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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Tin-graphene tubes as anodes for lithium-ion batteries with high volumetric and gravimetric energy densities

Limited by the size of microelectronics, as well as the space of electrical vehicles, there are tremendous demands for lithium-ion batteries with high volumetric energy densities. Current lithium-ion batteries, however, adopt graphite-based anodes with low tap density and gravimetric capacity, resulting in poor volumetric performance metric. Here, by encapsulating nanoparticles of metallic tin in mechanically robust graphene tubes, we show tin anodes with high volumetric and gravimetric capacities, high rate performance, and long cycling life. Pairing with a commercial cathode material LiNi0.6Mn0.2Co0.2O2, full cells exhibit a gravimetric and volumetric energy density of 590 W h Kg-1 and 1,252 W h L-1 , respectively, the latter of which doubles that of the cell based on graphite anodes. This work provides an effective route towards lithium-ion batteries with high energy density for a broad range of applications.

25 ENERGY STORAGE↗
DOE OSTI2023

The effectiveness of D 2 pellet injection in reducing intra-ELM and inter-ELM tungsten divertor erosion rates in DIII-D during the Metal Rings Campaign

Abstract Edge localized modes (ELMs) in H-mode plasmas erode plasma-facing components (PFCs) and lead to impurities in the core, reducing confinement. This study analyzes D 2 pellet injection on the DIII-D fusion experiment used as an ELM mitigation technique applied during the 2016 tungsten Metal Rings Campaign to reduce W erosion during ELMs. The 400.9 nm photon wavelength line emission intensity of tungsten atoms (WI) filterscope channels and Langmuir probes were used to infer the gross erosion rate of tungsten-coated tiles installed in the divertor of DIII-D. D 2 mass injection rates ranging from 34 to 41 arbitrary units (A.U.) and no D 2 injection resulted in a similar total W erosion rate during ELMs (intra-ELM). On average, results show a 29% increase in the total gross W erosion rate with intermediate mass injection rates (∼13–23 A.U.) compared to the no pellets and the highest injection rate cases. On average, the fast D 2 mass injection rate cases had 15% less erosion in the inter-ELM phase than the case with no pellets. Generally, higher D 2 mass injection rates increased the ELM frequency, and the highest injection rates reduced the average erosion per ELM and fractional carbon impurities at the top of the pedestal by nearly 40% when compared to the no-pellet case. As expected, a higher D 2 pellet injection rate led to a higher plasma density and lower plasma temperature in the divertor. Additionally, an increasing divertor inter-ELM plasma electron density directly correlated to more frequent pellet injection and a decrease in both the average gross intra-ELM W erosion and the total gross intra-ELM W erosion rate. Simulations of intra-ELM erosion using the ‘free-streaming plus recycling model’ (FSRM) underestimate W erosion during pellet injection by about 30% on average. The discrepancies between the experimental measurements and the FSRM intra-ELM W erosion predictions are postulated to be due to C/W material mixing. A simple analytic mixed-material model is presented and results in better agreement with the experimental data. These results highlight the importance of incorporating the effects of a mixed-material layer in the analysis of PFC erosion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Assessing Metal Ion Assignment Accuracy in Protein Data Bank Models via Elemental Spectroscopy

Accurate representation of metal ions in macromolecular structures is critical for chemical interpretation, computational modeling, and machine-learning methods that rely on Protein Data Bank (PDB) entries. However, the elemental identity of metals modeled in crystallographic structures is often inferred indirectly and rarely validated experimentally. Here, we combine Particle Induced X-ray Emission (PIXE) and X-ray Fluorescence Spectroscopy (XRFS) to determine the elemental composition of protein samples used to generate 70 deposited metalloprotein crystal structures. By analyzing the original protein material employed for crystallization, but before the addition of crystallization buffer solutions, we assess whether the modeled metal ions in deposited structures are consistent with experimentally detectable elemental content. We find that in a majority of cases, the metals modeled in the corresponding PDB entries are inconsistent with the metals present in the protein samples before crystallization, or that additional metals are present but not represented in the structural models. Spectroscopic results were integrated with automated crystallographic validation metrics, including real-space Z-difference (RSZD) analysis and systematic rerefinement, to evaluate atomic-number mismatch at metal sites. PIXE and XRFS show strong agreement for dominant elemental signals and provide complementary, scalable approaches for identifying suspect metal assignments. This work does not address physiological or functional metalation but instead highlights a widespread data integrity issue in deposited macromolecular structures, PDB-wide. These results establish an experimentally corroborated link between elemental identity and crystallographic validation metrics, enabling the large-scale detection of chemically inconsistent annotations in structural databases used for computational modeling and machine learning.

