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At least 757 records · Page 42

X-ray emission from a rapidly accreting narrow-line Seyfert 1 galaxy at z = 6.56

The space density of X-ray-luminous, blindly selected active galactic nuclei (AGN) traces the population of rapidly accreting super-massive black holes through cosmic time. It is encoded in the X-ray luminosity function, whose bright end remains poorly constrained in the first billion years after the Big Bang as X-ray surveys have thus far lacked the required cosmological volume. With the eROSITA Final Equatorial-Depth Survey (eFEDS), the largest contiguous and homogeneous X-ray survey to date, X-ray AGN population studies can now be extended to new regions of the luminosity–redshift space (L 2 - 10 keV > 10 45 erg s -1 and z > 6). The current study aims at identifying luminous quasars at z > 5.7 among X-ray-selected sources in the eFEDS field in order to place a lower limit on black hole accretion well into the epoch of re-ionisation. A secondary goal is the characterisation of the physical properties of these extreme coronal emitters at high redshifts. Cross-matching eFEDS catalogue sources to optical counterparts from the DESI Legacy Imaging Surveys, we confirm the low significance detection with eROSITA of a previously known, optically faint z = 6.56 quasar from the Subaru High-z Exploration of Low-luminosity Quasars (SHELLQs) survey. We obtained a pointed follow-up observation of the source with the Chandra X-ray telescope in order to confirm the low-significance eROSITA detection. Using new near-infrared spectroscopy, we derived the physical properties of the super-massive black hole. Finally, we used this detection to infer a lower limit on the black hole accretion density rate at z > 6. The Chandra observation confirms the eFEDS source as the most distant blind X-ray detection to date. The derived X-ray luminosity is high with respect to the rest-frame optical emission of the quasar. With a narrow MgII line, low derived black hole mass, and high Eddington ratio, as well as its steep photon index, the source shows properties that are similar to local narrow-line Seyfert 1 galaxies, which are thought to be powered by young super-massive black holes. In combination with a previous high-redshift quasar detection in the field, we show that quasars with L 2 - 10 keV > 10 45 erg s -1 dominate accretion onto super-massive black holes at z ~ 6.

79 ASTRONOMY AND ASTROPHYSICS↗

Discovery of the luminous X-ray ignition eRASSt J234402.9-352640: I. Tidal disruption event or a rapid increase in accretion in an active galactic nucleus?

In November 2020, a new, bright object, eRASSt J234402.9-352640, was discovered in the second all-sky survey of SRG/eROSITA. The object brightened by a factor of at least 150 in 0.2–2.0 keV flux compared to an upper limit found six months previous, reaching an observed peak of 1.76 -0.24 +0.03 × 10 -11 erg cm -2 s -1 . The X-ray ignition is associated with a galaxy at z = 0.10, making the peak luminosity log 10 (L 0.2-2 keV /[erg s -1 ]) = 44.7 ± 0.1. Around the time of the rise in X-ray flux, the nucleus of the galaxy brightened by approximately 3 mag. in optical photometry, after correcting for the host contribution. We present X-ray follow-up data from Swift, XMM-Newton, and NICER, which reveal a very soft spectrum as well as strong 0.2–2.0 keV flux variability on multiple timescales. Optical spectra taken in the weeks after the ignition event show a blue continuum with broad, asymmetric Balmer emission lines, and high-ionisation ([OIII]λλ4959,5007) and low-ionisation ([NII]λ6585, [SII]λλ6716,6731) narrow emission lines. Following the peak in the optical light curve, the X-ray, UV, and optical photometry all show a rapid decline. The X-ray light curve shows a decrease in luminosity of ~0.45 over 33 days and the UV shows a drop of ~0.35 over the same period. eRASSt J234402.9-352640 also shows a brightening in the mid-infrared, likely powered by a dust echo of the luminous ignition. We find no evidence in Fermi-LAT γ-ray data for jet-like emission. The event displays characteristics of a tidal disruption event (TDE) as well as of an active galactic nucleus (AGN), complicating the classification of this transient. Based on the softness of the X-ray spectrum, the presence of high-ionisation optical emission lines, and the likely infrared echo, we find that a TDE within a turned-off AGN best matches our observations.

