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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Thermo-mechanical modeling and experimental validation for multilayered metallic microstructures

This paper presents thermo-mechanical modeling on multilayered metallic microstructures consisting of two bilayers that enable 3D deployment once being Joule heated. Additionally, a representative design of such microstructures, as well as their working principle is introduced. Furthermore, a mathematical model is derived using Euler–Bernoulli beam theory, and analytical solutions describing out-of-plane displacement of the multilayered microstructures when uniformly heated, which is validated by finite element analysis. Parametric analysis on thermal load and dimensional change of beam shows a good agreement between the analytical solutions and results given by finite element analysis. The phases of the near-equiatomic NiTi layer are analyzed by EDS and XRD, which prove to be austenite during the Joule heating process. The mechanical properties of austenite NiTi are incorporated into the analytical solutions that provides a good estimation of 3D deployment of microstructures made of NiTi and aluminum. The experimental results provide an approximately 7 µm out-of-plane deployment by applying a uniform temperature increase of 132 K, and parametric analysis on the dimension of top aluminum beam offers another promising approach to larger 3D deployment. The proposed mathematical model provides an efficient tool for predicting the out-of-plane deployment of such multilayered microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Inversion of coherent surface scattering images via deep learning network

Coherent surface scattering imaging is a powerful tool for imaging a surface/interface of a thin nanostructure deposited on an opaque substrate. A mathematical conversion of an object image from a scattering pattern is essential for coherent surface scattering imaging to visualize structures of specimens. It has been achieved by using phase retrieval algorithms requiring oversampling in scattering patterns and employing alternating projection approaches. It is a computationally challenging and time-consuming process. In this paper, we demonstrate CSSI-NN, which is a deep learning neural network model to predict images of objects from scattering intensities in coherent surface scattering imaging. This model allowing for the instant outcome from scattering patterns would be tremendously beneficial not only for effective experiments but also for data analysis of phase retrieval.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Shining light on nanoscale ‘vine-on-stick’ eutectic structures in the Al-Ce-Ni system

Multiphase eutectics often comprise entangled solid phases with nanoscale periodicity, making it difficult to unravel their 3D connectivity using conventional 2D techniques. Among such systems, the three-phase eutectic Al-Al 11 Ce 3 -Al 3 Ni stands out for its ultrafine (∼100 nm) interphase spacing and promising creep resistance, yet its microstructure remains relatively unexplored despite its potential for high-temperature applications. Here, we use scanning hard X-ray microscopy with an unprecedented ∼10 nm pixel size to resolve its 3D morphology. Reconstructions reveal a novel “vine-on-stick” motif, wherein Al 11 Ce 3 wraps around Al 3 Ni pillars. Analysis of phase tortuosities confirms that Al 11 Ce 3 exhibits more convoluted morphologies than Al 3 Ni. No orientation relationship was observed between the two intermetallics, suggesting that growth is controlled by local solute gradients rather than epitaxy. Fragmentation of intermetallics along their longitudinal axis suggests a Rayleigh-type breakup mechanism in solid state. The “vine-on-stick” pattern may generalize to other alloy systems with variable interfacial anisotropies and low mutual solubilities.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Phase retrieval for refraction-enhanced x-ray radiography using a deep neural network

X-ray refraction-enhanced radiography (RER) or phase contrast imaging is widely used to study internal discontinuities within materials. The resulting radiograph captures both the decrease in intensity caused by material absorption along the x-ray path, as well as the phase shift, which is highly sensitive to gradients in density. A significant challenge lies in effectively analyzing the radiographs to decouple the intensity and phase information and accurately ascertain the density profile. Conventional algorithms often yield ambiguous and unrealistic results due to difficulties in including physical constraints and other relevant information. We have developed an algorithm that uses a deep neural network to address these issues and applied it to extract the detailed density profile from an experimental RER. To generalize the applicability of our algorithm, we have developed a technique that quantitatively evaluates the complexity of the phase retrieval process based on the characteristics of the sample and the configuration of the experiment. Accordingly, this evaluation aids in the selection of the neural network architecture for each specific case. Beyond RER, the model has potential applications for other diagnostics where phase retrieval analysis is required.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Exploring the High-Pressure Phases of Carbon through X-ray Diffraction of Dynamic Compression Experiments on Sandia’s Z Pulsed Power Facility

