC 1068, with a significant TeV neutrino excess, favors a compact, strongly magnetized corona with a large turbulence coherence length relative to the coronal size. NGC 7469, with two ∼100 TeV neutrino events, points instead to a somewhat larger corona with much smaller coherence length and high magnetization, but a very small fraction of energy in nonthermal protons. We obtain the diffuse flux from a population of Seyfert galaxies identical to either NGC 1068 or NGC 7469. Finally, we consider a third scenario, motivated by the spectral break observed in the diffuse neutrino flux at tens of TeV, with coronal properties intermediate between the two point-source-inspired models. To enable detailed comparisons with the IceCube and electromagnetic observations, we release our model predictions in a GitHub repository.

Testagrossa, Federico [Deutsches Elektronen-Synchr↗
DOE OSTI2024

Short-Term Probabilistic Solar Forecasting via Reinforcement Learning over ECMWF

In this paper, we present an innovative reinforcement learning approach for short-term solar forecasting, leveraging data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The methodology begins with the application of the System Advisor Model (SAM) to transform various ECMWF numerical weather prediction members into predictive photovoltaic power generation. To enhance the precision of deterministic forecasting, we introduce a dynamic model selection algorithm based on Q-learning. This algorithm dynamically identifies and utilizes the most accurate ensemble member for forecasting purposes. Furthermore, we employ a support vector regression surrogate model with a Gaussian distribution to generate probabilistic forecasts, providing a holistic view of solar energy generation uncertainty. To expedite the training process and make it more practical for real-world applications, we integrate a rolling update workflow. This innovative workflow reduces the training period from months to a mere 19 days, making our method highly efficient. Numerical results of the case study show that in comparison to benchmark models, the proposed method improves the deterministic and probabilistic solar forecasting accuracy by up to 40.84% and 48.42%, respectively.

ensemble forecasting↗
DOE OSTI2025

Perturbative model for the saturation of energetic-particle-driven modes limited by self-generated zonal modes

We present a simplified energy-conserving approach to incorporate wave–wave nonlinear effects within the framework commonly used to describe wave–particle nonlinearities. In particular, the effects of zonal mode (ZM) generation on the determination of the saturation amplitude of energetic particle (EP)-driven Alfvénic instabilities is studied. The model assumes that the zonal perturbations grow at a rate twice that of the original (pump) wave, consistent with a beat-driven (or force-driven) generation mechanism. The evolution and saturation of the mode amplitude are investigated both analytically and numerically within our reduced model assumptions, in both the collisionless and scattering-dominated regimes. These studies underscore the crucial role of sources and sinks in capturing the impact and the role of beat-driven zonal perturbations on mode evolution. In the realistic case of saturation set by sources and sinks, we discuss the role of a finite amplitude ZM in reducing microturbulent particle scattering, thus limiting the energy source for the resonant mode. We then discuss comparisons between the model’s predictions and simulation results. The model reproduces key features observed in gyrokinetic simulations as the reduction in saturated mode amplitude and the onset of wave–wave nonlinear effects as functions of mode growth rate and amplitude. Thanks to its simplicity, it can be readily implemented into codes based on reduced models, thereby improving their predictive capability for strongly driven instabilities.

Alfvén eigenmodes↗
DOE OSTI2026

A fast and robust computational modeling approach for density and shape predictions in powder metallurgy hot isostatic pressing

