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At least 397 records · Page 22

Absolute ion density measurements in the afterglow of a radiofrequency atmospheric pressure plasma jet

Atmospheric pressure plasma jets (APPJs) can enable large fluxes of reactive species impinging on treated substrates in many applications. The relative importance of ionic versus neutral reactive species fluxes produced by APPJs is to date mainly deduced from modeling due to the challenge of measuring absolute ion densities/fluxes. In this study, a calibration was performed to determine the absolute densities of cold ions in the afterglow region of an RF-driven atmospheric pressure plasma jet (APPJ) in Ar + 1% O 2 by molecular beam mass spectrometry. Here, positive ion densities were found to be about 3-4 orders of magnitudes lower than the densities of the dominant reactive neutral species (O, O 2 (a 1 Δ g ), O 3 ) in the afterglow region of the APPJ at a distance larger than 2 mm from the visible plasma plume. The results illustrate the ability of molecular beam mass spectrometry to enable a quantitative evaluation of both neutral and ionic species in many applications using APPJs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Spectrally-dependent positive and negative photo-plastic effects in CdZnTe and CdZnTeSe

We studied the Vickers microhardness HV0.025 of CdZnTe and CdZnTeSe samples upon illumination with quasi-monochromatic light with wavelengths ranging between 750 and 1540 nm. We observed that light with a wavelength close to or above the bandgap of the samples results in a positive photo-plastic effect (hardening), and light in the spectral range well below the band gap can lead both to positive or negative effects depending on the parameters of deep levels in the bandgap. We performed measurements of spectrally dependent photoconductivity and compared them with HV0.025. Based on the analysis, we propose a complex qualitative model explaining the spectral dependence of HV0.025 by the charging and neutralization of deep levels by optical transitions between the valence and conduction bands and between the bands and deep levels in the band gap. Tuning of parameters of deep levels could be used to control the sign and magnitude of the photo-plastic effect.

36 MATERIALS SCIENCE↗

The Sensitivity of Joint Inversions of Seismic and Geodynamic Data to Mantle Viscosity

Seismic tomography has revealed the existence of large-scale velocity heterogeneities in the mantle. The interpretation of seismic velocity anomalies in terms of temperature and chemical composition is nonunique. We use geodynamic observations including gravity, plate motions, dynamic topography, and excess ellipticity of the core-mantle boundary combined with seismic observations to investigate the thermo-chemical structure of the mantle through joint inversions. An outstanding issue, however, is the physical connection between mantle density anomalies and the surface geodynamic observations, which requires knowledge of the mantle viscosity structure. Here we perform joint inversions assuming different viscosity profiles and examine the dependence of the results on the viscosity. We first assume that mantle heterogeneity is due to thermal variations, which places a constraint on the relation between seismic velocity and density, and we subsequently relax the constraint to allow for potential nonthermal effects. In all of our joint inversions, a nonthermal origin of density anomalies is required to explain the geodynamic data, though the amount varies with the assumed viscosity structure. A common observation is a high-density chemical signal in the center of the large low-shear-velocity provinces at the base of the mantle resulting in a near neutral or slightly dense overall buoyancy there. Using the derived density models and their corresponding viscosity profiles, we also calculate instantaneous mantle flow fields. The predicted flow fields derived from joint inversions are generally similar but are quite different from flow fields using density models derived from a posteriori scaling of pure seismic tomography models.

58 GEOSCIENCES↗

O-GlcNAc forces an α-synuclein amyloid strain with notably diminished seeding and pathology

