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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Intrinsic kinetics of water-inhibited ultra-lean methane oxidation over PtPd-Mg/ θ -Al 2 O 3 catalyst

Here, this study develops intrinsic methane oxidation kinetics for ultra-lean methane conditions in the presence of water over a highly active and stable PtPd–Mg/θ-Al 2 O 3 catalyst. Comprehensive laboratory experiments were conducted over a wide range of methane concentrations (150–1200 ppm CH 4 ), water contents (1–5% H 2 O), and industrially relevant space velocities (80,000 ≤ GHSV ≤ 160,000 h -1 ). These systematic experiments informed a two-dimensional, axisymmetric, multiscale reactor model that was used to develop and validate methane oxidation kinetics under practically relevant conditions, including non-isothermal operation and high conversion regimes. Combined experimental and modeling results revealed significant intraparticle diffusion resistance and transport-induced reaction exotherm at elevated temperatures, which limited catalyst utilization despite high intrinsic activity. These transport effects were explicitly incorporated into the reactor model, enabling accurate estimation of intrinsic kinetic parameters without reliance on conventional effectiveness-factor corrections. The resulting kinetic model successfully captured both kinetically controlled and mass-transfer-limited regimes and reliably predicted CH 4 conversion across broad ranges of temperature, methane concentration, and water content

Heat and mass transfer limitations↗
DOE OSTI2024

Computing the solubility of argon and xenon in molten sodium chloride and potassium chloride salts

Molten salt reactors (MSRs) offer significant advancements in nuclear reactor safety and efficiency by operating at higher temperatures and lower pressures compared to traditional reactors. A critical aspect of MSR operation involves understanding the solubility of fission byproducts, particularly noble gases, in the molten salts used. This study employs molecular dynamics (MD) simulations to compute Henry’s law constants and enthalpies of solvation for argon and xenon in molten sodium chloride (NaCl) and potassium chloride (KCl). We developed a new pairwise potential for the noble gas and salt interactions based on first principles calculations. We then used this potential to calculate Henry’s law constants of the two gases in the molten salts, which were modeled using both a rigid ion model (RIM) and a polarizable ion model (PIM). The solubility calculations, performed using the Widom insertion method, show qualitative agreement with limited experimental data, highlighting the temperature dependence and greater solubility of both gases in KCl compared to NaCl. Additionally, free volume analysis elucidated the role of available space within the molten salts in governing solubility trends. Our findings suggest that PIM trajectories provide more reliable predictions for noble gas solubility than RIM due to their accurate density representation. Furthermore, these results enhance understanding of gas solubility in MSR environments, and the methods can be readily extended to other systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Pool boiling heat transfer evaluation of next-generation dielectric fluid: Opteon™ 2P50

The growing use of artificial intelligence has led to heavy thermal loads and high heat dissipation rates in data centers. Conventional air-cooled technologies are not able to fulfill these requirements. To overcome these challenges, two-phase immersion cooling (2PIC) has emerged as one of the leading technologies for high power-density chips. 2PIC increases the heat dissipation rate and efficiency of the system while reducing the footprint of the cooling equipment. A fluid with adequate dielectric properties, a suitable normal boiling temperature to maintain chip temperatures, and good material compatibility, is desired for 2PIC system. In this study, the pool boiling heat transfer of a new developmental dielectric fluid, Opteon™ 2P50, was experimentally investigated. The heat transfer coefficients at various heat fluxes (20–150 kW/m 2 ) and the critical heat flux were measured using a smooth aluminum surface. Compared with HFE-7100, Opteon™ 2P50 shows higher heat transfer coefficient (up to 59% higher) and a slightly lower value of critical heat flux (around 5.9% lower). The modified Cooper correlation with the optimized leading constant resulted in reliable prediction accuracy with a 5.3% mean absolute error percentage. Overall, these results indicate that the new dielectric fluid provides similar thermal performance to some legacy fluids.

2P50↗
DOE OSTI2024

Quantification of grain boundary effects on the geometrically necessary dislocation density evolution and strain hardening of polycrystalline Mg 4Al using in situ tensile testing in scanning electron microscope and HR-EBSD

In situ tensile testing in a scanning electron microscope (SEM) in conjunction with high-resolution electron backscatter diffraction (HR-EBSD) under load was used to characterize the evolution of geometrically necessary dislocation (GND) densities at individual grain boundaries as a function of applied strain in a polycrystalline Mg—4Al alloy. The increase in GND density was investigated at plastic strains of 0 %, 0.6 %, 2.2 %, 3.3 % from the area including 76 grains and correlated with (i) geometric compatibility between slip systems across grain boundaries, and (ii) plastic incompatibility. We develop expressions for the grain boundary GND density evolution as a function of plastic strain and plastic incompatibility, from which uniaxial tensile stress-strain response of polycrystalline Mg—4Al are computed and compared with experimental measurement. The findings in this study contribute to understanding the mechanisms governing the strain hardening response of single-phase polycrystalline alloys and more reliable prediction of mechanical behaviors in diverse microstructures.