Powder metallurgy hot isostatic pressing (PM-HIP) is an advanced manufacturing process that produces near-net-shape parts with high material utilization and uniform microstructures. PM-HIP is frequently used for producing small-scale parts with complicated geometries and is potentially economical for producing large-scale parts. However, excessive post-HIP shape distortions can reduce its effectiveness and economic advantage, especially for larger parts. A PM-HIP computational model can predict and help mitigate these distortions. However, due to complex deformation mechanisms and thermo-mechanical coupling present in PM-HIP processes, these non-linear computational models sometimes become numerically unstable. The numerical instabilities in these models can lead to very slow convergence or no convergence at all, which often translates to slow and unreliable models. These limitations are more pronounced in large models with complicated geometries. Hence, in this work, an alternative modeling approach is presented that improves numerical stability and computational performance. The presented approach achieves these improvements through approximating the fully coupled thermo-mechanical PM-HIP model as a decoupled model and adding inertial damping to the model’s mechanical part. In conclusion, a comparison with the fully coupled model indicated a slight dip in prediction accuracy (<5% error) but significant improvements in numerical stability (>20 times larger time step size) and computational performance (5-10 times speed-up with less computational resource usage) when using the presented approach.

Hot isostatic pressing↗
DOE OSTI2024

Impact of ionization and transport on pedestal density structure in DIII-D and Alcator C-Mod

Abstract This paper investigates the role of ionization on the pedestal structure using both measurements and modeling for H-mode plasmas on DIII-D and Alcator C-Mod to enhance our ability to predict pedestal behavior in future pilot plants. The impact of the neutral penetration depth on the pedestal density is investigated using dimensionally matching hydrogen and deuterium DIII-D H-mode discharges at low and high electron density. The DIII-D Lyman- α diagnostic measurements show that hydrogen neutrals penetrate deeper inside the plasma on both the high field and low field side, while the pedestal electron density structure is similar for both isotopes. However, as the opaqueness increases we observe that the pedestal density gradient becomes stiff, similar to prior observations on DIII-D and C-Mod (Mordijck 2020 Nuclear Fusion 60 082006). In addition, these results also confirm prior measured and modeled poloidal asymmetries in neutral densities, indicating that to make transport predictions, 2D neutral modeling is necessary. The first direct validation of SOLPS-ITER for the measured brightness, emissivity and neutral densities for three different confinement regimes on C-Mod is introduced. The SOLPS-ITER model shows good agreement, within the constrains of the model for all regimes. In addition, a comparison of SOLPS-ITER modeling for DIII-D and C-Mod shows that as opaqueness increases, the role of divertor fueling and thus poloidal asymmetries in the neutral density profiles decreases. Based on these experimental and modeling results we estimate the size of a potential particle pinch using typical values for the diffusion coefficient for both DIII-D and C-Mod H-mode discharges.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Application of an Empirical Density Law via Python for Aqueous Plutonium Chloride Systems for MCNP6

Criticality safety models for aqueous plutonium chloride systems often contain a significant bias due to assumptions in material compositions. These systems are currently modeled as a fictitious metal-water mixture because little is known about the true solution density. Furthermore, no predictive density tools or capabilities for modeling aqueous plutonium chloride systems are approved for use at Los Alamos National Laboratory. Recent density measurements of this ternary system (PuCl 3 -HCl-H 2 O) have allowed for the development of a more realistic density law, which is applied in this work via an empirical method based in Python. This tool, entitled PuCS (Plutonium Chloride Solution tool) may be used to determine solution density and composition based on the plutonium content, acid content, and temperature for MCNP6 inputs. PuCS has been found to predict density within 2% of experimental data. In conclusion, MCNP6 calculations have found that crediting minimal amounts of free acid (0.5 M) may correspond to a ~12% decrease in peak reactivity in comparison to current modeling methods.

42 ENGINEERING↗
DOE OSTI2025

Dense granular flows with MFIX-Exa

This report extends the linear spring dashpot collision model the discrete element method available in MFIX-Exa to include static a static tangential friction force. Additionally, two rolling friction models frequently used in the literature are also implemented. The governing equations are provided with an emphasis on the new terms. The new model is validated by comparison to existing experimental data of single particle oblique collisions. The model is then tested on three dense granular flow problems: the formation of static piles, the discharge from a flat-bottom hopper and the self-induced granular Rayleigh-Taylor instability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

The stellar origins of 96 Zr excesses in presolar graphites from the Murchison meteorite

