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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Beamline Electrostatic Levitator (BESL) for in-situ High Energy K-Ray Diffraction Studies of Levitated Solids and Liquids at High Temperature

Determinations of the phase formation sequence, the crystal structures and the thermodynamic properties of materials at high temperatures are difficult because of contamination from the sample container and environment. Containerless processing techniques, such as electrostatic (ESL), electromagnetic (EML), aerodynamic, and acoustic levitation, are most suitable these studies. An adaptation of ESL for in-situ structural studies of a wide range of materials, including metals, semiconductors, insulators using high energy (125 keV) synchrotron x-rays is described here. This beamline ESL (BESL) allows the in-situ determination of the atomic structures of equilibrium solid and liquid phases, including undercooled liquids, as well as real-time studies of solid-solid and liquid-solid phase transformations. The use of image plate (MAR345) or GE-Angio detectors enables fast (30 ms - 1s) acquisition of complete diffraction patterns over a wide q-range (4 - 140/mm). The wide temperature range (300 - 2500 K), containerless processing under high vacuum (10(exp -7) - 10(exp -8) torr), and fast data acquisition, make BESL particularly suitable for phase diagram studies of high temperature materials. An additional, critically important, feature of BESL is the ability to also make simultaneous measurement of a host of thermo-physical properties, including the specific heat, enthalpy of transformation, solidus and liquidus temperatures, density, viscosity, and surface tension; all on the same sample and simultaneous with the structural measurements.

Gangopadhyay, A. K.↗
DOE OSTI2022

Time-dependent dynamical Bragg diffraction in deformed crystals by the beam propagation method

Herein, this paper describes how to efficiently solve time-dependent X-ray dynamic diffraction problems in distorted crystals with a fast Fourier transform based beam propagation method. Examples are given of using the technique to simulate the propagation of X-ray beams in deformed crystals in space and time domains relevant to the cavity-based X-ray free-electron lasers and X-ray free-electron laser self-seeding systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thick filament activation is different in fast- and slow-twitch skeletal muscle

The contractile properties of fast-twitch and slow-twitch skeletal muscles are primarily determined by the myosin isoform content and modulated by a variety of sarcomere proteins. X-ray diffraction studies of regulatory mechanisms in muscle contraction have focused predominately on fast- or mixed-fibre muscle with slow muscle being much less studied. Here, we used time-resolved X-ray diffraction to investigate the dynamic behaviour of the myofilament proteins in relatively pure slow-twitch-fibre rat soleus (SOL) and pure fast-twitch-fibre rat extensor digitorum longus (EDL) muscle during twitch and tetanic contractions at optimal length. During twitch contractions the diffraction signatures indicating a transition in the myosin heads from ordered OFF states, where heads are held close to the thick filament backbone, to disordered ON states, where heads are free to bind to thin filaments, were found in EDL and not in SOL muscle. During tetanic contraction, changes in the disposition of myosin heads as active tension develops is a quasi-stepwise process in EDL muscle whereas in SOL muscle this relationship appears to be linear. The observed reduced extensibility of the thick filaments in SOL muscle as compared to EDL muscles indicates a molecular basis for this behaviour. These data indicate that for the EDL, thick filament activation is a cooperative strain-induced mechano-sensing mechanism, whereas for the SOL, thick filament activation has a more graded response. Further, these different approaches to thick filament regulation in fast- and slow-twitch muscles may be adaptations for short-duration, strong contractions versus sustained, finely controlled contractions, respectively.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Electrochemical Modeling and Experimental Verification of Lithiation Gradients in Oxide Cathodes of Lithium-Ion Cells

Lithiated nickel-cobalt-manganese oxides, such as NCM523, are used in the positive electrode (cathode) of Li-ion cells. Using operando X-ray diffraction profilometry, lithiation gradients in the cathode matrix can be observed and quantified by expansion into Legendre polynomials with time-dependent weights. These weights (referred to as gradients) increase in magnitude when electric current flows through the cell, decrease during potentiostatic hold and finally relax to zero when the current is interrupted during open circuit rest. Both physics-based electrochemical models and operando X-ray experiments suggest that the time constants for gradient growth and abatement are primarily determined by ionic diffusion in the oxide particles, which in turn depends on their lithium content. In contrast, the magnitude of gradients depends mainly on the applied current. The X-ray profilometry provides a way of directly probing the formation and disappearance of Li gradients across the cathode during fast cycling, which can help to diagnose the effects of material degradation in the cells.