Amyloid-forming proteins such α-synuclein and tau, which are implicated in Alzheimer’s and Parkinson’s disease, can form different fibril structures or strains with distinct toxic properties, seeding activities and pathology. Understanding the determinants contributing to the formation of different amyloid features could open new avenues for developing disease-specific diagnostics and therapies. Here we report that O-GlcNAc modification of α-synuclein monomers results in the formation of amyloid fibril with distinct core structure, as revealed by cryogenic electron microscopy, and diminished seeding activity in seeding-based neuronal and rodent models of Parkinson’s disease. Although the mechanisms underpinning the seeding neutralization activity of the O-GlcNAc-modified fibrils remain unclear, our in vitro mechanistic studies indicate that heat shock proteins interactions with O-GlcNAc fibril inhibit their seeding activity, suggesting that the O-GlcNAc modification may alter the interactome of the α-synuclein fibrils in ways that lead to reduce seeding activity in vivo. Our results show that posttranslational modifications, such as O-GlcNAc modification, of α-synuclein are key determinants of α-synuclein amyloid strains and pathogenicity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Looking through the photoionisation wake: Vela X-1 at φ orb ≈ 0.75 with Chandra /HETG

In this work, we detect and identify five narrow radiative recombination continua (Mg XI-XII, Ne IX-X, O VIII) and several emission lines from Fe, S, Si, Mg, Ne, Al, and Na, including four He-like triplets (S XV, Si XIII, Mg XI, and Ne IX). Photoionisation models reproduce the overall spectrum well, except for the near-neutral fluorescence lines of Fe, S, and Si. We conclude that the plasma is mainly photoionised, but more than one component is most likely present, which is consistent with a multi-phase plasma scenario, where denser and colder clumps of matter are embedded in the hot, photoionised wind of the companion star. Simulations with the future X-ray satellites Athena and XRISM show that a few hundred seconds of exposure is sufficient to disentangle the lines of the Fe Kα doublet and the He-like Fe XXV, improving, in general, the determination of the plasma parameters.

79 ASTRONOMY AND ASTROPHYSICS↗

Robust and ultrafast state preparation by ramping artificial gauge potentials

Abstract The implementation of static artificial magnetic fields in ultracold atomic systems has become a powerful tool, e.g. for simulating quantum-Hall physics with charge-neutral atoms. Taking an interacting bosonic flux ladder as a minimal model, we investigate protocols for adiabatic state preparation via magnetic flux ramps. Considering the fact that it is actually the artificial vector potential (in the form of Peierls phases) that can be experimentally engineered in optical lattices, rather than the magnetic field, we find that the time required for adiabatic state preparation dramatically depends on which pattern of Peierls phases is used. This can be understood intuitively by noting that different patterns of time-dependent Peierls phases that all give rise to the same magnetic field ramp, generally lead to different artificial electric fields during the ramp. As an intriguing result, we find that an optimal choice allows for preparing the ground state almost instantaneously in the non-interacting system, which can be related to the concept of counterdiabatic driving. Remarkably, we find extremely short preparation times also in the strongly-interacting regime. Our findings open new possibilities for robust state preparation in atomic quantum simulators.

Wang, Botao (ORCID:0000000282202452)↗

High harmonic generation in mixed XUV and NIR fields at a free-electron laser

Abstract We present the results of an experiment investigating the generation of high-order harmonics by a femtosecond near-infrared (NIR) laser pulse in the presence of an extreme ultraviolet (XUV) field provided by a free-electron laser (FEL), a process referred to as XUV-assisted high-order harmonic generation (HHG). Our experimental findings show that the XUV field can lead to a small enhancement in the harmonic yield when the XUV and NIR pulses overlap in time, while a strong decrease of the HHG yield and a red shift of the HHG spectrum is observed when the XUV precedes the NIR pulse. The latter observations are in qualitative agreement with model calculations that consider the effect of a decreased number of neutral emitters but are at odds with the predicted effect of the correspondingly increased ionization fraction on the phase matching. Our study demonstrates the technical feasibility of XUV-assisted HHG experiments at FELs, which may provide new avenues to investigate correlation-driven electron dynamics as well as novel ways to study and control propagation effects and phase matching in HHG.

