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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 865 records · Page 48

Understanding cold electron impact on parallel-propagating whistler chorus waves via moment-based quasilinear theory

Earth's magnetosphere hosts a wide range of collisionless particle populations that interact through various wave-particle processes. Among these, cold electrons, with energies below 100 eV, often dominate the plasma density but remain poorly characterized due to measurement challenges such as spacecraft charging and photoelectron contamination. Understanding the contribution of these cold populations to wave–particle interaction is of significant interest. Recent kinetic simulations identified a secondary drift-driven instability, in which parallel-propagating whistler-mode chorus waves excite oblique electrostatic whistler waves near the resonance cone and Bernstein-mode turbulence. These secondary modes enable a new channel of energy transfer from the parallel-propagating whistler wave to the cold electrons. In this work, we develop a moment-based quasilinear theory of the secondary instabilities to quantify such energy exchange. Our results show that these secondary instabilities persist for a wide range of parameters and, in many cases, lead to nearly complete damping of the primary wave. Such secondary instability might limit the amplitude of parallel-propagating whistler waves in Earth's magnetosphere and might explain why high-amplitude oblique whistler or electron Bernstein waves are rarely observed simultaneously with high-amplitude field-aligned whistler waves in the inner magnetosphere.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Understanding the mechanisms of anisotropic dissolution in metal oxides by applying radiolysis simulations to liquid-phase TEM

Iron-based redox-active minerals are ubiquitous in soils, sediments, and aquatic systems. Their dissolution is of great importance for microbial impacts on carbon cycling and the biogeochemistry of the lithosphere and hydrosphere. Despite its widespread significance and extensive prior study, the atomic-to-nanoscale mechanisms of dissolution remain poorly understood, particularly the interplay between acidic and reductive processes. Here, we use in situ liquid-phase-transmission electron microscopy (LP-TEM) and simulations of radiolysis to probe and control acidic versus reductive dissolution of akaganeite (β–FeOOH) nanorods. Informed by crystal structure and surface chemistry, the balance between acidic dissolution at rod tips and reductive dissolution at rod sides was systematically varied using pH buffers, background chloride anions, and electron beam dose. We find that buffers, such as bis-tris, effectively inhibited dissolution by consuming radiolytic acidic and reducing species such as superoxides and aqueous electrons. In contrast, chloride anions simultaneously suppressed dissolution at rod tips by stabilizing structural elements while promoting dissolution at rod sides through surface complexation. Dissolution behaviors were systematically varied by shifting the balance between acidic and reductive attacks. The findings show LP-TEM combined with simulations of radiolysis effects can provide a unique and versatile platform for quantitatively investigating dissolution mechanisms, with implications for understanding metal cycling in natural environments and the development of tailored nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A unified understanding of minimum lattice thermal conductivity

Here, we propose a first-principles model of minimum lattice thermal conductivity ($κ^{min}_L$) based on a unified theoretical treatment of thermal transport in crystals and glasses. We apply this model to thousands of inorganic compounds and find a universal behavior of $κ^{min}_L$ in crystals in the high-temperature limit: The isotropically averaged $κ^{min}_L$ is independent of structural complexity and bounded within a range from ~0.1 to ~2.6 W/(m K), in striking contrast to the conventional phonon gas model which predicts no lower bound. We unveil the underlying physics by showing that for a given parent compound, $κ^{min}_L$ is bounded from below by a value that is approximately insensitive to disorder, but the relative importance of different heat transport channels (phonon gas versus diffuson) depends strongly on the degree of disorder. Moreover, we propose that the diffuson-dominated $κ^{min}_L$ in complex and disordered compounds might be effectively approximated by the phonon gas model for an ordered compound by averaging out disorder and applying phonon unfolding. With these insights, we further bridge the knowledge gap between our model and the well-known Cahill–Watson–Pohl (CWP) model, rationalizing the successes and limitations of the CWP model in the absence of heat transfer mediated by diffusons. Finally, we construct graph network and random forest machine learning models to extend our predictions to all compounds within the Inorganic Crystal Structure Database (ICSD), which were validated against thermoelectric materials possessing experimentally measured ultralow κ L . Our work offers a unified understanding of $κ^{min}_L$, which can guide the rational engineering of materials to achieve .

42 ENGINEERING↗

Is stochastic thermodynamics the key to understanding the energy costs of computation?