Crystallization↗
DOE OSTI2022

A Facile Potential Hold Method for Fostering an Inorganic Solid‐Electrolyte Interphase for Anode‐Free Lithium‐Metal Batteries

Abstract Anode‐free lithium batteries are regarded as an ultimate form of high‐energy‐density lithium‐ion batteries. Unfortunately, irreversible lithium loss during cycling plays a major role in degrading the overall cell performance in the anode‐free configuration. To alleviate the deterioration, building a robust solid‐electrolyte interface on an anode current collector is an indispensable requirement. Here, we present a facile in‐situ electrochemical method of a potential hold during the first charge to guide more salt‐derived (less solvent‐derived) decomposition on the anode interface. We show the distinctive decomposition potential of lithium salts and ether/carbonate solvents, where the Li‐solvation structures with salt contact‐ion‐pairs preferentially decompose to form LiF‐rich and less organic components, leading to enhanced lithium Coulombic efficiency in Li||Cu cells as well as mitigating the capacity fade of Cu||LiFePO 4 and Cu||LiNi 0.8 Mn 0.1 Co 0.1 O 2 cells.

Shin, Woochul↗
DOE OSTI2020

Fluorination effect for stabilizing cationic and anionic redox activities in cation-disordered cathode materials

We see that cation-disordered Li-excess cathodes with oxygen redox reactions are promising candidates for high-energy-density Li ion batteries. Nevertheless, the oxygen redox process that is required for the high capacity often comes with the oxygen loss, which leads to severe capacity degradation and voltage decay. In this work, we have successfully synthesized a series of Li-excess cation-disordered cathodes (Li 1.2 Mn 0.4+x Ti 0.4-x O 2-x Fx) (0 ≤ x ≤ 0.2) with different fluorine (F) contents. The electrochemical performance results show that the Li 1.2 Mn 0.55 Ti 0.25 O 1.85 F 0.15 (LMTOF0.15) exhibits the highest reversible capacity (275 mAh g -1 , under 30 mA g -1 ), cyclability, and voltage retentions. The mapping of resonant inelastic X-ray scattering (mRIXS) and differential electrochemical mass spectroscopy (DEMS) results reveal that the fluorination enhances the reversible lattice oxygen redox reaction while suppressing irreversible gas release and surface reactions. The X-ray Absorption Spectroscopy (XAS) during the initial two cycles shows that F-substitution alleviates the reduction of the Mn valence state during the whole (dis)charge processes in the bulk and at the surface of the material, results in higher average discharge voltage. In addition, the introduction of F improves the structural stability and suppresses local lattice distortion of the material. Therefore, LMTOF 0.15 is able to cycle with smaller polarization, less interfacial side reaction and Mn dissolution, and therefore results in enhanced cyclability. This work provides a comprehensive understanding of the fluorination effect on the cationic and anionic redox activities in cation-disordered Li-excess cathodes.

25 ENERGY STORAGE↗
DOE OSTI2022

Performance evaluation of an industrial ceramic nanofiltration unit for wastewater treatment in oil production

An industrial ceramic nanofiltration membrane (pore size 0.9 nm) was tested in a Canadian oil field for more than 12,500 h to treat wastewater directly from daily operations, without any type of pre-treatment. This wastewater contained a high content of total suspended solids (13 to 510 mg/kg), and total organic carbon (31 to 134 mg/kg). The membrane unit was operated at different transmembrane pressure (TMP) set points (4–16 bar) and recovery set points (40–80%). The data show that ion and compound rejection depend strongly on a combination of both TMP and recovery, with the largest rejection occurring at low recovery values and high TMP values. Two mechanisms were responsible for rejection: sieving, which mostly impacted compound rejection, and electrostatic phenomena that impacted ion rejection. It is shown that ion rejection depends linearly on charge density of the ion. Ion rejection was measured as high as 85% and compounds (such as TSS) were rejected as high as 100%. The specific flux varied between 1–10 L/(m 2 .h.bar). Results from this field testing indicate the possibility of using these types of ceramic membranes for oil field wastewater treatment.

