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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Experimental Results from the Thermal Energy Storage-2 (TES-2) Flight Experiment

Thermal Energy Storage-2 (TES-2) is a flight experiment that flew on the Space Shuttle Endeavour (STS-72), in January 1996. TES-2 originally flew with TES-1 as part of the OAST-2 Hitchhiker payload on the Space Shuttle Columbia (STS-62) in early 1994. The two experiments, TES-1 and TES-2 were identical except for the fluoride salts to be characterized. TES-1 provided data on lithium fluoride (LiF), TES-2 provided data on a fluoride eutectic (LiF/CaF2). Each experiment was a complex autonomous payload in a Get-Away-Special payload canister. TES-1 operated flawlessly for 22 hr. Results were reported in a paper entitled, Effect of Microgravity on Materials Undergoing Melting and Freezing-The TES Experiment, by David Namkoong et al. A software failure in TES-2 caused its shutdown after 4 sec of operation. TES-1 and 2 were the first experiments in a four experiment suite designed to provide data for understanding the long duration microgravity behavior of thermal energy storage salts that undergo repeated melting and freezing. Such data have never been obtained before and have direct application for the development of space-based solar dynamic (SD) power systems. These power systems will store energy in a thermal energy salt such as lithium fluoride or a eutectic of lithium fluoride/calcium difluoride. The stored energy is extracted during the shade portion of the orbit. This enables the solar dynamic power system to provide constant electrical power over the entire orbit. Analytical computer codes were developed for predicting performance of a space-based solar dynamic power system. Experimental verification of the analytical predictions were needed prior to using the analytical results for future space power design applications. The four TES flight experiments were to be used to obtain the needed experimental data. This paper will address the flight results from the first and second experiments, TES-1 and 2, in comparison to the predicted results from the Thermal Energy Storage Simulation (TESSIM) analytical computer code. An analysis of the TES-2 data was conducted by Cleveland State University Professor, Mounir Ibrahim. TESSIM validation was based on two types of results; temperature history of various points on the containment vessel and TES material distribution within the vessel upon return from flight. The TESSIM prediction showed close comparison with the flight data. Distribution of the TES material within the vessel was obtained by a tomography imaging process. The frozen TES material was concentrated toward the colder end of the canister. The TESSIM prediction indicated a similar pattern. With agreement between TESSIM and the flight data, a computerized representation was produced to show the movement and behavior of the void during the entire melting and freezing cycles.

Tolbert, Carol↗
NASA NTRS2004

Discharge Chamber Performance of the NEXIS Ion Thruster

The Nuclear-Electric Xenon Ion System (NEXIS) thruster was designed to produce greater than or equal to 70% efficiency at ISPs in excess of 6500 sec and total power levels in excess of 15 kW. In order to achieve this performance, the thruster requires a large area plasma generator capable of high propellant utilimtion efficiency and low discharge loss while producing a very flat, uniform beam profile. Fortunately, larger thrusters can be made more uniform and efficient due to the higher volume to surface ratio, provided that the magnetic cusp confinement is designed properly and the thruster length to diameter ratio is adequate. This paper describes the discharge chamber performance of the NEXIS Laboratory Model (LM) thruster. The LM discharge chamber is 65 cm in diameter at the grid plane and uses 6 ring-cusps to provide magnetic confinement of the plasma. The thruster was tested with flat carbon-carbon composite grids with the hole pattern masked to 57 cm in diameter and a conventional Type-B "1/2" diameter hollow cathode. During the preliminary "discharge only" tests, the LM thruster demonstrated profile factors of 0.84 and a discharge loss of about 160 eV/ion at 25 V discharge voltage and over 90% propellant utilization efficiency in simulated beam extraction experiments at 3.9 A of beam current. Analysis of the data from these tests used the discharge-only model developed by Brophy. Subsequent beam extraction experiments validated the key variables used in the model to predict the performance from the discharge-only data, and demonstrated 3.9 A of beam current at over 90% propellant utilization efficiency with a flatness parameter of better than 0.8 and a discharge loss of about 185 eV/ion. The slightly higher discharge loss measured during beam extractions was found to be due to a lower screen transparency in the as-manufactured LM grid set. Plasma measurements with a scanning probe internal to the thruster near the screen grid showed plasma densities over l x 10(exp 11) per cubic centimeter and electron temperatures of 3.5 to 5.5 eV depending on the operation parameters. The performance of the NEXIS discharge chamber contributed to the over 78% thruster efficiency measured during beam extraction at 7500 sec ISP and 25 kW of power, and over 81% thruster efficiency measured at 8500 sec ISP.