Geometrically necessary dislocations↗
DOE OSTI2024

Temperature and Composition Dependence Modeling of Viscosity and Electrical Conductivity of Low-Activity Waste Glass Melts

The development of models that accurately relate the properties of a glass melt to its temperature and composition is important for glass formulation, melter control, and modeling the melt flow, refractory corrosion, and production rate. Using a database consisting of more than 4,000 data points measured between 900 °C and 1250 °C for over 600 unique low-activity waste glass compositions, we developed models for the melt viscosity and electrical conductivity. Models based on the Gaussian process regression approach outperformed models based on the Vogel–Fulcher–Tammann equation according to four standard metrics and yielded reliable prediction intervals. The models found primarily linear effects between properties and individual components, except for the effect of the Na 2 O mass fraction on the electrical conductivity. The effects were found to be consistent with current theories on physical processes involved with those properties.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Influence of fabrication on microstructure and heat affected zone width in weldments of nuclear reactor pressure vessel steel

Advanced manufacturing routes such as electron beam welding and powder metallurgy with hot isostatic pressing are increasingly used across energy and aerospace industries, where the reliable prediction of weld behavior and heat affected zone (HAZ) evolution is critical. This study examines how fabrication routes and post-weld heat treatments influence phase distribution, crystallite size, microstrain, and dislocation density in nuclear reactor pressure vessel steels using synchrotron X-ray diffraction (SXRD). Retained austenite occurs only in samples that did not undergo austenitization, whereas an austenitizing heat treatment fully eliminates retained austenite and produces a more uniform microstructure across the weldment in terms of phase fraction, dislocation density, and microstrain. The Rosenthal solution underestimates the HAZ width for powder metallurgy samples. A newly proposed modified Rosenthal solution, reducing density by accounting for porosity, matches the SXRD-measured HAZ width with a 0.65% error. Structure–property correlations reveal that dislocation density correlates strongly with nanohardness in homogenous microstructures, while in heterogenous weldments nanohardness is further influenced by the presence of dissimilar phase boundaries. These findings provide new insight into the thermal and microstructural response of powder metallurgy fabricated steels and offer a framework for optimizing welding procedures and heat treatments in advanced manufacturing applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Radiative and continuum dampings of reversed shear Alfvén eigenmodes and perturbative analysis limitations for tokamaks

A careful theoretical analysis of the excitation of Alfvén eigenmodes (AEs), such as TAE (toroidicity-induced AE) and RSAE (reversed shear AE), by superalfvenic energetic particles is required for reliable predictions of energetic ion relaxation in present day fusion experiments. This includes the evaluation of different AE damping mechanisms including radiative and continuum dampings which are the focus of this study. A recent comprehensive benchmark of different eigenmode solvers including gyrokinetic, gyrofluid and hybrid magenetohydrodynamics (MHD) has shown that employed models may have deficiencies when addressing some of them (Taimourzadeh et al., Nucl. Fusion, vol. 59, 2019, 066006). Here, in this paper, we are studying the radiative and continuum dampings of RSAEs in details which were missing in hybrid NOVA/NOVA-C calculations to prepare a NOVA-C package with a substantial upgrade. Both dampings require the finite Larmor radius (FLR) corrections to AE mode structures to be accounted for. Accurately calculating different damping rates and understanding their parametric dependencies, we resolve the limitation coming out of the perturbative approach. In particular, here, the radiative damping is included perturbatively, whereas the continuum damping is computed non-perturbatively. Our comparison leads to the conclusion that the non-perturbative treatment of the unstable RSAE modes is needed to find the agreement with the gyrokinetic calculations. We expect that the RSAE mode structure modification plays a dominant role in determining the RSAE stability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Improving Bond Dissociations of Reactive Machine Learning Potentials through Physics-Constrained Data Augmentation

