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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 1,783 records · Page 99
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Dynamic Analysis of Reynolds Number Effects on Trailing Edge Transonic Vortex Shedding and Its Impact on Turbine Blade Aerodynamic Performance

In this work, we will discuss observations from images acquired from a time-resolved, high-speed self-aligned focusing Schlieren campaign that was performed at the CW-22 facility at NASA Glenn Research Center to understand the dynamic behavior of thick trailing-edge high-pressure turbine blades simulating a ceramic matrix composite (CMC) construction at high inlet turbulence conditions. For the CMC-9 blade, which has a trailing edge thickness of 9% of the axial chord, we identified a regime where an excessive total pressure loss (loss anomaly) is observed only for a narrow range of Reynolds numbers at a fixed exit Mach number of 0.74. The loss anomaly is qualitatively explained by our images, which were taken at 10 distinct blade Reynolds numbers spanning a factor of 6. The images show a significant increase in energy related to the oscillations due to transonic vortex shedding at the Reynolds numbers related to the high loss conditions. This increased energy leads to the formation of strong acoustic waves that turn into shock waves at the highest loss conditions. From our observations stemming from Spectral POD analysis of the high-speed images, we see the acoustic waves produced by the trailing edge vortex shedding exist in all conditions tested; but the shedding frequency has a very slight trend upwards as the Reynolds number is increased, varying about 6% in the range tested. Considering this variation of shedding frequency as a function of Reynolds number, which is well-established for other bluff-body flows, we stipulate there may be a potential feedback mechanism involving an acoustic information transfer path across neighboring blades that may explain why only a narrow range of Reynolds numbers displays strong, shock-forming vortex shedding. We consider a few feedback paths and examine the timing based on the mean flow field from a high-resolution LES simulation. It appears that all feedback mechanisms are viable, presenting an integer number of delay cycles with respect to disturbances generated at the trailing edge. Most noteworthy, however, is the acoustic/shock-boundary layer interaction mechanism at the blade geometric throat. Based on our analysis, this mechanism likely plays an important role in realistic, curved turbine blade passages.

Aerodynamics↗
DOE OSTI2014

Adaptive two-regime method: Application to front propagation

The Adaptive Two-Regime Method (ATRM) is developed for hybrid (multiscale) stochastic simulation of reaction-diffusion problems. It efficiently couples detailed Brownian dynamics simulations with coarser lattice-based models. The ATRM is a generalization of the previously developed Two-Regime Method [Flegg et al., J. R. Soc., Interface 9, 859 (2012)] to multiscale problems which require a dynamic selection of regions where detailed Brownian dynamics simulation is used. Typical applications include a front propagation or spatio-temporal oscillations. In this paper, the ATRM is used for an in-depth study of front propagation in a stochastic reaction-diffusion system which has its mean-field model given in terms of the Fisher equation [R. Fisher, Ann. Eugen. 7, 355 (1937)]. It exhibits a travelling reaction front which is sensitive to stochastic fluctuations at the leading edge of the wavefront. Previous studies into stochastic effects on the Fisher wave propagation speed have focused on lattice-based models, but there has been limited progress using off-lattice (Brownian dynamics) models, which suffer due to their high computational cost, particularly at the high molecular numbers that are necessary to approach the Fisher mean-field model. By modelling only the wavefront itself with the off-lattice model, it is shown that the ATRM leads to the same Fisher wave results as purely off-lattice models, but at a fraction of the computational cost. The error analysis of the ATRM is also presented for a morphogen gradient model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Materials Data on BaSe by Materials Project

BaSe is Halite, Rock Salt structured and crystallizes in the cubic Fm-3m space group. The structure is three-dimensional. Ba2+ is bonded to six equivalent Se2- atoms to form a mixture of edge and corner-sharing BaSe6 octahedra. The corner-sharing octahedral tilt angles are 0°. All Ba–Se bond lengths are 3.34 Å. Se2- is bonded to six equivalent Ba2+ atoms to form a mixture of edge and corner-sharing SeBa6 octahedra. The corner-sharing octahedral tilt angles are 0°.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Non-Linear Optics at Twist Interfaces in h-BN/SiC Heterostructures

