SEARCH · Search NASA

Results for “Li extraction”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Remote surface optical phonon scattering in ferroelectric Ba 0.6 Sr 0.4 TiO 3 gated graphene

We report the effect of remote surface optical (RSO) phonon scattering on carrier mobility in monolayer graphene gated by ferroelectric oxide. We fabricate monolayer graphene transistors back-gated by epitaxial (001) Ba 0.6 Sr 0.4 TiO 3 films, with field effect mobility up to 23 000 cm 2 V –1 s –1 achieved. Switching ferroelectric polarization induces nonvolatile modulation of resistance and quantum Hall effect in graphene at low temperatures. Ellipsometry spectroscopy studies reveal four pairs of optical phonon modes in Ba 0.6 Sr 0.4 TiO 3 , from which we extract RSO phonon frequencies. The temperature dependence of resistivity in graphene can be well accounted for by considering the scattering from the intrinsic longitudinal acoustic phonon and the RSO phonon, with the latter dominated by the mode at 35.8 meV. Furthermore, our study reveals the room temperature mobility limit of ferroelectric-gated graphene transistors imposed by RSO phonon scattering.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Two- and three-particle nonflow contributions to the chiral magnetic effect measurement by spectator and participant planes in relativistic heavy ion collisions

Correlation measurements with respect to the spectator and participant planes in relativistic heavy ion collisions were proposed to extract the chiral magnetic effect (CME) from background dominated azimuthal correlators. Here, this paper investigates the effects of two- and three-particle nonflow correlations on the extracted CME signal fraction, f CME . It is found, guided by a multiphase transport (ampt) model and the heavy ion jet interaction generator (hijing) together with experimental data, that the nonflow effects amount to approximately (4 ± 5)% and (–5 ± 3)% without and with pseudorapidity gaps, respectively, in 20–50% centrality Au + Au collisions at √ s NN = 200 GeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Design and demonstration of a direct air capture system with moisture-driven CO 2 delivery into aqueous medium

Two direct air capture (DAC) systems were designed and demonstrated to passively capture CO 2 from ambient air and use moisture to release the CO2 into an alkaline medium. A bench-scale system delivering ∼1 g CO 2 d –1 was demonstrated in a laminar flow hood, and a small pilot-scale system that could deliver ∼100 g CO 2 d –1 was operated outdoors in a 4.2 m 2 raceway pond. Novel elongated mesh-tube packets containing anion-exchange resin (AER) beads were found to reduce drying and CO 2 loading time 4.3-fold compared to larger mesh bags. Technoeconomic analysis (TEA) estimates the cost of capturing CO 2 into an alkaline solution, suitable for cultivating photosynthetic microorganisms, to be $\$229$ per tonne for a practical scenario based on current results and $\$72$ per tonne for an aspirational scenario considering improvements to sorbent capacity, hydrophobicity, and sorbent lifetime. TEA further estimates an additional $\$110$ per tonne to extract CO 2 from solution, purify it, and compress it to 15 MPa, suitable for sequestration. Furthermore, moisture-driven processes have the potential to use up to 87% less energy than thermal and/or vacuum swing DAC by using energy from water evaporation.

09 BIOMASS FUELS↗

NASA NTRS2020

Monitoring VIIRS Thermal Emissive Bands Long-Term Performance Using Lunar Observations

Two Visible Infrared Imaging Radiometer Suite (VIIRS) instruments are currently operating in space, one onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite launched on October 28, 2011 and the other onboard the NOAA-20 satellite launched on November 18, 2017. The performance of the seven VIIRS thermal emissive bands (TEBs) is monitored via on-orbit calibration data, the analysis of Earth view observations, as well as inter-comparisons with other sensors. The Moon has been used as a unique invariant target for on-orbit sensor calibration because its surface property is considered extremely stable over time in spectra, radiometry, and geometry with a repeatable lunar phase. This paper presents the assessments of the S-NPP and NOAA-20 VIIRS TEB on-orbit calibration stability using near-monthly scheduled lunar observations over their respective missions. The methodology previously developed for MODIS is now applied to VIIRS to monitor the TEB long-term stability by extracting and trending the lunar brightness temperatures from selected unsaturated pixels. It includes a correction applied to reduce any impact from the Sun–Moon geometry (e.g. Sun-Moon distance variation). The results show that the mission-long brightness temperature trends from the lunar surface are stable for all VIIRS TEBs, despite noticeable seasonal variations in the lunar thermal emissive radiance.

