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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Direct evidence for low-energy electron emission following O LVV Auger transitions at oxide surfaces

Abstract Oxygen, the third most abundant element in the universe, plays a key role in the chemistry of condensed matter and biological systems. Here, we report evidence for a hitherto unexplored Auger transition in oxides, where a valence band electron fills a vacancy in the 2s state of oxygen, transferring sufficient energy to allow electron emission. We used a beam of positrons with kinetic energies of $$\sim 1$$ ∼ 1 eV to create O 2s holes via matter-antimatter annihilation. This made possible the elimination of the large secondary electron background that has precluded definitive measurements of the low-energy electrons emitted through this process. Our experiments indicate that low-energy electron emission following the Auger decay of O 2s holes from adsorbed oxygen and oxide surfaces are very efficient. Specifically, our results indicate that the low energy electron emission following the Auger decay of O 2s hole is nearly as efficient as electron emission following the relaxation of O 1s holes in $$\hbox {TiO}_2$$ TiO 2 . This has important implications for the understanding of Auger-stimulated ion desorption, Coulombic decay, photodynamic cancer therapies, and may yield important insights into the radiation-induced reactive sites for corrosion and catalysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Wind plants can impact long-term local atmospheric conditions

Abstract Long-term weather and climate observatories can be affected by the changing environments in their vicinity, such as the growth of urban areas or changing vegetation. Wind plants can also impact local atmospheric conditions through their wakes, characterized by reduced wind speed and increased turbulence. We explore the extent to which the wind plants near an atmospheric measurement site in the central United States have affected their long-term measurements. Both direct observations and mesoscale numerical weather prediction simulations demonstrate how the wind plants induce a wind deficit aloft, especially in stable conditions, and a wind speed acceleration near the surface, which extend $$\sim 30$$ ∼ 30 km downwind of the wind plant. Turbulence kinetic energy is significantly enhanced within the wind plant wake in stable conditions, with near-surface observations seeing an increase of more than 30% a few kilometers downwind of the plants.

17 WIND ENERGY↗
DOE OSTI2022

A laser parameter study on enhancing proton generation from microtube foil targets

Abstract The interaction of an intense laser with a solid foil target can drive $$\sim$$ ∼ TV/m electric fields, accelerating ions to MeV energies. In this study, we experimentally observe that structured targets can dramatically enhance proton acceleration in the target normal sheath acceleration regime. At the Texas Petawatt Laser facility, we compared proton acceleration from a $$1\, {\upmu }\hbox {m}$$ 1 μ m flat Ag foil, to a fixed microtube structure 3D printed on the front side of the same foil type. A pulse length (140–450 fs) and intensity ((4–10) $$\times 10^{20}$$ × 10 20 W/cm $$^2$$ 2 ) study found an optimum laser configuration (140 fs, 4 $$\times 10^{20}$$ × 10 20 W/cm $$^2$$ 2 ), in which microtube targets increase the proton cutoff energy by 50% and the yield of highly energetic protons ( $$>10$$ > 10 MeV) by a factor of 8 $$\times$$ × . When the laser intensity reaches $$10^{21}$$ 10 21 W/cm $$^2$$ 2 , the prepulse shutters the microtubes with an overcritical plasma, damping their performance. 2D particle-in-cell simulations are performed, with and without the preplasma profile imported, to better understand the coupling of laser energy to the microtube targets. The simulations are in qualitative agreement with the experimental results, and show that the prepulse is necessary to account for when the laser intensity is sufficiently high.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Multicolor multifocal 3D microscopy using in-situ optimization of a spatial light modulator

