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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 OSTI2022

Behavior of helium cavities in ion-irradiated W-Ni-Fe ductile-phase toughened tungsten

This study reports on the distribution of helium (He) cavities in a hot-rolled W-Ni-Fe ductile-phase toughened tungsten (DPT W) composite irradiated to a dose and a helium concentration that are comparable to those in the material after 5-year irradiation in a conceptual fusion power plant. Here, the DPT W sample consists of W particles embedded in a ductile-phase NiFeW matrix with a nominal composition of 90W-7Ni-3Fe by weight. It was hot-rolled to a thickness reduction by 87% (87R DPT W). Sequential irradiation of the material with 1.2 MeV Ni + ions to a fluence of 2.15×10 16 Ni + /cm 2 and 90 keV He + ions to 6.5×10 15 He + /cm 2 was performed at 973 K. Larger He cavities with a lower number density are observed in NiFeW than W. Helium cavities are aggregated preferentially along the NiFeW/W interphase boundary. This behavior is not observed along the W/W grain boundary under the same irradiation conditions. A similar distribution of He cavities with comparable sizes is observed in 87R DPT W irradiated with He + ions only, suggesting that the He cavity distribution is not significantly affected by pre-irradiation of Ni + ions at 973 K. The data from this study does not provide any evidence for formation of visible voids or Ni precipitates in W phase irradiated with Ni + ions only. Diffusion and clustering of He atoms and mobile vacancies during ion irradiation at 973 K are responsible for the formation and growth of the He cavities.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Evolution Of Lattice Structure And Chemical Composition Of The Surface Reconstruction Layer In Li1.2Ni0.2Mn0.6O2 Cathode Material For Lithium Ion Batteries

Voltage and capacity fading of layer structured lithium and manganese rich (LMR) transition metal oxide is directly related to the structural and composition evolution of the material during the cycling of the battery. However, understanding such evolution at atomic level remains elusive. Based on atomic level structural imaging, elemental mapping of the pristine and cycled samples and density functional theory calculations, it is found that accompanying the hoping of Li ions is the simultaneous migration of Ni ions towards the surface from the bulk lattice, leading to the gradual depletion of Ni in the bulk lattice and thickening of a Ni enriched surface reconstruction layer (SRL). Furthermore, Ni and Mn also exhibit concentration partitions within the thin layer of SRL in the cycled samples where Ni is almost depleted at the very surface of the SRL, indicating the preferential dissolution of Ni ions in the electrolyte. Accompanying the elemental composition evolution, significant structural evolution is also observed and identified as a sequential phase transition of C2/m →I41→Spinel. For the first time, it is found that the surface facet terminated with pure cation is more stable than that with a mixture of cation and anion. These findings firmly established how the elemental species in the lattice of LMR cathode transfer from the bulk lattice to surface layer and further into the electrolyte, clarifying the long standing confusion and debate on the structure and chemistry of the surface layer and their correlation with the voltage fading and capacity decaying of LMR cathode. Therefore, this work provides critical insights for designing of cathode materials with both high capacity and voltage stability during cycling.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2017

