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At least 109 records · Page 6

Observations of Binary Stars with the Differential Speckle Survey Instrument. IX. Observations of Known and Suspected Binaries, and a Partial Survey of Be Stars

We report 370 measures of 170 components of binary and multiple-star systems, obtained from speckle imaging observations made with the Differential Speckle Survey Instrument at Lowell Observatory’s Discovery Channel Telescope in 2015 through 2017. Of the systems studied, 147 are binary stars, 10 are seen as triple systems, and 1 quadruple system is measured. Seventy-six high-quality nondetections and 15 newly resolved components are presented in our observations. The uncertainty in relative astrometry appears to be similar to our previous work at Lowell, namely, linear measurement uncertainties of approximately 2 mas, and the relative photometry appears to be uncertain at the 0.1–0.15 mag level. Using these measures and those in the literature, we calculate six new visual orbits, including one for the Be star 66 Oph and two combined spectroscopic–visual orbits. The latter two orbits, which are for HD 22451 (YSC 127) and HD 185501 (YSC 135), yield individual masses of the components at the level of 2% or better, and independent distance measures that in one case agrees with the value found in the Gaia DR2 and in the other disagrees at the 2σ level. We find that HD 22451 consists of an F6V+F7V pair with orbital period of 2401.1 ± 3.2 days and masses of 1.342 ± 0.029 and 1.236±0.026 M{sub ⊙}. For HD 185501, both stars are G5 dwarfs that orbit one another with a period of 433.94 ± 0.15 days, and the masses are 0.898 ± 0.012 and 0.876±0.012 M{sub ⊙}. We discuss the details of both the new discoveries and the orbit objects.

79 ASTRONOMY AND ASTROPHYSICS↗

Data Assimilation with Machine Learning Surrogate Models: A Case Study with FourCastNet

Modern data-driven surrogate models for weather forecasting provide accurate short-term predictions but inaccurate and nonphysical long-term forecasts. This paper investigates online weather prediction using machine learning surrogates supplemented with partial and noisy observations. We empirically demonstrate and theoretically justify that, despite the long-time instability of the surrogates and the sparsity of the observations, filtering estimates can remain accurate in the long-time horizon. As a case study, we integrate FourCastNet, a weather surrogate model, within a variational data assimilation framework using partial, noisy ERA5 data. Our results show that filtering estimates remain accurate over a year-long assimilation window and provide effective initial conditions for forecasting tasks, including extreme event prediction.

Adrian, Melissa [Univ. of Chicago, IL (United Stat↗

Full fluid moment modeling of rotating spokes in Penning-type configuration

Rotating spokes are observed in a partially magnetized plasma using a two-dimensional full fluid moment (FFM) model. In the present setup, where the radial electric field and plasma density gradient exist in opposite directions, it is observed that the spokes propagate in the direction of the diamagnetic drift and not the E × B drift. This is contrary to the modified Simon–Hoh instability, and the results suggest that the spokes can be driven by a strong diamagnetic drift. Different parameters, including magnetic field amplitude and physical domain size, influence the growth of the rotational instability as well as the dominant wave modes that arise. Furthermore, the propagation speed of the rotating spokes obtained from the FFM simulation are in good agreement with the observations in experimental and other computational work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data Assimilation with Machine Learning Surrogate Models: A Case Study with FourCastNet

Modern data-driven surrogate models for weather forecasting provide accurate short-term predictions but inaccurate and nonphysical long-term forecasts. This paper investigates online weather prediction using machine learning surrogates supplemented with partial and noisy observations. We empirically demonstrate and theoretically justify that, despite the long-time instability of the surrogates and the sparsity of the observations, filtering estimates can remain accurate in the long-time horizon. As a case study, we integrate the Fourier Forecasting Neural Network (FourCastNet), a weather surrogate model, within a variational data assimilation framework using partial, noisy ERA5 global reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Here, our results show that filtering estimates remain accurate over a year-long assimilation window and provide effective initial conditions for forecasting tasks, including extreme event prediction.