47 OTHER INSTRUMENTATION↗

Chemical abundances in Seyfert galaxies – Ⅸ. Helium abundance estimates

For the first time, the helium abundance relative to hydrogen (He/H), which relied on direct measurements of the electron temperature, has been derived in the narrow line regions (NLRs) from a local sample of Seyfert 2 nuclei. In view of this, optical emission line intensities [3000 < λ(Å) < 7000] of 65 local Seyfert 2 nuclei (z < 0.2), taken from Sloan Digital Sky Survey Data Release 15 and additional compilation from the literature, were considered. Here we used photoionization model grid to derive an Ionization Correction Factor (ICF) for the neutral helium. The application of this ICF indicates that the NLRs of Seyfert 2 present a neutral helium fraction of ~50 percent in relation to the total helium abundance. We find that Seyfert 2 nuclei present helium abundance ranging from 0.60 to 2.50 times the solar value, while ~85 percent of the sample present oversolar abundance values. The derived (He/H)–(O/H) abundance relation from the Seyfert 2 is stepper than that of star-forming regions (SFs) and this difference could be due to excess of helium injected into the interstellar medium by the winds of Wolf–Rayet stars. From a regression to zero metallicity, by using Seyfert 2 estimates combined with SFs estimates, we obtained a primordial helium mass fraction Y p = 0.2441 ± 0.0037, a value in good agreement with the one inferred from the temperature fluctuations of the cosmic microwave background by the Planck Collaboration, i.e. $Y_{p}^{Planck}$ =0.2471 ± 0.0003.

79 ASTRONOMY AND ASTROPHYSICS↗

Complex Density Wave Orders and Quantum Phase Transitions in a Model of Square-Lattice Rydberg Atom Arrays

In this work, we describe the zero-temperature phase diagram of a model of a two-dimensional square-lattice array of neutral atoms, excited into Rydberg states and interacting via strong van der Waals interactions. Using the density-matrix renormalization group algorithm, we map out the phase diagram and obtain a rich variety of phases featuring complex density wave orderings, upon varying lattice spacing and laser detuning. While some of these phases result from the classical optimization of the van der Waals energy, we also find intrinsically quantum-ordered phases stabilized by quantum fluctuations. These phases are surrounded by novel quantum phase transitions, which we analyze by finite-size scaling numerics and Landau theories. Our work highlights Rydberg quantum simulators in higher dimensions as promising platforms to realize exotic many-body phenomena.

74 ATOMIC AND MOLECULAR PHYSICS↗

On the Radiation Effects of Strontium Ions on Satellite Solar Cells in Low Earth Orbits

This study focuses on the radiation effects 19 of Sr + ions—generated from high-altitude nuclear explosions (HANE)—on satellite solar cells in low-Earth orbits (LEO). Along four selected satellite orbits, ion fluences are sampled inside the evolving Sr + distributions for days, determined from our newly developed HANE environment model. These fluences, along with the help of radiation transport codes including the MULASSIS and SRIM models, enable us to quantify the radiation damages by determining the values of total ionizing doses and the equivalent 1 MeV electron fluences for displacement damages. Comparing the dose values to existing experimental data, we conclude that HANE-generated Sr + ions have limited darkening effects to quartz solar cell coverglasses in LEO with apogees of 100s to 1000 km. In addition, with the extremely high equivalent fluences, we also conclude that these Sr+ ions may cause severe or even fatal displacement damage to exposed solar photovoltaic (PV) cells on satellites in LEO. The radiation effects of Sr + ions are much less significant for the orbits with high apogees beyond ten thousand km. We also conducted model parameter sensitivity studies on the charge exchange cross-sections, neutral atmosphere density profiles and explosion local time positions, and the above conclusions stay unchanged. The methodology developed in this study can be extended to other HANE-generated heavy ion species in the future.

14 SOLAR ENERGY↗

Enhancing New Physics Searches with a Future Beam Dump Configuration at SBND

Accelerator-based neutrino experiments, especially those with high-intensity beams and highly capable detectors, offer a powerful and complementary method for probing new physics scenarios. The MiniBooNE experiment at Fermilab pioneered a special Booster Neutrino Beam (BNB) beam dump run and set new limits on sub-GeV dark matter. This white paper explores the physics opportunities enabled by operating the Short-Baseline Near Detector (SBND) at Fermilab in a future BNB beam dump configuration. Redirecting the proton beam away from the default target suppresses neutrino backgrounds, enabling SBND to significantly enhance sensitivity to many new physics scenarios. We evaluate two operational scenarios – off-target mode and a new dedicated beam dump mode – and demonstrate that both approaches can open new avenues in the search for physics beyond the Standard Model. We present two example cases, scalar dark matter and heavy neutral leptons via axion-like particle.

