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At least 1,315 records · Page 73
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NASA NTRSDate not supplied

Extinction of the Stagnation Point Diffusion Flame: Effect of Conductive Heat Loss into Solid Interior

The flammability boundary of a solid is U-shaped with the ordinate as ambient oxygen percentage (or total pressure) and the abscissa represents flow velocity, gravity level, stretch rate, etc. The left side of the flammability boundary is the quenching branch, and the right side is the blow-off branch. Quenching is due to a weak flame whose heat release from combustion cannot overcome the excessive heat losses from, for example, radiation. Blow-off is due to a short gas residence time that is smaller than the chemical reaction time (traditionally referred to as the small Damköhler number effect). For thick solids, the heat conduction into the solid interior has a long transient after ignition before the solid temperature reaches the steady state. During this slow transient, there is excessive (i.e. more than that at the steady state) gas phase heat conduction into the solid interior. From the viewpoint of the quasi-static gaseous flame, this is an additional heat loss that will affect the gas flame's flammability. In this work, a previously developed one-dimensional axisymmetric stagnation-point diffusion flame model is extended to account for the excessive heat loss into the solid beyond the steady burning state. A non-dimensional excessive conductive heat loss parameter Ψ is defined in the paper to account for the transient solid effect. For each Ψ, the gas phase is considered reaching a quasi-steady state. Extensive numerical computations have been performed to determine the extinction boundary and the characteristics of near-limit flames. The U-shaped flammability boundary is now a series of boundaries with Ψ as a parameter. Flame structures under the same environment condition but with different Ψ are compared. For a given oxygen ambient, the extinction boundary Ψ vs stretch rate is an inverted U-shape. The boundary consists of a blowoff branch and a radiative quenching branch. Extensive computed data including flame and pyrolysis temperatures, burning rate, flame standoff distance, species concentration, and reaction rate are presented along the extinction boundaries. Heat balance analysis is performed for both the gas phase and the gas-solid interface. Along the extinction boundary, the relative importance of conduction, convection, radiation, and chemical reaction are analyzed in detail.

Stagnation point diffusion flame↗
DOE OSTI2025

Generative learning for slow manifolds and bifurcation diagrams

In dynamical systems characterized by separation of time scales, the approximation of so called “slow manifolds”, on which the long term dynamics lie, is a useful step for model reduction. Initializing on such slow manifolds is a useful step in modeling, since it circumvents fast transients, and is crucial in multiscale algorithms (like the equation-free approach) alternating between fine scale (fast) and coarser scale (slow) simulations. In a similar spirit, when one studies the infinite time dynamics of systems depending on parameters, the system attractors (e.g., its steady states) lie on bifurcation diagrams (curves for one-parameter continuation, and more generally, on manifolds in state parameter space. Sampling these manifolds gives us representative attractors (here, steady states of ODEs or PDEs) at different parameter values. Algorithms for the systematic construction of these manifolds (slow manifolds, bifurcation diagrams) are required parts of the “traditional” numerical nonlinear dynamics toolkit. In more recent years, as the field of Machine Learning develops, conditional score-based generative models (cSGMs) have been demonstrated to exhibit remarkable capabilities in generating plausible data from target distributions that are conditioned on some given label. It is tempting to exploit such generative models to produce samples of data distributions (points on a slow manifold, steady states on a bifurcation surface) conditioned on (consistent with) some quantity of interest (QoI, observable). In this work, we present a framework for using cSGMs to quickly (a) initialize on a low-dimensional (reduced-order) slow manifold of a multi-time-scale system consistent with desired value(s) of a QoI (a “label”) on the manifold, and (b) approximate steady states in a bifurcation diagram consistent with a (new, out-of-sample) parameter value. This conditional sampling can help uncover the geometry of the reduced slow-manifold and/or approximately “fill in” missing segments of steady states in a bifurcation diagram. Finally, the quantity of interest, which determines how the sampling is conditioned, is either known a priori or identified using manifold learning-based dimensionality reduction techniques applied to the training data.