The relationship between the thermodynamic and computational properties of physical systems has been a major theoretical interest since at least the 19th century. It has also become of increasing practical importance over the last half-century as the energetic cost of digital devices has exploded. Importantly, real-world computers obey multiple physical constraints on how they work, which affects their thermodynamic properties. Moreover, many of these constraints apply to both naturally occurring computers, like brains or Eukaryotic cells, and digital systems. Most obviously, all such systems must finish their computation quickly, using as few degrees of freedom as possible. This means that they operate far from thermal equilibrium. Furthermore, many computers, both digital and biological, are modular, hierarchical systems with strong constraints on the connectivity among their subsystems. Yet another example is that to simplify their design, digital computers are required to be periodic processes governed by a global clock. None of these constraints were considered in 20th-century analyses of the thermodynamics of computation. The new field of stochastic thermodynamics provides formal tools for analyzing systems subject to all of these constraints. We argue here that these tools may help us understand at a far deeper level just how the fundamental thermodynamic properties of physical systems are related to the computation they perform.

computation↗

Unified understanding of the impact of semiflexibility, concentration, and molecular weight on macromolecular-scale ring diffusion

Conformationally fluctuating, globally compact macromolecules such as polymeric rings, single-chain nanoparticles, microgels, and many-arm stars display complex dynamic behaviors due to their rich topological structure and intermolecular organization. Synthetic rings are hybrid objects with conformations that display both ideal random walk and compact globular features, which can serve as models of genomic DNA. To date, emphasis has been placed on the effect of ring molecular weight on their unusual behaviors. Here, we combine simulations and a microscopic force-level theory to build a unified understanding for how key aspects of ring dynamics depend on different tunable molecular properties including backbone rigidity, monomer concentration, degree of traditional entanglement, and molecular weight. Our large-scale molecular dynamics simulations of ring melts with very different backbone stiffnesses reveal unanticipated behaviors which agree well with our generalized theory. This includes a universal master curve for center-of-mass diffusion constants as a function of molecular weight scaled by a chemistry and thermodynamic state-dependent critical molecular weight that generalizes the concept of an entanglement cross-over for linear chains. The key physics is how backbone rigidity and monomer concentration induced changes of the entanglement length, interring packing, degree of interpenetration, and liquid compressibility slow down space-time dynamic-force correlations on macromolecular scales. A power law decay of the center-of-mass diffusion constant with inverse molecular weight squared is the first consequence, followed by an ultraslow activated hopping transport regime. Our results set the stage to address slow dynamics and kinetic arrest in different families of compact synthetic and biological polymeric systems.

Science & Technology - Other Topics↗

Understanding the superconductivity and charge density wave interaction through quasi-static lattice fluctuations

In unconventional superconductors, coupled charge and lattice degrees of freedom can manifest in ordered phases of matter that are intertwined. In the cuprate family, fluctuating short-range charge correlations can coalesce into a longer-range charge density wave (CDW) order which is thought to intertwine with superconductivity, yet the nature of the interaction is still poorly understood. Here, by measuring subtle lattice fluctuations in underdoped YBa 2 Cu 3 O 6+y on quasi-static timescales (thousands of seconds) through X-ray photon correlation spectroscopy, we report sensitivity to both superconductivity and CDW. The atomic lattice shows remarkably faster relaxational dynamics upon approaching the superconducting transition at T c ≈ 65 K. By tracking the momentum dependence, we show that the intermediate scattering function almost monotonically scales with the relaxation distance of atoms away from their average positions above T c and in the presence of the CDW state, while this peculiar trend is reversed for other temperatures. These observations are consistent with an incipient CDW stabilized by local strain. This work provides insights into the crucial role of relaxational atomic fluctuations for understanding the electronic physics cuprates, which are inherently disordered due to carrier doping.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Cartesian equivariant representations for learning and understanding molecular orbitals

Qualitative and quantitative orbital properties such as bonding/antibonding character, localization, and orbital energies are critical to how chemists understand reactivity, catalysis, and excited-state behavior. Despite this, representations of orbitals in deep learning models have been very underdeveloped relative to representations of molecular geometries and Hamiltonians. Here, we apply state-of-the-art equivariant deep learning architectures to the task of assigning global labels to orbitals, namely energies characterizations, given the molecular coefficients from Hartree–Fock or density functional theory. The architecture we have developed, the Cartesian Equivariant Orbital Network (CEONET), shows how molecular orbital coefficients are readily featurized as equivariant node features common to all graph-based machine-learned potentials. We find that CEONET performs well at predicting difficult quantitative labels such as the orbital energy and orbital entropy. Furthermore, we find that the CEONET representation provides an intuitive latent space for differentiating orbital character for the qualitative assignment of e.g. bonding or antibonding character. In addition to providing a useful representation for further integrating deep learning with electronic structure theory, we expect CEONET to be useful for automatizing and interpreting the results of advanced electronic structure methods such as complete active space self-consistent field theory. In particular, the ability of CEONET to infer multireference character via the orbital entropy paves the way toward the machine-learned selection of active spaces.

