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At least 1,045 records · Page 58

Stellar wind impact on early atmospheres around unmagnetized Earth-like planets

ABSTRACT Stellar rotation at early ages plays a crucial role in the survival of primordial atmospheres around Earth-mass exoplanets. Earth-like planets orbiting fast-rotating stars may undergo complete photoevaporation within the first few hundred Myr driven by the enhanced stellar XUV [X-rays and extreme ultraviolet (EUV)] radiation, while planets orbiting slow-rotating stars are expected to experience difficulty in losing their primordial envelopes. Besides the action of stellar radiation, stellar winds induce additional erosion on these primordial atmospheres, altering their morphology, extent, and causing supplementary atmospheric losses. In this paper, we study the impact of activity-dependent stellar winds on primordial atmospheres to evaluate the extent to which the action of these winds can be significant in the whole planetary evolution at early evolutionary stages. We performed 3D magnetohydrodynamical (MHD) simulations of the interaction of photoevaporating atmospheres around unmagnetized Earth-mass planets in the time span between 50 and 500 Myr, analysing the joint evolution of stellar winds and atmospheres for both fast- and slow-rotating stars. Our results reveal substantial changes in the evolution of primordial atmospheres when influenced by fast-rotating stars, with a significant reduction in extent at early ages. In contrast, atmospheres embedded in the stellar winds from slow-rotating stars remain largely unaltered. The interaction of the magnetized stellar winds with the ionized upper atmospheres of these planets allows us to evaluate the formation and evolution of different MHD structures, such as double bow shocks and induced magnetospheres. This work will shed light on the first evolutionary stages of Earth-like exoplanets, which are of crucial relevance in terms of planet habitability.

Astronomy & Astrophysics↗

Microphysically modified magnetosonic modes in collisionless, high-β plasmas

With the support of hybrid-kinetic simulations and analytic theory, we describe the nonlinear behaviour of long-wavelength non-propagating (NP) modes and fast magnetosonic waves in high-β collisionless plasmas, with particular attention to their excitation of and reaction to kinetic micro-instabilities. The perpendicularly pressure balanced polarization of NP modes produces an excess of perpendicular pressure over parallel pressure in regions where the plasma β is increased. For mode amplitudes |δB/B 0 |≳0.3, this excess excites the mirror instability. Particle scattering off these micro-scale mirrors frustrates the nonlinear saturation of transit-time damping, ensuring that large-amplitude NP modes continue their decay to small amplitudes. At asymptotically large wavelengths, we predict that the mirror-induced scattering will be large enough to interrupt transit-time damping entirely, isotropizing the pressure perturbations and morphing the collisionless NP mode into the magnetohydrodynamic (MHD) entropy mode. In fast waves, a fluctuating pressure anisotropy drives both mirror and firehose instabilities when the wave amplitude satisfies |δB/B 0 |≳2β -1 . The induced particle scattering leads to delayed shock formation and MHD-like wave dynamics. Taken alongside prior work on self-interrupting Alfvén waves and self-sustaining ion-acoustic waves, our results establish a foundation for new theories of electromagnetic turbulence in low-collisionality, high-β plasmas such as the intracluster medium, radiatively inefficient accretion flows and the near-Earth solar wind.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Feedstock and Catalyst Impact on Bio-Oil Production and FCC Co-Processing to Fuels

NREL’s thermochemical biomass conversion research is focused on ex-situ upgrading of biomass fast-pyrolysis (FP) vapors as an efficient and economical route to completely biogenic pyrolysis-based fuel precursors, potential fuels, and value-added chemicals depending on catalyst choice and process conditions. In this approach, biomass vapors are generated via fast pyrolysis with destabilizing vapor components (char, inorganics, tar aerosols) removed by hot gas filtration to produce conditioned vapors more responsive to catalytic upgrading. A Davison Circulating Riser (DCR), a petroleum industry standard for fluidized catalytic cracking (FCC) catalyst evaluation, was coupled with a custom pyrolyzer system designed to produce consistent composition pyrolysis vapors as feed to the DCR. The coupled system is shown below (Figure 1). Pyrolysis vapors, derived from pure hardwood and softwood, were upgraded using commercially available and laboratory modified zeolite-based catalysts. Upgraded oils were analyzed via 31P and 13C NMR spectroscopy, GCxGC-TOF/MS, carbonyl and ultimate analysis (CHNO), and micro distillation to assess both oil chemistry and distillation behavior as they relate to catalyst and feedstock type for producing fungible hydrocarbon product liquids. Measured process parameters identified from technoeconomic process analysis included achieving oil oxygenate contents of 20% or less, carbon-conversion efficiencies of 30% or more, and catalyst coking rates of 10% or less. A proprietary modified zeolite catalyst from Johnson Matthey produced oils that met these requirements. Using the DCR equipped with a proprietary nozzle system, a second approach focused on reducing the carbon intensity of petroleum-derived hydrocarbon fuels by FCC co-processing these CFP oils with petroleum vacuum gas oil (VGO) to produce biogenic carbon containing fuels. The vapor-phase upgrading results demonstrated for the first time the feasibility of producing refinery-compatible hydrocarbon fuel intermediates entirely from biomass-derived fast-pyrolysis vapors using an industry-accepted DCR system for catalytic upgrading. The co-processing results demonstrated the feasibility of using CFP oils with VGO feeds in FCC refinery operations to produce biogenic carbon containing fuels.