Data assimilation↗

Dynamic domain kinematic modelling for predicting interflow over leaky impeding layers

Traditional Boussinesq or kinematic simulations of interflow (i.e., lateral subsurface flow) assume no leakage through the impeding layer and require a no-flow boundary condition at the ridge top. However, recent analyses of many interflow-producing landscapes indicate that leaky impeding layers are common, that most interflow percolates well before reaching the toe slope, and therefore, the downslope contributing length is shorter than the hillslope length. In watersheds characterised by perched interflow over a low conductivity layer through permeable topsoil, interflow with percolation may be modelled with a kinematic wave model using a mobile upslope boundary condition defining the hillslope portion contributing interflow to valleys. Here, we developed and applied a dynamic interflow model to simulate interflow using a downslope travel distance concept such that only the active contributing length is modelled at any time. The model defines a variable active area based on the depth of the perched layer, the topographic slope and the ratio of the hydraulic conductivity of topsoil to that of the impeding layer. It incorporates a two-layer soil moisture accounting water balance analysis, a pedo-transfer function, and percolation and evaporation routines to predict interflow rates in continuous and event-based scenarios. We tested the modelling concept on two sets of data (2-year dataset of rainfall observations for the continuous simulation and a multi-day irrigation experiment for the event simulation) from a 121-m-long open interflow collection trench on an experimental hillslope at the Savannah River Site, South Carolina. The continuous model simulation partially represented the observed interflow hydrograph and perched water depth in the experimental hillslope with correlation coefficients of 0.85 and 0.35, respectively. Model performance improved significantly at event-scale analysis. The modelling approach realistically represents interflow dynamics in hillslopes with leaky impeding layers and can be integrated into catchment-scale hydrology models for more detailed hillslope process modelling.

54 ENVIRONMENTAL SCIENCES↗

Molecular Simulation of Lithium Carbonate Reactive Vapor–Liquid Equilibria Using a Deep Potential Model

We developed a first-principles machine learning model for the reactive vapor–liquid phase behavior of molten Li 2 CO 3 . The model was trained on ab initio electronic density functional theory data using the Deep Potential (DP) methodology, and its accuracy was evaluated by comparing model predictions of density and viscosity to experimental measurements. Direct coexistence simulations with the DP model over time scales of tens of nanoseconds were used to observe equilibrium dissociation of Li 2 CO 3 into CO 2 residing primarily in the vapor phase and Li 2 O which remains dissolved in the liquid. The simulations covered a range of temperatures, overall system sizes, and vapor-to-liquid volume ratios. Results were analyzed in terms of the observed chemical composition of the liquid and vapor phases, product structure, and CO 2 partial pressures. In addition, we calculated equilibrium constants for the dissociation reaction by assuming ideal-solution behavior for the liquid. As expected on the basis of thermodynamic arguments and prior experiments for this system, the observed partial pressure of CO 2 in the gas phase depends on both the temperature and the ratio of vapor to liquid volumes, while the calculated equilibrium constants only depend on temperature. DP model predictions for the equilibrium constant of the reaction are generally consistent with the available experimental measurements. Furthermore, the present study establishes the validity of the DP methodology for the description of reactive, multiphase equilibria from first principles, with possible applications to many other systems of scientific and technological interest even in the absence of relevant experimental measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal–Organic Frameworks

Computational high-throughput screening using molecular simulations is a powerful tool for identifying top-performing metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges are often required to model the electrostatic interactions between the MOF and the adsorbate, especially when the adsorption involves molecules with dipole or quadrupole moments such as water and CO 2 . Although ab initio methods can be used to calculate accurate partial atomic charges, these methods are impractical for screening large material databases because of the high computational cost. We developed a random forest machine learning model to predict the partial atomic charges in MOFs using a small yet meaningful set of features that represent both the elemental properties and the local environment of each atom. The model was trained and tested on a collection of about 320 000 density-derived electrostatic and chemical (DDEC) atomic charges calculated on a subset of the Computation-Ready Experimental Metal–Organic Framework (CoRE MOF-2019) database and separately on charge model 5 (CM5) charges. The model predicts accurate atomic charges for MOFs at a fraction of the computational cost of periodic density functional theory (DFT) and is found to be transferable to other porous molecular crystals and zeolites. In conclusion, a strong correlation is observed between the partial atomic charge and the average electronegativity difference between the central atom and its bonded neighbors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermodynamic and kinematic drivers of atmospheric boundary layer stability in the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)

Observations collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) provide a detailed description of the impact of thermodynamic and kinematic forcings on atmospheric boundary layer (ABL) stability in the central Arctic. This study reveals that the Arctic ABL is stable and near-neutral with similar frequencies, and strong stability is the most persistent of all stability regimes. MOSAiC radiosonde observations, in conjunction with observations from additional measurement platforms, including a 10 m meteorological tower, ceilometer, microwave radiometer, and radiation station, provide insight into the relationships between atmospheric stability and various atmospheric thermodynamic and kinematic forcings of ABL turbulence and how these relationships differ by season. We found that stronger stability largely occurs in low-wind (i.e., wind speeds are slow), low-radiation (i.e., surface radiative fluxes are minimal) environments; a very shallow mixed ABL forms in low-wind, high-radiation environments; weak stability occurs in high-wind, moderate-radiation environments; and a near-neutral ABL forms in high-wind, high-radiation environments. Surface pressure (a proxy for synoptic staging) partially explains the observed wind speeds for different stability regimes. Cloud frequency and atmospheric moisture contribute to the observed surface radiation budget. Unique to summer, stronger stability may also form when moist air is advected from over the warmer open ocean to over the colder sea ice surface, which decouples the colder near-surface atmosphere from the advected layer, and is identifiable through observations of fog and atmospheric moisture.

