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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quartz-hosted inclusions and embayments reveal storage, fluxing, and ascent of the Mesa Falls Tuff, Yellowstone

Quartz-hosted glasses from the Mesa Falls Tuff provide a geochemical window into the pre-eruptive magmatic system from one of Yellowstone's largest-volume caldera-forming eruptions. H 2 O and CO 2 concentrations, along with major and trace elements, were measured in both fully enclosed glass inclusions and partially enclosed embayments in the same quartz crystals. Major elements are largely consistent between the inclusions and embayments, except for K 2 O and Na 2 O. Of note, K 2 O is enriched by ~1 wt.% in embayment interiors relative to inclusions. Most trace elements are also enriched in the embayment interiors compared to inclusions from the same crystals. Fractionation trends of trace elements are consistent with ~30-60% crystallization. Quartz-hosted glass inclusions preserve 3.1±0.9 wt.% H 2 O and 493±227 ppm CO 2 whereas embayment interiors have 0.9±0.1 wt.% H 2 O and 399±229 ppm CO 2 . The CO 2 is roughly similar, but the distinct ~2 wt.% discrepancy between inclusion and embayment interior H 2 O contents may have been produced by CO 2 fluxing sourced from underplated Yellowstone basalts. H 2 O gradients within embayments are flat in their interiors and modified by sharp positive gradients near embayment exteriors which were produced by post-eruptive rehydration. CO 2 gradients occur as gently sloping concentration gradients that extend inward 150 to 250 μm from the embayment exterior. Finally, finite-difference 1D and 2D diffusion modeling indicates the distribution of H 2 O and CO 2 in embayments was produced by slow, fluid-saturated decompression that preceded rapid ascent during the caldera-forming eruption.

2D diffusion modeling↗
DOE OSTI2017

Turbulent mixing and removal of ozone within an Amazon rainforest canopy

Simultaneous profiles of turbulence statistics and mean ozone mixing ratio are used to establish a relation between eddy diffusivity and ozone mixing within the Amazon forest. A one–dimensional diffusion model is proposed and used to infer mixing time scales from the eddy diffusivity profiles. Data and model results indicate that during daytime conditions, the upper (lower) half of the canopy is well (partially) mixed most of the time and that most of the vertical extent of the forest can be mixed in less than an hour. During nighttime, most of the canopy is predominantly poorly mixed, except for periods with bursts of intermittent turbulence. Even though turbulence is faster than chemistry during daytime, both processes have comparable time scales in the lower canopy layers during nighttime conditions. Nonchemical loss time scales (associated with stomatal uptake and dry deposition) for the entire forest are comparable to turbulent mixing time scale in the lower canopy during the day and in the entire canopy during the night, indicating a tight coupling between turbulent transport and dry deposition and stomatal uptake processes. Because of the significant time of day and height variability of the turbulent mixing time scale inside the canopy, it is important to take it into account when studying chemical and biophysical processes happening in the forest environment. In conclusion, the method proposed here to estimate turbulent mixing time scales is a reliable alternative to currently used models, especially for situations in which the vertical distribution of the time scale is relevant.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Thermal diffusion, exhaust gas recirculation and blending effects on lean premixed hydrogen flames

Thermodiffusively-unstable lean premixed hydrogen flames are investigated using two-dimensional direct numerical simulation employing finite-rate chemical kinetics. Three databases are generated focussing on the inclusion of the Soret effect, the recirculation of exhaust gas, and blending with methane. A simple rescaling of a classic thermal diffusion model is presented and shown to mimic multicomponent diffusion with very low computational cost and little-to-no loss in accuracy. It is also shown that a previously developed model for mean local flame speeds in lean premixed hydrogen flames can still be used provided Soret effects are taken into account in one-dimensional calculations. The addition of exhaust gas to the unburned mixture is found to enhance thermodiffusive instability; the primary mechanism for this was shown to be the highly-efficient third-body nature of water, with the reduction of adiabatic flame temperature a second-order effect. Again, the existing mean local flame speed model proved sufficient. Finally, blending with methane was found to reduce the thermodiffusive response of the flame, more so than the existing model suggests, despite adjustment of the fuel Lewis number; an adapted model is presented to account for this.