In the field of computational chemistry, predicting bond dissociation energies (BDEs) presents well-known challenges, particularly due to the multireference character of reactive systems. Many chemical reactions involve configurations where single-reference methods fall short, as the electronic structure can significantly change during bond breaking. As generating training data for partially broken bonds is a challenging task, even state-of-the-art reactive machine learning interatomic potentials (MLIPs) often fail to predict reliable BDEs and smooth dissociation curves. By contrast, simple and inexpensive physics-based models, such as the well-established Morse potential, do not suffer from any such limitations. This work leverages the Morse potential to improve reactive MLIPs by augmenting the training data set with inexpensive Morse data along the dissociation pathways. Further, this physics-constrained data augmentation (PCDA) approach results in MLIPs with smooth bond dissociation curves as well as near coupled-cluster level BDEs, all without requiring any expensive multireference quantum mechanical calculations. A case study for methane combustion demonstrates how the PCDA approach can improve an existing reactive MLIP, namely, ANI-1xnr. In conclusion, not only are the BDEs and bond dissociation curves for all radicals and molecules significantly improved compared to ANI-1xnr but the PCDA-trained MLIP retains the reliability of ANI-1xnr when performing reactive molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Ripening of Rh Nanoparticle Catalysts in Reverse Water–Gas Shift via a Data-Driven Model Combining Physics, Theory, and Experiment

Degradation via sintering is an ongoing challenge that impedes the broad commercial success of supported metallic nanoparticle catalysts. To mitigate degradation via informed catalyst design and process operations, here we aim to disambiguate the underlying mechanisms of sintering by combining theory and experiment in a quantitative framework. While mechanistic sintering models exist, they only model a single sintering pathway, even though multiple sintering mechanisms can occur simultaneously or dominate at different stages of the process. Data-driven machine learning models have emerged as a means to represent complex processes through data regression. However, machine learning models have very large data needs and lack mechanistic insights due to their black-box encoding. To develop an interpretive model of catalyst degradation via sintering, we constructed a hybrid model combining mechanistic “physics-based” models and data-driven methods to obtain both reliable predictions and mechanistic insights regarding experimentally observed sintering phenomena. Focusing on nanoparticle sintering in the Rh–TiO 2 catalyst for the reverse water–gas shift (RWGS) reaction, the hybrid model couples a mechanistic term for Ostwald ripening with energy values calculated via density functional theory (DFT) with a parametric, data-driven discrepancy function term for unmodeled mechanisms. The hybrid model is trained using Bayesian inference with data collected from small-angle X-ray scattering (SAXS) in situ experiments wherein average nanoparticle diameter versus time was measured at three relevant operating temperatures. The calibrated hybrid model results show that an Ostwald ripening-only model parameterized with fixed DFT energies does not fully capture the time and temperature dependence of the SAXS-observed sintering kinetics, and that an additional functional contribution, or DFT energy calibration, is required to reconcile simulation and experiment. Analysis of the hybrid-model error confirms that the hybrid model outperforms both the purely mechanistic and purely data-driven alternatives in terms of expected predictive accuracy for time-evolving average particle sizes. Furthermore, the results support the hypothesis that the Ostwald ripening mechanism is less important for explaining the sintering phenomena as operating temperature increases under an assumed fixed DFT parameterization. This could be explained in one of two ways: either latent, unmodeled sintering mechanisms dominate at higher temperatures, or the DFT uncertainty increases with temperature. The proposed modeling approach directly links theory to experiments and simulations via a statistical hybrid modeling framework and can be extended to other catalytic systems to improve predictive models and mechanistic understanding.

Bayesian hybrid modeling↗
DOE OSTI2025

Advancing simulations of coupled electron and phonon nonequilibrium dynamics using adaptive and multirate time integration

Electronic structure calculations in the time domain provide a deeper understanding of nonequilibrium dynamics in materials. The real-time Boltzmann equation (rt-BTE), used in conjunction with accurate interactions computed from first principles, has enabled reliable predictions of coupled electron and lattice dynamics. However, the timescales and system sizes accessible with this approach are still limited, with two main challenges being the different timescales of electron and phonon interactions and the cost of computing collision integrals. As a result, only a few examples of these calculations exist, mainly for two-dimensional (2D) materials. Here we leverage adaptive and multirate time integration methods to achieve a major step forward in solving the coupled rt-BTEs for electrons and phonons. Relative to conventional (non-adaptive) time-stepping, our approach achieves a 10x speedup for a target accuracy, or greater accuracy by 3–6 orders of magnitude for the same computational cost, enabling efficient calculations in both 2D and bulk materials. This efficiency is showcased by computing the coupled electron and lattice dynamics in graphene up to ~100 ps, as well as modeling ultrafast lattice dynamics and thermal diffuse scattering maps in bulk materials (silicon and gallium arsenide). In addition to improved efficiency, our adaptive method can resolve the characteristic rates of different physical processes, thus naturally bridging different timescales. This enables simulations of longer timescales and provides a framework for modeling multiscale dynamics of coupled degrees of freedom in matter. Our work opens new opportunities for quantitative studies of nonequilibrium physics in materials, including driven lattice dynamics with phonons coupled to electrons, spin, and other degrees of freedom.

