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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 451 records · Page 25

Modeling the energetic tail of a dusty plasma's electron energy distribution and its effect on dust grain charge and behavior

A model for a weakly ionized dusty plasma is proposed in which UV or x-ray radiation continuously creates free electrons at high energy, which then cool through collisions with a cold neutral gas before recombining. The transition of a free electron from high energy at birth to low energy at demise implies that the electron energy distribution is not the simple Maxwellian of an isolated system in thermal equilibrium, but instead has a high-energy tail that depends on the recombination time. This tail can have a major effect on dust grain charging because the flux of tail electrons can be substantial even if the density of tail electrons is small. Detailed analytic and numerical calculations of dust grain charging show that situations exist in which a small high-energy tail dominates charge behavior. This implies that dust grain charge in terrestrial and space dusty plasmas may be significantly underestimated if a Maxwellian distribution is assumed and the non-thermal dynamics are neglected.

Physics↗

A comparison of the dielectric function for p-point water models

We compute the longitudinal dielectric function ɛl(k) for p-point water models, p = 3 (SPC/E, TIP3P), p = 4 (TIP4P-EW, OPC), and p = 5 (TIP5P-E) from the charge–charge fluctuation function SZZ(k), obtained from two methods: average of the charge in k-space (method:sum) and from the pair distribution function in Fourier space (method:integral). The latter requires a continuation to small k-values, which we thoroughly discuss. We conclude with a detailed comparison of the longitudinal dielectric function for the different p-point models and its main characteristics: small k and large k limits, position of the poles, and its (complex) zeros.

Shevy, Noah [Ames National Laboratory, Department ↗

Constraints on Lightly Ionizing Particles from CDMSlite

The Cryogenic Dark Matter Search low ionization threshold experiment (CDMSlite) achieved effcient detection of very small recoil energies in its germanium target, resulting in sensitivity to Lightly Ionizing Particles (LIPs) in a previously unexplored region of charge, mass, and velocity parameter space. We report first direct-detection limits on the vertical intensity of cosmogenically-produced LIPs with an electric charge smaller than e/(3x10^5), as well as the strongest limits for charge <= e/160, with a minimum vertical intensity of 1.36 x 10^-7 cm^-2s^-1sr^-1 at charge e/160. These results apply over a wide range of LIP masses (5 MeV/c^2 to 100 TeV/c^2) and cover a wide range of beta-gamma values (0.1--10^6), thus excluding non-relativistic LIPs with beta-gamma as small as 0.1 for the first time.

Alkhatib, I↗

Electric Vehicles at Scale (EVs@Scale) Laboratory Consortium Deep-Dive Technical Meetings: High Power Charging (HPC) Summary Report

Electric vehicle (EV) adoption will change the composition of EV charging load to higher-power charging as more medium- (MD) and heavy-duty (HD) applications are electrified, and as all vocations, including light-duty (LD) vehicles, are capable of faster charging. These shifts provide the opportunity for high-power charging (HPC) and facility equipment to evolve and improve efficiency, cost, and space. High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP) project designs and develops a high-power, interoperable charging experimental platform to research, develop, and demonstrate the integration approaches and technology solutions. The project addresses (1) interconnection and management of a grid-tied inverter; (2) development of a DC distribution system that is responsible for system energy management, interoperability, and DC protection; (3) modular DC/DC conversion for vehicle charging; (4) EV charging interface and DC/DC integration; and (5) smart charge control and vehicle-to-edge (vehicle-to-building [V2B], vehicle-to-everything [V2X]) capability. This summary presentation is the first technical progress output of the project. It provides insight for the first deep-dive technical meeting outputs in terms of research presentations and also includes summary of the discussions occurred in the follow-up breakout sessions. The summary presentation covers three technical areas: (1) HPC: State of the art power architectures and the design of the power electronics, (2) Modeling, energy management, and power control in the HPC station, and (3) Codes and standards work that are in line with the previous two topic areas.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

Electric Vehicles at Scale (EVs@Scale) Laboratory Consortium Deep-Dive Technical Meetings: High Power Charging (HPC) Summary Report

Electric vehicle (EV) adoption will change the composition of EV charging load to higher-power charging as more medium- (MD) and heavy-duty (HD) applications are electrified, and as all vocations, including light-duty (LD) vehicles, are capable of faster charging. These shifts provide the opportunity for high-power charging (HPC) and facility equipment to evolve and improve efficiency, cost, and space. High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP) project designs and develops a high-power, interoperable charging experimental platform to research, develop, and demonstrate the integration approaches and technology solutions. The project addresses (1) interconnection and management of a grid-tied inverter; (2) development of a DC distribution system that is responsible for system energy management, interoperability, and DC protection; (3) modular DC/DC conversion for vehicle charging; (4) EV charging interface and DC/DC integration; and (5) smart charge control and vehicle-to-edge (vehicle-to-building [V2B], vehicle-to-everything [V2X]) capability. This summary presentation is the first technical progress output of the project. It provides insight for the first deep-dive technical meeting outputs in terms of research presentations and also includes summary of the discussions occurred in the follow-up breakout sessions. The summary presentation covers three technical areas: (1) HPC: State of the art power architectures and the design of the power electronics, (2) Modeling, energy management, and power control in the HPC station, and (3) Next Generation Profiles for high power charging characterization.