Dutta, Bhaskar [TAMU, College Station]↗

Assessing boundary condition and parametric uncertainty in numerical-weather-prediction-modeled, long-term offshore wind speed through machine learning and analog ensemble

To accurately plan and manage wind power plants, not only does the time-varying wind resource at the site of interest need to be assessed but also the uncertainty connected to this estimate. Numerical weather prediction (NWP) models at the mesoscale represent a valuable way to characterize the wind resource offshore, given the challenges connected with measuring hub-height wind speed. The boundary condition and parametric uncertainty associated with modeled wind speed is often estimated by running a model ensemble. However, creating an NWP ensemble of long-term wind resource data over a large region represents a computational challenge. Here, we propose two approaches to temporally extrapolate wind speed boundary condition and parametric uncertainty using a more convenient setup in which a mesoscale ensemble is run over a short-term period (1 year), and only a single model covers the desired long-term period (20 year). We quantify hub-height wind speed boundary condition and parametric uncertainty from the short-term model ensemble as its normalized across-ensemble standard deviation. Then, we develop and apply a gradient-boosting model and an analog ensemble approach to temporally extrapolate such uncertainty to the full 20-year period, for which only a single model run is available. As a test case, we consider offshore wind resource characterization in the California Outer Continental Shelf. Both of the proposed approaches provide accurate estimates of the long-term wind speed boundary condition and parametric uncertainty across the region (R 2 >0.75), with the gradient-boosting model slightly outperforming the analog ensemble in terms of bias and centered root-mean-square error. At the three offshore wind energy lease areas in the region, we find a long-term median hourly uncertainty between 10 % and 14 % of the mean hub-height wind speed values. Finally, we assess the physical variability in the uncertainty estimates. In general, we find that the wind speed uncertainty increases closer to land. Also, neutral conditions have smaller uncertainty than the stable and unstable cases, and the modeled wind speed in winter has less boundary condition and parametric sensitivity than summer.

17 WIND ENERGY↗

An implicit-explicit time splitting strategy for the far SOL plasma fluid model with DG-FEM discretization

We consider a far scrape-off layer (SOL) plasma fluid model of ions that is governed by a Braginskiitype model: a one-dimensional, nonlinear system of advection-diffusion equations coupled with a diffusion equation for neutral particles. Our motivation for studying this system arises from the coupling between the edge plasma and radio-frequency (RF) heating, where solving a far SOL plasma fluid model provides critical insights into edge plasma dynamics. Numerical simulations of plasma fluid models require advanced computational techniques to achieve both efficiency and accuracy, especially when resolving the boundary layer in magnetically confined plasmas. In this work, we propose an implicit-explicit time operator splitting strategy that allows for an efficient solution algorithm, where the diffusive terms are treated semi-implicitly requiring only a linear solve, while the advection part is handled explicitly using a strong-stability-preserving Runge-Kutta (SSP-RK3) scheme. This leads to a fully decoupled system in which the diffusion and advection sub-problems can be solved separately, simplifying the overall solution procedure and allowing for efficient parallelization, which is particularly relevant for exploring the impact of RF heating on the SOL plasma. The main challenge of the discretization is due to the strong coupling between diffusion and advection, particularly through the boundary conditions. This makes implementation of such a scheme in an accurate and stable manner nontrivial. We discuss in detail how to split the equations and manage boundary conditions to maintain stability and well-posedness for each subsystem. We also describe a spatial discretization approach, based on the discontinuous Galerkin finite element method (DG-FEM) and present numerical results for a one-dimensional system.