Scanning Quantum Cryogenic Atom Microscope

Microscopic imaging of local magnetic fields provides a window into the organizing principles of complex and technologically relevant condensed-matter materials. However, a wide variety of intriguing strongly correlated and topologically nontrivial materials exhibit poorly understood phenomena outside the detection capability of state-of-the-art high-sensitivity high-resolution scanning probe magnetometers. We introduce a quantum-noise-limited scanning probe magnetometer that can operate from room-to-cryogenic temperatures with unprecedented dc-field sensitivity and micron-scale resolution. The Scanning Quantum Cryogenic Atom Microscope (SQCRAMscope) employs a magnetically levitated atomic Bose-Einstein condensate (BEC), thereby providing immunity to conductive and blackbody radiative heating. The SQCRAMscope has a field sensitivity of 1.4 nT per resolution-limited point (approximately 2 μm) or 6 nT/√Hz per point at its duty cycle. Furthermore, compared to point-by-point sensors, the long length of the BEC provides a naturally parallel measurement, allowing one to measure nearly 100 points with an effective field sensitivity of 600 pT/√Hz for each point during the same time as a point-by-point scanner measures these points sequentially. Moreover, it has a noise floor of 300 pT and provides nearly 2 orders of magnitude improvement in magnetic flux sensitivity (down to 10 -6 Φ 0 /√Hz) over previous atomic probe magnetometers capable of scanning near samples. These capabilities are carefully benchmarked by imaging magnetic fields arising from microfabricated wire patterns in a system where samples may be scanned, cryogenically cooled, and easily exchanged. We anticipate the SQCRAMscope will provide charge-transport images at temperatures from room temperature to 4 K in unconventional superconductors and topologically nontrivial materials.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Search for minimal supersymmetric standard model Higgs Bosons H / A and for a $Z^{\prime}$ boson in the $\tau\tau $ final state produced in pp collisions at $\sqrt{s}$= 13 TeV with the ATLAS detector

A search for neutral Higgs bosons of the minimal supersymmetric standard model (MSSM) and for a heavneutral Z ' boson is performed using a data sample corresponding to an integrated luminosity of 3.2 fb - 1 from proton–proton collisions at √s=13 TeV recorded by the ATLAS detector at the LHC. The heavy resonance is assumed to decay to a τ + τ - pair with at least one τ lepton decaying to final states with hadrons and a neutrino. The search is performed in the mass range of 0.2–1.2 TeV for the MSSM neutral Higgs bosons and 0.5–2.5 TeV for the heavy neutral Z ' boson. The data are in good agreement with the background predicted by the Standard Model. The results are interpreted in MSSM and Z ' benchmark scenarios. The most stringent constraints on the MSSM m A –tan β space exclude at 95 % confidence level (CL) tan β > 7.6 for m A = 200 GeV in the m$mod+\atop{h}$ MSSM scenario. For the Sequential Standard Model, a Z$'\atop{SSM}$ mass up to 1.90 TeV is excluded at 95 % CL and masses up to 1.82–2.17 TeV are excluded for a Z'$\atop{SFM}$ of the strong flavour model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Leaching Behavior of Rare Earth Elements in Fort Union Lignite Coals of North America

Rare earth elements are crucial materials in an incredible array of consumer goods, energy system components and military defense applications. However, the global production and entire value chain for rare earth elements is dominated by China, with the U.S. currently 100% import reliant for these critical materials. Traditional mineral ores including those previously mined in the U.S., however, have several challenges. Chief among these is that the content of the most critical and valuable of the rare earths are deficient, making mining uneconomical. Further, the supply of these most critical rare earths is nearly 100% produced in China from a single resource that is only projected to last another 10 to 20 years. The U.S. currently considers the rare earths market an issue of national security. It is imperative that alternative domestic sources of rare earths be identified and methods developed to produce them. Recently, coal and coal byproducts have been identified as one of these promising alternative resources. This paper details the results of a study on characterization of North Dakota lignite and lignite-related feedstocks as an assessment of their feasibility for rare earth element recovery. The abundance, distribution and modes of occurrence of the rare earth elements in the samples collected were determined in this initial study to inform the selection of appropriate extraction and concentration methods to recover the rare earth elements. Materials investigated include the lignite coals, clay-rich sediments associated with the coal seams, and materials associated with a lignite beneficiation system and power plant. The results show that high rare earth element levels exist both in lignite coals and associated sediments. The form of the rare earth elements in the clay materials is primarily as ultra-fine mineral grains. In the lignite coals, approximately 80-95% of the rare earths content is organically associated, primarily as coordination complexes.