bio-oil↗

Gamma Rays from Fast Black-hole Winds

We study massive black holes at the centers of galaxies that can launch powerful wide-angle winds that, if sustained over time, can unbind the gas from the stellar bulges of galaxies. These winds may be responsible for the observed scaling relation between the masses of the central black holes and the velocity dispersion of stars in galactic bulges. Propagating through the galaxy, the wind should interact with the interstellar medium creating a strong shock, similar to those observed in supernovae explosions, which is able to accelerate charged particles to high energies. In this work we use data from the Fermi Large Area Telescope to search for the γ-ray emission from galaxies with an ultrafast outflow (UFO): a fast (v ~0.1 c), highly ionized outflow, detected in absorption at hard X-rays in several nearby active galactic nuclei (AGN). Adopting a sensitive stacking analysis we are able to detect the average γ-ray emission from these galaxies and exclude that it is due to processes other than UFOs. Moreover, our analysis shows that the γ-ray luminosity scales with the AGN bolometric luminosity and that these outflows transfer ~0.04% of their mechanical power to γ-rays. Interpreting the observed γ-ray emission as produced by cosmic rays (CRs) accelerated at the shock front, we find that the γ-ray emission may attest to the onset of the wind–host interaction and that these outflows can energize charged particles up to the transition region between galactic and extragalactic CRs.

79 ASTRONOMY AND ASTROPHYSICS↗

Luminosity measurement for lead-lead collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV in 2015 and 2018 at CMS

Measurements of the luminosity delivered to the CMS experiment during the lead-lead data-taking periods in 2015 and 2018 are presented for the first time. The collisions were recorded at a nucleon-nucleon center-of-mass energy of 5.02 TeV; the 2018 data sample is three times larger than the 2015 data sample. Three subdetectors are used: the pixel luminosity telescope, the forward hadron calorimeters, and the fast beam conditions monitor. The absolute luminosity calibration is determined using the van der Meer technique that relies on transverse beam separation scans. The dominant sources of uncertainty are the transverse factorizability of the bunch density profiles and, in 2015, the difference between the results obtained using various detectors. The total uncertainty in the integrated luminosity, including the stability of the calibrated subdetector response over time, amounts to 3.0% for 2015, 1.7% for 2018, and 1.6% for the combined data sample.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Portable Soft X-Ray Diagnostics for Transformative Fusion-Energy Concepts (Final Scientific/Technical Report)

A time-gated extreme-ultraviolet spectrometer was fielded on a transformative fusion-energy device, FuZE-Q at Zap Energy, Inc. (ZEI), a sheared-flow-stabilized z-pinch. Plasma emission spectra were collected in the 5–40 nm wavelength (30–250 eV) range. This was the first time a direct-vacuum-coupled, high-voltage, deposition-sensitive diagnostic was fielded on this type of dense-plasma fusion device. To overcome the special challenges of such a coupling, a unique, highly effective implementation was developed, with fast (10-ns risetime) pulsed high-voltage electronics and a multi-stage differential pumping system. This enabled the UNR spectrometer to collect three independently timed spectra per FuZE-Q shot while also protecting sensitive internal components. Analysis of line emission identified oxygen (N-, C-, B-, Be-, Li-, and He-like O), peaking in intensity shortly after maximum current (>500 kA). Spectral databases and collisional-radiative modeling have been used to identify impurities and estimate edge-plasma temperatures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Results and lessons learned from accelerating radio frequency modeling using machine learning [slides]