Dynamical systems↗
NASA NTRS1992

The faint galaxy contribution to the diffuse extragalactic background light

Models of the faint galaxy contribution to the diffuse extragalactic background light are presented, which are consistent with current data on faint galaxy number counts and redshifts. The autocorrelation function of surface brightness fluctuations in the extragalactic diffuse light is predicted, and the way in which these predictions depend on the cosmological model and assumptions of biasing is determined. It is confirmed that the recent deep infrared number counts are most compatible with a high density universe (Omega-0 is approximately equal to 1) and that the steep blue counts then require an extra population of rapidly evolving blue galaxies. The faintest presently detectable galaxies produce an interesting contribution to the extragalactic diffuse light, and still fainter galaxies may also produce a significant contribution. These faint galaxies still only produce a small fraction of the total optical diffuse background light, but on scales of a few arcminutes to a few degrees, they produce a substantial fraction of the fluctuations in the diffuse light.

Cole, Shaun↗
DOE OSTI2015

Predicting X-ray diffuse scattering from translation–libration–screw structural ensembles

A method of simulating X-ray diffuse scattering from multi-model PDB files is presented. Despite similar agreement with Bragg data, different translation–libration–screw refinement strategies produce unique diffuse intensity patterns. Identifying the intramolecular motions of proteins and nucleic acids is a major challenge in macromolecular X-ray crystallography. Because Bragg diffraction describes the average positional distribution of crystalline atoms with imperfect precision, the resulting electron density can be compatible with multiple models of motion. Diffuse X-ray scattering can reduce this degeneracy by reporting on correlated atomic displacements. Although recent technological advances are increasing the potential to accurately measure diffuse scattering, computational modeling and validation tools are still needed to quantify the agreement between experimental data and different parameterizations of crystalline disorder. A new tool, phenix.diffuse, addresses this need by employing Guinier’s equation to calculate diffuse scattering from Protein Data Bank (PDB)-formatted structural ensembles. As an example case, phenix.diffuse is applied to translation–libration–screw (TLS) refinement, which models rigid-body displacement for segments of the macromolecule. To enable the calculation of diffuse scattering from TLS-refined structures, phenix.tls-as-xyz builds multi-model PDB files that sample the underlying T, L and S tensors. In the glycerophosphodiesterase GpdQ, alternative TLS-group partitioning and different motional correlations between groups yield markedly dissimilar diffuse scattering maps with distinct implications for molecular mechanism and allostery. These methods demonstrate how, in principle, X-ray diffuse scattering could extend macromolecular structural refinement, validation and analysis.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Assessment of ion kinetic effects in shock-driven inertial confinement fusion implosions using fusion burn imaging

The significance and nature of ion kinetic effects in D{sup 3}He-filled, shock-driven inertial confinement fusion implosions are assessed through measurements of fusion burn profiles. Over this series of experiments, the ratio of ion-ion mean free path to minimum shell radius (the Knudsen number, N{sub K}) was varied from 0.3 to 9 in order to probe hydrodynamic-like to strongly kinetic plasma conditions; as the Knudsen number increased, hydrodynamic models increasingly failed to match measured yields, while an empirically-tuned, first-step model of ion kinetic effects better captured the observed yield trends [Rosenberg et al., Phys. Rev. Lett. 112, 185001 (2014)]. Here, spatially resolved measurements of the fusion burn are used to examine kinetic ion transport effects in greater detail, adding an additional dimension of understanding that goes beyond zero-dimensional integrated quantities to one-dimensional profiles. In agreement with the previous findings, a comparison of measured and simulated burn profiles shows that models including ion transport effects are able to better match the experimental results. In implosions characterized by large Knudsen numbers (N{sub K} ∼ 3), the fusion burn profiles predicted by hydrodynamics simulations that exclude ion mean free path effects are peaked far from the origin, in stark disagreement with the experimentally observed profiles, which are centrally peaked. In contrast, a hydrodynamics simulation that includes a model of ion diffusion is able to qualitatively match the measured profile shapes. Therefore, ion diffusion or diffusion-like processes are identified as a plausible explanation of the observed trends, though further refinement of the models is needed for a more complete and quantitative understanding of ion kinetic effects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Glacial cycles influence marine methane hydrate formation