The carbon phase diagram is rich with polymorphs which possess very different physical and optical properties ideal for different scientific and engineering applications. An understanding of the dynamically driven phase transitions in carbon is particularly important for applications in inertial confinement fusion, as well as planetary and meteorite impact histories. Experiments on the Z Pulsed Power Facility at Sandia National Laboratories generate dynamically compressed high-pressure states of matter with exceptional uniformity, duration, and size that are ideal for investigations of fundamental material properties. X-ray diffraction (XRD) is an important material physics measurement because it enables direct observation of the strain and compression of the crystal lattice, and it enables the detection and identification of phase transitions. Several unique challenges of dynamic compression experiments on Z prevent using XRD systems typically utilized at other dynamic compression facilities, so novel XRD diagnostics have been designed and implemented. We performed experiments on Z to shock compress carbon (pyrolytic graphite) samples to pressures of 150–320 GPa. The Z-Beamlet Laser generated Mn-Heα (6.2 keV) X-rays to probe the shock-compressed carbon sample, and the new XRD diagnostics measured changes in the diffraction pattern as the carbon transformed into its high-pressure phases. Quantitative analysis of the dynamic XRD patterns in combination with continuum velocimetry information constrained the stability fields and melting of high-pressure carbon polymorphs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Element differentiation with a Hartmann- based X-ray phase imaging system

Significant efforts are currently ongoing in X-ray imaging to provide multimodal imaging systems, targeting better sensitivity and specificity for both biomedical or non-destructive testing applications. Knowing the elemental composition of specific structures, such as breast microcalcifications in mammography, would help to differentiate malign and benign tumours. Standard X-ray Phase Contrast Imaging techniques provide only qualitative information on elements with similar absorption properties. However, their chemical composition can be determined from the measurement of the phase as it is directly related to the optical index of elemental materials. We will show new experimental results obtained with an X-ray phase imaging system based on a Hartmann mask. Early data treatment succeeded in retrieving both the real and imaginary parts of the refractive index. The system demonstrates the capability to discriminate materials based on elemental composition.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Phase evolution during conventional and reactive flash sintering of (Mg,Ni,Co,Cu,Zn)O via in situ X-ray diffraction

Reactive flash sintering (RFS) enables the simultaneous synthesis and sintering of ceramics and has been shown to affect the reaction pathway of different materials. Herein, in situ synchrotron X-ray diffraction (XRD) is used to investigate the (Mg,Ni,Co,Cu,Zn)O entropy-stabilized oxide formation during: (i) conventional heating and (ii) RFS under current rate-controlled mode. The same reaction pathway is verified in both instances: the starting rock-salt (RS), spinel (Co 3 O 4 ), tenorite (CuO), and wurtzite (ZnO) phases transform into a single RS phase with a (1 1 1) to (2 0 0) intensity ratio of 0.67, consistent with a random distribution of the cations into the structure. Pt lattice peak shift from the XRD patterns is used as standard to monitor the sample surface temperature, revealing a strong endothermic reaction during the RS single-phase formation (Pt peaks shift toward higher angles while increasing sample temperature/current density). Furthermore, in RFS, the single-phase RS structure is formed in just 60 s at a furnace temperature of 600°C and a current rate of 220 mA mm -2 /min. Therefore, RFS greatly accelerates the synthesis of (Mg,Ni,Co,Cu,Zn)O, however, it does not play a role in the reaction pathway for this material formation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Exploring the Atmospheric Dynamics of the Extreme Ultrahot Jupiter KELT-9b Using TESS Photometry

We carry out a phase-curve analysis of the KELT-9 system using photometric observations from NASA’s Transiting Exoplanet Survey Satellite (TESS). The measured secondary eclipse depth and peak-to-peak atmospheric brightness modulation are 650{sub −15}{sup +14} and 566 ± 16 ppm, respectively. The planet’s brightness variation reaches maximum 31 ± 5 minutes before the midpoint of the secondary eclipse, indicating a 5.°2 ± 0.°9 eastward shift in the dayside hot spot from the substellar point. We also detect stellar pulsations on KELT-9 with a period of 7.58695 ± 0.00091 hr. The dayside emission of KELT-9b in the TESS bandpass is consistent with a blackbody brightness temperature of 4600 ± 100 K. The corresponding nightside brightness temperature is 3040 ± 100 K, comparable to the dayside temperatures of the hottest known exoplanets. In addition, we detect a significant phase-curve signal at the first harmonic of the orbital frequency and a marginal signal at the second harmonic. While the amplitude of the first harmonic component is consistent with the predicted ellipsoidal distortion modulation assuming equilibrium tides, the phase of this photometric variation is shifted relative to the expectation. Placing KELT-9b in the context of other exoplanets with phase-curve observations, we find that the elevated nightside temperature and relatively low day–night temperature contrast agree with the predictions of atmospheric models that include H{sub 2} dissociation and recombination. The nightside temperature of KELT-9b implies an atmospheric composition containing about 50% molecular and 50% atomic hydrogen at 0.1 bar, a nightside emission spectrum that deviates significantly from a blackbody, and a 0.5–2.0 μm transmission spectrum that is featureless at low resolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Shock-induced transformation of nitinol shape memory alloy: Effect of stress state on transformation