The “advanced tokamak” reactor concept is a leading candidate for a steady state fusion pilot plant. An advanced tokamak (AT) sustains a majority of the required plasma current with effects resulting from maintenance of the peaked pressure at the device center. This current is augmented by auxiliary current drive sources. These auxiliary actuators may consist of neutral particle beams and/or radio frequency (RF) systems such as lower hybrid current drive (LHCD) and high harmonic fast wave (HHFW) current drive using radio and microwaves from antennas. The primary focus of this work is to develop models of RF current profile control suitable for use in integrated modeling frameworks and for real-time control in experiments. Direct physics models of RF current drive can be computationally intensive. In order to achieve predictive times appropriate for the thousands of calls needed in real-time control of experiments and for use in integrated models, we will apply modern machine learning (ML) techniques to accelerate these models and interpolate their results. To generate the fast and accurate models for use in control level algorithms and integrated modeling we need to replace present models with high dimensional interpolation of their results. We will perform additional simulations across a broader parameter range for EAST and other tokamaks in different physics regimes (Alcator C-Mod, DIII-D, WEST, CFETR, ARC, ITER) and combine them into a larger database for training and testing of the ML models. Further testing of the control level models with experimental current profile data from EAST and C-Mod tokamaks will provide additional confirmation of the control level model before integration in a tokamak control system or integrated modeling suite. ML will be used to optimize the selection of training data consisting of RF current driven at different values of density profile, temperature profile, plasma current, and wavenumber. ML will also be used to facilitate classification of current drive from these input data. The output of this effort will be a validated classifier capable of determining the current drive profiles for HHFW CD and LHCD on a mille-second timescale. This will provide a breakthrough capability enabling real-time control of RF driven current profiles in experiments including ITER ICRF and use integrated modeling frameworks requiring thousands of current profile calculations in discharge simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

On the competition between mixing rate and uniformity in a coaxial hydrodynamic focusing mixer

Fast microfluidic mixers for use with line-of-sight integrating detection schemes pose unique challenges. Such detectors typically cannot discriminate signal from slow moving (e.g. near internal walls) and fast-moving portions of the fluid stream. This convolves reaction rate dynamics with fluid flow residence time dynamics. Further, the small cross sections of typical three-dimensional hydrodynamic focusing devices lead to lower detection signals. The current study focuses on achieving both small time scales of mixing and homogenous residence times. This is achieved by injecting sample through a center capillary and hydrodynamically focusing using a sheath flow within a tapered second capillary. The current design also features a third, larger coaxial capillary. The mixed stream flows into the large cross-section of this third capillary to decelerate and expand the stream by up to 14-fold to improve line-of-sight signal strength of reaction products. Hydrodynamic focusing, mixing, and expansion are studied using analytical and numerical models and also studied experimentally using a fluorescein-iodide quenching reaction. The experimentally validated models are used to explore trade-offs between mixing rate and uniformity. For the first time, this work presents detailed analysis of the Lagrangian time history of species transport during mixing inside coaxial capillaries to measure mixing nonuniformity. The mixing region enables order 100 μs mixing times and residence time widths of the same order (140 μs).

42 ENGINEERING↗

Diffused trenches for high fill-factor Low-Gain Avalanche Diodes

Low-Gain Avalanche Diodes (LGADs) are a class of silicon detectors that have been specifically designed for the fast detection of minimum ionizing particles (mips) in High-Energy Physics experiments. While they provide timing resolution on the order of a few tens of picoseconds, they cannot achieve high spatial resolution due to the intrinsic characteristics of their structures. Thus, active R&D is on-going to develop detectors based on LGADs to improve their spatial resolution while maintaining the timing performance of the LGADs. Such devices are, for example, AC-coupled LGADs and Deep-Junction LGADs. Another device option is the Trench-Isolated LGAD (TI LGAD), where trenches etched at the periphery of the pixels isolate them while providing a high fill-factor. Here, in this paper, we present a variation of this latter approach, demonstrating its feasibility by means of 2-dimensional TCAD simulations.

47 OTHER INSTRUMENTATION↗

Active learning of reactive Bayesian force fields applied to heterogeneous catalysis dynamics of H/Pt

Abstract Atomistic modeling of chemically reactive systems has so far relied on either expensive ab initio methods or bond-order force fields requiring arduous parametrization. Here, we describe a Bayesian active learning framework for autonomous “on-the-fly” training of fast and accurate reactive many-body force fields during molecular dynamics simulations. At each time-step, predictive uncertainties of a sparse Gaussian process are evaluated to automatically determine whether additional ab initio training data are needed. We introduce a general method for mapping trained kernel models onto equivalent polynomial models whose prediction cost is much lower and independent of the training set size. As a demonstration, we perform direct two-phase simulations of heterogeneous H 2 turnover on the Pt(111) catalyst surface at chemical accuracy. The model trains itself in three days and performs at twice the speed of a ReaxFF model, while maintaining much higher fidelity to DFT and excellent agreement with experiment.