plasma generation↗
DOE OSTI2023

A forward modeling approach to analyzing galaxy clustering with S IM BIG

We present cosmological constraints from a simulation-based inference (SBI) analysis of galaxy clustering from the SimBIG forward modeling framework. SimBIG leverages the predictive power of high-fidelity simulations and provides an inference framework that can extract cosmological information on small nonlinear scales. In this work, we apply SimBIG to the Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxy sample and analyze the power spectrum, P ℓ (k), to k max = 0.5 h/Mpc. We construct 20,000 simulated galaxy samples using our forward model, which is based on 2,000 high-resolution Quijote N -body simulations and includes detailed survey realism for a more complete treatment of observational systematics. We then conduct SBI by training normalizing flows using the simulated samples and infer the posterior distribution of ΛCDM cosmological parameters: Ω m , Ω b , h, n s , σ 8 . We derive significant constraints on Ω m and σ 8 , which are consistent with previous works. Our constraint on σ 8 is 27% more precise than standard P ℓ analyses because we exploit additional cosmological information on nonlinear scales beyond the limit of current analytic models, k > 0.25 h/Mpc. This improvement is equivalent to the statistical gain expected from a standard P ℓ analysis of galaxy sample ~ 60% larger than CMASS. While we focus on P ℓ in this work for validation and comparison to the literature, SimBIG provides a framework for analyzing galaxy clustering using any summary statistic. We expect further improvements on cosmological constraints from subsequent SimBIG analyses of summary statistics beyond P ℓ .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Beware of fake ν ’s: The effect of massive neutrinos on the nonlinear evolution of cosmic structure

Massive neutrinos suppress the growth of cosmic structure on small, nonlinear scales. It is thus often proposed that using statistics beyond the power spectrum can tighten constraints on the neutrino mass by extracting additional information from these nonlinear scales. We study the information content regarding neutrino mass at the field level, quantifying how much of this information arises from the difference in nonlinear evolution between a cosmology with one fluid [cold dark matter (CDM)] and two fluids ( CDM + neutrinos ). We do so by running two N -body simulations, one with and one without massive neutrinos, both with the same phases, and matching their linear power spectrum at a given low redshift. This effectively isolates the information encoded in the linear initial conditions from the nonlinear cosmic evolution. We demonstrate that, for k ≲ 1 h / Mpc , and for a single redshift, there is negligible difference in the real-space CDM field between the two simulations. This suggests that all the information regarding neutrino mass is in the linear power spectrum set by the initial conditions. Thus, any probe based on the CDM field alone will have negligible constraining power beyond that which exists at the linear level over the same range of scales. Consequently, any probe based on the halo field will contain little information beyond the linear power. We find similar results for the matter field responsible for weak lensing. We also demonstrate that there may be much information beyond the power spectrum in the 3D matter field; however, this is not observable in modern surveys via dark matter halos or weak lensing. Finally, we show that there is additional information to be found in redshift space.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

Average power effects in parametric oscillators and amplifiers

Average power effects relative to the operation of parametric oscillators and amplifiers have been calculated. Temperature gradients have been calculated for both radial and longitudinal heat extraction. In many instances, the thermal load on a parametric oscillator is higher than the thermal load on a parametric amplifier with the same pump power. Having one or both these wavelengths resonant increases the chances that a generated photon will be absorbed by the nonlinear crystal. Temperature profiles and thermal diffusion time constants have been calculated for Gaussian beams, given the heat-deposition rate. With radical heat extraction the temperature profile can be expressed in a power series or approximated by a Gaussian distribution function.