79 ASTRONOMY AND ASTROPHYSICS↗

Metamodels for Rapid Analysis of Large Sets of Building Designs for Robotic Constructability: Technology Demonstration Using the NASA 3D Printed Mars Habitat Challenge

Disruptive robotic construction technologies such as additive deposition of cementitious materials like concrete (or "3D concrete printing") require the synchronous operation of multiple pieces of equipment in the production setup. In such an environment, it is crucial to simulate the robotic motions (for toolpath clashes) and the cementitious material behavior (for toolpath failures) to ensure fail-proof constructability of the envisioned building geometry. However, toolpath clash detection requires 4D simulations of the production setup, which are computationally graphics intensive, whereas toolpath failure detection requires actual 3D printing of test parts from the geometry to identify areas prone to failure while 3D printing, which is physically tedious. Both these processes, being computationally and physically intensive, have largely curtailed designers from simulating and exploring large sets of design options with varying geometries and toolpath configurations. To overcome this and allow designers to explore large sets of design possibilities, this paper proposes two novel computational metamodels capable of performing robotic toolpath clash detection and failure detection with significantly reduced times than the earlier approaches. The developed metamodels were used to rapidly simulate large sets of building design options for robotic constructability in the NASA 3D-Printed Mars Habitat Challenge.

clash detection↗

A proton beam energy modulator for rapid proton therapy

We present the design for a rapid proton energy modulator with radiofrequency accelerator cavities, which can deliver the proton radiation dose to varied depth in human tissues much faster than traditional mechanical beam energy degraders. The proton energy modulator is designed as a multi-cell 1-m long accelerator working at 2.856 GHz. Each individual accelerator cavity is powered by a 400 kW compact klystron to provide an accelerating/decelerating gradient of 30 MV/m. The high gradient is enabled by the individual power coupling regime, which provides a high shunt impedance. Beam dynamics simulations were performed, showing that the energy modulator can provide ±30 MeV of beam energy change for a 150 MeV, 7 mm long (full length) proton bunch, and the total energy spread of 3 MeV is satisfactory to clinical needs. A prototype experiment of a single cell has been built and tested, and the low-power microwave measurement results agree very well with simulations. The energy modulator is optimized for the 150 MeV cyclotron proton beam, while this approach can work with different beam energies.

47 OTHER INSTRUMENTATION↗

Investigating 3,4-bis(3-nitrofurazan-4-yl)furoxan detonation with a rapidly tuned density functional tight binding model

In this work, we describe a machine learning approach to rapidly tune density functional tight binding models for the description of detonation chemistry in organic molecular materials. Resulting models enable simulations on the several 10s of ps scales characteristic to these processes, with “quantum-accuracy.” We use this approach to investigate early shock chemistry in 3,4-bis(3-nitrofurazan-4-yl)furoxan, a hydrogen-free energetic material known to form onion-like nanocarbon particulates following detonation. We find that the ensuing chemistry is significantly characterized by the formation of large C x N y O z species, which are likely precursors to the experimentally observed carbon condensates. Beyond utility as a means of investigating detonation chemistry, the present approach can be used to generate quantum-based reference data for the development of full machine-learned interatomic potentials capable of simulation on even greater time and length scales, i.e., for applications where characteristic time scales exceed the reach of methods including Kohn–Sham density functional theory, which are commonly used for reference data generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid water dynamics structures the OH-stretching spectra of solitary water in ionic liquids and dipolar solvents

In a recent study [J. Phys. Chem. B 126, 4584–4598 (2022)], we have used infrared spectroscopy to investigate the solvation and dynamics of solitary water in ionic liquids and dipolar solvents. Complex shapes observed for water OH-stretching bands, common to all high-polarity solvents, were assigned to water in several solvation states. Here, in the present study, classical molecular dynamics simulations of a single water molecule in four ionic liquids and three dipolar solvents were used to test and refine this interpretation. Consistent with past assignments, simulations show solitary water usually donates two hydrogen bonds to distinct solvent molecules. Such symmetrically solvated water produces the primary pair of peaks identified in the OH spectra of water in nearly all solvents. We had further proposed that additional features flanking this main peak are due to asymmetric solvation states, states in which only one OH group makes a hydrogen bond to solvent. Such states were found in significant concentrations in all of the systems simulated. Simulations of the OH stretching spectra using a semiclassical description and the vibrational map developed by Auer and Skinner [J. Chem. Phys. 128, 224511–224512 (2008)] provided semi-quantitative agreement with experiment. Analysis of species-specific spectra confirmed assignment of the additional features in the experimental spectra to asymmetrically solvated water. The simulations also showed that rapid water motions cause a marked motional narrowing compared with the inhomogeneous limit. This narrowing is largely responsible for making the additional features due to minority solvation states manifest in the spectra.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High dopant activation in arsenic doped single-crystal CdTe thin films: Insights from MBE growth and rapid thermal processing