25 ENERGY STORAGE↗
DOE OSTI2023

Artifact identification in X-ray diffraction data using machine learning methods

In situ synchrotron high-energy X-ray powder diffraction (XRD) is highly utilized by researchers to analyze the crystallographic structures of materials in functional devices ( e.g. battery materials) or in complex sample environments ( e.g. diamond anvil cells or syntheses reactors). An atomic structure of a material can be identified by its diffraction pattern along with a detailed analysis of the Rietveld refinement which yields rich information on the structure and the material, such as crystallite size, microstrain and defects. For in situ experiments, a series of XRD images is usually collected on the same sample under different conditions ( e.g. adiabatic conditions) yielding different states of matter, or is simply collected continuously as a function of time to track the change of a sample during a chemical or physical process. In situ experiments are usually performed with area detectors and collect images composed of diffraction patterns. For an ideal powder, the diffraction pattern should be a series of concentric Debye–Scherrer rings with evenly distributed intensities in each ring. For a realistic sample, one may observe different characteristics other than the typical ring pattern, such as textures or preferred orientations and single-crystal diffraction spots. Textures or preferred orientations usually have several parts of a ring that are more intense than the rest, whereas single-crystal diffraction spots are localized intense spots owing to diffraction of large crystals, typically >10 µm. In this work, an investigation of machine learning methods is presented for fast and reliable identification and separation of the single-crystal diffraction spots in XRD images. The exclusion of artifacts during an XRD image integration process allows a precise analysis of the powder diffraction rings of interest. When it is trained with small subsets of highly diverse datasets, the gradient boosting method can consistently produce high-accuracy results. The method dramatically decreases the amount of time spent identifying and separating single-crystal diffraction spots in comparison with the conventional method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Quaternary Cu 2 TSiS 4 (T = Fe, Mn) Anodes for Li-Ion Batteries

Developing high-capacity and fast-charging anode materials is critical for achieving high-performance Li-ion batteries (LIBs). Herein, polycrystalline quaternary transition metal silicon sulfides, Cu 2 TSiS 4 (T = Fe, Mn), were synthesized using a solid-state method and investigated as anode materials in LIBs. Cu 2 FeSiS 4 retains a reversible capacity of 670 mAh g –1 at 200 mA g –1 for 400 cycles, while Cu 2 MnSiS 4 suffers from a fast capacity loss in the initial 50 cycles. More importantly, Cu 2 FeSiS 4 can maintain a reversible capacity of 379 mAh g –1 after 700 cycles at a high current density of 2 A g –1 , demonstrating high cyclic stability and fast-charging capacity. To further understand the structure degradation and phase transformation, we investigated the postcycling electrodes using multiple techniques, including the scanning electron microscope with energy-dispersive X-ray spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy techniques. The results indicated that Cu 2 FeSiS 4 undergoes reversible phase transitions with Li 2 S as a major product component. To further assess the performance for practical applications, Cu 2 FeSiS 4 was coupled with LiFePO 4 to make LiFePO 4 ||Cu 2 FeSiS 4 full cells, which delivered superior electrochemical performance. These results demonstrate great promise for using quaternary transition metal silicon sulfides as anodes to achieve low-cost and sustainable LIBs.