Abstract Multifocal microscopy enables high-speed three-dimensional (3D) volume imaging by using a multifocal grating in the emission path. This grating is typically designed to afford a uniform illumination of multifocal subimages for a single emission wavelength. Using the same grating for multicolor imaging results in non-uniform subimage intensities in emission wavelengths for which the grating is not designed. This has restricted multifocal microscopy applications for samples having multicolored fluorophores. In this paper, we present a multicolor multifocal microscope implementation which uses a Spatial Light Modulator (SLM) as a single multifocal grating to realize near-uniform multifocal subimage intensities across multiple wavelength emission bands. Using real-time control of an in-situ-optimized SLM implemented as a multifocal grating, we demonstrate multicolor multifocal 3D imaging over three emission bands by imaging multicolored particles as well as Escherichia coli ( E. coli ) interacting with human liver cancer cells, at $$\sim 2.5$$ ∼ 2.5 multicolor 3D volumes per second acquisition speed. Our multicolor multifocal method is adaptable across SLM hardware, emission wavelength band locations and number of emission bands, making it particularly suited for researchers investigating fast processes occurring across a volume where multiple species are involved.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Ultrafast laser filament-induced fluorescence for detecting uranium stress in Chlamydomonas reinhardtii

Abstract Plants and other photosynthetic organisms have been suggested as potential pervasive biosensors for nuclear nonproliferation monitoring. We demonstrate that ultrafast laser filament-induced fluorescence of chlorophyll in the green alga Chlamydomonas reinhardtii is a promising method for remote, in-field detection of stress from exposure to nuclear materials. This method holds an advantage over broad-area surveillance, such as solar-induced fluorescence monitoring, when targeting excitation of a specific plant would improve the detectability, for example when local biota density is low. After exposing C. reinhardtii to uranium, we find that the concentration of chlorophyll a, chlorophyll fluorescence lifetime, and carotenoid content increase. The increased fluorescence lifetime signifies a decrease in non-photochemical quenching. The simultaneous increase in carotenoid content implies oxidative stress, further confirmed by the production of radical oxygen species evidence in the steady-state absorption spectrum. This is potentially a unique signature of uranium, as previous work finds that heavy metal stress generally increases non-photochemical quenching. We identify the temporal profile of the chlorophyll fluorescence to be a distinguishing feature between uranium-exposed and unexposed algae. Discrimination of uranium-exposed samples is possible at a distance of $$\sim $$ ∼ 35 m with a single laser shot and a modest collection system, as determined through a combination of experiment and simulation of distance-scaled uncertainty in discriminating the temporal profiles. Illustrating the potential for remote detection, detection over 125 m would require 100 laser shots, commensurate with the detection time on the order of 1 s.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Complexity-calibrated benchmarks for machine learning reveal when prediction algorithms succeed and mislead

Abstract Recurrent neural networks are used to forecast time series in finance, climate, language, and from many other domains. Reservoir computers are a particularly easily trainable form of recurrent neural network. Recently, a “next-generation” reservoir computer was introduced in which the memory trace involves only a finite number of previous symbols. We explore the inherent limitations of finite-past memory traces in this intriguing proposal. A lower bound from Fano’s inequality shows that, on highly non-Markovian processes generated by large probabilistic state machines, next-generation reservoir computers with reasonably long memory traces have an error probability that is at least $$\sim 60\%$$ ∼ 60 % higher than the minimal attainable error probability in predicting the next observation. More generally, it appears that popular recurrent neural networks fall far short of optimally predicting such complex processes. These results highlight the need for a new generation of optimized recurrent neural network architectures. Alongside this finding, we present concentration-of-measure results for randomly-generated but complex processes. One conclusion is that large probabilistic state machines—specifically, large $$\epsilon$$ ϵ -machines—are key to generating challenging and structurally-unbiased stimuli for ground-truthing recurrent neural network architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Multireference diffusion Monte Carlo reaches 2D materials