Single-crystal model systems are valuable tools to investigate fundamental material properties. In this work, we use molecular beam epitaxy to deposit in situ arsenic (As) doped single-crystal CdTe films on large area Si substrates to better understand As doping for photovoltaic applications. We found that As incorporation is highly temperature dependent: a substrate temperature difference of 50 °C can lead to several orders of magnitude difference in As concentration. Cd overpressure during in situ doping may limit out-diffusion of As but decrease As incorporation, especially at lower growth temperatures. Carrier concentrations greater than 10 16 cm −3 can be achieved with or without Cd overpressure when annealed at temperatures above 500 °C. However, unlike the low (∼1% to 5%) dopant activation commonly observed in polycrystalline CdTe, our films achieve significantly higher activation ratios—exceeding 50%, and in some cases approaching 80%. These values are consistent with or exceed prior reports in single-crystal CdTe systems. In addition to as-deposited arsenic concentrations, we also consider arsenic distribution after different rapid thermal processing temperatures. We propose a detailed definition and description of how arsenic incorporation is considered and calculated. Due to carrier concentration saturation, As incorporation also needs to be controlled to average levels of 10 17 cm −3 to achieve high activation. These findings suggest that higher annealing temperature regimes may be beneficial to polycrystalline CdTe based PV devices.

36 MATERIALS SCIENCE↗

Fully synthetic platform to rapidly generate tetravalent bispecific nanobody–based immunoglobulins

Nanobodies bind a target antigen with a kinetic profile similar to a conventional antibody, but exist as a single heavy chain domain that can be readily multimerized to engage antigen via multiple interactions. Presently, most nanobodies are produced by immunizing camelids; however, platforms for animal-free production are growing in popularity. Here, we describe the development of a fully synthetic nanobody library based on an engineered human V H 3-23 variable gene and a multispecific antibody-like format designed for biparatopic target engagement. To validate our library, we selected nanobodies against the SARS-CoV-2 receptor–binding domain and employed an on-yeast epitope binning strategy to rapidly map the specificities of the selected nanobodies. We then generated antibody-like molecules by replacing the V H and V L domains of a conventional antibody with two different nanobodies, designed as a molecular clamp to engage the receptor-binding domain biparatopically. The resulting bispecific tetra-nanobody immunoglobulins neutralized diverse SARS-CoV-2 variants with potencies similar to antibodies isolated from convalescent donors. Subsequent biochemical analyses confirmed the accuracy of the on-yeast epitope binning and structures of both individual nanobodies, and a tetra-nanobody immunoglobulin revealed that the intended mode of interaction had been achieved. This overall workflow is applicable to nearly any protein target and provides a blueprint for a modular workflow for the development of multispecific molecules.

60 APPLIED LIFE SCIENCES↗

Deep learning models map rapid plant species changes from citizen science and remote sensing data

Anthropogenic habitat destruction and climate change are reshaping the geographic distribution of plants worldwide. However, we are still unable to map species shifts at high spatial, temporal, and taxonomic resolution. Here, we develop a deep learning model trained using remote sensing images from California paired with half a million citizen science observations that can map the distribution of over 2,000 plant species. Our model— Deepbiosphere— not only outperforms many common species distribution modeling approaches (AUC 0.95 vs. 0.88) but can map species at up to a few meters resolution and finely delineate plant communities with high accuracy, including the pristine and clear-cut forests of Redwood National Park. These fine-scale predictions can further be used to map the intensity of habitat fragmentation and sharp ecosystem transitions across human-altered landscapes. In addition, from frequent collections of remote sensing data, Deepbiosphere can detect the rapid effects of severe wildfire on plant community composition across a 2-y time period. These findings demonstrate that integrating public earth observations and citizen science with deep learning can pave the way toward automated systems for monitoring biodiversity change in real-time worldwide.

Gillespie, Lauren E.↗

Ultrahigh strength and plasticity in laser rapid solidified Al–Si nanoscale eutectics

As-cast Al–20wt.% Si alloys were processed via laser rapid solidification (LRS) techniques to create eutectic microstructures with nanoscale interconnected, nanotwinned Si fibers. LRS morphologies exhibit higher flow stress, exceeding 800 MPa and uniform plastic deformation above 20% compared to as-cast alloy that fractures at strains below 8% at flow strength of approximately 200 MPa. The strengthening mechanisms of LRS morphologies are interpreted in terms of the interfacial constraints: increase in yield strength as well as strain hardening rate due to nanoscale confined slip in fibrous Al–Si eutectic, and load transfer and eventual plasticity in the nanoscale Si fibers.