42 ENGINEERING↗
DOE OSTI2025

Critically assessing sodium-ion technology roadmaps and scenarios for techno-economic competitiveness against lithium-ion batteries

Sodium-ion batteries have garnered notable attention as a potentially low-cost alternative to lithium-ion batteries, which have experienced supply shortages and price volatility for key minerals. Here we assess their techno-economic competitiveness against incumbent lithium-ion batteries using a modelling framework incorporating componential learning curves constrained by minerals prices and engineering design floors. We compare projected sodium-ion and lithium-ion price trends across over 6,000 scenarios while varying Na-ion technology development roadmaps, supply chain scenarios, market penetration and learning rates. Assuming that substantial progress can be made along technology roadmaps via targeted research and development, we identify several sodium-ion pathways that might reach cost-competitiveness with low-cost lithium-ion variants in the 2030s. In addition, we show that timelines are highly sensitive to movements in critical minerals supply chains—namely that of lithium, graphite and nickel. Our modelled outcomes suggest that being price advantageous against low-cost lithium-ion variants in the near term is challenging and increasing sodium-ion energy densities to decrease materials intensity is among the most impactful ways to improve competitiveness.

25 ENERGY STORAGE↗
DOE OSTI2022

Investigating the effects of electron bounce-cyclotron resonance on plasma dynamics in capacitive discharges operated in the presence of a weak transverse magnetic field

Recently, Patil et al. [Phys. Rev. Res. 4, 013059 (2022)] have reported the existence of an enhanced operating regime when a low-pressure (5 mTorr) capacitively coupled discharge (CCP) is driven by a very high radio frequency (60 MHz) source in the presence of a weak external magnetic field applied parallel to its electrodes. Their particle-in-cell simulations show that a significantly higher bulk plasma density and ion flux can be achieved at the electrode when the electron cyclotron frequency equals half of the applied radio frequency for a given fixed voltage. In the present work, we take a detailed look at this phenomenon and further delineate the effect of this “electron bounce-cyclotron resonance (EBCR)” on the electron and ion dynamics of the system. We find that the ionization collision rate and stochastic heating are maximum under resonance condition. The electron energy distribution function also indicates that the population of tail-end electrons is highest for the case where EBCR is maximum. Formation of electric field transients in the bulk plasma region is also seen at lower values of applied magnetic field. Finally, we demonstrate that the EBCR-induced effect is a low-pressure phenomenon and weakens as the neutral gas pressure increases. The potential utility of this effect to advance the operational performance of CCP devices for industrial purposes is discussed in this report.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Studying fast-ion populations using oscillations in solid-state neutral-particle analyzer signal and neutral-beam injection power

A method for determining the fast-ion population density in magnetically confined plasmas as a function of pitch-radius, (λ, R), using a solid-state neutral-particle analyzer (ssNPA) signal and neutral-beam injection (NBI) power-output data has been developed. Oscillations in the NBI power output are replicated only in the active part of the ssNPA signal, allowing this to be separated from the passive and background signals, which usually complicate data from this diagnostic. Results obtained using this method are compared with those from standard techniques using data from the Mega-Amp Spherical Tokamak Upgrade spherical tokamak.

Instruments & Instrumentation↗
DOE OSTI2026

Accelerating kinetic plasma simulations with machine-learning-generated initial conditions

Computational models of plasma technologies often solve for the system operating conditions by time-stepping an initial value problem to a quasi-steady solution. However, the strongly nonlinear and multi-timescale nature of plasma dynamics often necessitate millions, or even hundreds of millions, of steps to reach convergence, reducing the effectiveness of these simulations for computer-aided engineering. We consider acceleration of kinetic plasma simulations via data-driven machine-learning-generated initial conditions, which initialize the simulations close to their final quasi-steady-state, thereby reducing the number of steps to reach convergence. Three machine-learning models are developed to predict the density and ion kinetic profiles of capacitively coupled plasma discharges relevant to the microelectronics industry. The models are trained on kinetic simulations over a range of device operating frequencies and pressures. Best performance was observed when simulations were initialized with ion kinetic profiles generated by a convolutional neural network, reducing the mean number of steps to reach convergence by 17.1× when compared to initialization with a zero-dimensional global model. We also outline a workflow for continuous data-driven model improvement and simulation speedup, with the aim of generating sufficient data for full device digital twins.