Abstract Quantum confinement in 2D materials strongly enhances electronic correlation effects. Therefore, predicting the properties of these unique materials, with both a high level of accuracy and computational efficiency, without relying on adjustable parameters or functionals, remains an outstanding theoretical challenge. The majority of theoretical studies are based on the approximations of density functional theory (DFT). The reliability of DFT predictions are heavily dependent on the choice of an approximated exchange-correlation functional. Here, we estimate the magnitude of impact of correlation on the total energy for the quintessential 2D material, graphene, by performing and comparing state-of-the-art selected CI and quantum Monte Carlo extrapolated calculations for a single unit cell at the$$\Gamma$$point. We demonstrate that Self-Healing Diffusion Monte Carlo (SHDMC) obtains a very compact, but high-quality wavefunction for this system that lacks the strong basis set dependence displayed by state of the art quantum chemistry methods. The SHDMC wavefunction is of higher quality compared to that obtained from sCI, in the same orbital basis, while being$$\sim$$ 1000 times smaller in terms of determinant count compared to sCI. We also demonstrate that extrapolating SHDMC results to the infinite determinant limit compares extremely well with complete basis set extrapolated sCI. Our work paves the way for future validation of SHDMC applied to challenging 2D materials.

Science & Technology - Other Topics↗
DOE OSTI2015

Vertical and lateral morphology effects on solar cell performance for a thiophene–quinoxaline copolymer:PC 70 BM blend

The distribution of electron donor and acceptor in the active layer is known to strongly influence the electrical performance of polymer solar cells for most of the high performance polymer:fullerene systems. The formulation of the solution from which the active layer is spincoated plays an important role in the quest for morphology control. We have studied how the choice of solvent and the use of small amounts of a low vapour pressure additive in the coating solution influence the film morphology and the solar cell performance for blends of poly[2,3-bis-(3-octyloxyphenyl)quinoxaline-5,8-diyl-alt-thiophene-2,5-diyl] (TQ1) and [6,6]-phenyl C 71 -butyric acid methyl ester (PC 70 BM). We have investigated the lateral morphology using atomic force microscopy (AFM) and scanning transmission X-ray microscopy (STXM), the vertical morphology using dynamic secondary ion mass spectrometry (d-SIMS) and variable-angle spectroscopic ellipsometry (VASE), and the surface composition using near-edge X-ray absorption fine structure (NEXAFS). The lateral phase-separated domains observed in films spincoated from single solvents, increase in size with increasing solvent vapour pressure and decreasing PC 70 BM solubility, but are not observed when 1-chloronaphthalene (CN) is added. A strongly TQ1-enriched surface layer is formed in all TQ1:PC 70 BM blend films and rationalized by surface energy differences. The photocurrent and power conversion efficiency strongly increased upon the addition of CN, while the leakage current decreased by one to two orders of magnitude. The higher photocurrent correlates with the finer lateral structure and stronger TQ1-enrichment at the interface with the electron-collecting electrode. This indicates that the charge transport and collection are not hindered by this polymer-enriched surface layer. Neither the open-circuit voltage nor the series resistance of the devices are sensitive to the differences in morphology.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Understanding ligand effects in gold clusters using mass spectrometry

This review summarizes recent research on the influence of phosphine ligands on the size, stability, and reactivity of gold clusters synthesized in solution. Sub-nanometer clusters exhibit size- and composition-dependent properties that are unique from those of larger nanoparticles. The highly tunable properties of clusters and their high surface-to-volume ratio make them promising candidates for a variety of technological applications. However, because “each-atom-counts” toward defining cluster properties it is critically important to develop robust synthesis methods to efficiently prepare clusters of predetermined size. For decades phosphines have been known to direct the size-selected synthesis of gold clusters. Despite the preparation of numerous species it is still not understood how different functional groups at phosphine centers affect the size and properties of gold clusters. Using electrospray ionization mass spectrometry (ESI-MS) it is possible to characterize the effect of ligand substitution on the distribution of clusters formed in solution at defined reaction conditions. In addition, ligand exchange reactions on preformed clusters may be monitored using ESI-MS. Collision induced dissociation (CID) may also be employed to obtain qualitative insight into the fragmentation of mixed ligand clusters and the relative binding energies of differently substituted phosphines. Quantitative ligand binding energies and cluster stability may be determined employing surface induced dissociation (SID) in a custom-built Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR-MS). Rice-Ramsperger-Kassel-Marcus (RRKM) based modeling of the SID data allows dissociation energies and entropy values to be extracted that may be compared with the results of high-level theoretical calculations. The charge reduction and reactivity of atomically precise gold clusters, including partially ligated species generated in the gas-phase by in source CID, on well-defined surfaces may be explored using ion soft landing (SL) in a custom-built instrument combined with in situ time of flight secondary ion mass spectrometry (TOF-SIMS). Jointly, this multipronged experimental approach allows characterization of the full spectrum of relevant phenomena including cluster synthesis, ligand exchange, thermochemistry, surface immobilization, and reactivity. The fundamental insights obtained from this work will facilitate the directed synthesis of gold clusters with predetermined size and properties for specific applications.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2017

