Search NASA⌕ Search

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.

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

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Partial muon capture rates in A = 3 and A = 6 nuclei with chiral effective field theory

Searches for neutrinoless-double beta decay rates are crucial in addressing questions within fundamental symmetries and neutrino physics. The rates of these decays depend not only on unknown parameters associated with neutrinos, but also on nuclear properties. In order to reliably extract information about the neutrino, one needs an accurate treatment of the complex many-body dynamics of the nucleus. Neutrinoless-double beta decays take place at momentum transfers on the order of 100 MeV/$c$ and require both nuclear electroweak vector and axial current matrix elements. Muon capture, a process in the same momentum transfer regime, has readily available experimental data to validate these currents. In this work, we present results of {\it ab initio} calculations of partial muon capture rates for $^3$He and $^6$Li nuclei using variational and Green's Function Monte Carlo computational methods. We estimate the impact of the three-nucleon interactions, the cutoffs used to regularize two-nucleon ($2N$) interactions, and the energy range of $2N$ scattering data used to fit these interactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Devices and methods for hydrogen generation via ammonia decomposition

Systems and methods for hydrogen generation via ammonia decomposition that utilize a fixed bed reactor configured to receive inflows of NH 3 and oxidant and to produce an outflow of high purity H 2 . The fixed bed reactor contains a fixed bed of a NH 3 decomposition catalyst wherewith the NH 3 decomposes to form N 2 and H 2 ; a plurality of ceramic hollows fibers with a high surface to volume ratio disposed in the fixed bed, the hollow fibers having an H 2 selective membrane disposed thereon for extracting H 2 from N 2 and to form a permeate of the high purity H 2 and a retentate of primarily N 2 ; and a catalytic H 2 burner also disposed in the fixed bed, the catalytic H 2 burner for burning a portion of the H 2 with the oxidant to provide thermal energy for the NH3 decomposition.

Li, Shiguang↗
DOE OSTI2023

Physics-based Models, Machine Learning, and Experiment: Towards Understanding Complex Electrode Degradation

Degradation phenomena in Li-ion batteries are highly complex, coupled, and sensitive to use history and operating conditions. In this study, we show how tracking model parameters in continuum-level physics-based models, expedited by machine learning, can be useful in testing hypotheses for degradation mechanisms. An exemplary analysis using this approach is presented for a set of lithium trivanadate ( L i x V 3 O 8 ) cathodes cycled over a range of current rates. A simple cell revival process is combined with the parameter estimates over the course of cycling to extract valuable insights into cathode evolution and eliminate hypothesized degradation mechanisms for these cathodes. The presented approach is expected to be broadly applicable for degradation analysis of other electrodes.

25 ENERGY STORAGE↗
DOE OSTI2026

Chemical-Free Lithium Separation from High-Salinity Brines Using Model-Informed and Machine Learning-Optimized Multi-Column Zwitterionic Chromatography

Direct Lithium Extraction (DLE) technologies often struggle to produce high-purity lithium salts from high-salinity brines, as current approaches require chemical-based elution, regeneration, and precipitation steps, resulting in significant environmental footprints. A novel salt fractionation approach using carboxybetaine resin, known as zwitterionic chromatography (ZIC), has demonstrated that lithium ions can be separated from divalent cations under high-salinity conditions using only water as eluent, with no regeneration required. To enable continuous and scalable deployment of this approach, we developed a chemical-free Multi-column Zwitterionic Chromatography (MZC) process and its theoretical and process models. To predict and optimize this nontraditional separation system, we introduced a novel anti-Langmuir isotherm, and the isotherm parameters were estimated through a machine learning-driven optimization based on artificial neural network ensembles with numerical feasibility assessment. Using machine learning-driven optimization, the MZC process achieved 98.0% lithium recovery, 99.5 % Li/(Li + Mg + Ca) purity, a 31.3% productivity increase, and a 33% reduction in water use compared to batch operation. The proposed MZC process enables lithium separation at $0.6-1.2 kg-1 Li, with costs dominated by resin manufacturing, while offering lower separation costs and carbon footprint compared with conventional carbonation. Overall, these findings position the MZC process as an effective polishing step within scalable and sustainable lithium production pipelines.

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

Phonon-exciton Interactions in WSe 2 under a quantizing magnetic field

Strong many-body interaction in two-dimensional transitional metal dichalcogenides provides a unique platform to study the interplay between different quasiparticles, such as prominent phonon replica emission and modified valley-selection rules. A large out-of-plane magnetic field is expected to modify the exciton-phonon interactions by quantizing excitons into discrete Landau levels, which is largely unexplored. Here, we observe the Landau levels originating from phonon-exciton complexes and directly probe exciton-phonon interaction under a quantizing magnetic field. Phonon-exciton interaction lifts the inter-Landau-level transition selection rules for dark trions, manifested by a distinctively different Landau fan pattern compared to bright trions. This allows us to experimentally extract the effective mass of both holes and electrons. The onset of Landau quantization coincides with a significant increase of the valley-Zeeman shift, suggesting strong many-body effects on the phonon-exciton interaction. Our work demonstrates monolayer WSe 2 as an intriguing playground to study phonon-exciton interactions and their interplay with charge, spin, and valley.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
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↗
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↗
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↗
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↗