Artificial neural networks↗
DOE OSTI2022

Estimation of plasma properties using an extended Kalman filter with plasma global models

A physically-constrained extended Kalman filter (EKF) is applied to various zero-dimensional global models for the estimation of plasma properties using time-dependent experimental data such as the plasma density or ion flux. The capability of the EKF is demonstrated to estimate unknown system states simultaneously, such as reaction rate coefficients and the absorbed electron input power, which can be difficult, if not impossible, to measure experimentally. Global models accounting for pure argon reactions and argon-oxygen reactions are used in this work to demonstrate the ability of the filter to estimate dynamic and complex systems. Furthermore, the results obtained from the EKF plasma global model illustrate that model-data fusion techniques can be used to estimate plasma properties and processes for time-varying systems, such as pulsed discharges.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Experimental study of the influence of gas puff locations on H-mode boundary plasmas with argon seeding on EAST

To investigate the optimal scenario of impurity seeding to obtain divertor plasma detachment for target protection, experiments with Ar&D 2 seeding from two different poloidal locations, the upper outer (UO) divertor target and lower outer (LO) target, were carried out on EAST. Partial energy detachment (the electron temperature near the strike point T e,spt ≤ 10 eV) were obtained with Ar&D 2 mixture puffing from the UO target and, for the first time, from the LO target into H-mode plasmas in the upper single null (USN) configuration. The peak heat flux q t on the UO target was significantly reduced (by ~80%). The rollover of ion flux density j s did not appear probably due to insufficient momentum loss, which is independent of the puff locations. The poloidal asymmetries of particle and heat fluxes on the targets have also been investigated. The UO-dominant asymmetry of particle flux was reversed, while the UO-dominant asymmetry of heat flux was mitigated but not reversed. The plasma confinement dropped by only 14% and 8.2% in the LO-puff case and UO-puff case, respectively, during detachment. The high level of C may contributed greatly to the higher radiation in the bulk plasma region and the greater decline in W MHD in the LO-puff case.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Theory of mean E × B shear in a stochastic magnetic field: ambipolarity breaking and radial current

The mean E $ \times $ B shear in a stochastic magnetic field is calculated, using the radial force balance relation and transport equations. This analysis is relevant to the L → H transition with resonant magnetic perturbations, and special focus is placed upon the physics of non-ambipolar transport and radial current. The key physical process is the flow of fluctuating currents along wandering magnetic fields. The increments in poloidal and toroidal rotation, density and ion pressure are calculated. The radial envelope of the magnetic perturbations inside the plasma defines a new scale ${\ell _{{\text{env}}}}$, which is the characteristic scale of the magnetic fluctuation intensity profile. Here, the net particle outflow due to stochastic magnetic fields is calculated and is determined by the net radial current through the separatrix. Implications for the L → H transition are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

First evidence of dominant influence of E × B drifts on plasma cooling in an advanced slot divertor for tokamak power exhaust

Addressing power exhaust in tokamaks is presently recognized as one of the major remaining open issues for the development of fusion reactors. At the forefront of this endeavor is the effort to develop an advanced divertor by maximizing dissipation of plasma power and momentum inside the divertor. Here, we demonstrate, for the first time, that the electromagnetic (E × B) drifts exert a key influence on plasma and gas dynamics in a new advanced slot divertor in the DIII-D tokamak, named the small angle slot (SAS). SAS leverages the effect of drifts to achieve a highly dissipative divertor with electron temperature T e ≲ 10 eV over a wide range of plasma densities, for ion B × ∇B away from the divertor, as used for advanced tokamak operation on DIII-D. Modeling with the SOLPS-ITER code shows that for this drift direction, the E × B flow carries particles toward the outer common flux region (CFR) via the private flux region (PFR), reinforcing neutral recycling and enhancing divertor dissipation. In contrast, for the opposite field direction, the E × B flow carries particles away from the outer CFR into the PFR, offsetting the anticipated SAS geometric effects. Furthermore, this finding is an important step in the understanding of the behavior of advanced divertors for achieving a power exhaust solution for fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Machine learning-based real-time kinetic profile reconstruction in DIII-D