25 ENERGY STORAGE↗
DOE OSTI2021

In Situ High Energy X-ray Diffraction Characterization of Phase Transformations and Mechanical Behaviors in Rapidly Solidified Titanium and Stainless Steel Alloys [Thesis]

Advanced manufacturing techniques like additive manufacturing (AM) have poised themselves to revolutionize metal manufacturing. A wide range of AM techniques are capable of manufacturing metal components with unique, complex geometries and hastening the scientific-engineering-development cycle. Metal AM relies on a layer-by-layer rapid manufacturing process to build components from the substrate up. Rapid solidification is a large departure from traditional metal manufacturing due to its complex physics. Characterization of rapid solidification is difficult, stemming from the small volumes used in AM and the fast dynamics of the process. High energy X-ray diffraction (HEXRD) is a solution to the characterization problems of rapidly solidified alloys and AM. HEXRD can probe small volumes at fast rates and provides a wide range of thermomechanical and kinetic information. This thesis presents the application of HEXRD to rapidly solidified titanium and stainless steel alloys through a series of case studies. In the first two studies, HEXRD is applied to rapidly solidified titanium and stainless steel welds. The materials are characterized for their temperature history, phase changes, kinetics, and microstructural evolution. In the next case study, HEXRD is applied to characterize phase changes in elastocaloric NiTi shape memory alloys (SMAs) under thermomechanical load. HEXRD, in conjunction with other tools, is used to explain the superior performance of the additively manufactured SMAs. In the final two case studies, HEXRD is used to measure the mechanical response of AM parts with complex geometries; namely, the octet truss lattice. Diffraction reveals a wide range of materials information about the AM microstructure including unexpected phases, texture, and mechanical response to loading. The mechanical results from HEXRD and then compared with theoretical predictions about the performance of octet truss lattices. Summarily, HEXRD is a diverse tool that is poised to address the complex characterization problems of many aspects of the additive manufacturing process.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Adaptively driven X-ray diffraction guided by machine learning for autonomous phase identification

Machine learning (ML) has become a valuable tool to assist and improve materials characterization, enabling automated interpretation of experimental results with techniques such as X-ray diffraction (XRD) and electron microscopy. Because ML models are fast once trained, there is a key opportunity to bring interpretation in-line with experiments and make on-the-fly decisions to achieve optimal measurement effectiveness, which creates broad opportunities for rapid learning and information extraction from experiments. Here, we demonstrate such a capability with the development of autonomous and adaptive XRD. By coupling an ML algorithm with a physical diffractometer, this method integrates diffraction and analysis such that early experimental information is leveraged to steer measurements toward features that improve the confidence of a model trained to identify crystalline phases. We validate the effectiveness of an adaptive approach by showing that ML-driven XRD can accurately detect trace amounts of materials in multi-phase mixtures with short measurement times. The improved speed of phase detection also enables in situ identification of short-lived intermediate phases formed during solid-state reactions using a standard in-house diffractometer. Our findings showcase the advantages of in-line ML for materials characterization and point to the possibility of more general approaches for adaptive experimentation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effects of charging rates on LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622)/graphite Li-ion cells

Enabling fast charging capability of lithium-ion battery is of great importance to widespread adoption of electric vehicles. Increasing the charging rates from state-of-the-art 2C (30 min) to 6C (10 min) requires deep understanding on the cell aging mechanism. Here, 400 mAh pouch cells are cycled at 1C, 4C and 6C charging rates with 1C discharging rate. Capacity fading, cathode structural changes, Li inventory loss, electrolyte composition changes and Li plating on graphite electrodes are thoroughly studied by various characterization techniques. The rapid capacity fading in cells at 6C charging rate is mainly due to Li inventory loss from cathode structure and metallic Li plating on graphite electrode at higher charging rate. Post-mortem analysis also revealed changes in electrolyte such as increased salt molarity and transesterification during fast charging.

25 ENERGY STORAGE↗
DOE OSTI2022

Hydrogen Storage Performance of Preferentially Oriented Mg/rGO Hybrids

Chemical interactions on the surface of a functional nanoparticle are closely related to its crystal facets, which can regulate the corresponding energy storage properties like hydrogen absorption. In this study, we reported a one-step growth of magnesium (Mg) particles with both close- and nonclose-packed facets, that is, {0001} and {$2\overline{116}$} planes, on atomically thin reduced graphene oxide (rGO). The detailed microstructures of Mg/rGO hybrids were revealed by X-ray diffraction, selected-area electron diffraction, high-resolution transmission electron microscopy, and fast Fourier transform analysis. Hydrogen storage performance of Mg/rGO hybrids with different orientations varies: Mg with preferential high-index {$2\overline{116}$} crystal surface shows remarkably increased hydrogen absorption up to 6.2 wt % compared with the system exposing no preferentially oriented crystal surfaces showing inferior performance of 5.1 wt % within the first 2 h. First-principles calculations revealed improved hydrogen sorption properties on the {$2\overline{116}$} surface with a lower hydrogen dissociation energy barrier and higher stability of hydrogen atoms than those on the {0001} basal plane, supporting the hydrogen uptake experiment. In addition, the hydrogen penetration energy barrier is found to be much lower than that of {0001} because of low surface atom packing density, which might be the most critical process to the hydrogenation kinetics. Here, the experimental and calculation results present a new handle for regulating the hydrogen storage of metal hydrides by controlled Mg facets.