Laudal, Daniel A.↗
DOE OSTI2026

Process-driven roadmap for depositing super duplex stainless steel via wire Arc additive manufacturing

Here, this study systematically investigates the effects of shielding gas, bead spacing, weld mode, and travel speed on the phase balance, porosity, and hardness of wire arc additively manufactured (WAAM) super duplex stainless steel (ER2594). Robotic WAAM was employed to fabricate multilayer walls under systematically varied process conditions, followed by phase transformation simulations, X-ray computed tomography (XCT), electron backscatter diffraction (EBSD), and microhardness evaluation. Thermodynamic simulations predicted rapid cooling of AM process can suppress the potential formation of deleterious precipitates which was later validated via cross-sectional microstructure analyses of printed samples. XCT revealed porosity levels below 0.2% for all deposits, with reduced travel speed significantly lowering defect volume. Microstructural analyses revealed the evolution of various austenite precipitates, including grain boundary austenite (GBA), Widmanstätten austenite (WA), and intergranular austenite (IGA), sequentially upon cooling of the ferrite phase. Among all process parameters, weld transfer mode exhibited the strongest influence on phase balance; pulsed mode promoted higher ferrite retention (~ 36%) compared to RapidX mode. No consistent relationship between stabilized phase fraction and captured microhardness was observed. This work provides critical insights for optimizing WAAM parameters to control phase balance and mechanical performance, which is essential for producing high-integrity super duplex stainless-steel components for nuclear and marine applications.

Grain orientation↗
DOE OSTI2020

Differentiating and Quantifying Gas-Phase Conformational Isomers Using Coulomb Explosion Imaging

Conformational isomerism plays a crucial role in defining the physical and chemical properties and biological activity of molecules ranging from simple organic compounds to complex biopolymers. However, it is often a significant challenge to differentiate and separate these isomers experimentally as they can easily interconvert due to their low rotational energy barrier. Here, we use the momentum correlation of fragment ions produced after inner-shell photoionization to distinguish conformational isomers of 1,2-dibromoethane (C 2 H 4 Br 2 ). We demonstrate that the three-body breakup channel, C 2 H 4 + + Br + + Br + , contains signatures of both sequential and concerted breakup, which are decoupled to distinguish the geometries of two conformational isomers and to quantify their relative abundance. The sensitivity of our method to quantify these yields is established by measuring the relative abundance change with sample temperature, which agrees well with calculations. Finally, our study paves the way for using Coulomb explosion imaging to track subtle molecular structural changes.

Photoionization↗
DOE OSTI2018

Spatial distribution of organic functional groups supported on mesoporous silica nanoparticles (2): a study by 1 H triple-quantum fast-MAS solid-state NMR

The distribution of organic functional groups attached to the surface of mesoporous silica nanoparticles (MSNs) via co-condensation was scrutinized using 1D and 2D 1 H solid-state NMR, including the triple-quantum/single-quantum (TQ/SQ) homonuclear correlation technique. The excellent sensitivity of 1 H NMR and high resolution provided by fast magic angle spinning (MAS) allowed us to study surfaces with very low concentrations of aminopropyl functional groups. The sequential process, in which the injection of tetraethyl orthosilicate (TEOS) into the aqueous mother liquor was followed by dropwise addition of the organosilane precursor, resulted in deployment of organic groups on the surface, which were highly clustered even in a sample with a very low loading of ~0.1 mmol g -1 . The underlying mechanism responsible for clustering could involve fast aggregation of the aminopropyltrimethoxysilane (APTMS) precursor within the liquid phase, and/or co-condensation of the silica-bound molecules. Understanding the deposition process and the resulting topology of surface functionalities with atomic-scale resolution, can help to develop novel approaches to the synthesis of complex inorganic–organic hybrid materials.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Broadband multi-resonant strong field coherence breaking as a tool for single isomer microwave spectroscopy

Using standard hardware available in chirped-pulse Fourier transform microwave (CP-FTMW) spectroscopy, an experimental method is introduced to selectively extract from the microwave spectrum of an otherwise complicated multicomponent mixture a set of transitions due to a single component, thereby speeding spectral assignment. The method operates the broadband chirped-pulse used to excite the sample in the strong-field limit through a combination of high power and control of the sweep rate. A procedure is introduced that leads to selection of three transition frequencies that can be incorporated as a set of resonant sequential single-frequency microwave pulses that follow broadband chirped-pulse excitation, resulting in a reduction in the coherent signal from a set of transitions ascribable to the component of interest. The difference in the CP-FTMW spectrum with and without this set of multi-resonant single-frequency pulses produces a set of transitions that can confidently be assigned to a single component of the mixture, aiding the analysis of its spectrum. In conclusion, the scheme is applied to (i) selectively extract the spectrum of one of five singly 13 C-subsituted isotopologues of benzonitrile in natural abundance, (ii) obtain the microwave spectra of the two structural isomers (E)- and (Z)-phenylvinylnitrile, and (iii) obtain conformer-specific microwave spectra of methylbutyrate.