ADVANCED PROPULSION SYSTEMS↗

High-power electrically tunable switch

A high-voltage switch, whose operation leverages the speed of electrons to generate the “on” time of the pulse in combination with the speed of light to generate the “off” time of the pulse, is described. In one example, the high-voltage switch includes a first electrode, a second electrode spaced apart from the first electrode, a region of non-absorbing material occupying a portion of the space between the first and second electrodes and allowing a laser pulse to propagate therethrough without substantial absorption, and a region of absorbing material occupying another portion of the space and producing a charged particle cloud upon receiving the laser pulse. The high-voltage switch remains “on” upon the charged particle cloud reaching an electrode and until it has been collected by the electrode, and where the high-voltage switch remains “off” subsequent to the collection and until another generated charged particle cloud reaches the electrode.

Voss, Lars↗

Frustrated Ising charge correlations in the kagome metal ScV 6 Sn 6

Here we resolve the real-space nature of the high-temperature, short-range charge correlations in the kagome metal ScV 6 Sn 6 . Diffuse scattering appears along a frustrated wave vector q H = ($\frac{1}{3}, \frac{1}{3}, \frac{1}{2}$) at temperatures far exceeding the charge order T CO = 92 K, preempting long-range charge order with wave vectors along q$_{\bar{K}}$ = ($\frac{1}{3}, \frac{1}{3}, \frac{1}{3}$). Using a combination of real space and reciprocal space analysis, we resolve the nature of the interactions between the primary out-of-plane Sc-Sn chain instability and the secondary strain-mediated distortion of the in-plane V kagome network. Finally, a minimal model of the diffuse scattering data reveals a high-temperature, short-ranged "zig-zag" phase of in-plane correlations that maps to a frustrated triangular lattice Ising model with antiferromagnetic interactions and provides a real-space understanding of the origin frustrated charge order in this material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

High-dimensional maximum-entropy phase space tomography using normalizing flows

Particle accelerators generate charged-particle beams with tailored distributions in six-dimensional position-momentum space (phase space). Knowledge of the phase space distribution enables model-based beam optimization and control. In the absence of direct measurements, the distribution must be tomographically reconstructed from its projections. In this paper, we highlight that such problems can be severely underdetermined and that entropy maximization is the most conservative solution strategy. We leverage —invertible generative models—to extend maximum-entropy tomography to six-dimensional phase space and perform numerical experiments to validate the model's performance. Our numerical experiments demonstrate consistency with exact two-dimensional maximum-entropy solutions and the ability to fit complicated six-dimensional distributions to large measurement sets in reasonable time. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Minimizing phase-space energies

A primary technical challenge for harnessing fusion energy is to control and extract energy from a nonthermal distribution of charged particles. The fact that phase space evolves by symplectomorphisms fundamentally limits how a distribution may be manipulated. While the constraint of phase-space volume preservation is well understood, other constraints remain to be fully appreciated. To better understand these constraints, we study the problem of extracting energy from a distribution of particles using area-preserving and symplectic linear maps. When a quadratic potential is imposed, we find that the maximal extractable energy can be computed as trace minimization problems. We solve these problems and show that the extractable energy under linear symplectomorphisms may be much smaller than the extractable energy under special linear maps. As a result, the method introduced in the present study enables an energy-based proof of the linear Gromov nonsqueezing theorem.

First-principles calculations in plasma physics↗

Biasing topological charge injection in topological matter

Here we explore the interplay between topologies in the momentum and real spaces to formulate a thermodynamic description of nonequilibrium injection of topological charges under external bias. We show that the edge modes engendered by the momentum-space topology can play a functional role of connecting the external reservoirs to the bulk transport of topological charges in the real space. We illustrate our general results with two examples: the spin-torque injection of skyrmions in an electrically biased integer quantum Hall system, and the vortex injection in a topological $p + ip$ superconductor coupled to heat reservoirs. Based on the universal fractional entropy of the Majorana zero modes bound to the vortices, their controllable injection proposed in this work could provide a route for creating and manipulating Majorana fermions.

