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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

An FFT-based approach for Bloch wave analysis: application to polycrystals

A method based on the Fast Fourier Transform is proposed to obtain the dispersion relation of acoustic waves in heterogeneous periodic media with arbitrary microstructures. The microstructure is explicitly considered using a voxelized Representative Volume Element (RVE). The dispersion diagram is obtained solving an eigenvalue problem for Bloch waves in Fourier space. To this aim, two linear operators representing stiffness and mass are defined through the use of differential operators in Fourier space. The smallest eigenvalues are obtained using the implicitly restarted Lanczos and the subspace iteration methods, and the required inverse of the stiffness operator is done using the conjugate gradient with a preconditioner. The method is used to study the propagation of acoustic waves in elastic polycrystals, showing the strong effect of crystal anistropy and polycrystaline texture on the propagation. It is shown that the method combines the simplicity of classical Fourier series analysis with the versatility of Finite Elements to account for complex geometries proving an efficient and general approach which allows the use of large RVEs in 3D.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Denoising Seismic Waveforms Using a Wavelet-Transform-Based Machine-Learning Method

Seismic waveform data recorded at stations can be thought of as a superposition of the signal from a source of interest and noise from other sources. Frequency‐based filtering methods for waveform denoising do not result in desired outcomes when the targeted signal and noise occupy similar frequency bands. Recently, denoising techniques based on deep‐learning convolutional neural networks (CNNs), in which a recorded waveform is decomposed into signal and noise components, have led to improved results. These CNN methods, which use short‐time Fourier transform representations of the time series, provide signal and noise masks for the input waveform. These masks are used to create denoised signal and designaled noise waveforms, respectively. However, advancements in the field of image denoising have shown the benefits of incorporating discrete wavelet transforms (DWTs) into CNN architectures to create multilevel wavelet CNN (MWCNN) models. The MWCNN model preserves the details of the input due to the good time–frequency localization of the DWT. In this report we use a data set of over 382,000 constructed seismograms recorded by the University of Utah Seismograph Stations network to compare the performance of CNN and MWCNN‐based denoising models. Evaluation of both models on constructed test data shows that the MWCNN model outperforms the CNN model in the ability to recover the ground‐truth signal component in terms of both waveform similarity and preservation of amplitude information. Model evaluation of real‐world data shows that both the CNN and MWCNN models outperform standard band‐pass filtering (BPF; average improvement in signal‐to‐noise ratio of 9.6 and 19.7 dB, respectively, with respect to BPF). Evaluation of continuous data suggests the MWCNN denoiser can improve both signal detection capabilities and phase arrival time estimates.

58 GEOSCIENCES↗
DOE OSTI2021

Thermal Stability of Quasi-1D NbS 3 Nanoribbons and Their Transformation to 2D NbS 2 : Insights from in Situ Electron Microscopy and Spectroscopy

Here in situ electron microscopy imaging and spectroscopy enabled us to study the evolution of quasi-1D NbS 3 -IV nanoribbons with respect to morphology and chemical structure at temperatures between room temperature and 1000 °C. Scanning transmission electron microscopy (STEM) experiments included imaging in the secondary electron, (transmitted) bright field, and high-angle annular dark-field modes while operating in the low kV regime. The results showed that NbS 3 -IV samples transform dramatically from smooth nanoribbons into highly textured configurations featuring polyhedral divots and steps. Similar in situ heating experiments conducted with aberration-corrected STEM revealed that bilayers of NbS 3 -IV chains convert topotactically into aligned 2H-NbS 2 sheets upon loss of sulfur. Atomic resolution imaging, fast Fourier transform analysis, and electron energy loss spectroscopy confirmed these chemical changes, from which we propose an atomistic mechanism for the NbS 3 -IV → 2H-NbS 2 conversion.