Understanding the emergent electronic structure in twisted atomically thin layers has led to the exciting field of twistronics. However, practical applications of such systems are challenging since the specific angular correlations between the layers must be precisely controlled and the layers have to be single crystalline with uniform atomic ordering. Here, in this work, an alternative, simple, and scalable approach is suggested, where nanocrystalline two-dimensional (2D) film on 3D substrates yields twisted-interface-dependent properties. Ultrawide-bandgap hexagonal boron nitride (h-BN) thin films are directly grown on high in-plane lattice mismatched wide-bandgap silicon carbide (4H-SiC) substrates to explore the twist-dependent structure-property correlations. Concurrently, nanocrystalline h-BN thin film shows strong non-linear second-harmonic generation and ultra-low cross-plane thermal conductivity at room temperature, which are attributed to the twisted domain edges between van der Waals stacked nanocrystals with random in-plane orientations. First-principles calculations based on time-dependent density functional theory manifest strong even-order optical nonlinearity in twisted h-BN layers. This work unveils that directly deposited 2D nanocrystalline thin film on 3D substrates could provide easily accessible twist-interfaces, therefore enabling a simple and scalable approach to utilize the 2D-twistronics integrated in 3D material devices for next-generation nanotechnology.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Molecular Statics Analyses of Thermodynamics and Kinetics of Hydrogen Cottrell Atmosphere Formation Around Edge Dislocations in Aluminum

Aluminum alloys are being explored as lightweight structural materials for use in hydrogen-containing environments. In this paper, to understand hydrogen effects on deformation, we perform molecular statics studies of the hydrogen Cottrell atmosphere around edge dislocations in aluminum. First, we calculate the hydrogen binding energies at all interstitial sites in a periodic aluminum crystal containing an edge dislocation dipole. This allows us to use the Boltzmann equation to quantify the hydrogen Cottrell atmosphere. Based on these binding energies, we then construct a continuum model to study the kinetics of the hydrogen Cottrell atmosphere formation. Finally, we compare our results with existing theories and discuss the effects of hydrogen on deformation of aluminum-based alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Effect of glutathione-coated Mn-doped ZnS quantum dots on nutrient delivery in basil ( Ocimum basilicum ) plants

Ensuring efficient nutrient delivery while minimizing environmental impacts remains a significant challenge for modern agriculture. Nanotechnology-based fertilizers offer promising strategies to improve nutrient uptake and bioavailability in plants. This research aims to evaluate the use of Glutathione-coated Manganese-doped Zinc Sulfide quantum dots (GSH-ZnS-Mn QDs) as a potential nano fertilizer for basil (Ocimum basilicum). QDs' physicochemical properties were characterized using UV–Vis spectroscopy, photoluminescence, FTIR, and energy-dispersive X-ray spectroscopy, confirming successful Mn doping and glutathione surface functionalization. Basil plants were exposed to different concentrations of GSH-ZnS-Mn QDs under soil and hydroponic conditions. Plant growth parameters, oxidative stress responses, photosynthetic pigments, and macro- and micronutrient uptake were assessed using biochemical assays and inductively coupled plasma optical emission spectrometry (ICP-OES). Elemental uptake, spatial distribution, and zinc speciation were further investigated using synchrotron-based micro-X-ray fluorescence (μ-XRF) imaging and X-ray absorption near-edge structure (XANES) spectroscopy. Results show that exposure to GSH-ZnS-Mn QDs resulted in a concentration-dependent increase in leaf and stem biomass, accompanied by enhanced Zn accumulation in plant tissues. Catalase activity decreased across all tested concentrations, suggesting a shift toward glutathione-dependent antioxidant pathways rather than oxidative damage. Chlorophyll levels exhibited moderate reductions at higher concentrations. The higher increase in macronutrient (K, Ca, and Mg) uptake was reported in plants exposed to 200 ppm of QDs. μ-XRF imaging indicated a selective accumulation of Zn in roots and stems, with partial translocation to leaves. XANES analyses revealed that Zn from QDs was mainly converted into organic Zn species, such as Zn-phytate, Zn-acetate, and Zn-cysteine, indicating transformation and complexation within the plant. The findings demonstrate that a glutathione coating on GSH-ZnS-Mn QDs improves biocompatibility and nutrient delivery efficiency. These results highlight the relevance of surface functionalization in regulating nanoparticle fate, transformation, and nutrient bioavailability, supporting the potential application of GSH–ZnS–Mn QDs as modern nano fertilizers.