Barnes, Norman P.↗
DOE OSTI2020

U.S. Effort Support to Examinations at Fukushima - Meeting Notes with Updated Information Requests (FY2020)

Much is still not known about the end-state of core materials in each unit that was operating on March 11, 2011 at the Fukushima Daiichi Nuclear Power Station (Daiichi). Information obtained from Daiichi is required to inform Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This document, which has been updated to include Fiscal Year 2020 (FY2020) information, summarizes results from a U.S. effort to review Daiichi information and extract insights to enhance the safety of existing and future nuclear power plant designs. This U.S. effort, which was initiated in 2014 by the Department of Energy Office of Nuclear Energy (DOE-NE), is completed by a group of experts in reactor safety and plant operations that identify examination needs and evaluate recent Daiichi examination data to address these needs. Since its inception, comprehensive annual reports were issued that document significant safety insights being obtained in areas of special emphasis: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties related to severe accident modeling progression, these insights have and continue to be used to update guidance for severe accident prevention, mitigation, and emergency planning. Reduced uncertainties in modeling the events at Daiichi improve the realism of reactor safety evaluations that inform future D&D activities. For FY2020, it was decided that the program would gain more benefit from a more concise report that emphasizes new information and insights that affect prior findings and recommendations from the U.S. experts participating in this effort. A key aspect of prior U.S. efforts, the updated list of information requests, is included in this letter report to ensure that they are transmitted to organizations within Japan. In addition, findings and associated recommendations are provided regarding information presented by TEPCO Holdings, Nuclear Damage Compensation and Decommissioning Facilitation Corporation (NDF), and the Japan Atomic Energy Agency (JAEA). This letter report also continues to emphasize how information obtained from the affected reactors at Daiichi has been and will continue to be used to update severe accident management strategies, improve maintenance activities (especially in areas of radiation protection) and reduce uncertainties in systems analysis code models. In addition, recommendations are included that would expand the use of this information to provide insights regarding maintenance, radiation protection, design, and siting activities of existing and new reactors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Cyclable Variable Path Length Multilevel Structures for Lossless Ion Manipulations (SLIM) Platform for Enhanced Ion Mobility Separations

Ion mobility-mass spectrometry (IMS-MS) is increasingly used to analyze complex samples and provide structural information of unknown compounds. As the complexity of samples increases, there is a need to improve the resolution of IMS-MS instruments to increase the rate of molecular identification. In this work, we evaluated a cyclable and variable-pathlength multilevel Structures for Lossless Ion Manipulations (SLIM) platform to achieve a higher resolving power than previously possible. This new multilevel SLIM platform has eight separation levels connected by ion escalators and a path length of ~88 meters (~11 meters per level). Our new multilevel SLIM can also be operated in an ‘ion cycling’ mode where a set of return ion escalators transport ions from the eighth back to the first level, allowing even longer path lengths (and higher IMS resolution). The platform has been improved to enhance the ion transmission and IMS separation quality by reducing the spacing between SLIM boards as well as board thickness, reducing the ions’ escalator residence time. Compared to the previous generation, the new multilevel SLIM demonstrated a better transmission for a set of phosphazene ions, especially for the low-mobility ions. The new multilevel SLIM achieved better resolving powers than our previous 4-level SLIM. The collision cross-section-based resolving power of the SLIM platform was tested using a pair of singly-charged reverse sequence peptides (SDGRG 1+ , GRGDS 1+ ). We achieved 1100 resolving power using 88 meters of path length (i.e., 8 levels) and 1400 following an additional pass through the eight levels (i.e., 16 levels or 173.5 m). The multilevel SLIM was further evaluated to demonstrate the enhanced separation for a positively and negatively charged brain total lipid extract sample. Finally, the new multilevel SLIM enables much higher resolving powers for a wide range of ion mobilities, improved transmission for low-mobility ions, and the ability to perform even higher resolving power for ions of interest.

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

Feasibility of using crystal channeling for the beam loss mitigation in Slow Extraction at 8GeV

The mitigation of the beam losses in slow extraction is becoming more and more demanding in accelerator applications for HEP as the beam power is gradually increasing. The successful demonstration of using the proton beam channeling at 450GeV to deflect the beam away from the extraction septa opens the new levels of improving the slow extraction efficiency. It is yet to be demonstrated that this method is still effective at low and medium proton beam energies. Here we present the promising results of the recent computer simulation studies of the septum shadowing at 8GeV for the Mu2e project slow extraction at Fermilab. Depending on the beam parameters the beam loss reduction is shown to be achievable in the range of 1/3 to factor of 3.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Naphthalene‐Diimide‐Based Ionenes as Universal Interlayers for Efficient Organic Solar Cells