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

Conversion of Formic Acid on Single- and Nano-Crystalline Anatase TiO 2 (101)

Understanding thermochemical transformations of formic acid (FA) on metal oxide surfaces is important for many catalytical reactions. Here we study thermally induced reactions of FA on a single-crystalline and nanocrystalline anatase TiO 2 (101). We employ a combination of scanning tunneling microscopy (STM), temperature-programmed desorption (TPD), infrared reflection absorption spectroscopy (IRAS), diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and density functional theory (DFT) to follow the FA surface intermediates and reaction products above room temperature. We find that the primary reaction products desorbing at about 300, 480, and 515 K are molecular water, carbon monoxide, and formaldehyde, respectively. Bidentate (BD) formate and bridging hydroxyl (HO b ) are identified as central intermediates in the FA transformations. Bridging oxygen vacancies (V O ) are also likely participants despite their low stability at the surface. In conclusion, the parallel studies on single crystals and faceted TiO 2 (101) nanoparticles reveal the spectroscopic commonalities of surface species and of the thermal conversion of molecular and deprotonated forms of FA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Spectroscopic features of dissolved iodine in pristine and gamma-irradiated nitric acid solutions

While iodine speciation is important for a wide range of nuclear activities, understanding the mechanisms of the transformations of iodine between chemical forms and the sensitivity of these transitions to solution conditions and exposure to radiation remains an active area of research. This work curates spectroscopic data from several experimental techniques and establishes their sensitivity and limitations in detecting changes in iodine speciation in both neutral and acidic regimes. The techniques include Raman spectroscopy, Fourier Transform Infrared (FTIR) spectroscopy, 127 I NMR spectroscopy, and ultraviolet-visible (UV-Vis) spectroscopy. Analysis of these data indicates that these commonly accessible spectroscopies often have dynamic ranges of measurable concentrations that do not always overlap between all techniques. The experimental techniques are disparately sensitive to iodide (I - ), molecular iodine (I 2 ), iodate (IO 3 - ), and periodate (IO 4 - ) species. Raman, FTIR, and NMR spectra were subsequentially analyzed using two-dimensional correlation analyses to generate high-resolution autocorrelation spectra. Here, the use of these spectroscopies is then extended to tracking acidification-induced and gamma irradiation-induced transformations of dissolved sodium iodate in deionized water and concentrated nitric acid. Both dissolution into nitric acid and irradiation with a gamma source are demonstrated to perturb the iodine speciation promoting their assembly into molecular iodine (I 2 ) and/or triiodide (I 3 - ). While I 2 and I 3 - species are undetectable with FTIR spectroscopy and 127 I NMR spectroscopy, the species can be detected with UV-Vis spectroscopy, and in some instances, I 3 - can be detected with Raman spectroscopy in the low wavenumber region. Ultimately, the results of this work provide a path to designing optimal combinations of techniques to detect forms of iodine across a wide range of concentrations and conditions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Effects of Co doping on the structure and physicochemical properties of hausmannite (Mn 3 O 4 ) and its transformation during aging

Hausmannite is a common low-valence manganese oxide mineral with a distorted spinel structure in surficial sediments. Although natural Mn oxides often contain various transition metal (TM) impurities, few studies have addressed the substitution mechanisms of TMs, such as cobalt (Co), with hausmannite and induced changes in the mineral physicochemical properties. In this study, Co-doped hausmannites with final Co/Mn molar ratios of 0.05 and 0.11 were synthesized and characterized by wet chemical analysis, powder X-ray diffraction (XRD), Fourier transformed infrared spectra (FTIR), high resolution transmission electron microscope (HRTEM), X-ray photoelectron spectroscopy (XPS) and X-ray absorption fine structure spectroscopy (XAFS). Co-doped samples have larger crystallite sizes and smaller specific surface areas than those of the hausmannite without Co. The Co cations exist in a mixed-valence of +3 and + 2. Powder XRD and acid dissolution experiments indicate that Co incorporates into the mineral structures, and increases the mineral structural stability. Co K-edge extended X-ray adsorption fine structure (EXAFS) analysis demonstrates that Co likely substitutes for lattice Mn(III). After aging at room temperature for three years, 14.1 ± 1.9% of pure hausmannite is transformed to manganite while only 2.6 ± 0.7% of manganite appears in the aged Co-doped sample with an initial Co/Mn molar ratio of 0.10. Finally, these results provide new insights into the incorporation mechanisms of TMs into low valence Mn oxides, and the stability of these minerals in natural environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Supported molybdenum oxides for the aldol condensation reaction of acetaldehyde