Burkovska, Olena [ORNL] (ORCID:0000000163101130)↗

A Virtual Space Vector Model Predictive Control for a Seven-Level Hybrid Multilevel Converter

This paper proposes a virtual space vector (VSV) model predictive control (MPC) for a three-phase seven-level (7L) hybrid multilevel converter (HMC), where each phase consists of an active-neutral-point-clamped converter with a floating H-bridge. To achieve the best current tracking, which is the primary goal of the proposed algorithm, a novel geometrical positioning approach is proposed to select the optimal voltage vector among all the realspace vectors and VSVs. Then, all the possible switching sequences that belong to the optimal voltage vector are evaluated to realize the dc capacitor voltage balancing and common-mode voltage reduction. Through an external modulator, the optimal voltage vector can be synthesized by using either one-, three-, or seven-segment switching sequence. Compared with the conventional MPC, the proposed VSV-MPC can reduce not only the computational burden but also the current THD. Both simulation and experimental results obtained on silicon carbide based 7L-HMC prototype are presented to validate the feasibility and effectiveness of the proposed VSVMPC strategy.

42 ENGINEERING↗

Modeling plasma-induced surface charge effects on CO 2 activation by single atom catalysts supported on reducible and irreducible metal oxides

Abstract The accumulation of negative surface charge on catalytic surfaces in the presence of low-temperature plasma (LTP) could influence catalytic performance. However, it is difficult to disentangle the role of surface charging and other LTP catalytic effects in experiment. Herein, we use density functional theory (DFT) modeling to understand the effect of plasma-induced surface charging on CO 2 activation by atomically dispersed single atom (SA) catalysts on both reducible and irreducible metal oxide supports. We model CO 2 adsorption strength and CO 2 dissociation barriers for Co 1 , Ni 1 , Cu 1 , Rh 1 , Pd 1 , and Ag 1 SAs on both reducible and irreducible supports, namely, CeO 2 (100), TiO 2 (101), and γ -Al 2 O 3 (110), to elucidate trends. We find that accumulated surface charge on the SA increases the CO 2 adsorption strength and decreases the CO 2 dissociation barrier for all studied SA/support combinations. For both charged and uncharged (neutral) systems, SAs on the reducible CeO 2 (100) support generally adsorb CO 2 more weakly compared to when on irreducible supports like γ -Al 2 O 3 (110). SAs on γ -Al 2 O 3 (110) typically have larger barriers for CO 2 dissociation for both charged and uncharged systems compared to TiO 2 (101) and CeO 2 (100). The magnitude of surface charging effects on CO 2 binding energies and dissociation barriers depends sensitively on both the SA and the support. In some cases, the CO 2 activation trends qualitatively change between neutral and charged systems for a fixed SA across different supports. This DFT modeling study demonstrates that surface charging should be considered in strong electric fields because it can have a large effect on molecule adsorption and bond-breaking on catalytic surfaces.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Utilizing Machine Learning to Improve Neutralization Potency of an HIV-1 Antibody Targeting the gp41 N-Heptad Repeat

The N-heptad repeat (NHR) of the HIV-1 gp41 prehairpin intermediate (PHI) is an attractive potential vaccine target with high sequence conservation across diverse strains. However, despite the potency of NHR-targeting peptides and clinical efficacy of the NHR-targeting entry inhibitor enfuvirtide, no potently neutralizing NHR-directed monoclonal antibodies (mAbs) nor antisera have been identified or elicited to date. The lack of potent NHR-binding mAbs both dampens enthusiasm for vaccine development efforts at this target and presents a barrier to performing passive immunization experiments with NHR-targeting antibodies. To address this challenge, we previously developed an improved variant of the NHR-directed mAb D5, called D5_AR, which is capable of neutralizing diverse tier-2 viruses. Building on that work, here we present the 2.7Å-crystal structure of D5_AR bound to NHR mimetic peptide IQN17. We then utilize protein language models and supervised machine learning to generate small (n < 100) libraries of D5_AR variants that are subsequently screened for improved neutralization potency. We identify a variant with 5-fold improved neutralization potency, D5_FI, which is the most potent NHR-directed monoclonal antibody characterized to date and exhibits broad neutralization of tier-2 and −3 pseudoviruses as well as replicating R5 and X4 challenge strains. Additionally, our work highlights the ability of protein language models to efficiently identify improved mAb variants from relatively small libraries.