42 ENGINEERING↗

Once in a blue stream: Detection of recent star formation in the NGC 7241 stellar stream with MEGARA

Aims.In this work we study the striking case of a narrow blue stream with a possible globular cluster-like progenitor around the NGC 7241 galaxy and its foreground dwarf companion. We want to figure out if the stream was generated by tidal interaction with NGC 7241 or if it first interacted with the foreground dwarf companion and later both fell together toward NGC 7241. Methods.We used four sets of observations, including a follow-up spectroscopic study of this stream based on data taken with the MEGARA instrument at the 10.4 m Gran Telescopio Canarias using the integral field spectroscopy mode, the Mount Lemmon 0.80 m telescope, the Telescopio NazionaleGalileo, the DESI Imaging Legacy surveys, and GALEX archival data. We also used high-resolution zoomed-in cosmological simulations. Results.Our data suggest that the compact object we detected in the stream is a foreground Milky Way halo star. Near this compact object we detect emission lines overlapping a less compact, bluer, and fainter blob of the stream that is clearly visible in both ultraviolet and optical deep images. From its heliocentric systemic radial velocity derived from the [O III]λ5007 Å lines (V syst = 1548.58 ± 1.80 km s −1 ) and new UV and optical broadband photometry, we conclude that this overdensity could be the actual core of the stream, with an absolute magnitude ofM g ∼ −10 and ag − r = 0.08 ± 0.11, consistent with a remnant of a low-mass dwarf satellite undergoing a current episode of star formation. From the width of the stream and assuming a circular orbit, we calculate that the progenitor mass can be typical of a dwarf galaxy, but it could also be substantially lower if the stream is on a very radial orbit or if it was created by tidal interaction with the companion dwarf instead of with NGC 7241. These estimates also suggest that this is one of the lowest mass streams detected to date beyond the Local Group. Finally, we find that blue stellar streams containing star formation regions are commonly predicted by high-resolution cosmological simulations of galaxies lighter than the Milky Way. This scenario is consistent with the processes explaining the bursty star formation history of some dwarf satellites, which are followed by a gas depletion and a fast quenching once they enter within the virial radius of their host galaxies for the first time. Thus, it is likely that the stream’s progenitor is undergoing a star formation burst comparable to those that have shaped the star formation history of several Local Group dwarfs in the last few gigayears.

Astronomy & Astrophysics↗

High-resolution in-beam video rate imaging with the ClearXCam for synchrotron beamlines

The ClearXCam detector is a new video rate imaging in-beam monitor based on a diamond sensor. Imaging with 2304 effective pixels is achieved by sequentially biasing one of 48 metal stripes on one side of a diamond sensor, while reading out the current from 48 stripes on the other side of the sensor. This system was characterized for real-time X-ray beam diagnostics at synchrotron beam­line 17-BM at the National Synchrotron Light Source II. Significant results include: detection of in-beam structure via the imaging mode, beam focusing in one minute with real-time imaging feedback during a focusing event, linearity over five orders of magnitude, validation of a fast mode operating at 100 Hz, and sub-micron beam-positioning resolution. The system is now available commercially.

36 MATERIALS SCIENCE↗

Optimizing Grid Regulation With Gravity Storage Systems: A Comparative Analysis With Different Motor Inertias

The integration of renewable energy sources into power grids necessitates solutions for grid support and stability during fluctuations in electricity generation and demand. Gravity energy storage systems (GESS) are emerging as a promising technology for managing the balance between energy supply and demand. However, their capacity to optimize energy flow and offer voltage and frequency regulation amid imbalances in generation and demand is less reported. This paper investigates the control of GESS for optimizing energy flow during voltage and frequency regulation. The study evaluates the regulation capabilities of GESS with different motor inertias during a Texas grid event: one with a high-speed, low-inertia motor and another with a low-speed, high-inertia motor. Results indicate that both GESS scenarios provide fast frequency response by converting potential energy into kinetic energy and vice versa, with a response time of 1.5 s from the frequency variation. This aligns with grid requirements for primary frequency response from traditional synchronous generators and motors with large inertia. Furthermore, a GESS based on a high-inertia motor may be able to operate over a broader range of frequency variations, whereas a low-inertia system may be limited by thermal constraints of the motor.

frequency regulation↗

Optimizing Error-Bounded Lossy Compression for Scientific Data by Dynamic Spline Interpolation