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

Correlation of Advanced Accelerated Stress Testing with Polyamide-Based Photovoltaic Backsheet Field-Failures

Cracking of polyamide (PA)-based photovoltaic (PV) backsheet materials has been widely reported for field-aged modules. Failure was not detected by conventional accelerated stress tests (ASTs), which lacked the necessary combination of stress factors and/or factor sequences. PA-based AAA backsheet cracking has since been reproduced through combined and sequential stress testing. Planar- and cross-sectional-optical microscopy as well as Fourier-transform Infrared Spectroscopy (FTIR), have been used to elucidate the mechanical and chemical changes which lead to failure of the backsheet. Field-aged backsheet samples demonstrating failure in various climates (including locations in China and Italy) are also analyzed. Through the analysis, a comparison is made between the different stress testing protocols and the field-aged samples to validate relevance of the advanced stress tests. It is shown that the changes induced through combined-accelerated stress testing (C-AST) were most representative of changes induced by the field, supporting the relevance of C-AST and providing validity for the test protocol.

14 SOLAR ENERGY↗
DOE OSTI2015

MO-F-CAMPUS-J-02: Automatic Recognition of Patient Treatment Site in Portal Images Using Machine Learning

Purpose: To investigate the method to automatically recognize the treatment site in the X-Ray portal images. It could be useful to detect potential treatment errors, and to provide guidance to sequential tasks, e.g. automatically verify the patient daily setup. Methods: The portal images were exported from MOSAIQ as DICOM files, and were 1) processed with a threshold based intensity transformation algorithm to enhance contrast, and 2) where then down-sampled (from 1024×768 to 128×96) by using bi-cubic interpolation algorithm. An appearance-based vector space model (VSM) was used to rearrange the images into vectors. A principal component analysis (PCA) method was used to reduce the vector dimensions. A multi-class support vector machine (SVM), with radial basis function kernel, was used to build the treatment site recognition models. These models were then used to recognize the treatment sites in the portal image. Portal images of 120 patients were included in the study. The images were selected to cover six treatment sites: brain, head and neck, breast, lung, abdomen and pelvis. Each site had images of the twenty patients. Cross-validation experiments were performed to evaluate the performance. Results: MATLAB image processing Toolbox and scikit-learn (a machine learning library in python) were used to implement the proposed method. The average accuracies using the AP and RT images separately were 95% and 94% respectively. The average accuracy using AP and RT images together was 98%. Computation time was ∼0.16 seconds per patient with AP or RT image, ∼0.33 seconds per patient with both of AP and RT images. Conclusion: The proposed method of treatment site recognition is efficient and accurate. It is not sensitive to the differences of image intensity, size and positions of patients in the portal images. It could be useful for the patient safety assurance. The work was partially supported by a research grant from Varian Medical System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Low soil phosphorus availability triggers maize growth stage specific rhizosphere processes leading to mineralization of organic P