54 ENVIRONMENTAL SCIENCES↗

Impact of amorphous pockets on displacement damage evolution in silicon

Silicon has long been known to exhibit amorphization in response to heavy particle bombardment. For doses below the total amorphization threshold, partial amorphization is observed in the form of scattered amorphous pockets. While extensive research has gone into modeling the formation and evolution of amorphous pockets in response to irradiation, no studies yet investigate their impact on the evolution of other damage such as interstitial supersaturation and clustering. In this study, we survey the impact of amorphous pockets on defect evolution in silicon when treated as static sinks. MD is first used to show that amorphous pockets provide energetically favorable sites for point defects relative to the crystalline bulk, supporting the hypothesis that they act as sinks. A 0-D cluster dynamics model is then constructed, taking an interstitial clustering model from the literature and including amorphous pockets as a sink species. We conduct our survey for temperatures between 30 and 400 °C and sink strengths between 1 to 6 x 10 10 cm −2 . Both implantation- and radiation-induced damage states are investigated using interstitial and vacancy concentrations as initial condition variables. We find that, due to the differing migration rates of the interstitial and the vacancy, amorphous pockets have a non-monotonic impact on the final damage state depending on the effective sink strength of the amorphous pockets, resulting in increased damage formation in regimes of intermediate amorphization. In conclusion, this result emphasizes the important role of amorphous pockets in governing the evolution of damage in partially amorphized crystalline materials.

36 MATERIALS SCIENCE↗

Characterization of Partial Charge Collection Induced by Neutron Damage in High-Purity Germanium Detectors

This paper investigates the correlation of damage induced by neutron interactions and degradation in the spectra of HPGe detectors. As neutrons kinetically interact with germanium crystals, they create interstitial and vacancy defects within the lattice. These defects then interfere with the charge migration of electron-hole pairs and reduce resolution in the observed energy spectrum. The partial charge collection produces observable spectral changes by increasing the peak width and reducing resolution (full width half maximum). A detailed characterization using various check sources was performed before and after iterations of neutron exposure in order to observe the effects of the neutron damage. An additional set of measurements was performed along with characterizations to show the detector’s response at discrete locations on the HPGe crystal. This was done to observe how the spectrum changes when the gamma rays are isolated to regions of various thicknesses of germanium. In order to impart damage, the detector was placed inside a californium shuffler with the face of the detector against the guide tube for the 252 Cf source. For irradiation of the HPGe, the source was then positioned in front of the face of the detector using the stepper motor of the shuffler. The neutron exposure time intervals were recorded and increased based on the initial damage observed. An MCNP simulation was performed to estimate the amount of interactions that occurred in the germanium crystal to ensure enough damage had occurred. Studying the effects that neutron damage imparts on a bullet-type HPGe detector can help provide necessary data to estimate total neutron exposure limits, reduce the likelihood of decisions made on suspect data, and aid in diagnostics of a damaged detector.

36 MATERIALS SCIENCE↗

High-resolution absorption spectroscopy of room-temperature and jet-cooled ammonia between 59,000 and 93,000 cm -1

Here, we present new high-resolution photoabsorption spectra of ammonia spanning the region between 59,000 cm -1 and 93,000 cm -1 that were recorded by using the Fourier Transform Spectrometer at the Synchrotron SOLEIL. This region extends from just above the Franck-Condon envelope for the $\tilde{A}$ 1 $A$ 2 " ← $\tilde{X}$ 1 $A$ 1 ' transition to well above the NH 3 + $\tilde{X}$ + 2 $A$ 2 " ionization threshold. The spectra were recorded at a measured resolution of 0.23 cm -1 in both a room-temperature cell (293 K) and in a slit-jet supersonic expansion (~70 K). The absolute photoabsorption cross section with an uncertainty of ±5% is also reported for the room-temperature spectrum. The present resolution is a factor of 10 – 100 times higher than in other recently reported broad band spectra of ammonia, and many of the observed bands show partially resolved rotational structure. We have attempted to assign this structure for a number of these bands. The oscillator strengths extracted from the data are in good agreement with previous measurements but, in the case of structured bands, the present higher resolution measurements return higher peak absorption cross sections, that increase further when the sample is cooled. The present higher resolution spectra suggest that a number of previous vibronic band assignments that were based on quantum defect considerations may require some revision. Finally, we discuss the substantial differences between the photoabsorption and photoionization data just above the first ionization threshold.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