Abstract Kinetic equilibrium reconstruction plays a vital role in the physical analysis of plasma stability and control in fusion tokamaks. However, the traditional approach is subjective and prone to human biases. To address this, the consistent automatic kinetic equilibrium reconstruction (CAKE) method was introduced, providing objective results. Nonetheless, its offline nature limits its application in real-time plasma control systems (PCSs). To address this limitation, we present RTCAKENN, a machine learning model that approximates 7 CAKE-level output profiles, namely pressure, inverse q , toroidal current density, electron temperature and density, carbon ion impurity temperature and rotation profiles, using real-time available inputs. The deep neural network consists of an encoder layer, where the scalars and interdependent inputs such as plasma boundary coordinates and motional Stark effect data are encoded using multi-layer perceptrons (MLPs), while profile inputs are encoded by 1D convolutional layers. The encoded data is passed through a MLP for latent feature extraction, before being decoded in the decoding layers, which consist of upsampling and convolutional layers. RTCAKENN has been implemented in the DIII-D PCS and our model achieves accuracy comparable to CAKE and surpasses existing real-time alternatives. Through clever dropout training, RTCAKENN exhibits robustness and can operate even in the absence of Thomson scattering data or charge exchange recombination data. It executes in under 8 ms in the real-time environment, enabling future application in real-time control and analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Multifunctional, Self-Healing Polyelectrolyte Gels for Long-Cycle-Life, High-Capacity Sulfur Cathodes in Li-S Batteries (FY2020 Final Report)

The project aims to develop polyelectrolyte gels consisting of partially crosslinked ionomer, interpenetrated with self-healing/polysulfide-trapping chains and swelled with a mixture of room temperature ionic liquid (RTIL) and lithium salt. To our knowledge, no other sulfur-based cathode design has combined self-healing behavior, polysulfide containment, and lithium dendrite suppression into a single design. We have demonstrated the benefits of multifunctional ionomer gel polyelectrolytes / gel cathodes with self-healing properties, as well as chemical modification of mesoporous carbons for S/C composite cathodes. Success of the proposed program of study would have wide ranging impact on the electric vehicle industry and society as a whole. A Li-S battery system with the capability of doubling lithium-ion energy density would enable the production of lighter, longer range electric vehicles at a cost that is affordable to the average U.S. household. The availability of such vehicles should lead to wide-ranging adoption over the coming years which, in combination with increased renewable electricity generation, will drastically decrease carbon emissions across the country and reduce U.S. dependency on fossil fuel sources.

25 ENERGY STORAGE↗
DOE OSTI2025

Langevin Dynamics modeling of gas-phase ion-ion recombination (Final Technical Report)

A self-consistent trajectory simulation approach to model MN reactions (Fig. 1) which incorporates the probability of electron transfer as a Monte Carlo operator (Fig. 2) was developed and published as Liu et al. J. Chem. Phys. 159, 114111 (2023). The electron transfer probability p ET estimated using the two-state Landau-Zener (LZ) theory was incorporated into classical trajectory simulations to elicit predictions of MN reaction cross-section σ (vacuum) or rate constant β (finite pressure). Electronic structure calculations with multireference configuration interaction (MRCI) and large correlation consistent basis sets were used to derive inputs to the LZ theory. The key advance of our trajectory simulation approach is the incorporation of electron transfer probability and the inclusion of the effect of ion-neutral interactions on MN using a Langevin representation of the effect of neutral gas on ions. For H + – H - and Li + – H(D) - pairs, our approach quantitatively agrees with measured speed-dependent cross-sections for up to ~10 5 m/s. For the ion pair Ne + – Cl - , our predictions of the MN rate constant at ~1 torr are a factor of ~2 – 3 higher than the experimentally measured value. Similarly, for Xe + – F - in the pressure range of ~20000 – 80000 Pa, our predictions of the MN rate constant are ~20% lower but are in excellent qualitative agreement with experimental data. The paradigm of using trajectory simulations to self-consistently model MN reactions is the basis for inclusion of additional non-classical, and static magnetic and electric field effects. Subsequent work, published as Roy et al. focused on modeling recombination rate constant for three ion pairs (rare gas Ar + cation and halide anions): Ar + – Cl - , Ar + – Br - , Ar + – I - , 2) considering spin-orbit couplings in the electronic structure calculations to obtain high-fidelity estimates of the electron transfer probability and incorporated within the classical trajectory simulations to elicit predictions. In addition to calculations of ion-ion recombination rate constants, a classical trajectory simulation technique (published as Roy et al. J. Chem. Phys. 162(9), 094104 (2023)) that uses quaternions to represent orientation of non-spherical particles (ions or aerosol particles) was developed to simulate the recombination of diatomic or more generally, polyatomic molecules. Finally, several other ion pairs such as Ne + – Cl - , Kr + – Cl - , were explored using the developed semi-classical trajectory simulations to understand various challenges in tackling electronic structure calculations. Using empirical approaches to parameterize the electron transfer radius, trajectory simulations were also used to probe the effect of ion number density on MN rate constant.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