Fully convolutional neural network for removing background in noisy images of uranium bearing particles

A fully convolutional neural network (FCN) was developed to supersede automatic or manual thresholding algorithms used for tabulating SIMS particle search data. The FCN was designed to perform a binary classification of pixels in each image belonging to a particle or not, thereby effectively removing background signal without manually or automatically determining an intensity threshold. Using 8,000 images from 28 different particle screening analyses, the FCN was trained to accurately predict pixels belonging to a particle with near 99% accuracy. Background eliminated images were then segmented using a watershed technique in order to determine isotopic ratios of particles. A comparison of the isotopic distributions of an independent data set segmented using the neural network, compared to a commercially available automated particle measurement (APM) program developed by CAMECA, highlighted the necessity for effective background removal to ensure that resulting particle identification is not only accurate, but preserves valuable signal that could be lost due to improper segmentation. The FCN approach improves the robustness of current state-of-the-art particle searching algorithms by reducing user input biases, resulting in an improved absolute signal per particle and decreased uncertainty of the determined isotope ratios.

Tarolli, Jay G. (ORCID:0000000307369057)↗
DOE OSTI2017

Two coexisting liquid phases in switchable ionic liquids

Switchable ionic liquids (SWILs) derived from organic bases and alcohols are attractive due to their applications in gas capture, separations, and nanomaterial synthesis. However, their exact solvent structure still remains a mystery. Here, we present the first chemical mapping of a SWIL solvent structure using in situ time-of-flight secondary ion mass spectrometry. In situ chemical mapping discovers two coexisting liquid phases and molecular structures vastly different from conventional ionic liquids. SWIL chemical speciation is found to be more complex than the known stoichiometry. Dimers and ionic clusters have been identified in SIMS spectra; and confirmed to be the chemical species differentiating from non-ionic liquids via spectral principal component analysis. Our unique in situ molecular imaging has advanced the understanding of SWIL chemistry and how this “heterogeneous” liquid structure may impact SWILs’ physical and thermodynamic properties and associated applications.

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

A combined SECM and electrochemical AFM approach to probe interfacial processes affecting molecular reactivity at redox flow battery electrodes

Redox flow batteries are attractive technologies for grid energy storage since they use solutions of redox-active molecules that enable a superior scalability and the decoupling of power and energy density. However, the reaction mechanisms of the redox active components at RFB electrodes are complex, and there is currently a pressing need to understand how interfacial processes impact the kinetics and operational reversibility of RFB systems. Here, we developed a combined electrochemical imaging methodology rooted in scanning electrochemical microscopy (SECM) and atomic force microscopy (AFM) for exploring the impact of electrode structure and conditioning on the electron transfer properties of model redox-active dialkoxybenzene derivatives, 2,5-di-tert-butyl-1,4-bis(2-methoxyethoxy)benzene (C1) and 2,3-dimethyl-1,4-dialkoxybenzene (C7). Using AFM and secondary-ion mass spectrometry (SIMS), we observed the formation of interfacial films with distinct mechanical properties compared to those of cleaved graphitic surfaces, and exclusively during reduction of electrogenerated radical cations. These films had an impact on the median rate and distribution of the electron transfer rate constant at the basal plane of multilayer and single layer graphene electrodes, displaying kinetically-limited values that did not yield the activation expected per the Butler–Volmer model with a transfer coefficient ~0.5. These changes were dependent on redoxmer structure: furthermore, SECM showed strong attenuation of C7 kinetics by a surface layer on MLG and SLG, while C1 kinetics were only affected by SLG. SECM and AFM results together show that these limiting films operate exclusively on the basal plane of graphite, with the edge plane showing a relative insensitivity to cycling and operation potential. Ultimately, this integrated electrochemical imaging methodology creates new opportunities to understand the unique role of interfacial processes on the heterogeneous reactivity of redoxmers at electrodes for RFBs, with a future role in elucidating phenomena at high active concentrations and spatiotemporal variations in electrode dynamics.