Basil↗
DOE OSTI2019

Comprehensive investigation of the role of Nb on the oxidation kinetics of Zr-Nb alloys

Zirconium oxidation, and the associated hydrogen pickup, has long been considered the life-limiting degradation mechanism of fuel elements in pressurized-water reactor (PWR) systems. Currently, PWRs use Zr-Nb alloys as the cladding material of choice. However, oxidation kinetics for Zr-Nb alloys can vary greatly depending on the Nb content; moreover, even Zr-Nb with the same composition can exhibit radically different oxidation kinetics if heat treated at different temperatures. To improve the fundamental understanding of the corrosion of Zr-Nb, it is necessary to determine mechanistically how Nb affects the oxidation kinetics of the overall system. To achieve this, nano-beam X-ray absorption near-edge spectroscopy (XANES), energy-dispersive spectroscopy (EDS), transmission electron microscopy (TEM), and modelling using the physically based C4 model have been performed in concert on samples of Zr-1.0Nb annealed at two different temperatures, 580 °C and 720 °C, and oxidized in an autoclave environment. Through TEM/EDS, it has been seen that β-Zr precipitates dissolved upon oxidation, releasing Nb to the surrounding environment, while β-Nb precipitates remain intact and retard oxidation of Nb. Comparison of the XANES results and C4 model predictions illustrate that space charge generated in the oxide can lead to subparabolic oxidation kinetics in Zr-Nb alloys, which have been shown to negatively affect the hydrogen-pickup fraction. However, sufficient Nb in solid solution can become oxidized to compensate this mechanism to maintain parabolic kinetics in select alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Shadow masks predictions in SPARC tokamak plasma-facing components using HEAT code and machine learning methods

Here, this work uses machine learning (ML) to complement HEAT (Heat flux Engineering Analysis Toolkit) by developing 3-D footprint surrogate models for fast and accurate heat load calculations in the divertor of the SPARC tokamak. The focus is on shadowed regions, or magnetic shadows, caused by the 3-D geometry of plasma-facing components (PFCs). ML classifiers are employed to create a surrogate model for HEAT generated shadow masks, predicting these shadow masks and divertor heat flux profiles based on a diverse range of equilibria and only the plasma current, safety factor(q95) at the edge, and magnetic flux angles as input parameters. The ultimate goal is to integrate the model for real-time control and future operational decisions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Automating the detection of hydrological barriers and fragmentation in wetlands using deep learning and InSAR

The loss of hydrological connectivity and fragmentation of natural wetlands is a widespread driver of wetland degradation. Understanding where and how natural connectivity is impaired is essential for managing, protecting and remediating these ecosystems. Wetland Interferometric Synthetic Aperture Radar (Wetland InSAR) can provide information on surface flow orientation in wetlands at a high spatial resolution, which can be used for barrier detection. However, the broad application of this approach is constrained by the labour-intensive manual delineation of barriers based on mapped water levels. This study presents the first deep learning-based methodology for the automated detection of hydrological barriers. We trained a deep convolutional network to segment edge features of hydrological barriers in 25 image pairs captured by ALOS PALSAR-1 L-Band InSAR between 2006 and 2011. The training dataset consists of manually labelled and delineated barriers showing abrupt changes in water surface elevation and wrapped interferograms with high coherence. We tested this method across three wetland sites: the Everglades and southern Louisiana wetlands (United States) and the Cienaga de Zapata (Cuba). Across these sites, the convolutional network detected hydrological barriers with up to 84% accuracy. The model performed particularly well for linear hydrological barriers such as roads, dikes, and channels. Notably, some barriers impede flow only seasonally, appearing during low water levels and disappearing when water levels rise. Our automated approach to detecting and assessing wetland hydrologic connectivity can be applied more broadly to support the effective management of fragmented wetland ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

A Structural Investigation of Hydrous and Anhydrous Rare-Earth Phosphates

Rhabdophane- (REPO 4 ·nH 2 O; RE = La to Dy), monazite- (REPO 4 ; RE = La to Gd), and xenotime-type (REPO 4 and RE'PO 4 ·nH 2 O; RE = Tb to Lu and Y; RE' = Ho to Lu and Y) rare-earth phosphate materials are being considered for a number of applications including as photonic materials, for biolabeling studies, and as potential nuclear wasteforms. Structural studies of hydrous rare-earth phosphates are rather limited when compared to anhydrous rare-earth phosphates. In this study, rhabdophane- (REPO 4 ·nH 2 O; RE = La, Nd, Sm, Gd, and Dy) and xenotime-type (REPO 4 ·nH 2 O; RE = Y and Yb) materials were synthesized by a precipitation-based method and investigated using X-ray diffraction (XRD) and X-ray absorption near-edge spectroscopy (XANES). Examination of the powder XRD data from rhabdophane-type materials has confirmed that the rhabdophane structure crystallizes in the monoclinic crystal system rather than the hexagonal structure that has most often been reported. Materials adopting the rhabdophane- or xenotime-type structure were studied as a function of temperature to understand how the structure varies with increasing annealing temperature. Local structural information was obtained by collecting P K- and RE L 1 -edge XANES spectra. Examination of P K-edge XANES spectra from rhabdophane- and xenotime-type materials revealed changes in the local environment around P as a function of temperature. Furthermore, these changes were attributed to the removal of water from these structures as a result of high temperature annealing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Defect Properties, Anion Ordering, and Photochromic Mechanism in Yttrium Oxyhydride