chemical reactions↗

Understanding aerosol properties in convective outflows during TRACER

Convective outflow boundaries commonly form across the southeastern U.S., often originating from storms initiated along sea-breeze fronts. As outflows spread, merge, and collide, they frequently trigger secondary convection in air masses already modified by primary storm outflow. This resulting air mass carries a distinctive aerosol population, which can influence the development of secondary convective cells. During the U.S. DOE TRACER field campaign in summer 2022, we investigated how outflows affect aerosol size, composition, and hygroscopicity across Greater Houston, Texas. Using a novel detection algorithm, we identified and verified 72 outflow boundaries from surface meteorological observations. In the relatively simple continental environment northwest of Houston, a common relationship emerged between CCN-inferred hygroscopicity (κ) and size-resolved aerosol concentrations. The κ of aerosols typically decreased in size ranges where aerosol concentrations increased following outflow passage and increased where concentrations decreased. In contrast, at the Atmospheric Radiation Measurement’s (ARM) fixed site in La Porte, Texas, the aerosol response depended on outflow direction, shaped by concentrated industrial and shipping activity to the north and south/southeast along the Houston Ship Channel. Concurrent size distribution and composition changes suggested case-specific variability in κ, with either reinforcing or offsetting effects. Outflows passing over industrial/shipping sectors often promoted less hygroscopic aerosol populations while cleaner residential outflows often favored more hygroscopic aerosol populations. These results highlight key aerosol changes following outflow passage, providing a foundation for improved understanding of aerosol-cloud interactions related to secondary convection initiation along or in the wake of outflow boundaries.

Thompson, Seth A. [Texas A & M Univ., College Stat↗

How lipidomics can transform our understanding of virus infections

Traditionally, lipids have been thought of as molecules that provide structure and energy, but their functional relevance in disease mechanisms is increasingly clear, and with advancements in mass spectrometry technologies, lipidomics analyses is a tool gaining recognition. Beyond the utility of lipoprotein and fatty acid profiles in clinical diagnosis and chemotaxonomic identifications, respectively, lipidomics analysis that combines knowledge across disciplines and can resolve exact lipid structures has the potential to advance clinical diagnoses and associated treatment, differentiate pathogen types (e.g., virus vs. bacterial vs. fungal), detect natural vs lab-grown viruses, and perhaps distinguish a pathogen from a benign biological agent (i.e., threat potential). As new viruses emerge and localized outbreaks expand, lipidomics will accelerate our understanding of viral infections and aid in maximizing the discovery of novel biomarkers of pathogenicity and host response.

59 BASIC BIOLOGICAL SCIENCES↗

Present understanding of ignition and gain using indirect-drive inertial confinement fusion target designs on the U.S. National Ignition Facility

For many decades, the running joke in fusion research has been that 'fusion' is thirty years away and always will be. Yet, these past few years we find ourselves in a position where we can now talk about the milestones of burning plasmas, fusion ignition, and target energy gain greater than unity (scientific breakeven) in the past tense. Fusion is no longer a joke! Yet getting to fusion ignition, the tipping-point of thermonuclear instability resulting in an explosive increase in ion thermal temperature and fusion reaction-rate, and scientific breakeven (target gain, $G_{target} =$ fusion yield/deposited laser energy >1, in the laser-driven inertial confinement fusion context) has not been easy. Here, in this publication, we discuss our present understanding of the physics and technological challenges surrounding ignition and Gain as well as highlight some outstanding problems that still need resolution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Self-organization in 1 atm DC glows with liquid anodes: current understanding and potential applications

Self-organization refers to the spontaneous generation of spatially or temporally organized patterns in an otherwise disordered system. Self-organization is ubiquitous in plasma physics particularly in the low-pressure regime as observed in astrophysical jets or plasma loaded flux loops that form on the surface of the Sun. In recent times, self-organization in atmospheric pressure plasmas has captured the attention of researchers. Its occurrence has been observed in DBD discharges as well as DC 1 atm glows with liquid electrodes. The mechanism of pattern formation is still not well understood. In this work, we briefly review the current understanding of pattern formation in DC glows with liquid anode, surveying past work, application areas, theories on mechanisms of formation from the context of reaction diffusion systems, current experimental work and computational progress towards predicting pattern formation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Understanding the depletion of electrons in dusty plasmas at atmospheric pressure