08 HYDROGEN↗
DOE OSTI2020

Insights into the Water Transport Mechanism in Polymeric Membranes from Neutron Scattering

Polymeric membranes are ubiquitous in transport applications including gas separation, water desalination, solid-state batteries, and fuel cells. The transport mechanism in certain classes of membranes is well understood. It is generally believed that polymeric membranes used in gas separation follow the solution-diffusion model. However, the transport mechanism in other membranes such as the ones used in water desalination is less clear as both the solution-diffusion and hydrodynamic models have been proposed. In this contribution, we study the structure as well as the water and polymer dynamics of several polymeric membranes using small-angle and quasi-elastic neutron scattering. We demonstrate that on the scale of a few nanometers, water appears to diffuse through a desalination membrane at a rate comparable to bulk water, while water diffuses at a rate that is a factor of 2 slower in an anion-exchange membrane. These results illustrate the importance of studying both the structure and dynamics of membrane materials and have important implications in understanding the transport mechanisms that differentiate the different types of polymeric membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties

Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a computational framework that integrates evolutionary algorithms with three-dimensional diffusion models for property-driven molecular generation. The method operates through adaptive evolutionary optimization, where population-based selection guides the generation process toward desired property landscapes. EvoDiffMol supports both unconstrained molecular design and scaffold-constrained generation that preserves fixed substructures while optimizing complementary regions. Comprehensive evaluation demonstrates exceptional performance, achieving the highest drug-likeness score (0.94) among all compared state-of-the-art methods while maintaining excellent validity, uniqueness, and novelty. Beyond single property optimization, the framework demonstrates flexible multi-property optimization capabilities, simultaneously controlling multiple molecular descriptors including synthetic accessibility, lipophilicity, topological polar surface area, and clinically relevant ADMET properties such as cardiotoxicity (hERG) and intestinal permeability (Caco-2). This adaptability spans from simple descriptors to practical pharmaceutical endpoints without requiring complete model retraining. The framework achieves precise control over target property values, generating molecules with properties closely matching specified targets for both single and multiple descriptors. Scaffold-constrained experiments preserve fixed molecular cores while maintaining effective property optimization. The three-dimensional representation offers advantages in maintaining structural validity during iterative optimization, with potential for geometry-aware applications in materials science and drug discovery.

3D molecular generation↗
DOE OSTI2015

Numerical simulation of cathode plasma dynamics in magnetically insulated vacuum transmission lines

A novel algorithm for the simulation of cathode plasmas in particle-in-cell codes is described and applied to investigate cathode plasma evolution in magnetically insulated transmission lines (MITLs). The MITL electron sheath is modeled by a fully kinetic electron species. Electron and ion macroparticles, both modeled as fluid species, form a dense plasma which is initially localized at the cathode surface. Energetic plasma electron particles can be converted to kinetic electrons to resupply the electron flux at the plasma edge (the “effective” cathode). Using this model, we compare results for the time evolution of the cathode plasma and MITL electron flow with a simplified (isothermal) diffusion model. Simulations in 1D show a slow diffusive expansion of the plasma from the cathode surface. But in multiple dimensions, the plasma can expand much more rapidly due to anomalous diffusion caused by an instability due to the strong coupling of a transverse magnetic mode in the electron sheath with the expanding resistive plasma layer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks

In many complex networked systems such as online social networks, at any given time, activity originates at certain nodes and subsequently spreads on the network through influence. To model the spread of influence in such a scenario, we consider the problem of identification of influential entities in a complex network when nodal activation can happen through two different mechanisms. The first mode of activation is due mechanisms intrinsic to the node. The second mechanism is through the influence of connected neighbors. In this work, we present a simple probabilistic formulation that models such self-evolving systems where information diffusion occurs primarily because of the intrinsic activity of users and the spread of activity occurs due to influence. We provide an algorithm to mine for the influential seeds in such a scenario by modifying the well-known influence maximization framework with the independent cascade diffusion model. We provide small motivating examples to provide an intuitive understanding of the effect of including the intrinsic activation mechanism. We sketch a proof of the submodularity of the influence function under the new formulation and demonstrate the same with larger graphs. We then show by means of additional experiments on a real-world twitter dataset how the formulation can be applied to real-world social media datasets. Finally we derive a computationally efficient centrality metric that takes into account, both the mechanisms of activation and provides for an accurate as well as computationally efficient alternative approach to the problem of identifying influencers under intrinsic activation.

Visweswara Sathanur, Arun↗
DOE OSTI2021

Improved performance of a near-field thermophotovoltaic device by a back gapped reflector

Various spectral control techniques can be applied to improve the performance of a thermophotovoltaic (TPV) device. For example, a back surface reflector (BSR) is a common structure to improve the performance of TPV devices. A conventional metal BSR structure enhances the photogeneration rate by increasing the absorption probability of photons via back surface reflections, affording a second chance for absorption. However, the effects of surface passivation and external luminescence introduced by BSR structures have been previously ignored, which potentially decreases the performance of TPV devices. Recently, a back gapped reflector (BGR) structure was proposed to greatly improve the performance of far-field TPV devices by reducing imperfect reflections at the semiconductor-metal interface. In the present work, the performance improvement on a thin-film, near-field InAs TPV device with a BGR is investigated, comparing its performance to that with a conventional metal BSR. Surface passivation conditions are also investigated to further improve the performance of TPV devices with back reflectors. Further, the output power and efficiency are calculated using an iterative model combining fluctuational electrodynamics and the full drift diffusion model. For the well-passivated condition, when the BSR is replaced by the BGR, the calculated conversion efficiency of the near-field TPV was improved from 16.4% to 21% and the output power was increased by 10%. Finally, the absorption of the back reflectors and external luminescence loss are analyzed to explain the performance improvement.