Yttrium oxyhydride (YHO) undergoes a reversible photochromic transition when exposed to ultraviolet light. However, the mechanism for this transformation is not fully understood, and the structure and precise chemical composition of YHO remain under debate. Here, we use first-principles density functional theory calculations with a hybrid functional to study the structure, chemical stability, and point defect properties of YHO. As experiments have shown, we find that YHO prefers a cubic structure, with H and O anions present in equal concentrations and located on tetrahedral sites. Stoichiometric and ordered YHO is chemically stable, but it has a wide band gap of 5.01 eV, considerably larger than that measured in experiments (2.4–3.8 eV). On the other hand, Y4H10O has a smaller band gap of 2.97 eV and also has a region of chemical stability; thus, the actual material may include some fraction of this H-rich structure. The defect chemistry of YHO is dominated by anionic antisite species (H O and O H ), with hydrogen interstitials (H i ) and vacancies (V H ) also present in reasonably high concentrations. We show that antisite disorder lowers the band gap relative to the perfectly ordered structure, bringing the magnitude of the gap into closer agreement with experiment. Based on our calculations of defect migration and the positions of defect states relative to the band edges, we link the onset of photochromic behavior to the reaction H O – → V O 0 + H i – , which follows photoexcitation of a H O + defect. H i – can subsequently migrate away and be trapped by additional H O + defects, contributing to the persistence of the reaction, while the resultant oxygen vacancy, V O 0 , introduces an occupied defect state that leads to optical absorption at visible wavelengths. Our results can explain reported discrepancies between experimental and computational results for YHO, and they allow us to propose specific atomic-scale processes that can lead to photochromism. In conclusion, understanding these mechanisms is key for unlocking YHO’s application in devices ranging from smart windows and optoelectronics to electrochemical synapses for neural networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Synthesis and Photophysical Properties of a Covalently Linked Porphyrin Chromophore–Ru(II) Water Oxidation Catalyst Assembly on SnO 2 Electrodes

In this work, we describe the preparation and surface photophysical properties of a covalently linked, chromophore-catalyst assembly between a phenyl phosphonate-derivatized pentafluorophenyl-substituted porphyrin and the water oxidation catalyst, [Ru II (terpyridine)(2-benzimidazolylpyridine)(OH 2 )] 2+ , in a derivatized assembly of porph-Ru II –OH 2 2+ . The findings of nanosecond transient absorption measurements on nanoparticle SnO 2 electrodes in aqueous acetate buffer at pH 4.7 are consistent with rapid electron injection into SnO 2 with transfer of oxidative equivalents to the assembly. Electron transfer from the singlet excited state of the porphyrin to the conduction band of the electrode, SnO 2 (e – )|-porph + -Ru II –OH 2 2+ , is favored as the porphyrin singlet excited state lies 0.44 eV above the SnO 2 conduction band edge. Electron injection is rapid ($\langle$τ inj $\rangle$ < 10 –8 s), and occurs with high efficiency. Based on measured redox potentials, following excitation and injection, intra-assembly oxidation of the catalyst, -porph+-Ru II –OH 2 2+ → -porph-Ru III –OH 2+ + H + , is favored in the transient equilibrium state by 0.62 eV at pH 4.7. However, immediately after the flash, a distribution exists at the surface between isomers with SnO 2 (e – )|-porph+-Ru II –OH 2 2+ undergoing back electron transfer to the surface with an average lifetime of $\langle$τ 1 $\rangle$ ~ 10 –7 s and a slower component for back electron transfer from SnO 2 (e – )|-porph-Ru III –OH 2+ with $\langle$τ 2 $\rangle$ ~ 4 × 10 –5 s.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Additive Lithography–Organic Monolayer Patterning Coupled with an Area-Selective Deposition

The combination of area-selective deposition (ASD) with a patternable organic monolayer provides a versatile additive lithography platform, enabling the generation of a variety of nanoscale feature geometries. Stearate hydroxamic acid self-assembled monolayers (SAMs) were patterned with extreme ultraviolet (λ = 13.5 nm) or electron beam irradiation and developed with ASD to achieve line space patterns as small as 50 nm. Density functional theory was employed to aid in the synthesis of hydroxamic acid derivatives with optimized packing density to enhance the imaging contrast and improve dose sensitivity. Near-edge X-ray absorption fine structure spectroscopy and infrared spectroscopy reveal that the imaging mechanism is based on improved deposition inhibition provided by the cross-linking of the SAM to produce a more effective barrier during a subsequent deposition step. With patterned substrates composed of coplanar copper lines and silicon spacers, hydroxamic acids selectively formed monolayers on the metal portions and could undergo a pattern-wise exposure followed by ASD in the first combination of a patternable monolayer with ASD. This material system presents an additional capability compared to traditional ASD approaches that generally reflect a starting patterned surface. Finally, this bottoms-up additive approach to lithography may be a viable alternative to subtractive nanoscale feature generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Cerium(IV) Enhances the Catalytic Oxidation Activity of Single-Site Cu Active Sites in MOFs