New Evidence for the Importance of Non-Stomatal Pathways in Ozone Deposition During Extreme Heat and Dry Anomalies

Dry deposition could partially explain the observed response in ambient ozone to extreme hot and dry episodes. We examine the response of ozone deposition to heat and dry anomalies using three long-term co-located ecosystem-scale carbon dioxide, water vapor and ozone flux measurement records. We find that, as expected, canopy stomatal conductance generally decreases during days with dry air or soil. However, during hot days, concurrent increases in non-stomatal conductance are inferred at all three sites, which may be related to several temperature-sensitive processes not represented in the current generation of big-leaf models. This may offset the reduction in stomatal conductance, leading to smaller net reduction, or even net increase, in total deposition velocity. We find the response of deposition velocity to soil dryness may be related to its impact on photosynthetic activity, though considerable variability exists. Our findings emphasize the need for better understanding and representation of non-stomatal ozone deposition.

54 ENVIRONMENTAL SCIENCES↗

Liquid state properties and solidification features of the pseudo binary BaS-La 2 S 3

The high temperature thermodynamic properties of chalcogenides materials based on BaS remain elusive. Herein the pseudo binary BaS-La 2 S 3 is investigated above 1573 K. The liquid properties of BaS-La 2 S 3 are measured by means of high resolution in-situ visualization coupled with thermal arrest measurements in a thermal imaging furnace. This enables to report the first observation of such melts in a container-less setting. The melting points of BaS and La 2 S 3 are revisited at 2454 K and 2004 K respectively. La 2 S 3 demonstrates a high stability in its liquid state, in strike difference with the sublimation observed for BaS. BaS is however partially stabilized with the addition of few percents of La 2 S 3 . The remarkable chemical and thermal stability of La 2 S 3 -rich samples contrasts with the partial decomposition and high vapor pressure observed for BaS-rich samples. Observations and analysis of the solidified samples suggest three different solid solutions. Solid and liquid densities are investigated along the different compositions, supporting a first estimate of the volumetric thermal expansion coefficient for La 2 S 3 .

36 MATERIALS SCIENCE↗

Sputtered ferroelectric aluminum scandium boron nitride (Al 1−x−y B x Sc y N)/ n -GaN heterostructures

This work demonstrates ferroelectric switching in magnetron sputtered Al 1−x−y B x Sc y N/ n -GaN heterostructures. Using high power impulse magnetron sputtering, a silicon doped n -GaN bottom electrode with an electron concentration of 6.0 × 10 19 cm −3 is grown on c-plane sapphire. Al 1−x−y B x Sc y N films are prepared on the GaN surface with Al:B:Sc ratios that produce tensile, lattice matched, or compressive epitaxial strains. X-ray diffraction shows that lattice matched and compressively strained Al 1−x−y B x Sc y N compositions are pseudomorphic, while partial relaxation is observed for tensilely strained Al 1−x−y B x Sc y N/ n -GaN heterostructures. Electrically, the Al 1−x−y B x Sc y N/ n -GaN stacks show robust hysteresis; the P–E loops are fully saturated with both lattice matched and compressively strained Al 1−x−y B x Sc y N compositions exhibiting remanent polarization values of 135 μC/cm 2 . For comparison, Al 1−x−y B x Sc y N films are also prepared on metal organic chemical vapor deposition and single crystal GaN substrates to extend strain and morphology trends to more common substrate types. This report validates that sputter deposition is a feasible technique for fabricating strain-tunable ferroelectric III–N heterostructures with high crystalline fidelity and smooth surface morphologies.

42 ENGINEERING↗

Electrical breakdown dynamics in an argon bubble submerged in conductive liquid for nanosecond pulsed discharges

Abstract This study delves into the dynamics of cold atmospheric plasma and their interaction within conductive solutions under the unique conditions of nanosecond pulsed discharges (22 kV peak voltage, 10 ns FWHM, 4.5 kV ns −1 rate-of-rise). The research focuses on the electrical response, breakdown, and discharge propagation in an argon bubble, submerged in a NaCl solution of varying conductivity. Full or partial discharges were observed at conductivities of 1.5 µ S cm −1 (deionized water) to 1.6 mS cm −1 , but no breakdown was observed at 11.0 mS cm −1 when reducing the electrode gap. It is demonstrated that at higher conductivity electric breakdown is observed only when the gas bubble comes into direct contact with the electrode and multiple emission nodes were observed at different timescales. These nodes expanded in the central region of the bubble over timescales longer than the initial high-voltage pulse. This work offers a temporal resolution of 2 ns exposure times over the first 30 ns of the initial voltage pulse, and insight into plasma formation over decaying reflected voltage oscillations over 200 ns.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Microbiome-enabled genomic selection improves prediction accuracy for nitrogen-related traits in maize