Biopolymers↗

Fluid-kinetic modeling of a high power density radio frequency inductively coupled positive hydrogen ion source

High power density radio-frequency (RF) inductively coupled positive ion sources are attractive candidates for next-generation neutral beam injection (NBI) systems, where higher injected power and longer pulse lengths are desired without sacrificing source reliability. Operating at absorbed power densities of order $\gt 1~\mathrm{W\,cm}^{-3}$ places these sources in a regime with stronger gas heating, higher dissociation, and non-Maxwellian electron energy distributions. The Large Uniform Plasma for Ionizing Neutrals (LUPIN) is an RF inductively coupled plasma source designed to explore this high power density regime and to provide guidance for a positive ion source upgrade for the DIII-D NBI system. LUPIN is designed to operate at up to 20 kW of RF power at 2 MHz, coupling energy through a cylindrical quartz vessel to achieve target ion current densities of $2100\,\mathrm{A\,m}^{-2}$ . This paper presents fluid-kinetic modeling of LUPIN using the hybrid plasma equipment model where electrons are treated kinetically, and the simulations reveal that electron energy distribution function transitions from nearly Maxwellian in the core to bi-Maxwellian towards the edge. Parametric simulations investigate the effects of RF power, gas pressure, and frequency on plasma density, ion flux, and uniformity. Parametric sweeps reveal that increasing power shifts the primary ionization channel from molecular to atomic with diminishing flux gains due to skin-depth contraction and gas rarefaction. Higher frequency localizes heating and increases $\mathrm{H}_2^+$ and $\mathrm{H}_3^+$ delivery to the grid, while elevated pressure boosts ionization yet hinders ion transport due to increase in collisionality.

inductively coupled plasma↗

Nonlinear burn control in ITER using adaptive allocation of actuators with uncertain dynamics

Abstract ITER will be the first tokamak to sustain a fusion-producing, or burning, plasma. If the plasma temperature were to inadvertently rise in this burning regime, the positive correlation between temperature and the fusion reaction rate would establish a destabilizing positive feedback loop. Careful regulation of the plasma’s temperature and density, or burn control, is required to prevent these potentially reactor-damaging thermal excursions, neutralize disturbances and improve performance. In this work, a Lyapunov-based burn controller is designed using a full zero-dimensional nonlinear model. An adaptive estimator manages destabilizing uncertainties in the plasma confinement properties and the particle recycling conditions (caused by plasma–wall interactions). The controller regulates the plasma density with requests for deuterium and tritium particle injections. In ITER-like plasmas, the fusion-born alpha particles will primarily heat the plasma electrons, resulting in different electron and ion temperatures in the core. By considering separate response models for the electron and ion energies, the proposed controller can independently regulate the electron and ion temperatures by requesting that different amounts of auxiliary power be delivered to the electrons and ions. These two commands for a specific control effort (electron and ion heating) are sent to an actuator allocation module that optimally maps them to the heating actuators available to ITER: an electron cyclotron heating system (20 MW), an ion cyclotron heating system (20 MW), and two neutral beam injectors (16.5 MW each). Two different actuator allocators are presented in this work. The first actuator allocator finds the optimal mapping by solving a convex quadratic program that includes actuator saturation and rate limits. It is nonadaptive and assumes that the mapping between the commanded control efforts and the allocated actuators (i.e. the effector model) contains no uncertainties. The second actuator allocation module has an adaptive estimator to handle uncertainties in the effector model. This uncertainty includes actuator efficiencies, the fractions of neutral beam heating that are deposited into the plasma electrons and ions, and the tritium concentration of the fueling pellets. Furthermore, the adaptive allocator considers actuator dynamics (actuation lag) that contain uncertainty. This adaptive allocation algorithm is more computationally efficient than the aforementioned nonadaptive allocator because it is computed using dynamic update laws so that finding the solution to a static optimization problem is not required at every time step. A simulation study assesses the performance of the proposed adaptive burn controller augmented with each of the actuator allocation modules.

Physics↗