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

Fast Neutron Irradiation Embrittlement-ductilitization of an Iron-based Amorphous Alloy using In Situ Synchrotron X-ray Diffraction

Amorphous Fe-based nanostructured alloy coatings thermally sprayed on bcc steel substrate, were subjected to neutron irradiation doses up to 2 × 10 19 n/cm 2 . It is shown that the interplay between embrittlement and recovery of ductility is governed by amorphous to crystallization transition and phase decomposition in which temperature and irradiation dose have reciprocal effects. Microscopic (X-ray diffraction) observations on the behavior of the amorphous Fe-based alloy are correlated with relevant macroscopically observed mechanical behavior. It is shown that amorphous Fe-based alloy coatings maintain and even enhance their amorphous structure with irradiation, exhibit radiation-induced restoration of thermally-induced embrittlement and finally exhibit resistance to ductility loss up to the fluence of 2 × 10 18 n/cm 2 and good thermal stability up to 350 °C. The latter is deduced from X-ray diffraction experiments of in-situ tensile strain application on the irradiated coating.

36 MATERIALS SCIENCE↗
NASA NTRS1972

New coding technique for computer generated holograms.

A coding technique is developed for recording computer generated holograms on a computer controlled CRT in which each resolution cell contains two beam spots of equal size and equal intensity. This provides a binary hologram in which only the position of the two dots is varied from cell to cell. The amplitude associated with each resolution cell is controlled by selectively diffracting unwanted light into a higher diffraction order. The recording of the holograms is fast and simple.

Haskell, R. E.↗
DOE OSTI2025

Effect of pressure cycling and compression rate on the bcc-hcp transition in an FeNi alloy

Here, we investigate the body-centered cubic (bcc) to hexagonal close-packed (hcp) phase transition in Fe-10wt. %Ni alloy, combining pressure cycling and fast compression with time-resolved synchrotron x-ray diffraction in a dynamic diamond anvil cell. Three pressure cycles were conducted with compression rates ranging from 0.1 to nearly 10 3 GPa/s. During the first cycle with the slowest compression, the observed orientations in the bcc and hcp phases are consistent with the Burgers mechanism, followed by c-axis rotation of the hcp phase consistent with {$10$ $\bar{1}2$} twinning. During the following cycles with fast compression at 10 2 –10 3 GPa/s, the hcp phase exhibits negligible c-axis rotation with a nearly constant c/a ratio of ∼1.61 up to ∼30 GPa, indicating suppression of plastic deformation (especially, twinning) due to sample confinement from the gasket. Notably, the onset pressure of the transition decreases with additional pressure cycling and faster compression, which normally leads to over-pressurization. This suggests that defects or shear induced from the pressure cycling reduces the transition kinetics even during fast compression. These insights into the deformation and transition behavior in an FeNi alloy under multiple dynamic loading cycles can offer guidance for future design of advanced structural alloys and improve our understanding of planetary core processes.