The rates of catalytic oxidation of cyclohexane and CO are four and twenty times higher, respectively, with Cu supported on a cerium-based MOF than on the structurally analogous zirconium material. Both Ce- and Zr-based copper catalysts feature uncommon threecoordinate CuII sites bearing different nuclearities, as observed by Cu K-edge extended X-ray absorption fine structure analysis. These findings offer molecular-level understanding of the metal-support interface in MOF catalysts and establish correlations with the more established literature on zirconia and ceria-supported heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Evolution of Metastable Defects and Its Effect on the Electronic Properties of MoS 2 Films

Here, we report on structural and electronic properties of defects in chemical vapor-deposited monolayer and few-layer MoS 2 films. Scanning tunneling microscopy, Kelvin probe force microscopy, and transmission electron microscopy were used to obtain high resolution images and quantitative measurements of the local density of states, work function and nature of defects in MoS 2 films. We track the evolution of defects that are formed under heating and electron beam irradiation. We observe formation of metastable domains with different work function values after annealing the material in ultra-high vacuum to moderate temperatures. We attribute these metastable values of the work function to evolution of crystal defects forming during the annealing. The experiments show that sulfur vacancies formed after exposure to elevated temperatures diffuse, coalesce, and migrate bringing the system from a metastable to equilibrium ground state. The process could be thermally or e-beam activated with estimated energy barrier for sulfur vacancy migration of 0.6 eV in single unit cell MoS 2 . Even at equilibrium conditions, the work function and local density of states values are strongly affected near grain boundaries and edges. The results provide initial estimates of the thermal budgets available for reliable fabrication of MoS 2 -based integrated electronics and indicate the importance of defect control and layer passivation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions

In high energy density physics (HEDP) and inertial confinement fusion (ICF), predictive modeling is complicated by uncertainty in parameters that characterize various aspects of the modeled system, such as those characterizing material properties, equation of state (EOS), opacities, and initial conditions. Typically, however, these parameters are not directly observable. What is observed instead is a time sequence of radiographic projections using X-rays. In this work, we define a set of sparse hydrodynamic features derived from the outgoing shock profile and outer material edge, which can be obtained from radiographic measurements, to directly infer such parameters. Our machine learning (ML)-based methodology involves a pipeline of two architectures, a radiograph-to-features network (R2FNet) and a features-to-parameters network (F2PNet), that are trained independently and later combined to approximate a posterior distribution for the parameters from radiographs. We show that the machine learning architectures are able to accurately infer initial conditions and EOS parameters, and that the estimated parameters can be used in a hydrodynamics code to obtain density fields, shocks, and material interfaces that satisfy thermodynamic and hydrodynamic consistency. Finally, we demonstrate that features resulting from an unknown EOS model can be successfully mapped onto parameters of a chosen analytical EOS model, implying that network predictions are learning physics, with a degree of invariance to the underlying choice of EOS model. To the best of our knowledge, our framework is the first demonstration of recovering both thermodynamic and hydrodynamic consistent density fields from noisy radiographs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Charge state-dependent ion condensation near conjugated polymer backbones

Despite the technological appeal of polymeric organic mixed ionic/electronic conductors (OMIECs) for diverse applications, a deep understanding of the fundamentals of mixed charge transport in these materials, especially regarding the complex interplay between polymer, ion and solvent structure in determining transport, is lacking. Herein, extensive molecular dynamics (MD) simulations of a model OMIEC representing various electrochemically gated states are reported that reveal charge state-dependent counterion condensation. X-ray diffraction simulations based on the MD data predict a measurable change in the scattering intensity at the counterion absorption edge, indicative of counterion repositioning with charging. We leverage an operando resonant X-ray scattering technique to experimentally corroborate the simulated scattering and report excellent agreement between predicted and experimental data, confirming that counterions preferentially reside in the lamellar mid-plane of crystallites at low doping, and near the polymer backbone at higher doping. Driving forces for ion type-dependent spatial repositioning and implications thereof are discussed.

36 MATERIALS SCIENCE↗