external luminescence↗
DOE OSTI2016

Exciton dynamics at a single dislocation in GaN probed by picosecond time-resolved cathodoluminescence

We investigate the dynamics of donor bound excitons (D°X{sub A}) at T = 10 K around an isolated single edge dislocation in homoepitaxial GaN, using a picosecond time-resolved cathodoluminescence (TR-CL) setup with high temporal and spatial resolutions. An ∼ 1.3 meV dipole-like energy shift of D°X{sub A} is observed around the dislocation, induced by the local strain fields. By simultaneously recording the variations of both the exciton lifetime and the CL intensity across the dislocation, we directly assess the dynamics of excitons around the defect. Our observations are well reproduced by a diffusion model. It allows us to deduce an exciton diffusion length of ∼24 nm as well as an effective area of the dislocation with a radius of ∼95 nm, where the recombination can be regarded as entirely non-radiative.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Antimony diffusion in CdTe

Group V dopants may be used for next-generation high-voltage cadmium telluride (CdTe) solar photovoltaics, but fundamental defect energetics and kinetics need to be understood. Here, antimony (Sb) diffusion is studied in single-crystal and polycrystalline CdTe under Cd-rich conditions. Diffusion profiles are determined by dynamic secondary ion mass spectroscopy and analyzed with analytical bulk and grain-boundary diffusion models. Slow bulk and fast grain-boundary diffusion are found. Density functional theory is used to understand formation energy and mechanisms. Lastly, the theory and experimental results create new understanding of group V defect kinetics in CdTe.

14 SOLAR ENERGY↗
DOE OSTI2019

Ab initio study of phosphorus effect on vacancy-mediated process in nickel alloys – An insight into Ni 2 Cr ordering

The development of long range order in nickel-chromium alloys is of great technological interest but the kinetics and mechanisms of the transformation are poorly understood. The present research utilizes a combined computational and experimental approach to elucidate the mechanism by which phosphorus accelerates the ordering rate of stoichiometric Ni 2 Cr in Ni-Cr alloys. A series of Ni-33%Cr-x%P samples (in atomic percent) were fabricated with phosphorus concentrations, x = <0.005–0.1 at.% and aged between 373 and 470 °C for times up to 3000 h. The first-principles modeling considers fcc Ni with dilute P as a reasonable approximation for the complex Ni-Cr-P alloy system. Calculation results show a pronounced enhancement of vacancy transport by vacancy-solute pair diffusion via consecutive exchange and rotation jumps of vacancies associated with the phosphorus atom. The energy barriers of these two migration paths are at least 0.35 eV lower than that of vacancy-atom exchange in pure Ni solvent. The analytical diffusion model predicts enhanced solvent diffusion by 2 orders of magnitude for 0.1 at.% P at 400–500 °C. The model prediction is in good agreement with the evolution of micro-hardness. We characterize the micro-hardness result by a kinetic ordering model, showing a significant decrease of the activation energy of ordering transformation. These results help gauge the risk of industrial alloys developing long range order which increases strength but degrades ductility and toughness. Specifically, minor alloying additions that bind with excess vacancies and lower the vacancy migration barrier can greatly accelerate hardening via Ni 2 Cr precipitation.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Stochastic models for surface diffusion of molecules

We derive a stochastic model for the surface diffusion of molecules, starting from the classical equations of motion for an N-atom molecule on a surface. The equation of motion becomes a generalized Langevin equation for the center of mass of the molecule, with a non-Markovian friction kernel. In the Markov approximation, a standard Langevin equation is recovered, and the effect of the molecular vibrations on the diffusion is seen to lead to an increase in the friction for center of mass motion. This effective friction has a simple form that depends on the curvature of the lowest energy diffusion path in the 3N-dimensional coordinate space. We also find that so long as the intramolecular forces are sufficiently strong, memory effects are usually not significant and the Markov approximation can be employed, resulting in a simple one-dimensional model that can account for the effect of the dynamics of the molecular vibrations on the diffusive motion.