Methane hydrates in fine-grained continental slope sediments often occupy isolated depth intervals surrounded by hydrate-free sediments. As they are not connected to deep gas sources, these hydrate deposits have been interpreted as sourced by in situ microbial methane. We investigate here the hypothesis that these isolated hydrate accumulations form preferentially in sediments deposited during Pleistocene glacial lowstands that contain relatively large amounts of labile particulate organic carbon, leading to enhanced microbial methanogenesis. To test this hypothesis, we apply an advection-diffusion-reaction model with a time-dependent organic carbon deposition controlled by glacioeustatic sea level variations. In the model, hydrate forms in sediments with greater organic carbon content deposited during the penultimate glacial cycle (~120-240 ka). As a result, the model predictions match hydrate-bearing intervals detected in three sites drilled on the northern Gulf of Mexico continental slope, supporting the hypothesis of hydrate formation driven by enhanced organic carbon burial during glacial lowstands.

58 GEOSCIENCES↗
DOE OSTI2020

A Library of Atomically Thin 2D Materials Featuring the Conductive-Point Resistive Switching Phenomenon

Non-volatile resistive switching (NVRS) is a widely available effect in transitional metal oxides, colloquially known as memristors, and of broad interest for memory technology and neuromorphic computing. Until recently, NVRS was not known in other transitional metal dichalcogenides (TMDs), an important material class owing to their atomic thinness enabling the ultimate dimensional scaling. Here, various monolayer or few-layer 2D materials are presented in the conventional vertical structure that exhibit NVRS, including TMDs (MX 2 , M = transitional metal, e.g., Mo, W, Re, Sn, or Pt; X = chalcogen, e.g., S, Se, or Te), TMD heterostructure (WS2/MoS2), and an atomically thin insulator (h-BN). These results indicate the universality of the phenomenon in 2D non-conductive materials, and feature low switching voltage, large ON/OFF ratio, and forming-free characteristic. A dissociation–diffusion–adsorption model is proposed, attributing the enhanced conductance to metal atoms/ions adsorption into intrinsic vacancies, a conductive-point mechanism supported by first-principle calculations and scanning tunneling microscopy characterizations. Our results motivate further research in the understanding and applications of defects in 2D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Panoramic Mapping of Phonon Transport from Ultrafast Electron Diffraction and Scientific Machine Learning

Abstract One central challenge in understanding phonon thermal transport is a lack of experimental tools to investigate frequency‐resolved phonon transport. Although recent advances in computation lead to frequency‐resolved information, it is hindered by unknown defects in bulk regions and at interfaces. Here, a framework that can uncover microscopic phonon transport information in heterostructures is presented, integrating state‐of‐the‐art ultrafast electron diffraction (UED) with advanced scientific machine learning (SciML). Taking advantage of the dual temporal and reciprocal‐space resolution in UED, and the ability of SciML to solve inverse problems involving coupled Boltzmann transport equations, the frequency‐dependent interfacial transmittance and frequency‐dependent relaxation times of the heterostructure from the diffraction patterns are reliably recovered. The framework is applied to experimental Au/Si UED data, and a transport pattern beyond the diffuse mismatch model is revealed, which further enables a direct reconstruction of real‐space, real‐time, frequency‐resolved phonon dynamics across the interface. The work provides a new pathway to probe interfacial phonon transport mechanisms with unprecedented details.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Synthesizing realistic sand assemblies with denoising diffusion in latent space