The (retro-)aldol condensation reaction is an important chemical transformation in the upgrading of biomass-derived compounds into fuels and valuable specialty chemicals. In this study, we found that supported molybdenum oxide (MoO x ) catalysts were active and selective for the aldol condensation of acetaldehyde to crotonaldehyde under steady-state reactor conditions. Through a combination of transmission electron microscopy (TEM), ultraviolet–visible (UV–VIS) diffuse reflectance spectroscopy, Fourier transform infrared (FTIR) spectroscopy of adsorbed pyridine, and steady-state reactor testing, we determined that highly dispersed MoO x has a strong interaction with a γ-Al 2 O 3 support resulting in optimal catalyst performance at low weight loadings. In contrast, MoO x particles supported on SiO 2 have a weaker interaction with the support, resulting in a monotonic relationship between Mo loading and aldol condensation activity. The Lewis acid site density and strength are important parameters for predicting aldol condensation activity across all samples. The concentration of weak acid sites had a poor correlation with aldol condensation activity, most likely because these sites are too weak to activate acetaldehyde for the reaction. Medium and strong acid sites both had good correlations to aldol condensation activity. Results from X-ray absorption near edge structure (XANES) and acetaldehyde temperature programmed desorption (TPD) indicated that partially reduced MoO x was more active for aldol condensation, but pretreatment in reducing or oxidizing environments had no significant effect on steady-state catalytic activity. Finally, characterization of spent catalyst samples through temperature programmed oxidation (TPO) and thermogravimetric analysis (TGA) revealed that catalysts with high densities of strong acid sites tended to form more carbonaceous deposits on the surface over the course of the reaction.

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

Machine learning surrogate models for Landau fluid closure

The first result of applying the machine/deep learning technique to the fluid closure problem is presented in this letter. As a start, three different types of neural networks (multilayer perceptron (MLP), convolutional neural network (CNN) and two-layer discrete Fourier transform (DFT) network) were constructed and trained to learn the well-known Hammett-Perkins Landau fluid closure in configuration space. We found that in order to train a well-preformed network, a minimum size of training data set is needed; MLP also requires a minimum number of neurons in the hidden layers equals to the degrees of freedom in Fourier space despite training data is fed in configuration space. Out of three models DFT performs the best for the clean data most likely due to the existence of nice Fourier expression for Hammett-Perkins closure but it is least robust with respect to input noise. Overall, with appropriate tuning and optimization, all three neural networks are able to accurately predict Hammett-Perkins closure and reproduce the inherit nonlocal feature, suggesting a promising path to calculate more sophisticated closures with the machine/deep learning technique.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Quantum Hamilton-Jacobi theory, spectral path integrals, and exact WKB analysis

We propose a new way to perform path integrals in quantum mechanics by using a quantum version of Hamilton-Jacobi (HJ) theory. In classical mechanics, Hamilton-Jacobi theory is a powerful formalism, however, its utility is not explored in quantum theory beyond approximation schemes. The canonical transformation enables one to set the new Hamiltonian to constant or zero, but keeps the information about solution in Hamilton’s characteristic function. To benefit from this in quantum theory, one must work with a formulation in which classical Hamiltonian is used. This uniquely points to phase space path integral. However, the main variable in HJ formalism is energy, not time. Thus, we are led to consider the Fourier transform of the path integral, the spectral path integral Z ˜ ( E ) . The evaluation of path integrals reduces to determining the quantum Hamilton characteristic functions (which can be achieved via an asymptotic analysis) and a discrete sum over the quantum period lattice, generalizing Gutzwiller’s sum. Published by the American Physical Society 2025

Türe, Mustafa (ORCID:0009000975968618)↗
DOE OSTI2020

A History of Molecular Level Analysis of Natural Organic Matter by FTICR Mass Spectrometry and The Paradigm Shift in Organic Geochemistry

Natural organic matter (NOM) is a complex mixture of biogenic molecules resulting from the deposition and transformation of plant and animal matter. It has long been recognized that NOM plays an important role in many geological, geochemical, and environmental processes. Of particular concern is the fate of NOM in response to a warming climate in environments that have historically sequestered carbon (e.g., peatlands and swamps) but may transition to net carbon emitters. In this review, we will highlight developments in the application of high-field Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) in identifying the individual components of complex NOM mixtures, focusing primarily on the fraction that is dissolved in natural waters (dissolved organic matter or DOM). We will first provide some historical perspective on developments in FTICR technology that made molecular-level characterizations of DOM possible. In conclusion, a variety of applications of the technique will then be described, followed by our view of the future of high-field FTICR MS in carbon cycling research, including a particularly exciting metabolomic approach.