Context. Zirconium-96 is a stable isotope that can be synthesized under different neutron-rich nucleosynthetic conditions. Astrophysical models predict its production to occur in various stellar environments: from low-to-intermediate-mass asymptotic giant branch (AGB) stars to massive stars and core-collapse supernovae. Aims. Detections of 96Zr excesses, in combination with other isotopic measurements from presolar grains can provide unique constraints on its stellar origin. Presolar grains are microscopic particles found in primitive Solar System materials, which formed in stellar winds and supernova ejecta. The isotopic composition of each grain can provide us a snapshot of the nucleosynthetic processes that took place during the parent star’s lifetime. Methods. In this study, we measured the stable isotopes of C, N, O, Mo, Zr, and Ru in high-density presolar graphite grains from the Murchison meteorite and found four grains that contain positive isotopic anomalies in 96 Zr carried by their internal subgrains. We analyzed multi-element isotopic datasets from each grain to explore the source of the observed 96 Zr excesses. Results. Comparisons with stellar models indicate that two grains likely condensed in an intermediate-mass AGB star with initial metallicity of Z ≤ 0.014. Their 96 Zr/ 94 Zr ratios also match those predicted for born-again AGB stars undergoing a very late thermal pulse and rapidly accreting white dwarfs. After comparing the relative populations of the aforementioned dust-producing stars, we propose rapidly accreting white dwarfs as a new, and more likely, stellar source for one of the presolar grains. The remaining two grains could have originated in the supernova ejecta of massive stars, due to correlated excesses in the p-nuclides, 92, 94 Mo. Thus, grains with 96 Zr anomalies can have a variety of stellar origins, in agreement with theoretical studies. Conclusions. Our study highlights the importance of multi-element analysis in constraining the types of stars where presolar grains have condensed. These data will help improve our understanding of various nucleosynthesis processes in different stellar phases.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

2032 and 2036 risk enhancement from NEOs in the Taurid stream: Is there a significant coherent component to impact risk?

Impact risk is normally quantified by summing the product of the probability of an event and some measure of its consequences over the set of all possible events. The probability factor is considered to be more objective and is based on the size frequency distribution of Near Earth objects (NEOs) and an implicit assumption of randomness, which can be described as “stochastic risk”. Impact frequency does change with time, however, and there have been episodes in the deep geological past when the flux has been much higher. The hypothesis of “coherent catastrophism” suggests large variations on shorter timescales. It postulates the existence of a “Taurid resonant swarm” (TRS) of debris associated with Comet Encke that is stabilized by Jupiter and in a 7:2 resonance with it. The hypothetical cluster orbits in the broad Taurid stream, which crosses Earth's orbit twice a year at its nodes. Whereas the most extreme and fanciful versions of coherent catastrophism in recent geologic history have been comprehensively refuted, the possibility of a significant component of coherent (time-dependent) risk, associated with non-random correlated events, remains. This paper incorporates recently published data from observational campaigns associated with the Taurid stream. There is no evidence for objects in the Taurid stream that are above the global catastrophe threshold, but the possibility of a few large objects and a significant population of objects the size of the Chelyabinsk or Tunguska bodies has not been eliminated. Eyewitness accounts and comparison of airburst models to ground truth suggest that the Tunguska object was a Beta Taurid. The Tunguska event is probably an outlier when compared to the size frequency distributions under stochastic assumptions, but if there is a significant coherent component it may be representative of events that take place far more frequently, and risk assessments may have underestimated the contribution from airbursts. If so, the Earth will experience increased risk from objects this size, peaking in November 2032 and June 2036. We recommend targeted survey campaigns during these hypothetical TRS node crossings to quantify the population, search for potentially hazardous objects, and identify imminent impactors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Uncertainty quantification and optimization of precipitating hydrometeor parameters for winter precipitation in a cloud microphysics scheme