Abstract The shapes and morphological features of grains in sand assemblies have far‐reaching implications in many engineering applications, such as geotechnical engineering, computer animations, petroleum engineering, and concentrated solar power. Yet, our understanding of the influence of grain geometries on macroscopic response is often only qualitative, due to the limited availability of high‐quality 3D grain geometry data. In this paper, we introduce a denoising diffusion algorithm that uses a set of point clouds collected from the surface of individual sand grains to generate grains in the latent space. By employing a point cloud autoencoder, the three‐dimensional point cloud structures of sand grains are first encoded into a lower‐dimensional latent space. A generative denoising diffusion probabilistic model is trained to produce synthetic sand that maximizes the log‐likelihood of the generated samples belonging to the original data distribution measured by a Kullback‐Leibler divergence. Numerical experiments suggest that the proposed method is capable of generating realistic grains with morphology, shapes and sizes consistent with the training data inferred from an F50 sand database. We then use a rigid contact dynamic simulator to pour the synthetic sand in a confined volume to form granular assemblies in a static equilibrium state with targeted distribution properties. To ensure third‐party validation, 50,000 synthetic sand grains and the 1542 real synchrotron microcomputed tomography (SMT) scans of the F50 sand, as well as the granular assemblies composed of synthetic sand grains are made available in an open‐source repository.

Vlassis, Nikolaos N.↗
DOE OSTI2025

Co‐Doping Approach for Enhanced Electron Extraction to TiO 2 for Stable Inorganic Perovskite Solar Cells

Inorganic perovskite CsPbI 3 solar cells hold great potential for improving the operational stability of perovskite photovoltaics. However, electron extraction is limited by the low conductivity of TiO 2 , representing a bottleneck for achieving stable performance. In this study, a co‐doping strategy for TiO 2 using Nb(V) and Sn(IV), which reduces the material's work function by 80 meV compared to Nb(V) mono‐doped TiO 2 , is introduced. To gain fundamental understanding of the processes at the interfaces between the perovskite and charge‐selective layer, transient surface photovoltage measurements are applied, revealing the beneficial effect of the energetic and structural modification on electron extraction across the CsPbI 3 /TiO 2 interface. Using 2D drift‐diffusion simulations, it is found that co‐doping reduces the interface hole recombination velocity by two orders of magnitude, increasing the concentration of extracted electrons by 20%. When integrated into n–i–p solar cells, co‐doped TiO 2 enhances the projected T S80 lifetimes under continuous AM1.5G illumination by a factor of 25 compared to mono‐doped TiO 2 . This study provides fundamental insights into interfacial charge extraction and its correlation with operational stability of perovskite solar cells, offering potential applications for other charge‐selective contacts.

14 SOLAR ENERGY↗
DOE OSTI2015

Multiphase lattice Boltzmann simulations for porous media applications

Over the last two decades, lattice Boltzmann methods have become an increasingly popular tool to compute the flow in complex geometries such as porous media. In addition to single phase simulations allowing, for example, a precise quantification of the permeability of a porous sample, a number of extensions to the lattice Boltzmann method are available which allow to study multiphase and multicomponent flows on a pore scale level. In this work, we give an extensive overview on a number of these diffuse interface models and discuss their advantages and disadvantages. Furthermore, we shortly report on multiphase flows containing solid particles, as well as implementation details and optimization issues.

42 ENGINEERING↗
DOE OSTI2021

In situ synchrotron investigation of degenerate graphite nodule evolution in ductile cast iron

Ductile cast irons (DCIs) are of increasing importance in the renewable energy and transportation sectors. The distribution and morphology of the graphite nodules, in particular the formation of degenerate features during solidification, dictate the mechanical performance of DCIs. In situ high-speed synchrotron X-ray tomography was used to capture the evolution of graphite nodules during solidification of DCI, including degenerate features and the effect of the carbon concentration field. The degeneration of nodules is observed to increase with re-melting cycles, which is attributed to Mg-loss. The dendritic primary austenite and carbon concentration gradients in the surrounding liquid phase were found to control nodule morphology by locally restricting and promoting growth. A coupled diffusion-mechanical model was developed, confirming the experimentally informed hypothesis that protrusions form through liquation cracking of the austenite shell and subsequent localised growth. In conclusion, these results provide valuable insights into the solidification kinetics of cast irons, supporting the design of advanced alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Exploring the impact of hydro-mechanical coupling on compaction localization