VIIRS↗

DOE OSTI2020

Superfluid condensate fraction and pairing wave function of the unitary Fermi gas

The unitary Fermi gas is a many-body system of two-component fermions with zero-range interactions tuned to infinite scattering length. Despite much activity and interest in unitary Fermi gas and its universal properties, there have been great difficulties in performing accurate calculations of the superfluid condensate fraction and pairing wave function. In this paper, we present auxiliary-field lattice Monte Carlo simulations using a lattice interaction which accelerates the approach to the continuum limit, thereby allowing for robust calculations of these difficult observables. As a benchmark test, we compute the ground-state energy of 33 spin-up and 33 spin-down particles. As a fraction of the free Fermi gas energy $E_{\text{FG}}$, we find $E_0/E_{\text{FG}}$ = 0.369(2), 0.372(2), using two different definitions of the finite-system energy ratio, in agreement with the latest theoretical and experimental results. We then determine the condensate fraction by measuring off-diagonal long-range order in the two-body density matrix. We find that the fraction of condensed pairs is α = 0.43(2). Further, we also extract the pairing wave function and find the pair correlation length to be $ζ_pk_F$ = 1.8(3)ℏ, where $k_F$ is the Fermi momentum. Provided that the simulations can be performed without severe sign oscillations, the methods we present here can be applied to superfluid neutron matter as well as more exotic $\textit{P}$-wave and $\textit{D}$-wave superfluids.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1994

The validation by measurement theory of proposed object-oriented software metrics

Moving software development into the engineering arena requires controllability, and to control a process, it must be measurable. Measuring the process does no good if the product is not also measured, i.e., being the best at producing an inferior product does not define a quality process. Also, not every number extracted from software development is a valid measurement. A valid measurement only results when we are able to verify that the number is representative of the attribute that we wish to measure. Many proposed software metrics are used by practitioners without these metrics ever having been validated, leading to costly but often useless calculations. Several researchers have bemoaned the lack of scientific precision in much of the published software measurement work and have called for validation of software metrics by measurement theory. This dissertation applies measurement theory to validate fifty proposed object-oriented software metrics (Li and Henry, 1993; Chidamber and Kemerrer, 1994; Lorenz and Kidd, 1994).

Neal, Ralph D.↗

DOE OSTI2024

On a High-Mirror Stellarator Reactor Exploratory Concept With Neutrons Concentrated on Centrifuge Liquids

In the framework of fusion energy research based on magnetic confinement, stellarators allow numerous degrees of freedom for the design of the magnetic trap and plasma shape. Taking advantage of these features, some plasma shapes might benefit several of the many integrated elements involved in commercial fusion reactors, like, e.g., decreasing the number, mass and complexity of replaced activated in-vessel components (IVC) (i.e., by using liquids), extraction of large power, tritium generation, and remote maintenance. Certainly, free-surface liquid materials were proposed for tokamaks and field-reversed configuration (FRC) to try to improve some of such elements, i.e., in advanced power extraction (APEX) studies. Some reactor-relevant quasi-isodynamic (QI) magnetic configurations exhibit a relatively straight sector of plasma and high magnetic mirror. The combination of those elements and possibilities in a single stellarator reactor concept might have some advantages, in spite of the uncertainties due to the current low technological readiness level (TRL). The proposed and studied reactor concept is based on a vacuum vessel having short curved sectors and longer wide cylindrical sectors, which encloses a high-mirror low-vertical-excursion magnetic configuration, and swirling liquids or rotating cylinders, which centrifuge molten Li salts located at the low field region. Thus, the molten salts (if possible covered by a thin layer of liquid lithium) would be located on the internal perimeter of the cylinder, to act as particle exhaust (except for helium), neutron power extractor, and tritium breeder. The high-mirror feature tries to concentrate the neutron power at the cylindrical sectors, which might avoid using breeding materials at the curved sectors. The different elements of the concept are exploratorily studied and defined, and the difficulties assessed.