Phosphorus (P) is one of the essential nutrients for all living organisms. High-quality mineral P fertilizer is a finite resource with only an estimated 80-100 years of reserves remaining globally. Both plants and microbes have developed several mechanisms such as secretion of organic acids, acidification of the rhizosphere, and production of extracellular enzymes to enhance the acquisition of P from soils. Increased activity of phosphatase occurs in response to P deficiency as part of P starvation responses which catalyze the hydrolysis of P o from soil organic matter (SOM) and release inorganic P (P i ). However, the specific interactions between plants and microbial communities in the rhizosphere soil triggered by P deficiency are largely unknown. In a greenhouse study we grew maize plants in low and high P containing soils and examined the role of rhizosphere processes on mineralization of organic P (P o ) in soils with low and high P availability and different P speciation 23 (Po dominated versus P i dominated) and determine its effect on plant growth. Plant biomass was determined and rhizosphere soils, and soil samples from pots with and without plants were collected at key vegetative growth stages (VGS). A variety of biogeochemical parameters (e.g. microbial biomass C and P, potential phosphatase activities, plant biomass P, soil P species etc.) were determined using both conventional (sequential chemical extraction) and advanced (e.g. high resolution mass spectrometry (FTICR-MS) and 3129 P solution NMR) techniques. Here, we used phospholipid fatty acid (PLFA) and DNA based microbial community analysis to track changes in microbial community structure and diversity. Low P availability induced changes in biogeochemical processes and microbial community composition in the rhizosphere soils of plants grown in low P containing soil. At early VGS, the plants in low P soil were visually struggling which correlated with greater rhizosphere potential acid phosphatase activity and a reduction in P o fractions. At late VGS, the plants appeared to recover which correlated with a decrease in Meh (III) extractable P, an increase in microbial biomass C and P and greater total P in the plant biomass (roots, shoots and leaves). In high P containing soil, on the other hand, greater P availability masked these rhizosphere processes. Our results confirmed the degradation of SOM and Po mineralization in rhizosphere soils driven by microbe and plant need for P. P deficiency may have favored the abundance of fungi which utilized easily degradable root exudates for the production of extracellular enzymes responsible for the mineralize of SOM P o . This study highlights the intertwined mechanisms involved, and emphasizes the importance of, P o sources for plant nutrition and survival in marginal soils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Isotopic determination of uranium in soil by laser induced breakdown spectroscopy

Laser-induced breakdown spectroscopy (LIBS) operated under ambient pressure has been evaluated for isotopic analysis of uranium in real-world samples such as soil, with U concentrations in the single digit percentage levels. The study addresses the requirements for spectral decomposition of 235 U and 238 U atomic emission peaks that are only partially resolved. Although non-linear least-square fitting algorithms are typically able to locate the optimal combination of fitting parameters that best describes the experimental spectrum even when all fitting parameters are treated as free independent variables, the analytical results of such an unconstrained free-parameter approach are ambiguous. In this work, five spectral decomposition algorithms were examined, with different known physical properties (e.g., isotopic splitting, hyperfine structure) of the spectral lines sequentially incorporated into the candidate algorithms as constraints. It was found that incorporation of such spectral-line constraints into the decomposition algorithm is essential for the best isotopic analysis. The isotopic abundance of 235 U was determined from a simple two-component Lorentzian fit on the U II 424.437 nm spectral profile. For six replicate measurements, each with only fifteen laser shots, on a soil sample with U concentration at 1.1% w/w, the determined 235 U isotopic abundance was (64.6 ± 4.8)%, and agreed well with the certified value of 64.4%. Another studied U line - U I 682.691 nm possesses hyperfine structure that is comparatively broad and at a significant fraction as the isotopic shift. Thus, 235 U isotopic analysis with this U I line was performed with spectral decomposition involving individual hyperfine components. For the soil sample with 1.1% w/w U, the determined 235 U isotopic abundance was (60.9 ± 2.0)%, which exhibited a relative bias about 6% from the certified value. The bias was attributed to the spectral resolution of our measurement system - the measured line width for this U I line was larger than its isotopic splitting. In conclusion, although not the best emission line for isotopic analysis, this U I emission line is sensitive for element analysis with a detection limit of 500 ppm U in the soil matrix; the detection limit for the U II 424.437 nm line was 2000 ppm.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Using Flory–Huggins-informed human-in-the-loop Bayesian optimization to map the phase diagram of polymer blends