Due to its numerous practical applications and intriguing phase transformation behavior, shape memory alloys (SMAs) have garnered significant research and development interests. In the past, most studies on the mechanical behavior of SMAs have been conducted under uniaxial stress loadings. Limited research on SMAs under shock loading has not provided conclusive results regarding their transformation behavior and transformation stress under such loading. Additionally, there is a lack of comprehensive understanding regarding the effects of different stress states on transformation behavior. The main objectives of this study are to address these issues. To achieve these objectives, a series of shock wave experiments were designed and conducted. Additionally, quasi-static and dynamic uniaxial stress experiments were carried out to establish a baseline for comparison. The results revealed that the transformation stress under dynamic uniaxial strain shock loading was approximately 1.92 GPa in contrast to 0.5 GPa (quasi-static) to 0.8 GPa (dynamic) observed in uniaxial stress loading. The transformation behavior exhibited noticeable rate sensitivity for both types of loading. There appeared to be a critical strain rate above which the austenite phase was driven to a metastable state. This estimated critical axial strain rate along the loading direction was approximately 2 × 10 3 /s–4 × 10 3 /s for uniaxial stress loading and approximately 2 × 10 6 /s for uniaxial strain loading. The apparent high transformation stress for uniaxial strain loading can likely be attributed to a combination of high-pressure confinement and high strain rate. Furthermore, determining their relative contributions remains an open issue.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Production of Uranium from Seawater Using a Novel Polymer Adsorbent – Process Development and Cost Analysis (Final Scientific/Technical Report SBIR Phase II)

Research in developing techniques for extracting uranium from seawater is of considerable current interest. One reason which drives scientists to develop techniques of sequestering uranium from ocean is the prediction that the land-based uranium reserves would be depleted by the end of this century based on the current production rate. Uranium exists in seawater at a very low concentration (about 3 ppb) and as highly stable uranyl tris-carbonato complexes, primarily in the form Ca 2 [UO 2 (CO 3 ) 3 ]. Because of the enormous volume of seawater, the total amount of uranium in ocean is estimated to be a thousand times greater than the land-based uranium resources. As early as 1964, the idea of extracting uranium from seawater was discussed by Davies et al. in a Nature paper. In the past decades, many different materials were tested to evaluate their ability for sequestering uranium from seawater. Among them, amidoxime and carboxylate containing polymer fiber adsorbents appear most promising because of their high uranium adsorption capacity and stability in seawater. The carboxylate groups are necessary to make the polymer adsorbent hydrophilic whereas the amidoxime groups provide strong coordination sites for uranyl ions. Moreover, according to theoretical analysis, the adsorbability of uranium may involve synergistic effects of both amidoxime and carboxyl groups in the fiber adsorbent.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Visualizing the SEI formation between lithium metal and solid-state electrolyte

The solid electrolyte interphase (SEI) is regarded as the most important factor affecting the durability of lithium-metal anode in all-solid-state batteries (ASSBs). Despite its significance, the nucleation and growth mechanism of SEI is not yet well understood. Here, we elucidate the thermodynamics and kinetics governing SEI formation at the Li|β-Li 3 PS 4 interface at the atomic scale via thermodynamic phase equilibrium analysis and machine-learning-potential-assisted molecular dynamics (MD) simulations. An accurate moment tensor potential using the machine-learning method is developed for a reactive model of Li|β-Li 3 PS 4 . This potential enabled us to perform large-scale MD simulations with the model size expanded to the experimental dimensions (~40 nm) while maintaining the same level of accuracy as density functional theory calculations. The results reveal a four-stage evolution process at the Li|β-Li 3 PS 4 interface, namely (i) fast ion diffusion, (ii) nucleation, (iii) Li 2 S growth, and (iv) stabilization. Notably, we demonstrate that the SEI can be categorized into crystalline and amorphous regions. The simulated SEI thickness, structure, and composition closely match experimental findings, validating the accuracy of the MD simulations. We further disclose the significant impact of ion diffusion kinetic limitations on the phase formation and crystallization of interfacial products. Furthermore, we shed light on the detailed potential energy (PE) distribution of lithium along the direction perpendicular to the interface. Finally, this information is crucial for better understanding interfacial ion mobility.