Yao, Jia [California Institute of Technology (CalT↗
DOE OSTI2026

Characterization of volcanic tuff pores pre- and post-underground nuclear detonation using ultra-small and small angle neutron scattering

The ability to accurately model the subsurface transport of radionuclides is fundamental to the remote detection and characterization of underground nuclear explosion (UNE) events. Developing more sophisticated transport models presents a significant opportunity to enhance monitoring capabilities, particularly in the reliable prediction of signature migration. Experimentally determined characterization of geologic materials associated with transport properties is the pertinent base information for such robust model development and calibration. Here, we report results from an unprecedented study demonstrating changes to the pore and fracture network structures in geological materials in response to UNEs over nanometer to micrometer length scales. Volcanic tuffs of five different lithological formations from pre- and post-UNE environments were collected from the Nevada National Security Site. Combined ultra-small and small-angle neutron scattering techniques were used to characterize the tuff pore structure. The results demonstrate measurable differences in the specific surface area and porosity of samples pre- and post-shot from texturally similar lithological formations, indicating that pore properties can serve as a direct physical signature of a UNE. The results also provide experimentally determined transport parameters in support of advanced model development through the integration of gas migration, hydrodynamic simulations, and geologic framework models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Chaos as the cause of randomness in tearing mode onset times in DIII-D ITER baseline scenario plasmas

The first evidence of widespread chaotic plasma dynamics relevant to the onset of disruptive tearing modes is found in DIII-D tokamak discharges. This evidence is obtained by calculating positive maximal Lyapunov exponents from Mirnov signals using the Rosenstein algorithm, implying the chaotic growth and/or rotation of magnetohydrodynamic modes in DIII-D [Luxon, Nucl. Fusion 42, 614 (2002)] plasmas. Such chaotic dynamics offer an explanation for the random tearing mode onset times previously observed in ITER baseline scenario discharges. Further, the Lyapunov timescales associated with this chaos could inhibit reliable prediction of tearing mode onset beyond the angular momentum confinement timescale; this constraint should inform the design of plasma control systems on ITER.

Chaotic dynamics↗
DOE OSTI2025

Theoretical tools for neutrino scattering: interplay between lattice QCD, EFTs, nuclear physics, phenomenology, and neutrino event generators

Maximizing the discovery potential of increasingly precise neutrino experiments will require an improved theoretical understanding of neutrino-nucleus cross sections over a wide range of energies. Low-energy interactions are needed to reconstruct the energies of astrophysical neutrinos from supernovae bursts and search for new physics using increasingly precise measurement of coherent elastic neutrino scattering. Higher-energy interactions involve a variety of reaction mechanisms including quasi-elastic scattering, resonance production, and deep inelastic scattering that must all be included to reliably predict cross sections for energies relevant to DUNE and other accelerator neutrino experiments. Refined nuclear interaction models in these energy regimes will also be valuable for other applications, such as measurements of reactor, solar, and atmospheric neutrinos. This manuscript discusses the theoretical status, challenges, required resources, and path forward for achieving precise predictions of neutrino-nucleus scattering and emphasizes the need for a coordinated theoretical effort involved lattice QCD, nuclear effective theories, phenomenological models of the transition region, and event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Turbulent drifts of impurity ions as an explanation for anomalous radial transport in the far-SOL of DIII-D

Abstract Successful fusion reactor operation relies on minimal core contamination by impurities, otherwise too much power may be radiated and harm performance. This requires reliable predictions of impurity transport from the scrape-off layer (SOL) into the core, beyond the traditional ‘anomalous’ diffusion approach. We report a set of far-SOL tungsten transport simulations that demonstrate the role of turbulent drifts on radial impurity transport. A turbulent plasma background is simulated using the gyrokinetic SOL code Gkeyll. Tungsten ions are followed within the plasma background using only their drifts. We find that tungsten tends to travel radially outwards with velocities between v r = 300–1200 m s −1 primarily due to polarization drift. We also extract an anomalous radial diffusion coefficient that varies from D r anom = 5–20 m 2 s −1 . These results are compared to and agree with previous interpretive modeling results. We also show how the turbulent polarization drift can transport some tungsten ions from the wall inwards with effective pinch velocities up to 10 000 m s −1 . We conclude that turbulent drifts are a likely explanation for historically anomalous radial impurity transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Dependence of divertor turbulence on plasma density and current in TCV