The nucleation and growth of NPs in the gas phase using atmospheric-pressure plasma systems is an important approach to synthesizing novel dimensionally-controlled materials. In this paper, we investigated the effect of the NPs on a typical type of continuous-flow, substrate-free plasma at atmospheric pressure to understand their potential contribution to electron density changes. A tandem plasma system was set up consisting of one plasma reactor that produced carbonaceous NPs from mixtures of argon and hexane, and another identical plasma reactor where the as-grown particles were injected and non-intrusive electrical and optical measurements were performed. The electron densities obtained from conductivity measurements and a plasma fluid model were found to decrease in the presence of NPs. However, control experiments revealed that the main source of the electron depletion was residual vapor or reaction byproducts in the form of molecular species or nanoclusters and not the particles themselves. These results were validated by constant number Monte Carlo simulations which showed that at the experimentally-measured conditions, the NPs were not of sufficiently high enough concentration to reduce the electron density; however, if molecules or clusters are ionizable, they remain in sufficient concentration to deplete electron densities. Our study shows that at atmospheric pressure, because of their typically larger electron density values, particle-producing plasmas are distinct from those at low pressure, and nanoparticle formation does not have the same impact while molecular-scale species may be a more important consideration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Understanding attosecond streaking

Abstract This tutorial provides an overview on the theory of attosecond streaking, a pump-probe scheme to extract timing information of ionization processes that has been widely used in the past decade. Emphasis is put on the origin of the Coulomb-laser-coupling (CLC) term, which is crucial in the interpretation of streaking delays. Having gained a proper understanding of how the CLC terms in various publications relate to each other, we will be able to analyze in which regime the streaking delay can be split into a measurement-induced CLC term and a ‘pure’ ionization delay and under which conditions this splitting may break down. Thus we address the long-standing question of the validity of the widely applied interpretation of the streaking delay as a sum of the CLC term and a ‘pure’ ionization delay.

Physics↗

Understanding polaronic transport in complex oxides by combining precise synthesis and first-principles many-body theory

In complex oxides, charge carriers often couple strongly with lattice vibrations to form polarons–entangled electron–phonon quasiparticles whose transport properties remain difficult to characterize. Experimental access to intrinsic polaronic transport requires ultraclean samples, while theoretical description demands methods beyond low-order perturbation theory. Here, we show a predictive theory–experiment workflow to study polaron transport in complex oxides. Focusing on a prototypical polaronic oxide, anatase TiO 2 , we combine growth of high-quality oxygen-vacancy-doped films using hybrid molecular beam epitaxy with a first-principles electron–phonon diagrammatic Monte-Carlo (FEP-DMC) framework recently developed for accurate polaron predictions. Our films exhibit record-high electron mobility for anatase TiO 2 , in excellent agreement with FEP-DMC calculations conducted prior to experiment, which predict a room-temperature mobility of 45 ± 15 cm −2 V −1 s −1 and a mobility-temperature scaling of μ ∝ T −1.9 ± 0.077 . Microscopic analysis using scanning transmission electron microscopy and x-ray photoelectron spectroscopy reveals the role of oxygen vacancies in modulating transport at lower temperatures. FEP-DMC further provides quantitative insight into polaron formation energy, phonon cloud distribution, lattice distortion around the polaron, and the polaronic contribution to mobility. Together, these results provide a deeper microscopic understanding of large-polaron transport in a complex oxide and provide the blueprint to characterize other polaronic materials.

anatase TiO2↗

Understanding PDF uncertainty in W boson mass measurements*

Abstract We study the dependence of the transverse mass distribution of charged leptons and the missing energy on parton distributions (PDFs) adapted to W boson mass measurements at the CDF and ATLAS experiments. We compare the shape variations of the distribution induced by different PDFs and find that the spread of predictions from different PDF sets can be significantly larger than the PDF uncertainty predicted by a specific PDF set. We suggest analyzing the experimental data using up-to-date PDFs to gain a better understanding of the PDF uncertainties in W boson mass measurements. We also perform a series of Lagrange multiplier scans to identify the constraints on the transverse mass distribution imposed by individual data sets in the CT18 global analysis. In the case of the CDF measurement, the distribution is mostly sensitive to d -quark PDFs in the intermediate x region, which are largely constrained by DIS and Drell-Yan data on deuteron targets and Tevatron lepton charge asymmetry data.