36 MATERIALS SCIENCE↗

Full Counting Statistics of Charge in Chaotic Many-Body Quantum Systems

We investigate the full counting statistics of charge transport in U(1)-symmetric random unitary circuits. We consider an initial mixed state prepared with a chemical potential imbalance between the left and right halves of the system and study the fluctuations of the charge transferred across the central bond in typical circuits. Using an effective replica statistical mechanics model and a mapping onto an emergent classical stochastic process valid at large on-site Hilbert space dimension, we show that charge transfer fluctuations approach those of the symmetric exclusion process at long times, with subleading t –1/2 quantum corrections. Here, we discuss our results in the context of fluctuating hydrodynamics and macroscopic fluctuation theory of classical nonequilibrium systems and check our predictions against direct matrix-product state calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Rare earth separation in voltage-gated 2D MXene membranes

The separation of rare earth elements (REEs) has historically been a complicated and expensive process, producing significant amounts of pollution. To this end, MXene membranes (MXMs) have attracted researchers' interest. It has been demonstrated that MXMs are capable of separating ions and that it is possible to precisely control the separation rate by applying a voltage to the membrane. Indeed, due to their chemical nature, MXenes show outstanding electrical conductivity. However, the effect of applied voltage on the permeation rate and separation effects of iconic species remains an intriguing area of research. In this work, we demonstrate how applying different voltages (gate voltage) to a MXM affects the permeation rate of various REE ions. Our hypothesis to explain MXMs behavior towards REE is that under negative voltage, the interlayer spacing decreases due to attraction between charged MXene surfaces and intercalated cations, increasing the separation factor between REEs. Under positive voltage, the interlayer spacing increases due to repulsion between the MXene surfaces and intercalated cations. However, we demonstrate relatively poor separation capability for REEs at 1mM starting concentration and 1.0 V applied DC voltage (separation factor ~1-3). This study demonstrates the need for future experiments to observe varied experimental conditions and chemical functionalization to determine whether MXene membranes can be an efficient platform for REE separation.

36 MATERIALS SCIENCE↗

Molecular Understanding of Charge Storage in MoS 2 Supercapacitors with Ionic Liquids

Owing to high electrical conductivity and ability to reversibly host a variety of inserted ions, 2D metallic molybdenum disulfide (1T-MoS 2 ) has demonstrated promising energy storage performance when used as a supercapacitor electrode. However, its charge storage mechanism is still not fully understood, in particular, how the interlayer spacing of 1T-MoS 2 would affect its capacitive performance. In this work, molecular dynamics simulations of 1T-MoS 2 with interlayer spacing ranging from 0.615 to 1.615 nm have been performed to investigate the resulting charge storage capacity in ionic liquids. Simulations reveal a camel-like capacitance-potential relation, and MoS 2 with an interlayer spacing of 1.115 nm has the highest volumetric and gravimetric capacitance of 118 F cm –3 and 42 F g –1 , respectively. Although ions in MoS 2 with an interlayer spacing of 1.115 nm diffuse much faster than with interlayer spacings of 1.365 and 1.615 nm, the MoS 2 with larger interlayer spacing has a much faster-charging process. Our analyses reveal that the ion number density and its charging speed, as well as ion motion paths, have significant impacts on the charging response. Here, this work helps to understand how the interlayer spacing affects the interlayer ion structures and the capacitive performance of MoS 2 , which is important for revealing the charge storage mechanism and designing MoS 2 supercapacitor.

25 ENERGY STORAGE↗

Closed-loop optimization of fast-charging protocols for batteries with machine learning

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years. Furthermore, both large parameter spaces and high sampling variability necessitate a large number of experiments. As such, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users. We combine two key elements to reduce the optimization cost: an early-prediction model, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces.

25 ENERGY STORAGE↗

Importance of Nuclear Quantum Effects on Aqueous Electrolyte Transport under Confinement in Ti 3 C 2 MXenes

Protons display a high chemical activity and strongly affect the charge storage capability in confined interlayer spaces of two-dimensional (2D) materials. As such, an accurate representation of proton dynamics under confinement is important for understanding and predicting charge storage dynamics in these materials. While often ignored in atomistic-scale simulations, nuclear quantum effects (NQEs), e.g., tunneling, can be significant under confinement even at room temperature. Here, using the thermostatted ring polymer molecular dynamics implementation of path integral molecular dynamics (PIMD) in conjunction with the ReaxFF force field, density functional tight binding (DFTB), and NequIP neural network potential simulations, we investigate the role of NQEs on proton and water transport in bulk water and aqueous electrolytes under confinement in Ti 3 C 2 MXenes. Although overall NQEs are relatively small, especially in bulk, we find that they can alter both quantitative values and qualitative trends on both proton transport and water self-diffusion under confinement relative to classical MD predictions. Therefore, our results suggest the need for NQEs to be considered to simulate aqueous systems under confinement for both qualitative and quantitative accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