The precipitating hydrometeor parameters used in cloud microphysics schemes carry inherent uncertainties. The quantification of these uncertainties, together with parameter optimization, can significantly improve precipitation forecasts. This study investigates the effects of 13 parameters in the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) microphysics scheme, which define the hydrometeor characteristics such as fall velocity–diameter and mass–diameter relationships, as well as the shape parameter of the drop size distribution for precipitating particles such as rain, snow, and graupel on simulated winter precipitation. A comparison between the model's pre-defined parameters and observations from the International Collaborative Experiments for the PyeongChang 2018 Olympic and Paralympic winter games (ICE-POP 2018) field campaign reveals that the fall velocity–diameter relationship for rain, the mass–diameter relationships for snow and graupel, and the shape parameters for all precipitating particles in the WDM6 scheme deviate from the median values observed by the two-dimensional video disdrometer (2DVD). To quantify parameter sensitivities, a perturbed parameter ensemble (PPE) of 256 simulations was conducted within parameter ranges constrained by 2DVD observations for three winter precipitation cases. Bayesian optimization was then applied to identify parameter sets that minimized the root mean square error (RMSE) for each case, achieving reductions of up to 30.2 %. These results demonstrate that ensemble-based uncertainty quantification and parameter optimization can help identify key parameters and provide a pathway to improving precipitation simulation performance. In addition, measurement sites can be strategically selected based on regions that show high sensitivity to variations in hydrometeor characteristic parameters.

Bayesian optimization↗
DOE OSTI2025

Slender-body approach for computing second-order wave loads in the frequency domain

This work presents a slender-body approach to evaluate the second-order wave loads acting on a floating structure in the frequency domain. The approach is in the same spirit as the common use of Morison’s equation to approximate the wave loads without solving the radiation/diffraction problem. To do so, we employ Rainey’s equation, which can be seen as an extension of the inertial part of Morison’s equation to include nonlinear effects. We introduce modifications to Rainey’s formulation in order to evaluate wave kinematics at the mean body position instead of the original approach of considering instantaneous displacements. We also propose a simple approximation to partially account for wave scattering effects on the second-order loads based on the analytical solution of a surface-piercing bottom-mounted vertical circular cylinder. Though limited to structures composed of cylinders, this slender-body approach is orders of magnitude faster than computing second-order wave coefficients with a radiation/diffraction code. We implemented this approach for difference-frequency (slow drift) loads in an open-source frequency-domain floating wind turbine model. We present comparisons against results obtained with radiation/diffraction theory for three reference floating wind turbine designs: the OC3-Hywind spar, the OC4-DeepCwind semisubmersible, and the VolturnUS-S semisubmersible. In general, the results show that the proposed slender-body approach with the correction to approximate wave scattering effects provides useful estimations of the difference-frequency wave loads and the resulting motions of the floater.

17 WIND ENERGY↗
DOE OSTI2026

Multiplicity dependence of K*(892) ± production in pp collisions at $\sqrt{s}$ = 13 TeV

The first results of K*(892) ± production at midrapidity (|y| < 0.5) in pp collisions at $\sqrt{s}$= 13 TeV as a function of the event multiplicity are presented. The K*(892) ± has been reconstructed via its hadronic decay channel K*(892) ± → π ± + K$^0_{\textrm{S}}$ using the ALICE detector at the LHC. For each multiplicity class, the differential transverse momentum (p T ) spectrum, the mean transverse momentum ⟨p T ⟩, the p T -integrated yield (dN/dy), and the ratio of the K*(892) ± to K$^0_{\textrm{S}}$ yields are reported. These are consistent with previous K*(892) 0 resonance results with a higher level of precision. Comparisons with phenomenological models such as PYTHIA6, PYTHIA8, EPOS-LHC, and DIPSY are also discussed. For the first time, a significant K*(892) ± /K$^0_{\textrm{S}}$ suppression in pp collisions is observed at a 7σ level passing from low to high multiplicity events. The ratios of the p T -differential yields of K*(892) ± and K$^0_{\textrm{S}}$ in high and low multiplicity events are also presented along with their double ratio. For p T ≲ 2 GeV/c this double ratio persists below unity by more than 3σ suggesting that the suppression affects mainly low p T resonances. The measured decreasing trend of the K*(892) ± /K$^0_{\textrm{S}}$ ratio with increasing multiplicity, which in heavy-ion collisions is typically attributed to the rescattering of decay particles of the short-lived resonances, is reproduced by the EPOS-LHC model without the use of hadronic afterburners.