25 ENERGY STORAGE↗
DOE OSTI2022

Different interfacial reactivity of lithium metal chloride electrolytes with high voltage cathodes determines solid-state battery performance

A deep understanding of the interaction of the surface of cathode materials with solid electrolytes is crucial to design advanced solid-state batteries (SSBs). This is especially true for the new class of lithium metal chloride (Li-M-Cl) solid electrolytes which are receiving rapidly growing attention due to their very high oxidative stability (>4 V) in combination with good ionic conductivity that can enable long cell cycle life. While Li-M-Cl electrolytes typically contain resource-limited metals (M) such as indium or rare earths, work has focused on substituting M with more abundant elements such as zirconium. Via operando resistance measurements using intermittent current interruption we explore the dynamic evolution of the interphase at the surface of Ni-rich NCM85 or NCM111 cathode particles inside a working SSB with three different Li-(M 1 ,M 2 )-Cl catholytes (Li 3 InCl 6 , Li 2 Sc 1/3 In 1/3 Cl 4 and Li 5/2 Y 1/2 Zr 1/2 Cl 6 ) to reveal the impact of the cationic metal substitution on the interfacial chemistry. We show that the metal plays a critical role in determining high voltage stability, contrary to prior assumptions. Using a combination of cyclic voltammetry and ultraviolet photoelectron spectroscopy measurements of the electronic band structure to assess oxidative stability; coupled with DFT calculations and ToF-SIMS to evaluate products formed at the interface at different upper cutoff potentials and degrees of delithiation, we are able to differentiate between electrochemical and chemical degradation. We find that Li 2 Sc 1/3 In 1/3 Cl 4 yields the highest (and Li 3 InCl 6 the lowest) stability against electrochemical oxidation, while Li 5/2 Y 1/2 Zr 1/2 Cl 6 undergoes a detrimental chemical reaction with oxygen released from Ni-rich NCM85 at high potentials, resulting in fast capacity fading. Altogether, our work establishes a platform for the metrics and an approach that can be utilized to efficiently evaluate the stability of new halide SEs in SSB cells.

25 ENERGY STORAGE↗
DOE OSTI2025

Uranium particle age dating, aggregation, and model age best estimators

We present important aspects of uranium particle age dating by Large-Geometry Secondary Ion Mass Spectrometry (LG-SIMS) that can introduce bias and increase model age uncertainties, especially for small, young, and/or low-enriched particles. This metrology is important for applications related to International Nuclear Safeguards. We explore influential factors related to model age estimation, including the effects of evolving surface chemistry on inter-element measurements of particles (e.g., Th and U), detector background, and aggregation methods using simulated and actual particle samples. We introduce a new model age estimator, called “mid68”, that supplements 95% confidence intervals, providing a “best estimate” and uncertainty about the most likely age. The mid68 estimator can be calculated using the Feldman and Cousins method or Bayesian methods and provides a value with a symmetric uncertainty that can be used for calculations and approximate aggregation of processed model age values when the raw data and correction factors are not available. For particles yielding low 230 Th counts amidst nonzero detector background, their underlying model age probability distributions are asymmetric, so the mid68 estimator provides additional robust information regarding the underlying model age likelihood. This study provides a comprehensive and timely examination of critical aspects of uranium particle age dating as more laboratories establish particle chronometry capabilities.