Abstract Self‐doping ionene polymers were efficiently synthesized by reacting functional naphthalene diimide (NDI) with 1,3‐dibromopropane ( NDI‐NI ) or trans ‐1,4‐dibromo‐2‐butene ( NDI‐CI ) via quaternization polymerization. These NDI‐based ionene polymers are universal interlayers with random molecular orientation, boosting the efficiencies of fullerene‐based, non‐fullerene‐based, and ternary organic solar cells (OSCs) over a wide range of interlayer thicknesses, with a maximum efficiency of 16.9 %. NDI‐NI showed a higher interfacial dipole (Δ), conductivity, and electron mobility than NDI‐CI , affording solar cells with higher efficiencies. These polymers proved to efficiently lower the work function ( WF ) of air‐stable metals and optimize the contact between metal electrode and organic semiconductor, highlighting their power to overcome energy barriers of electron injection and extraction processes for efficient organic electronics.

Liu, Ming↗
DOE OSTI2020

Naphthalene‐Diimide‐Based Ionenes as Universal Interlayers for Efficient Organic Solar Cells

Abstract Self‐doping ionene polymers were efficiently synthesized by reacting functional naphthalene diimide (NDI) with 1,3‐dibromopropane ( NDI‐NI ) or trans ‐1,4‐dibromo‐2‐butene ( NDI‐CI ) via quaternization polymerization. These NDI‐based ionene polymers are universal interlayers with random molecular orientation, boosting the efficiencies of fullerene‐based, non‐fullerene‐based, and ternary organic solar cells (OSCs) over a wide range of interlayer thicknesses, with a maximum efficiency of 16.9 %. NDI‐NI showed a higher interfacial dipole (Δ), conductivity, and electron mobility than NDI‐CI , affording solar cells with higher efficiencies. These polymers proved to efficiently lower the work function ( WF ) of air‐stable metals and optimize the contact between metal electrode and organic semiconductor, highlighting their power to overcome energy barriers of electron injection and extraction processes for efficient organic electronics.

Liu, Ming↗
DOE OSTI2022

Decoding the Mechanisms of Phase Transitions from In Situ Microscopy Observations

Abstract Analysis of the temperature‐ and stimulus‐dependent imaging data toward elucidation of the physical transformations is an ubiquitous problem in multiple fields. Here, temperature‐induced phase transition in BaTiO 3 is explored using the machine learning analysis of domain morphologies visualized via variable‐temperature scanning transmission electron microscopy (STEM) imaging data. This approach is based on the multivariate statistical analysis of the time or temperature dependence of the statistical descriptors of the system, derived in turn from the categorical classification of observed domain structures or projection on the continuous parameter space of the feature extraction‐dimensionality reduction transform. The proposed workflow offers a powerful tool for the exploration of the dynamic data based on the statistics of image representation as a function of the external control variable to visualize the transformation pathways during phase transitions and chemical reactions. This can include the mesoscopic STEM data as demonstrated here, but also optical, chemical imaging, etc., data. It can further be extended to the higher dimensional spaces, for example, analysis of the combinatorial libraries of materials compositions.

Valleti, Sai Mani Prudhvi↗
DOE OSTI2023

A Si-Substituted Spirobifluorene Hole-Transporting Material for Perovskite Solar Cells

Hybrid organic-inorganic perovskite solar cells (PSCs) have shown promise for next-generation photovoltaics. Here, this study presents a simple approach for enhancing the performance and stability of PSCs by substituting the center carbon atom of the common hole transport material (HTM) Spiro-MeOTAD with a silicon atom. This modification, termed Si-Spiro, results in an increased hole mobility. A density functional theory simulation indicates that the enhanced hole mobility is due to the structural change of Si-Spiro. Electron beam-induced current microscopy measurements indicate improved charged extraction at the Si-Spiro/perovskite interface. A power conversion efficiency of 22.5% is achieved in Si-Spiro-based PSCs, outperforming standard Spiro-MeOTAD. Additionally, Si-Spiro-based PSCs demonstrate enhanced stability, maintaining over 90% of performance over 120 h of one-sun operation. Depth-profiling X-ray photoelectron spectroscopy revealed that Si-Spiro effectively blocks metal ion migration, which contributes to its enhanced stability. The findings suggest that Si-Spiro could be promising a HTM for high-performing, stable PSCs.