To reliably predict the distribution of heat and particle fluxes at the target plates of tokamaks, a comprehensive understanding of turbulence throughout the entire Scrape-Off-Layer (SOL) is imperative. This study examines divertor turbulence systematically across a broad parameter range on the TCV tokamak, including variations in magnetic field direction, plasma current I p ∈ [140,320] kA, edge safety factor q 95 ∈ [2.6,4.7] and Greenwald fraction f G ∈ [0.18,0.6]. The TCV X-point Gas Puff Imaging (GPI) system is used to measure 2D filament properties in the inner and outer divertor region. The fluctuation levels in the divertor are found to strongly increase with density (to 80% over most of the SOL) while remaining insensitive to I p . The previously identified divertor-localized filaments (DLF), located on the bad curvature side of the outer divertor leg, are found to be a common feature on TCV, while no filaments are observed in the PFR. DLFs are present over most of the parameter space and in both field directions. However, they are absent, or appear only closer to the target, for sufficiently large Λ div ≳ 10 or q 95 ≳ 3.7. Across both I p and f G scans, some clear trends with Λ div are found for divertor filament sizes and velocities, and with target fall-off lengths of density and heat flux profiles at the outer target. This study provides important experimental insights to turbulent transport in the divertor also for comparison with self-consistent, turbulence simulations and extrapolation to future reactor conditions.

cross-field transport↗
DOE OSTI2024

Drug-induced kidney injury: challenges and opportunities

Abstract Drug-induced kidney injury (DIKI) is a frequently reported adverse event, associated with acute kidney injury, chronic kidney disease, and end-stage renal failure. Prospective cohort studies on acute injuries suggest a frequency of around 14%–26% in adult populations and a significant concern in pediatrics with a frequency of 16% being attributed to a drug. In drug discovery and development, renal injury accounts for 8 and 9% of preclinical and clinical failures, respectively, impacting multiple therapeutic areas. Currently, the standard biomarkers for identifying DIKI are serum creatinine and blood urea nitrogen. However, both markers lack the sensitivity and specificity to detect nephrotoxicity prior to a significant loss of renal function. Consequently, there is a pressing need for the development of alternative methods to reliably predict drug-induced kidney injury (DIKI) in early drug discovery. In this article, we discuss various aspects of DIKI and how it is assessed in preclinical models and in the clinical setting, including the challenges posed by translating animal data to humans. We then examine the urinary biomarkers accepted by both the US Food and Drug Administration (FDA) and the European Medicines Agency for monitoring DIKI in preclinical studies and on a case-by-case basis in clinical trials. We also review new approach methodologies (NAMs) and how they may assist in developing novel biomarkers for DIKI that can be used earlier in drug discovery and development.

Connor, Skylar (ORCID:0000000233479180)↗
DOE OSTI2026

Compact representation and long-time extrapolation of real-time data for quantum systems using the ESPRIT algorithm

Representing real-time data as a sum of complex exponentials provides a compact form that enables both denoising and extrapolation. As a fully data-driven method, the Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithm is agnostic to the underlying physical equations, making it broadly applicable to various observables and experimental or numerical setups. In this work, we consider applications of the ESPRIT algorithm primarily to extend real-time dynamical data from simulations of quantum systems. We evaluate ESPRIT's performance in the presence of noise and compare it to other extrapolation methods. We demonstrate its ability to extract information from short-time dynamics to reliably predict long-time behavior and determine the minimum time interval required for accurate results. We discuss how this insight can be leveraged in numerical methods that propagate quantum systems in time, and we show how ESPRIT can predict infinite-time values of dynamical observables, offering a purely data-driven approach to characterizing quantum phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Weak-charge radius of 40 Ar: From CREX constraints to CE⁢𝜈⁢NS sensitivity

Despite significant theoretical efforts, the CREX-PREX dilemma remains unresolved, preventing the reliable prediction of neutron (or weak-charge) radii that, besides their intrinsic nuclear-structure interest, often serve to quantify the impact of nuclear uncertainties in searches for new physics. Coherent elastic neutrino-nucleus scattering is a clean and attractive portal to new physics, whose sensitivity may be impacted by such nuclear uncertainties. In this paper I use CREX as the basis, together with a strong calcium-argon correlation, to provide a robust baseline for the weak radius of 40 Ar : 𝑅$^{40}_{wk}$ = 3.452 ± 0.028 (stat) ± 0.022 (syst) fm. Here, the weak radius of argon is an observable, highly relevant to ongoing and future liquid-argon campaigns, that encodes the loss of coherence at small momentum transfers.

39 ≤ A ≤ 58↗