centrifuge↗

DOE OSTI2021

PARIS: Predicting application resilience using machine learning

The traditional method to study application resilience to errors in HPC applications uses fault injection (FI), a time-consuming approach. Furthermore, while analytical models have been built to overcome the inefficiencies of FI, they lack accuracy. In this paper, we present PARIS, a machine-learning method to predict application resilience that avoids the time-consuming process of random FI and provides higher prediction accuracy than analytical models. PARIS captures the implicit relationship between application characteristics and application resilience, which is difficult to capture using most analytical models. We overcome many technical challenges for feature construction, extraction, and selection to use machine learning in our prediction approach. Our evaluation on 16 HPC benchmarks shows that PARIS achieves high prediction accuracy. PARIS is up to 450x faster than random FI (49x on average). Compared to the state-of-the-art analytical model, PARIS is at least 63% better in terms of accuracy and has comparable execution time on average.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

(CrMnCoNiZn) 3 O 4 @PPy core-shell nanocomposite with excellent electrochemical performance as lithium-ion battery anode

High entropy oxides (HEOs) have an excellent potential for use as electrode materials in lithium-ion batteries (LIBs) due to their high theoretical specific capacity. In this work, spinel-structured (CrMnCoNiZn) 3 O 4 HEO nanoparticles with five elements in equal molar ratio is first generated by solution combustion method. (CrMnCoNiZn) 3 O 4 @polypyrrole (PPy) nanocomposites are prepared by in-situ polymerization method. As an anode for lithium-ion batteries, the electrochemical performance of the (CrMnCoNiZn) 3 O 4 @PPy composite outperforms that of (CrMnCoNiZn) 3 O 4 nanoparticles. The capacity is 802 mAh/g after 100 cycles at a current density of 100 mA/g, 416 mAh/g after 1000 cycles at a high current density of 1 A/g, and 360 mAh/g rate capacity at 2 A/g. The excellent electrochemical performance of the composites is mainly due to the fact that the conductive and flexible PPy is encapsulated on the high-entropy oxides, which can alleviate the volume change triggered by extraction-insertion of lithium ions process, as well as enhance the electrical conductivity and reduce the occurrence of some side reactions. Finally, this method of compositing materials can also be used in other HEOs and conductive polymers, providing a new idea to enhance the electrochemical properties of HEOs.

25 ENERGY STORAGE↗

DOE OSTI2026

Connecting ground-state properties of 6 Li to each other and to scattering data

We examine the relationship between the asymptotic normalization coefficient (ANC) of 6 Li and other low-energy observables in the α–deuteron system. Our analysis uses a set of calculations carried out within the ab initio no core shell model with continuum (NCSMC) using a variety of inter-nucleon interactions and basis sizes, and yielding 6 Li deuteron separation energies between 1.3 and 1.8 MeV (Hebborn et al 2022 Phys. Rev. Lett. 129 042503). These NCSMC calculations show that the square of the ANC is strongly correlated with the separation energy over this range. In this work, we investigate the origin of this correlation using the phenomenological R-matrix, a single-channel potential and a perturbative approach. We show that this correlation occurs because the depth of the α–deuteron central potential changes by only a small relative amount as the separation energy varies. We then investigate if the ANC can be accurately extracted from α–deuteron phase shifts in an ideal case in which low-energy data are available and there are no experimental errors. We find that both R-matrix and Coulomb-modified effective-range theory (CM-ERE) yield extracted ANCs close to, although not exactly equal to, the NCSMC value, provided the extrapolation is constrained by the known position of the bound-state pole and at least three terms are included in the fit function. The R-matrix approach converges faster than the CM-ERE as the number of parameters increases and is also more robust against the inclusion of low-energy and high-energy phase shift data. Finally, our study also shows that a naive quantification of uncertainties by comparing different truncations used in both theories is not accurate, and suggests the accuracy of ANCs extracted from phase shift data needs further investigation.