Root-associated microbiomes in the rhizosphere (rhizobiomes) are increasingly known to play an important role in nutrient acquisition, stress tolerance, and disease resistance of plants. However, it remains largely unclear to what extent these rhizobiomes contribute to trait variation for different genotypes and if their inclusion in the genomic selection protocol can enhance prediction accuracy. To address these questions, we developed a microbiome-enabled genomic selection method that incorporated host SNPs and amplicon sequence variants from plant rhizobiomes in a maize diversity panel under high and low nitrogen (N) field conditions. Our cross-validation results showed that the microbiome-enabled genomic selection model significantly outperformed the conventional genomic selection model for nearly all time-series traits related to plant growth and N responses, with an average relative improvement of 3.7%. The improvement was more pronounced under low N conditions (8.4–40.2% of relative improvement), consistent with the view that some beneficial microbes can enhance N nutrient uptake, particularly in low N fields. However, our study could not definitively rule out the possibility that the observed improvement is partially due to the amplicon sequence variants being influenced by microenvironments. Using a high-dimensional mediation analysis method, our study has also identified microbial mediators that establish a link between plant genotype and phenotype. Some of the detected mediator microbes were previously reported to promote plant growth. The enhanced prediction accuracy of the microbiome-enabled genomic selection models, demonstrated in a single environment, serves as a proof-of-concept for the potential application of microbiome-enabled plant breeding for sustainable agriculture.

60 APPLIED LIFE SCIENCES↗

Quasi-two-dimensional ferromagnetism and anisotropic interlayer couplings in the magnetic topological insulator MnBi 2 Te 4

MnBi 2 Te 4 (MBT) is a promising van der Waals layered antiferromagnetic (AFM) topological insulator that combines a topologically nontrivial inverted Bi-Te band gap with ferromagnetic (FM) layers of Mn ions. Here, the inelastic neutron scattering on single crystals reported here describes rather complex magnetism in MBT. The magnetic anisotropy that controls the bulk and surface magnetic field response of MBT is found to have contributions from both single-ion and interlayer two-ion terms. A description of the quasi-two-dimensional intralayer FM spin waves requires long-range, competing FM and AFM interactions and anomalous damping. While this might suggest carrier-mediated magnetic coupling, abinitio calculations in insulating MBT also find long-range interactions, and classical spin dynamics simulations suggest that magnetic vacancies are at least partially responsible for observations of anomalous damping near the zone boundary.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Insulators at fractional fillings in twisted bilayer graphene partially aligned to hexagonal boron nitride

At partial fillings of its flat electronic bands, magic-angle twisted bilayer graphene (MATBG) hosts a rich variety of competing correlated phases that show sample-to-sample variations. Divergent phase diagrams in MATBG are often attributed to the sublattice polarization energy scale, tuned by the degree of alignment of the hexagonal boron nitride (hBN) substrates typically used in van der Waals devices. Unaligned MATBG exhibits unconventional superconductor and correlated insulator phases, while nearly perfectly aligned MATBG/hBN exhibits zero-field Chern insulating phases and lacks superconductivity. Here we use scanning tunneling microscopy and spectroscopy (STM/STS) to observe gapped phases at partial fillings of the flat bands of MATBG in a new intermediate regime of sublattice polarization, observed when MATBG is only partially aligned (θ Gr-hBN ≈ 1.65°) to the underlying hBN substrate. Under this condition, MATBG hosts not only phenomena that naturally interpolate between the two sublattice potential limits, but also unexpected gapped phases absent in either of these limits. At charge neutrality, we observe an insulating phase with a small energy gap (Δ < 5 meV) likely related to weak sublattice symmetry breaking from the hBN substrate. In addition, we observe new gapped phases near fractional fillings ν = ±1/3 and ν = ±1/6, which have not been previously observed in MATBG. Importantly, energy-resolved STS unambiguously identifies these fractional filling states to be of single-particle origin, possibly a result of the super-superlattice formed by two moiré superlattices. Finally, our observations emphasize the power of STS in distinguishing single-particle gapped phases from many-body gapped phases in situations that could be easily confused in electrical transport measurements, and demonstrate the use of substrate engineering for modifying the electronic structure of a moiré flat-band material.

Physics↗