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

Calibration and characterization of the line-VISAR diagnostic at the HED-HIBEF instrument at the European XFEL

In dynamic-compression experiments, the line-imaging Velocity Interferometer System for Any Reflector (VISAR) is a well-established diagnostic used to probe the velocity history, including wave profiles derived from dynamically compressed interfaces and wavefronts, depending on material optical properties. Knowledge of the velocity history allows for the determination of the pressure achieved during compression. Such a VISAR analysis is often based on Fourier transform techniques and assumes that the recorded interferograms are free from image distortions. In this paper, we describe the VISAR diagnostic installed at the HED-HIBEF instrument located at the European XFEL along with its calibration and characterization. It comprises a two-color (532, 1064 nm), three-arm (with three velocity sensitivities) line imaging system. We provide a procedure to correct VISAR images for geometric distortions and evaluate the performance of the system using Fourier analysis. We finally discuss the spatial and temporal calibrations of the diagnostic. As an example, we compare the pressure extracted from the VISAR analysis of shock-compressed polyimide and silicon.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Constructing Co Cluster Sites for Selective CO 2 Hydrogenation via Phase Segregation from Co-Doped TiO 2 Nanocrystals

This article presents a Co phase segregation strategy for creating stable Co cluster catalytic sites on TiO 2 , enabling selective CO 2 hydrogenation to CO. Through oxidative calcination, pre-synthesized Co-doped brookite TiO 2 nanorods transform into a mixed TiO 2 phase, leading to the phase segregation of Co species. The resulting Co clusters, stabilized by strong Co-TiO 2 interactions during reductive CO 2 hydrogenation, effectively suppress the formation of larger nanoparticles. The undercoordinated sites of these clusters promote a high CO production rate with near-unit selectivity, contrasting with Co nanoparticles, which favor CH 4 formation under identical conditions. In-situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) analysis indicates that the weakened CO adsorption on Co clusters is key to their enhanced CO selectivity, highlighting this method as a promising approach for efficient CO 2 utilization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Visualizing Crystallization Dynamics and Transformation Pathways of Disordered Rocksalt Oxides During Thermally Activated Sol–Gel Synthesis

Sol–gel synthesis is a wet-chemical processing route for fabricating functional materials with control over composition and microstructure at relatively low temperatures compared to conventional solid-state synthesis. While sol–gel process initiates with intermixed molecular precursors, the early-stage nucleation pathways are insufficiently understood. Here, in this study, the chemical and structural transformation of ion disordered rocksalt (DRX) Li 1.2 Mn 0.4 Ti 0.4 O 2 (LMTO), a promising cathode material for lithium batteries, is studied by multiscale characterizations. In situ heating transmission electron microscopy (TEM) using a liquid cell visualizes and identifies crystallization pathways at the nanoscale. While some regions follow a classical multi-step transition through thermodynamically stable intermediates, others exhibit a kinetic shortcut via a localized amorphous matrix to directly form the DRX structure. Macroscale Fourier transform infrared spectroscopy corroborates the findings and reveals that transition metal ions are more strongly incorporated into the acetate-coordinated network than lithium. Although in situ heating TEM captures diverse local transformation pathways, in situ synchrotron X-ray diffraction indicates that the macroscopic transformation proceeds predominantly through spinel LMTO and lithium titanates toward DRX-LMTO. The findings uncover the spatiotemporal chemical and structural transformations in sol–gel derived DRX-LMTO materials, and call for fine-tuning of such sol–gel chemistries to manipulate the crystallization pathways and achieve target material homogeneity more efficiently.

cathode material↗
DOE OSTI2021

Solid phase characterization and transformation of illite mineral with gas-phase ammonia treatment

In situ remediation applications of ammonia (NH 3 ) gas have potential for sequestration of subsurface contamination. Ammonia gas injections initially increase the pore water pH leading to mineral dissolution followed by formation of secondary precipitates as the pH is neutralized. However, there is a lack of understanding of fundamental alteration processes due to NH 3 treatment. In these batch studies, phyllosilicate minerals (illite and montmorillonite) were exposed to NH 3 gas with subsequent aeration to simulate in situ remediation. Following treatments, solids were characterized using a variety of techniques, including X-ray diffraction, N 2 adsorption-desorption analysis for surface area, Fourier transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR), and microscopy methods to investigate physicochemical transformations. The results of this study indicate that, at high pH, the clays are altered as observed by differences in morphology and particle size via microscopy. However, the two clays interact differently with NH 3 . While montmorillonite interlayers collapsed due to intercalation, illite layers were unaffected as confirmed by FTIR analysis. Further, structural changes in silicate ([SiO 4 ] n- ) and aluminol (Al-OH) groups were identified by NMR and FTIR. This research showed that mineral alteration processes occur during and after NH 3 gas treatment which may be used to remove radionuclides from the aqueous phase through sorption, co-precipitation, and coating with secondary phyllosilicate alteration products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multimodal imaging of hemorrhagic transformation biomarkers in an ischemic stroke model.