Today's scientific simulations are producing vast volumes of data that cannot be stored and transferred efficiently because of limited storage capacity, parallel I/O bandwidth, and network bandwidth. The situation is getting worse over time because of the ever-increasing gap between relatively slow data transfer speed and fast-growing computation power in modern supercomputers. Error-bounded lossy compression is becoming one of the most critical techniques for resolving the big scientific data issue, in that it can significantly reduce the scientific data volume while guaranteeing that the reconstructed data is valid for users because of its compression-error-bounding feature. In this paper, we present a novel error-bounded lossy compressor based on a state-of-the-art prediction-based compression framework. Our solution exhibits substantially better compression quality than all of the existing error-bounded lossy compressors, with comparable compression speed. Specifically, our contribution is threefold. (1) We provide an in-depth analysis of why the best-existing prediction-based lossy compressor can only minimally improve the compression quality. (2) We propose a dynamic spline interpolation approach with a series of optimization strategies that can significantly improve the data prediction accuracy, substantially improving the compression quality in turn. (3) We perform a thorough evaluation using six real-world scientific simulation datasets across different science domains to evaluate our solution vs. all other related works. Experiments show that the compression ratio of our solution is higher than that of the second-best lossy compressor by 20%similar to 460% with the same error bound in most of the cases.

Zhao, Kai↗

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We suggest a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118-and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Probing-Based Inertia Estimation Method Using Hybrid Power Plants

With the displacement of synchronous generation by inverter-based resources (IBRs), power systems could face the challenge of reduced inertia since IBRs do not inherently contribute to system inertia. Therefore, there is rising interest in monitoring system inertia in real-time applications for situational awareness. In addition, there is a growing number of IBRs that provide fast frequency responses (FFR) in the form of synthetic inertia and P-f droop. It is desirable to quantify the contribution of these FFR controls as equivalent inertia. This paper proposes a probing-based inertia estimation method using a PV-battery hybrid power plant in the Kauai island power system. The method is validated under different operating conditions.

hybrid power plant↗

Development of Strong Anaerobic Fluorescent Reporters for Clostridium acetobutylicum and Clostridium ljungdahlii Using HaloTag and SNAP-tag Proteins

One of the biggest limitations in the study and engineering of anaerobic Clostridium organisms is the lack of strong fluorescent reporters capable of strong and real-time fluorescence. Recently, we developed a strong fluorescent reporter system for Clostridium organisms based on the FAST protein. Here, we report the development of two new strong fluorescent reporter systems for Clostridium organisms based on the HaloTag and SNAP-tag proteins, which produce strong fluorescent signals when covalently bound to fluorogenic ligands. These new fluorescent reporters are orthogonal to the FAST ligands and to each other, allowing for simultaneous labeling and visualization. We used HaloTag and SNAP-tag to label the strictly anaerobic organisms Clostridium acetobutylicum and Clostridium ljungdahlii. We have also identified a new strong promoter for protein expression in C. acetobutylicum, based on the phosphotransacetylase gene (pta) from C. ljungdahlii. Furthermore, the HaloTag and the SNAP-tag, in combination with the previously described FAST system, were successfully used to measure cell populations in bacterial mixed cultures and showed the simultaneous orthogonal labeling of HaloTag and SNAP-tag together with the FAST protein reporter. Finally, we show the expression of recombinant fusion protein of FAST and the ZapA division protein (from C. acetobutylicum) in C. ljungdahlii. The availability of multiple strong fluorescent reporters is a major addition to the genetic toolkit of Here, Clostridium and other anaerobes that will lead to better understanding of these unique organisms.

59 BASIC BIOLOGICAL SCIENCES↗

Swab Testing Results

1. All 3D printed swabs bend to at least 90° without breaking. 2. All 3D printed swabs are at least as strong under tensile testing as their commercial counterparts. a. The Abiogenix FAST Spiral NP and EnvisionTEC swabs retain their tensile strength after sterilization and after 7 days of aging. b. For the Formlabs swabs, steam sterilization significantly reduces their tensile strength, which mostly recovers after 7 days of aging. However, the swabs are stronger than commercial ones at all times. c. The Resolution Medical Lattice swabs retain their tensile strength after 5 days of aging. Five different swab types were tested: 1. Abiogenix FAST Spiral NP Swab; 2. Formlabs NP Swab; 3. EnvisionTEC NP Swab; 4. Resolution Medical Lattice Swab; and 5. Fosun Pharma NP Swab The Abiogenix FAST Spiral NP, EnvisionTEC NP, Resolution Medical Lattice, and Fosun Pharma NP swabs were provided by their respective suppliers. The Formlabs NP swabs were printed at LLNL using the Form 3B Printer and Formlabs Surgical Guide resin

59 BASIC BIOLOGICAL SCIENCES↗