In deep subsurface environments, where porous rocks are saturated with fluids, hydromechanical coupling plays a critical role in the formation and propagation of localized deformation zones, such as compaction bands. In this study, we numerically investigate the influence of fluid-rock interactions on the development of compaction localization in fluid-saturated rocks. For this purpose, it uses a numerical framework that adapts the heat equation to model the diffusion of pore pressure caused by deformation. This is achieved with specialized subroutines for material behavior and heat transfer formulated within the ABAQUS platform and by allowing changes in rock permeability during strain localization. The results highlight that hydromechanical coupling significantly alters the compaction behavior compared to dry conditions. Under high confining stress, excess pore pressure inhibits the progression of compaction fronts, while in time-dependent processes like rock creep, pore pressure transients accelerate deformation by creating feedback loops between mechanical forces and fluid flow. These findings underscore the importance of saturation in controlling the dynamics of compaction localization and provide insights into the interplay between pore pressure, deformation, and permeability. The implications of this study extend to applications in geological storage, resource extraction, and subsurface geomechanics, offering a deeper understanding of coupled hydromechanical processes in porous rocks.

58 GEOSCIENCES↗
DOE OSTI2018

Experimentally determined effects of olivine crystallization and melt titanium content on iron isotopic fractionation in planetary basalts

Olivine is the most abundant mantle mineral at depths relevant to oceanic crust production through melting. It is also a liquidus phase for a wide range of mafic and ultramafic magma compositions. We have experimentally investigated the effects of olivine crystallization and melt composition on the fractionation of Fe isotopes in igneous systems. To test whether there is a melt compositional control on Fe isotopic fractionation, we have conducted nuclear resonant inelastic X-ray scattering (NRIXS) measurements on a suite of synthetic glasses ranging from 0.4 to 16.3 wt.% TiO 2 . The resulting force constants are similar to those of the reduced ( f O 2 = IW) terrestrial basalt, andesite, and dacite glasses reported by Dauphas et al. (2014), indicating that there is no measurable effect of titanium composition on Fe isotopic fractionation in the investigated compositional range. We have also conducted olivine crystallization experiments and analyzed the Fe isotopic composition of the experimental olivines and glasses using solution MC-ICPMS. Olivine and glass separates from a given experimental charge have the same iron isotopic composition within error. This result is robust in both the high-Ti glass (Apollo 14 black) and low-Ti glass (Apollo 14 VLT) compositions, and at the two oxygen fugacities investigated (IW-1, IW+2). Additionally, we have determined that Fe loss in reducing one-atmosphere gas-mixing experiments occurs not only as loss to the Re wire container, but also as evaporative loss, and each mechanism of experimental Fe loss has an associated Fe isotopic fractionation. We apply our results to interpreting Fe isotopic variations in the lunar mare basalts and lunar dunite 72415-8. Our experimental results indicate that neither melt TiO 2 composition nor equilibrium olivine crystallization can explain the observed difference in the iron isotopic composition of the lunar mare basalts. Additionally, equilibrium iron isotopic fractionation between olivine and melt cannot account for the "light" iron isotopic composition of lunar dunite 72415-8, unless the melt from which it is crystallizing was already enriched in light iron isotopes. Here, our results support models of diffusive fractionation to explain the light iron isotopic compositions measured in olivine from a variety of rock types and reduced ( f O 2 = IW-1 to IW+2) igneous environments (e.g., lunar dunite and basalts, terrestrial peridotites and basalts, martian shergottites).

58 GEOSCIENCES↗
DOE OSTI2017

Study on corrosion migrations within catalyst-coated membranes of proton exchange membrane electrolyzer cells

The corrosion of low-cost, easily manufactured metallic components inside the electrochemical environment of proton exchange membrane electrolyzer cells (PEMECs) has a significant effect on their performance and durability. Here, 316 stainless steel (SS) mesh was used as a model liquid/gas diffusion layer material to investigate the migration of corrosion products in the catalyst-coated membrane of a PEMEC. Iron and nickel cation particles were found distributed throughout the anode catalyst layer, proton exchange membrane, and cathode catalyst layer, as revealed by scanning transmission electron microscopy and energy dispersive X-ray spectroscopy. Our results indicate the corrosion products of 316 SS are transported from anode to cathode through the nanochannels of the Nafion membrane, resulting in impeded proton transport and overall PEMEC performance loss.

08 HYDROGEN↗