79 ASTRONOMY AND ASTROPHYSICS↗

Recent progress in understanding electron thermal transport in NSTX

The anomalous level of electron thermal transport inferred in magnetically confined configurations is one of the most challenging problems for the ultimate realization of fusion power using toroidal devices: tokamaks, spherical tori and stellarators. It is generally believed that plasma instabilities driven by the abundant free energy in fusion plasmas are responsible for the electron thermal transport. The National Spherical Torus eXperiment (NSTX) (Ono et al 2000 Nucl. Fusion 40 557) provides a unique laboratory for studying plasma instabilities and their relation to electron thermal transport due to its low toroidal field, high plasma beta, low aspect ratio and large ExB flow shear. Recent findings on NSTX have shown that multiple instabilities are required to explain observed electron thermal transport, given the wide range of equilibrium parameters due to different operational scenarios and radial regions in fusion plasmas. Here we review the recent progresses in understanding anomalous electron thermal transport in NSTX and focus on mechanisms that could drive electron thermal transport in the core region. The synergy between experiment and theoretical/ numerical modeling is essential to achieving these progresses. The plans for newly commissioned NSTX-Upgrade will also be discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Enhanced understanding of non-axisymmetric intrinsic and controlled field impacts in tokamaks

Here, an extensive study of intrinsic and controlled non-axisymmetric field (δB) impacts in KSTAR has enhanced the understanding about non-axisymmetric field physics and its implications, in particular, on resonant magnetic perturbation (RMP) physics and power threshold (P th ) for L–H transition. The n=1 intrinsic non-axisymmetric field in KSTAR was measured to remain as low as δB/B 0 ~ 4×10 –5 even at high-beta plasmas (β N ~ 2), which corresponds to approximately 20% below the targeted ITER tolerance level. As for the RMP edge-localized-modes (ELM) control, robust n=1 RMP ELM-crash-suppression has been not only sustained for more than ~90 τ E , but also confirmed to be compatible with rotating RMP. An optimal window of radial position of lower X-point (i.e. R x = $1.44\pm 0.02\,$ m) proved to be quite critical to reach full n=1 RMP-driven ELM-crash-suppression, while a constraint of the safety factor could be relaxed (q 95 = 5 $\pm $ 0.25). A more encouraging finding was that even when R x cannot be positioned in the optimal window, another systematic scan in the vicinity of the previously optimal R x allows for a new optimal window with relatively small variations of plasma parameters. Also, we have addressed the importance of optimal phasing (i.e. toroidal phase difference between adjacent rows) for n=1 RMP-driven ELM control, consistent with an ideal plasma response modeling which could predict phasing-dependent ELM suppression windows. In support of ITER RMP study, intentionally misaligned RMPs have been found to be quite effective during ELM-mitigation stage in lowering the peaks of divertor heat flux, as well as in broadening the 'wet' areas. Besides, a systematic survey of P th dependence on non-axisymmetric field has revealed the potential limit of the merit of low intrinsic non-axisymmetry. Considering that the ITER RMP coils are composed of 3-rows, just like in KSTAR, further 3D physics study in KSTAR is expected to help us minimize the uncertainties of the ITER RMP coils, as well as establish an optimal 3D configuration for ITER and future reactors.

3D physics↗

Understanding detachment of the W7-X island divertor

The fundamental behavior of the W7-X island divertor under detached conditions, which has been theoretically predicted with the EMC3-Eirene code, is re-examined here under the experimental conditions achieved so far and compared with the first experimental results. Both simulations and experiments cover a range of divertor configurations and plasma parameters, and show the following common trends: (1) with rising impurity radiation, the target heat load decreases 'uniformly' over the entire target surface in the sense that both the peak and average heat loads can drop by an order of magnitude. Impurity radiation (mainly from intrinsic carbon) occurs primarily at the plasma edge and the resulting negative impact on the stored energy is less than 10%. (2) When the total radiation exceeds a critical level, the target particle flux (the recycling flux Γrecy) begins to fall and can drop by a factor of 3–5 at high radiation levels without an obvious indication of significant volume recombination. (3) While Γ recy decreases, the divertor neutral pressure continues to build up and reaches a maximum, at which point Γ recy has declined significantly. (4) During detachment, the electron temperature at the last closed flux surface falls in a way that is not quantitatively understandable from parallel classical heat conduction processes. This paper presents a physical explanation of the numerical/experimental results described above. Furthermore, using the EMC3-Eirene code as a diagnostic tool, we are able, apparently for the first time, to provide a full quantitative analysis of each transport channel in the island divertor, aiming to clarify how the island divertor plasma self-regulates to maintain particle, energy, and momentum balance under detached conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