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

Advanced spectroscopic studies of (PPh 4 ) 2 [Co(N 3 ) 4 ], a field-induced single-ion magnet

The high-spin Co II complex (PPh 4 ) 2 [Co(N 3 ) 4 ] (Co-N 3 )has been investigated using advanced spectroscopic techniques [far-IR magneto-spectroscopy (FIRMS), high-frequency and high-field EPR (HFEPR), and inelastic neutron scattering (INS)] to study its zero-field-splitting (ZFS), giving spin-Hamiltonian (SH) parameters. The analysis of multi-frequency HFEPR reveals the easy-axis anisotropy with a D value of −10.39(5) cm −1 and a rhombic ratio (E/D) of 0.21(1). The magnetic properties have also been probed by direct-current (DC) magnetometry, suggesting minor differences in anisotropy from the previously reported polymorph (Co-N 3 ′). Ligand-field theory (LFT) analysis indicates that the structures of Co-N 3 and Co-N 3 ′ are closer to D 2d symmetry than other symmetries considered. Alternate-current (AC) susceptibility reveals slow magnetic relaxation under an applied field, indicating that Co-N 3 is a field-induced single-ion magnet (SIM). Here, while both Co-N 3 and Co-N 3 ′ were studied by DC magnetometry, one unusual aspect of the current work on Co-N 3 is that advanced spectroscopies HFEPR, FIRMS, and INS were used to directly observe transitions between ZFS split states, giving accurate SH parameters.

Hand, Adam T. [Univ. of Tennessee, Knoxville, TN (↗
DOE OSTI2020

WEC fault modelling and condition monitoring: A graph-theoretic approach

The nature of wave resources usually requires wave energy converter (WEC) components to handle peak loads (i.e., torques, forces, and powers) that are many times greater than their average loads, accelerating equipment degradation. Moreover, due to their isolated nature and harsh operating environment, WEC systems are projected to possess high operations and maintenance (O&M) cost, i.e., around 27% of their leveled cost of energy. As such, developing techniques to mitigate these costs through the application of condition monitoring and fault tolerant control will significantly impact the economic feasibility of grid connected WEC power. Toward this goal, models of faulty components are developed in the open source modeling platform, WEC-Sim, to estimate the performance and measurable states of a WEC operating with likely device and sensor failures. Two types of faulty component models are then applied to a point absorber WEC model with basic controller damping and spring forces. Resulting changes in device behavior are recorded as a benchmark, and a graph-theoretic approach is proposed for fault detection and identification utilizing multivariate time series. Simulation results demonstrate that these faults can greatly affect the WEC performance, and that the proposed method can effectively detect and classify different types of faults.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Modular horizontal pendulum wave energy converter: Exploring feasibility to power ocean observation applications in the U.S. pacific northwest

Abstract Marine renewable energy as a power source for ocean observation applications has the potential to allow longer deployment operations due to the consistent, higher, and denser energy available from this resource. This additionally could encourage deployments in remote locations where maintenance is costly or resource availability is low if dependent on solar power. More importantly, gaps in spatial data could be filled. This paper examines the feasibility of a modular horizontal pendulum wave energy converter to power National Data Buoy Center's Self‐Contained Ocean Observations Payload (SCOOP) off the coast of Washington State, U.S. The effect on power output was studied when the pendulum's radius arm, mass, and power take‐off damping were varied. Results using Matlab toolbox WEC‐Sim revealed positive correlation between radius arm length and mass to power output, where power maximised for optimal damping values. Seasonal trends in power were not significant, where a 20 kg pendulum mass was needed to meet the SCOOP base power requirement of 5 W throughout the year.

16 TIDAL AND WAVE POWER↗