Hadronic resonance production↗
DOE OSTI2026

Response to the comments on creep-induced elemental redistribution at grain boundaries of 304L stainless steel – An experimental evidence for diffusional creep mechanisms

Sandström and He reanalyzed our 304L creep data (Acta Materialia 121137, 2025) at 10 MPa/750 °C and proposed that: (i) primary dislocation creep dominates based on the ϕ -model; (ii) measured creep rates deviate from published 304H data and Coble creep predictions using literature grain boundary (GB) diffusivity; and (iii) creep-induced elemental redistribution (CIER) could be explained by dislocation emission/absorption (DEAA) and GB creep (GBC), as opposed to diffusional creep. Here, in this response, we propose that: (i) the creep behavior at 15 MPa/750 °C—for which we demonstrated CIER—is only partially captured by the ϕ -model; (ii) direct comparison between 304L and 304H creep data is inappropriate due to carbides in 304H, and Coble creep predictions estimated from CALPHAD-based bulk diffusivity span experimental rates; and (iii) CIER exhibits distinct fingerprint for diffusional creep characterized by anisotropy and stress orientation dependence whereas neither DEAA nor GBC have been mechanistically substantiated.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Tracking Local pH Dynamics during Water Electrolysis via In-Line Continuous Flow Raman Spectroscopy

The performance of electrochemical devices, which play a critical role in decarbonization efforts, is often governed by proton-coupled electron transfer reactions at the electrode–electrolyte interface. These reactions are highly sensitive to the complex and dynamic microenvironment present at the electrode surface. However, characterizing this environment─particularly monitoring interfacial pH and its evolution under reaction conditions─remains challenging, necessitating the development of advanced analytical tools. Here, in this study, we introduce in-line continuous flow Raman spectroscopy (CFRS) as a spectroelectrochemical platform for quantifying interfacial pH swings generated during water-splitting. By monitoring phosphate ion speciation and controlling the hydrodynamics with a flow cell, we measure pH swings as a function of current density, flow rate, and distance from the electrode. Comparison with theoretical models reveals the impact of bulk pH, boundary layer thickness, and bubble dynamics at high current densities. Collectively, these findings establish CFRS as a platform for quantitatively investigating pH dynamics, offering critical insights for advancing electrochemical energy conversion technologies.

Marquez, Raul A. [Univ. of Texas, Austin, TX (Unit↗
DOE OSTI2025

X-ray absorption spectroscopy measurements of radiatively ionized argon gas

X-ray absorption spectroscopy is a diagnostic tool that can characterize the temperature and ionization state of a plasma. This technique requires experiments to characterize the platform, careful data calibration, and comparison with atomic models to understand the plasma parameters. We performed ionizing radiation wave experiments at the OMEGA Laser Facility that used an ∼ 80 eV X-ray source to heat an Argon (Ar) gas cell at fill pressures of 3 atm. To diagnose the Ar plasma, we used a capsule backlighter offset 10 mm from the gas cell, to produce X-rays that were absorbed by the ionized Ar gas. The absorption analysis was calibrated using the significant line structure in the backlighter spectrum, which served as independent energy fiducials enabling definitive measurements of a 50-eV shift in the energy of the Ar K-edge due to ionization. We compare the measured absorption spectra to two independent atomic models, PrismSPECT and SCRAM, and show that the observed K-edge shift in the heated gas is consistent with ionization up to Ar 4+ and temperatures of 10 eV.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