25 ENERGY STORAGE↗
DOE OSTI2023

Group-equivariant autoencoder for identifying spontaneously broken symmetries

We introduce the group-equivariant autoencoder (GE autoencoder), a deep neural network (DNN) method that locates phase boundaries by determining which symmetries of the Hamiltonian have spontaneously broken at each temperature. We use group theory to deduce which symmetries of the system remain intact in all phases, and then use this information to constrain the parameters of the GE autoencoder such that the encoder learns an order parameter invariant to these “never-broken” symmetries. This procedure produces a dramatic reduction in the number of free parameters such that the GE-autoencoder size is independent of the system size. We include symmetry regularization terms in the loss function of the GE autoencoder so that the learned order parameter is also equivariant to the remaining symmetries of the system. By examining the group representation by which the learned order parameter transforms, we are then able to extract information about the associated spontaneous symmetry breaking. We test the GE autoencoder on the 2D classical ferromagnetic and antiferromagnetic Ising models, finding that the GE autoencoder (1) accurately determines which symmetries have spontaneously broken at each temperature; (2) estimates the critical temperature in the thermodynamic limit with greater accuracy, robustness, and time efficiency than a symmetry-agnostic baseline autoencoder; and (3) detects the presence of an external symmetry-breaking magnetic field with greater sensitivity than the baseline method. Lastly, we describe various key implementation details, including a quadratic-programming-based method for extracting the critical temperature estimate from trained autoencoders and calculations of the DNN initialization and learning rate settings required for fair model comparisons.

42 ENGINEERING↗
DOE OSTI2023

Phase 1: Duke Energy Zero Emission Resource Integration Study (ZERIS); Phase 2: Carbon-Free Resource Integration Study for Duke Energy (Final Report)

Phase 1: This statement of work makes up Phase 1 of a larger effort. During this Phase 1 effort, NREL will work with Duke Energy to analyze the impacts of integrating significant amounts of new solar power into the Duke Energy power system under a variety of different penetrations scenarios, with a maximum of ten (10) full scenarios examined. The existing fleet, particularly the nuclear generation, will be considered in the quantitative assessments and discussions. Duke Energy is looking to quantify how much solar generation its system can handle. NREL will work with Duke Energy to quantify solar potential, identify likely integration challenges and possible opportunities for wind, storage, demand side resources and other technologies. Phase 2: This Statement of Work consists of a follow-up effort (Phase 2) to a recently completed Phase 1 modeling effort. During Phase 2, NREL will work closely with Duke Energy to analyze the impacts of integrating significant amounts of variable generation resources (wind and solar) and storage into Duke Energy's system in the Carolinas. The existing fleet, particularly nuclear generation, will be considered in the quantitative assessment and discussions. This Statement of Work also includes an extension to Phase II of the Carbon-Free Resource Integration Study for Duke Energy. In this extension, NREL will work closely with Duke Energy to extend the production cost analysis developed in Phase II to 2018 weather and load data for Duke Energy's territory. This extension leverages the modeling tools and datasets developed as part of Phase II. The analysis will compare results from Phase II (using 2012 weather and load) with 2018 results to assess system operations with increased penetration of renewables and storage. Simplifying assumptions will be made for modeling Duke Energy's neighbors in the production cost model.

14 SOLAR ENERGY↗
DOE OSTI2024

Unveiling mesoscopic structures in distorted lamellar phases through deep learning-based small angle neutron scattering analysis