Mapping the phase diagram of polymer blends is an essential step in controlling the structure–property relationship of polymer-based materials. However, traditional grid-based approaches are inefficient and rely on subjective judgements for terminating the experimental campaign. Artificial intelligence-guided experimentation offers a compelling alternative, especially when data-driven decision-making is interfaced with established polymer thermodynamics to improve efficiency and interpretability. Here, we introduce a physics-informed Bayesian optimization approach to guide the mapping of the phase diagram of a model blend containing poly(methyl methacrylate) and poly(styrene-ran-acrylonitrile). Physical information is derived from a Flory–Huggins representation of the spinodal curve, which is integrated into the Bayesian optimization process as a structured prior mean that acts as a soft constraint. Implemented as a human-in-the-loop workflow, the approach leverages optical imaging of film cloudiness with iterative Gaussian process surrogate modeling and a parameter selection decision policy to identify the composition-temperature conditions for sequential iterations. Convergence of kernel and Flory–Huggins-based hyperparameters provided a stopping criterion, ensuring an objective and interpretable termination of the experimental campaign. The framework recovered the known lower critical solution temperature (∼160 °C), while increasing material efficiency through targeted sampling. This work establishes a proof-of-concept for the application of Bayesian optimization workflows to study polymer blend miscibility.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Electrically driven photon emission from individual atomic defects in monolayer WS 2

Quantum dot–like single-photon sources in transition metal dichalcogenides (TMDs) exhibit appealing quantum optical properties but lack a well-defined atomic structure and are subject to large spectral variability. Here, we demonstrate electrically stimulated photon emission from individual atomic defects in monolayer WS 2 and directly correlate the emission with the local atomic and electronic structure. Radiative transitions are locally excited by sequential inelastic electron tunneling from a metallic tip into selected discrete defect states in the WS 2 bandgap. Coupling to the optical far field is mediated by tip plasmons, which transduce the excess energy into a single photon. The applied tip-sample voltage determines the transition energy. Atomically resolved emission maps of individual point defects closely resemble electronic defect orbitals, the final states of the optical transitions. Inelastic charge carrier injection into localized defect states of two-dimensional materials provides a powerful platform for electrically driven, broadly tunable, atomic-scale single-photon sources.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Machine learning-based inversion for acoustic impedance with large synthetic training data: Workflow and data characterization

Where wells are sparse or training data are difficult to label with high-quality wireline-derived impedance logs, machine learning (ML)-based inversion of acoustic impedance typically depends on small training data sets, leading to biased prediction. We have advanced a novel workflow that applies large synthetic seismic training data to reduce facies-related bias. Using a geologically realistic model as the truth model, we randomly select sparse seed wells to perform sequential Gaussian simulation (SGS) for impedance models of the same geometry and simulate facies variability. We implement random forest regression on 30 features extracted from the synthetic volume. We observe that more seed wells tend to reduce facies-induced bias by sampling more types of facies, resulting in a better prediction. We then focus on the responses of SGS models to facies changes, the number of seed wells necessary for a useful synthetic model, and how much a synthetic model can help ML-based inversion. Here, we observe that the SGS synthetic training model outperforms well-direct training in general. For modeled clastic shore-zone systems in Miocene Gulf of Mexico, two or more seed wells are necessary for a significant reduction of root-mean-square error and outliners, and improvement of facies imaging. In a field-data test, we apply a similar workflow to quantitatively predict acoustic impedance, which is then converted to a sand-volume map at a high-frequency sequence (10–100 m), revealing detailed facies and sandstone patterns. Such results are valuable in many geologic and engineering applications, such as hydrocarbon and CO 2 reservoir prospecting, reserve estimation, simulation, etc.

3D seismic↗
DOE OSTI2017

Speciation of mercury in sludge solids: washed sludge

The objective of this applied research task was to study the type and concentration of mercury compounds found within the contaminated Savannah River Site Liquid Waste System (SRS LWS). A method of selective sequential extraction (SSE), developed by Eurofins Frontier Global Sciences1,2 and adapted by SRNL, utilizes an extraction procedure divided into seven separate tests for different species of mercury. In the SRNL’s modified procedure four of these tests were applied to a washed sample of high level radioactive waste sludge.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