14 SOLAR ENERGY↗
DOE OSTI2021

Selective sulfidation of metal compounds

There is urgent, unprecedented demand for critical by-product and co-product metallic elements for the infrastructure (magnets, batteries, catalysts and electronics) needed to power society with renewable electricity1,2,3. However, the extraction of d-block and f-block metals from mineral and recycled streams is thermodynamically difficult, typically requiring complete dissolution of the materials, followed by liquid–liquid separation using metal-ion complexing or chelating behaviour4,5. The similar electronic structure of these metals results in poor separation factors, necessitating immense energy, water and chemicals consumption6,7,8. Here a metal-processing approach based on selective anion exchange is proposed. Several simple process levers (gas partial pressure, gas flowrate and carbon addition) are demonstrated to selectively sulfidize a target metal from a mixed metal-oxide feed. The physical and chemical differences between the sulfide and oxide compounds (for example, density, magnetic susceptibility and surface chemistry) can then be exploited for vastly improved separation compared with liquid–liquid methods9. The process conditions of sulfidation are provided for 56 elements and demonstrated for 15 of them. An assessment of the environmental and economic impacts suggests a path towards 60–90% reductions in greenhouse gas emissions while offering substantial capital cost savings compared with liquid–liquid hydrometallurgy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modelling nearest neighbour distributions of biased tracers using hybrid effective field theory

ABSTRACT We investigate the application of hybrid effective field theory (HEFT) – which combines a Lagrangian bias expansion with subsequent particle dynamics from N-body simulations – to the modelling of k-nearest neighbour cumulative distribution functions (kNN-CDFs) of biased tracers of the cosmological matter field. The kNN-CDFs are sensitive to all higher order connected N-point functions in the data, but are computationally cheap to compute. We develop the formalism to predict the kNN-CDFs of discrete tracers of a continuous field from the statistics of the continuous field itself. Using this formalism, we demonstrate how kNN-CDF statistics of a set of biased tracers, such as haloes or galaxies, of the cosmological matter field can be modelled given a set of low-redshift HEFT component fields and bias parameter values. These are the same ingredients needed to predict the two-point clustering. For a specific sample of haloes, we show that both the two-point clustering and the kNN-CDFs can be well-fit on quasi-linear scales (≳ 20h−1Mpc) by the second-order HEFT formalism with the same values of the bias parameters, implying that joint modelling of the two is possible. Finally, using a Fisher matrix analysis, we show that including kNN-CDF measurements over the range of allowed scales in the HEFT framework can improve the constraints on σ8 by roughly a factor of 3, compared to the case where only two-point measurements are considered. Combining the statistical power of kNN measurements with the modelling power of HEFT, therefore, represents an exciting prospect for extracting greater information from small-scale cosmological clustering.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Pulsed studies of intervalley transfer in Al 0.35 In 0.65 As: A paradigm for valley photovoltaics

Al 0.35 In 0.65 As is a direct semiconductor whose multivalley conduction-band structure has been proposed for use in so-called valley photovoltaics. In such hot-carrier solar cells, energetic (hot) photocarriers are stored in satellite valleys away from the Γ point, allowing them to be extracted prior to thermalization and to thereby increase power-conversion efficiency. While prior theoretical work has highlighted the potential of Al 0.35 In 0.65 As—a widely used barrier material in electronic and optoelectronic devices, for use in valley photovoltaics—surprisingly little is known about its electrical properties, especially how these are impacted by the application of high fields. In this work, we therefore undertake a detailed characterization of the electrical properties of Te-doped ($\textit{n}$-type) Al 0.35 In 0.65 As, over wide ranges of temperature (3–400 K) and electric field (<50 kV/cm). Using pulsed measurements to suppress the influence of Joule heating, we reveal the presence of clear negative-differential conductance in the current-voltage characteristics of the films, suggestive of the intervalley transfer of hot electrons. This conclusion is supported by the results of ensemble Monte Carlo simulations of the hot-carrier action, which confirm the connection of the observed negative-differential conductance to hot-electron transfer from the conduction-band (Γ) minimum, to the side valleys at the $\textit{L}$ point. Further, the quantitative features of the experimentally determined velocity-field curves are found to be in good agreement with the results of these calculations, providing further confidence in the role of the implied intervalley transfer mechanism. Overall, these results confirm the excellent potential of Al 0.35 In 0.65 As for use as the absorber material in hot-carrier solar cell technology.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the noise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.

Johnson, Hans↗
DOE OSTI2023

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the n oise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