Hypothesis: The formation of distorted lamellar phases, distinguished by their arrangement of crumpled, stacked layers, is frequently accompanied by the disruption of long-range order, leading to the formation of interconnected network structures commonly observed in the sponge phase. Nevertheless, traditional scattering functions grounded in deterministic modeling fall short of fully representing these intricate structural characteristics. Our hypothesis posits that a deep learning method, in conjunction with the generalized leveled wave approach used for describing structural features of distorted lamellar phases, can quantitatively unveil the inherent spatial correlations within these phases. Experiments and Simulations: This report outlines a novel strategy that integrates convolutional neural networks and variational autoencoders, supported by stochastically generated density fluctuations, into a regression analysis framework for extracting structural features of distorted lamellar phases from small angle neutron scattering data. To evaluate the efficacy of our proposed approach, we conducted computational accuracy assessments and applied it to the analysis of experimentally measured small angle neutron scattering spectra of AOT surfactant solutions, a frequently studied lamellar system. Findings: The findings unambiguously demonstrate that deep learning provides a dependable and quantitative approach for investigating the morphology of wide variations of distorted lamellar phases. It is adaptable for deciphering structures from the lamellar to sponge phase including intermediate structures exhibiting fused topological features. In conclusion, this research highlights the effectiveness of deep learning methods in tackling complex issues in the field of soft matter structural analysis and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Visualizing Intrinsic 3D-Strain Distribution in Gold Coated ZnO Microstructures by Bragg Coherent X-Ray Diffraction Imaging and Transmission Electron Microscopy with Respect to Piezotronic Applications

Novel devices ranging from bio magnetic field sensors to energy harvesting nano machines utilize the piezotronic effect. For optimal function, understanding the interaction of electrical and strain phenomena within the semiconductor crystal is necessary. Here, studies of a model piezotronic system are presented, consisting of a ZnO microrod coated by a thin layer of gold, which forms a Schottky contact with the piezoelectric ZnO material. Coherent X-ray diffraction imaging (CXDI) and transmission electron microscopy (TEM) are used to visualize the structure and strain distribution, showing that the ZnO microrod exhibits strains of multiple origins in the bulk and at the interface. Strain values of -6 × 10 -4 have been measured by CXDI at the ZnO/Au interface. The origin is shown to be a combination of an interface strain, possibly caused by the Schottky contact formation, and distinct, localized electrical fields inside the crystal which are assigned to electron depletion and screening in a bent ZnO/Au piezotronic rod. These findings will contribute to sensor development and to a better understanding of piezotronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Behavior of Ga, In, Sn, and Te in Copper Matte Smelting

The distributions of Ga, In, Sn, and Te between copper-iron mattes and silica-saturated iron silicate slags over a wide range of matte grades 55 to 75 pct Cu were determined at 1300 °C using a gas-phase equilibration-quenching technique and direct phase composition analysis by Electron Probe X-ray Microanalysis and Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry. Alumina from aluminum, a typical minor element of electric and electronic copper scrap, and lime were adopted as slag modifiers for increasing the trace element recoveries. Gallium and tin were distributed predominantly in the slag, indium preferred sulfide matte at low matte grades and slag at high, whereas tellurium strongly favored the sulfide matte in particular in high matte grades. The slag modifiers alumina and lime had a minor impact on the distribution coefficients of gallium and tin, but for indium and tellurium the distribution coefficients were more strongly affected by the basic oxides. The strong tendencies of tin and tellurium to vaporize at the experimental temperature were confirmed.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Effect of thermal treatments on electrochemical behavior of binder jetted 17-4 PH stainless steel

Binder jetted 17–4 PH stainless steel was post-processed to relate heat treatment, microstructure, and corrosion in 3.5 wt% NaCl. Specimens were sintered at 1380 or 1400 °C, solution-annealed at 1055 °C for 1 h, and aged at 482 °C for 1 h. Here, as-sintered parts showed α′-martensitic matrix with a δ-ferrite network and Cu-rich precipitates in ferrite; inclusions (MnS, NbC) promoted localized attack. solutionizing redistributed elements and reduced ferrite, while aging generated coherent Cu nano-precipitates. Corrosion resistance was highly sensitive to post-processing in which aged specimens exhibited the lowest corrosion current density and formed a thicker, stable Cr 2 O 3 -rich passive film, whereas sintered specimens degraded most. Pitting potential depended on sintering temperature and microstructure, with 1400 °C sintering yielding more positive pitting potentials and the best overall performance after aging. Although the 1400-solutionized condition showed a relatively noble pitting response versus 1380-solutionized, it displayed unstable corrosion kinetics attributed to an imperfect passive film linked to higher NbC density. XPS depth profiles corroborated these trends, showing thicker, more continuous Cr 2 O 3 in aged states and discontinuous/thinning oxides in less resistant conditions. Practically, high-temperature sintering (∼1400 °C) followed by solutionizing and aging is recommended, with further gains expected from reducing NbC/MnS populations and porosity via powder and process control.

36 MATERIALS SCIENCE↗