R-matrix↗

DOE OSTI2024

Dissecting a strongly coupled scalar nucleon

We continue our investigation of the stress within a strongly coupled scalar nucleon, and now dissect the gravitational form factors into contributions from its constituents, the (mock) nucleon and the (mock) pion. The computation is based on a nonperturbative solution of the scalar Yukawa model in the light-front Hamiltonian formalism with a Fock sector expansion, including up to one nucleon and two pions. By employing the “good currents” T i + + , T i + − and T i 12 , we extract the full set of gravitational form factors A i , D i , c ¯ i without the contamination of the spurious form factors and free of uncanceled UV divergences. With these results, we decompose the mass of the system into its constituents and compute the matter and mechanical radii, gaining insights into the strongly coupled system. Published by the American Physical Society 2024

Cao, Xianghui (ORCID:0009000359096713)↗

DOE OSTI2022

Graph Embeddings for CEBAF Operations: Progress and Future Plans

We describe research towards leveraging deep learning on graph representations of the injector beamline at the Continuous Electron Beam Accelerator Facility (CEBAF) in order to create a tool for improving the efficiency of beam tuning tasks. Specifically, we use graphs to represent the injector beamline at any arbitrary date and time and invoke a graph neural network to extract a low-dimensional, informative representation that can be visualized in two-dimensions. By analyzing years of operational data from the CEBAF archiver, good and bad regions of parameter space can be identified. The goal is to exercise this framework as a real-time tool to aid beam tuning, which represents the dominant source of machine downtime.

Tennant, C.↗

DOE OSTI2024

Graph Analytics for CEBAF Operations

We report on the progress achieved during a 2-year Laboratory Directed Research and Development (LDRD) project titled “Graph Analytics for CEBAF Operations”. The objective of this project is to leverage deep learning on graph representations of CEBAF’s injector beamline in order to create a tool for improving the efficiency of beam tuning tasks. Specifically, we use graphs to represent the injector beamline at any arbitrary date and time and invoke a graph neural network (GNN) to extract a low-dimensional, informative representation that can be visualized in two-dimensions. By analyzing years of operational data from the CEBAF archiver, good and bad regions of parameter space can be identified. The goal is to exercise this framework as a real-time tool to aid beam tuning, which represents the dominant source of machine downtime.

43 PARTICLE ACCELERATORS↗

NASA NTRS1995

Extraction of ozone and chlorophyll-A distribution from AVIRIS data

The potential of airborne imaging spectrometry for assessing and monitoring natural resources is studied. Therefore, an AVIRIS scene of the NASA's MacEurope 1991 campaign - acquired in Central Switzerland - is used. The test site consists of an urban area, the Lake Zug with its surrounding fields, the Rigi mountain in the center of the test site, and the Lake of Four Cantons. The region is covered by the AVIRIS flight #910705, run 6 and 7 of the NASA ER-2 aircraft resulting in an average nominal pixel size of about 18 m. Simultaneous to the ER-2 overflight spectroradiometric measurements have been taken in various locations. Preselected reference targets were measured in the field with a GER Mark V spectroradiometer, and radiance measurements were taken to the lake using a Li-Cor LI 1800UW specroradiometer below and above the water surface. A comprehensive meteorological data set was obtained by joining the POLLUMET experiment which carried out measurements to investigate the summer smog in Switzerland on the same day. The quality assessment for the actual data set can be found in detail in Meyer et al. A parametric approach calculating the location of the airplane was used to simulate the observation geometry. This parametric preprocessing procedure, which takes care of effects of flight line and attitude variations as well as the pixel-by-pixel topographic corrections is described in Meyer.