Abstract Hemorrhagic transformation of ischemic stroke has devastating consequences, with high mortality and poor functional outcomes. Animal models of ischemic stroke also demonstrate the potential for hemorrhagic transformation, which complicates biochemical characterization, treatment studies, and hinders poststroke functional outcomes in affected subjects. The incidence of hemorrhagic transformation of ischemic stroke in animal model research is not commonly reported. The postmortem brain of such cases presents a complex milieu of biomarkers due to the presence of healthy cells, regions of varying degrees of ischemia, dead and dying cells, dysregulated metabolites, and blood components (especially reactive Fe species released from lysed erythrocytes). To improve the characterization of hemorrhage biomarkers on an ischemic stroke background, we have employed a combination of histology, X-ray fluorescence imaging (XFI), and Fourier transform infrared (FTIR) spectroscopic imaging to assess 122 photothrombotic (ischemic) stroke brains. Rapid freezing preserves brain biomarkers in situ and minimizes metabolic artifacts due to postmortem ischemia. Analysis revealed that 25% of the photothrombotic models had clear signs of hemorrhagic transformation. The XFI and FTIR metabolites provided a quantitative method to differentiate key metabolic regions in these models. Across all hemorrhage cases, it was possible to consistently differentiate otherwise healthy tissue from other metabolically distinct regions, including the ischemic infarct, the ischemic penumbra, blood vessels, sites of hemorrhage, and a region surrounding the hemorrhage core that contained elevated lipid oxidation. Chemical speciation of deposited Fe demonstrates the presence of heme-Fe and accumulation of ferritin.

Pushie, M. J. (ORCID:0000000174945427)↗
DOE OSTI2021

Multi-Dimensional Scaling on Groups

Leveraging the intrinsic symmetries in data for clear and efficient analysis is an important theme in signal processing and other data-driven sciences. A basic example of this is the ubiquity of the discrete Fourier transform which arises from translational symmetry (i.e. time-delay/phase-shift). Particularly important in this area is understanding how symmetries inform the algorithms that we apply to our data. In this paper we explore the behavior of the dimensionality reduction algorithm multi-dimensional scaling (MDS) in the presence of symmetry. We show that understanding the properties of the underlying symmetry group allows us to make strong statements about the output of MDS even before applying the algorithm itself. In analogy to Fourier theory, we show that in some cases only a handful of fundamental ``frequencies'' (irreducible representations derived from the corresponding group) contribute information for the MDS Euclidean embedding.

Dimensionality reduction, Representation theory, D↗
DOE OSTI2022

Advantages of tandem versus simultaneous operation: The case of isomerization/hydrogenation of terpinolene epoxide to Terpinen-4-ol using a Ni/TiO 2 -SiO 2 bifunctional catalyst

The conversion of terpinolene epoxide to terpinen-4-ol is a desirable chemical transformation for the production of a valuable intermediate. Here this report describes a one-pot, two-step system for the reaction that uses a bifunctional Ni/TiO 2 -SiO 2 catalyst with isomerization and hydrogenation capabilities. The TiO 2 -SiO 2 serves to isomerize the starting epoxide. The Ni component works to hydrogenate the allylic double bond. The tandem system achieves a high 64% yield of terpinen-4-ol. X-ray diffraction analysis showed that TiO 2 -SiO 2 was a mixed binary oxide, and Fourier transform infrared spectroscopy of adsorbed pyridine suggested that acid sites were mainly Lewis acid sites. Electron microscopy showed that the Ni/TiO 2 -SiO 2 catalyst consisted of spherical particles comprising a titanosilicate phase with highly dispersed zero-valent Ni or anatase on the surface. Additionally, there was strong interaction between Ni and the TiO 2 -SiO 2 mixed oxides. Control kinetic experiments demonstrated that the tandem use of the catalysts was more effective than simultaneous operation.

42 ENGINEERING↗
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↗