FeNi alloy↗
DOE OSTI2023

A fast two-stage algorithm for non-negative matrix factorization in smoothly varying data

This article reports the study of algorithms for non-negative matrix factorization (NMF) in various applications involving smoothly varying data such as time or temperature series diffraction data on a dense grid of points. Utilizing the continual nature of the data, a fast two-stage algorithm is developed for highly efficient and accurate NMF. In the first stage, an alternating non-negative least-squares framework is used in combination with the active set method with a warm-start strategy for the solution of subproblems. In the second stage, an interior point method is adopted to accelerate the local convergence. The convergence of the proposed algorithm is proved. The new algorithm is compared with some existing algorithms in benchmark tests using both real-world data and synthetic data. Furthermore, the results demonstrate the advantage of the algorithm in finding high-precision solutions.

interior point method↗
NASA NTRS2016

Reaching the Diffraction Limit - Differential Speckle and Wide-Field Imaging for the WIYN Telescope

Speckle imaging allows telescopes to achieve diffraction limited imaging performance. The technique requires cameras capable of reading out frames at a very fast rate, effectively 'freezing out' atmospheric seeing. The resulting speckles can be correlated and images reconstructed that are at the diffraction limit of the telescope. These new instruments are based on the successful performance and design of the Differential Speckle Survey Instrument (DSSI).The instruments are being built for the Gemini-N and WIYN telescopes and will be made available to the community via the peer review proposal process. We envision their primary use to be validation and characterization of exoplanet targets from the NASA, K2 and TESS missions and RV discovered exoplanets. Such targets will provide excellent follow-up candidates for both the WIYN and Gemini telescopes. We expect similar data quality in speckle imaging mode with the new instruments. Additionally, both cameras will have a wide-field mode and standard SDSS filters. They will be highly versatile instruments and it is that likely many other science programs will request time on the cameras. The limiting magnitude for speckle observations will remain around 13-14th at WIYN and 16-17th at Gemini, while wide-field, normal CCD imaging operation should be able to go to much fainter, providing usual CCD imaging and photometric capabilities. The instruments will also have high utility as scoring cameras for telescope engineering purposes, or other applications where high time resolution is needed. Instrument support will be provided, including a software pipeline that takes raw speckle data to fully reconstructed images.

detector↗
NASA NTRS1984

Real-time X-ray Diffraction: Applications to Materials Characterization

With the high speed growth of materials it becomes necessary to develop measuring systems which also have the capabilities of characterizing these materials at high speeds. One of the conventional techniques of characterizing materials was X-ray diffraction. Film, which is the oldest method of recording the X-ray diffraction phenomenon, is not quite adequate in most circumstances to record fast changing events. Even though conventional proportional counters and scintillation counters can provide the speed necessary to record these changing events, they lack the ability to provide image information which may be important in some types of experiment or production arrangements. A selected number of novel applications of using X-ray diffraction to characterize materials in real-time are discussed. Also, device characteristics of some X-ray intensifiers useful in instantaneous X-ray diffraction applications briefly presented. Real-time X-ray diffraction experiments with the incorporation of image X-ray intensification add a new dimension in the characterization of materials. The uses of real-time image intensification in laboratory and production arrangements are quite unlimited and their application depends more upon the ingenuity of the scientist or engineer.

Rosemeier, R. G.↗
DOE OSTI2021

BraggNN : fast X-ray Bragg peak analysis using deep learning

X-ray diffraction based microscopy techniques such as high-energy diffraction microscopy (HEDM) rely on knowledge of the position of diffraction peaks with high precision. These positions are typically computed by fitting the observed intensities in detector data to a theoretical peak shape such as pseudo-Voigt. As experiments become more complex and detector technologies evolve, the computational cost of such peak-shape fitting becomes the biggest hurdle to the rapid analysis required for real-time feedback in experiments. To this end, we propose BraggNN, a deep-learning based method that can determine peak positions much more rapidly than conventional pseudo-Voigt peak fitting. When applied to a test dataset, peak center-of-mass positions obtained from BraggNN deviate less than 0.29 and 0.57 pixels for 75 and 95% of the peaks, respectively, from positions obtained using conventional pseudo-Voigt fitting (Euclidean distance). When applied to a real experimental dataset and using grain positions from near-field HEDM reconstruction as ground-truth, grain positions using BraggNN result in 15% smaller errors compared with those calculated using pseudo-Voigt. Recent advances in deep-learning method implementations and special-purpose model inference accelerators allow BraggNN to deliver enormous performance improvements relative to the conventional method, running, for example, more than 200 times faster on a consumer-class GPU card with out-of-the-box software.

36 MATERIALS SCIENCE↗