Schaepman, M.↗

DOE OSTI2020

Fractal breakage of porous carbonate sand particles: Microstructures and mechanisms

In situ, three-dimensional (3D) characterizations of particle breakage in porous carbonate sands are presented, for the first time, with synchrotron-based micro computed tomography. Evolution of grain-scale characteristics are identified and quantified via elaborate image processing and topology analyses. The sequential 3D images reveal distinctly different fracture mechanisms for carbonate sands from silica sands. The angular shape of carbonate sand particles facilitates bending fracture, and particles with a lower sphericity and a higher porosity are more prone to break. 3D crack networks extracted from fractured particles imply considerable cleavage along initial pores. The fractal dimension of crack networks increases with external loading due to crack branching via cleavage. The resultant fragment size distribution also appears fractal and the fractal feature is valid down to the breakage limit of calcium carbonate. Crack propagation along the initial pores reduces the energy barrier for particle breakage and thus fracture strength of particles

Carbonate sands↗

DOE OSTI2020

Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data

The dynamics of protein self-assembly on the inorganic surface and the resultant geometric patterns are visualized using high-speed atomic force microscopy. The time dynamics of the classical macroscopic descriptors such as 2D fast Fourier transforms, correlation, and pair distribution functions are explored using the unsupervised linear unmixing, demonstrating the presence of static ordered and dynamic disordered phases and establishing their time dynamics. Here, the deep learning (DL)-based workflow is developed to analyze detailed particle dynamics and explore the evolution of local geometries. Finally, we use a combination of DL feature extraction and mixture modeling to define particle neighborhoods free of physics constraints, allowing for a separation of possible classes of particle behavior and identification of the associated transitions. Overall, this work establishes the workflow for the analysis of the self-organization processes in complex systems from observational data and provides insight into the fundamental mechanisms.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Long interior carrier lifetime in selective-area InAs nanowires on silicon

Catalyst-free, position-controlled indium arsenide (InAs) nanowires (NWs) of variable diameters were grown on Si (111) by selective-area epitaxy (SAE). Ultrafast pump-probe spectroscopy was conducted, from which carrier recombination mechanisms on the NW surface and interior were resolved and characterized. NWs grown using SAE demonstrated high optical quality, showing minority carrier lifetimes more than two-fold longer than that of the randomly-positioned (RP) NWs. The extracted SAE-InAs NW interior recombination lifetime was found to be as long as 7.2 ns , 13X longer than previous measurements on RP-NWs; and the surface recombination velocity 4154 cm · s - 1 . Transmission electron microscopy revealed a high density of stacking defects within the NWs, suggesting that interior recombination lifetime can be further increased by improving NW interior crystalline quality.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Parameter extraction approaches for compact modeling of thermoelectric modules

Thermoelectric (TE) cooling has experienced rapid advancements with the foundational understanding of TE materials. TE modules, compact and lightweight devices, have become the prevalent approach for implementing TE technologies. Accurately quantifying TE physical parameters (Seebeck coefficient α, thermal conductivity κ, and thermal resistance ρ) is challenging due to the dynamic temperature changes in operation. Furthermore, extracting lumped property parameters is crucial for designing energy systems using TE modules. Existing research has several limitations, such as lack of comparative analysis between prevalent formulae, reliance on potentially inaccurate vendor-supplied data, disregard for fundamental assumptions, and absence of empirical measurements. Further, this study addresses these gaps by conducting TE material characterization, comparing three existing formulae using vendor datasheets, designing a laboratory test facility for model validation and refinement, and outlining a structured data extraction procedure. The study's novelty lies in multiple key contributions: (1) a detailed comparative analysis of existing formulae for extracting TE property parameter; (2) executing experimental work in a laboratory setting to validate the model and elucidate its limitations; (3) highlighting potential risks; (4) clarifying possible assumptions from both material and engineering perspectives; and (5) considering temperature differential impacts. This comprehensive approach addresses the current research gaps and provides valuable insights into the design and application of TE modules in various energy systems.

36 MATERIALS SCIENCE↗