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

GrainPaint: A multi-scale diffusion-based generative model for microstructure reconstruction of large-scale objects

Simulation-based approaches to microstructure generation can suffer from a variety of limitations, such as high memory usage, long computational times, and difficulties in generating complex geometries. Generative machine learning models present a way around these issues, but they have previously been limited by the fixed size of their generation area. Here, we present a new microstructure generation methodology leveraging advances in inpainting using denoising diffusion models to overcome this generation area limitation. We show that microstructures generated with the presented methodology are statistically similar to grain structures generated with a kinetic Monte Carlo simulator, SPPARKS.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Measuring the Local Diffusion Coefficient with H.E.S.S. Observations of Very High-Energy Electrons

The HAWC Collaboration has recently reported the detection of bright and spatially extended multi-TeV gamma-ray emission from Geminga, Monogem, and a handful of other nearby, middle-aged pulsars. The angular profile of the emission observed from these pulsars is surprising, in that it implies that cosmic-ray diffusion is significantly inhibited within ~25 pc of these objects, compared to the expectations of standard Galactic diffusion models. This raises the important question of whether the diffusion coefficient in the local interstellar medium is also low, or whether it is instead better fit by the mean Galactic value. Here, we utilize recent observations of the cosmic-ray electron spectrum (extending up to ~20 TeV) by the H.E.S.S. Collaboration to show that the local diffusion coefficient cannot be as low as it is in the regions surrounding Geminga and Monogem. Instead, we conclude that cosmic rays efficiently diffuse through the bulk of the local interstellar medium. Among other implications, this further supports the conclusion that pulsars significantly contribute to the observed positron excess and provides strong evidence for spatially varying diffusion coefficients throughout the Milky Way.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Semi-Analytical Simulation and Optimization of AlGaAs/GaAs p-i-n Quantum Well Solar Cell

This paper deals with a AlGaAs/GaAs p-i-n quantum well solar cell. The doped region are based on AlGaAs semiconductor while the intrinsic region “I” contain multi quantum well (MQW) system AlGaAs/GaAs. A semi-analytical model in the intrinsic region and numerical drift-diffusion model in doped regions are combined to extract the total current density of the cell versus voltage. The current-voltage (J-V) characteristics are generated for the AM1.5 solar spectrum. The effect of the Aluminum molar fraction x (Al{sub x}Ga{sub 1–x}As), the number, the width, the depth of the wells and barriers in the “i” layer and the doping densities on the electrical outputs of the solar cell are also presented. The optimized solar cell reached a conversion efficiency of 28.72% with a short circuit current density of 36.9 mA/cm{sup 2} and an open circuit voltage of 0.97 V.

14 SOLAR ENERGY↗
DOE OSTI2012

Validation of CONTAIN-LMR code for accident analysis of sodium-cooled fast reactor containments

CONTAIN-LMR 1 is an analytical tool for the containment performance of sodium cooled fast reactors. In this code, the modelling for the sodium fire is included: the oxygen diffusion model for the sodium pool fire, and the liquid droplet model for the sodium spray fire. CONTAIN-LMR is also able to model the interaction of liquid sodium with concrete structure. It may be applicable to different concrete compositions. Testing and validation of these models will help to qualify the simulation results. Three experiments with sodium performed in the FAUNA facility at FZK have been used for the validation of CONTAIN-LMR. For pool fire tests, calculations have been performed with two models. The first model consists of one gas cell representing the volume of the burn compartment. The volume of the second model is subdivided into 32 coupled gas cells. The agreement between calculations and experimental data is acceptable. The detailed pool fire model shows less deviation from experiments. In the spray fire, the direct heating from the sodium burning in the media is dominant. Therefore, single cell modeling is enough to describe the phenomena. Calculation results have reasonable agreement with experimental data. Limitations of the implemented spray model can cause the overestimation of predicted pressure and temperature in the cell atmosphere. The ability of the CONTAIN-LMR to simulate the sodium pool fire accompanied by sodium-concrete reactions was tested using the experimental study of sodium-concrete interactions for construction concrete as well as for shielding concrete. The model provides a reasonably good representation of chemical processes during sodium-concrete interaction. The comparison of time-temperature profiles of sodium and concrete shows, that the model requires modifications for predictions of the test results. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2011

Long-time integration methods for mesoscopic models of pattern-forming systems

Spectral methods for simulation of a mesoscopic diffusion model of surface pattern formation are evaluated for long simulation times. Backwards-differencing time-integration, coupled with an underlying Newton-Krylov nonlinear solver (SUNDIALS-CVODE), is found to substantially accelerate simulations, without the typical requirement of preconditioning. Quasi-equilibrium simulations of patterned phases predicted by the model are shown to agree well with linear stability analysis. Simulation results of the effect of repulsive particle-particle interactions on pattern relaxation time and short/long-range order are discussed.

97 MATHEMATICS AND COMPUTING↗