36 MATERIALS SCIENCE↗

Rapid assessment of interfacial stabilization mechanisms of metastable precipitates to accelerate high-temperature Al-alloy development

Precipitate strengthened high-temperature alloys are currently used in safety-critical applications. Understanding precipitate stability and solute segregation mechanisms at high temperatures is key to designing high-strength alloys. Rapid in-situ approaches, therefore, are pivotal in accelerating the alloy design process. Hereby using the test case of a promising high-temperature Al-Cu-Mn-Zr alloy, we demonstrate the value of in-situ atom probe tomography coupled with in-situ transmission electron microscopy to reveal atomic-scale mechanisms that lead to the emergence of non-equilibrium solute segregation. Mn and Zr segregation at strengthening precipitate(θ’)-matrix interface increases the kinetic barrier for phase transformation thus retaining high-temperature strength.

36 MATERIALS SCIENCE↗

Beyond the eutectic paradigm: nanolamellar patterns in a rapidly solidified peritectic alloy

Peritectic transformations are central to many structural alloys, yet pattern formation remains poorly understood due to complex growth dynamics and limited three-dimensional data. Here, we report an unusual two-phase microstructure in a Zn–Ag peritectic alloy subjected to rapid solidification by laser surface remelting. Synchrotron X-ray nanotomography reveals a lamellar structure of primary 𝜀-AgZn 3 and peritectic Zn with ∼700 nm spacing. Although resembling a eutectic morphology, this pattern forms without a eutectic reaction through non-steady coupled growth from the liquid. SEM and TEM-EDS confirm interface shapes and phase compositions. These findings expand the design space of peritectics for refined microstructural control.

36 MATERIALS SCIENCE↗

Large magnetocaloric effect in rapidly quenched Mn 50- x Co x Ni 40 In 10 nanomaterials

The effect of Co addition on magnetic hysteresis, martensitic transformation temperature, and magnetic entropy change of rapidly-quenched Mn 50- x Co x Ni 40 In 10 alloy nanomaterials has been investigated. The melt-spun Mn 50 Ni 40 In 10 sample exhibits a small magnetic hysteresis which is further reduced by Co doping as measured between 0 and 2 T. The martensitic transformation temperature increases linearly with the electron concentration in the alloy from 195 K for Mn 50 Ni 40 In 10 to 378 K for Mn 45 Co 5 Ni 40 In 10 . The Mn 47 Co 3 Ni 40 In 10 alloy, which has phase-transition temperature close to room temperature, exhibits a substantial peak entropy change of 29.7 J kg -1 K -1 at magnetic field change of 2 T. Our results demonstrate that Mn 47 Co 3 Ni 40 In 10 nanomaterial exhibits promising magnetocaloric properties for near-room-temperature magnetic refrigeration.

Physics↗

Exploring rapidity-even dipolar flow in isobaric collisions at RHIC

Abstract Employing the AMPT transport model, we investigate the response of the rapidity-even dipolar flow ( v 1 even ) and its associated Global Momentum Conservation (GMC) parameterKto structural disparities within 96 Ru and 96 Zr nuclei. We analyze Ru + Ru and Zr + Zr collisions at a center-of-mass energy of s NN = 200 GeV. Our analysis demonstrates that the eccentricityε 1 , v 1 even andKexhibit subtle yet discernible sensitivity to the input nuclear structure distinctions between 96 Ru and 96 Zr isobars. This observation suggests that measuring v 1 even and the GMC parameter in these isobaric collisions could serve as a means to fine-tune the comprehension of their nuclear structure disparities and offer insights to enhance the initial condition assumptions of theoretical models.

Physics↗

Rapidly-convergent flux-surface shape parameterization

We propose a novel flux-surface parameterization suitable for local MHD equilibrium calculations with strongly-shaped flux surfaces. The method is based on a systematic expansion in a small number of intuitive shape parameters, and reduces to the well-known Miller D-shaped parameterization in the limit where some of the coefficients are set to zero. Here, the new parameterization is valid for up-down asymmetric plasmas and provides an improvement to the Miller form. Simultaneously, the method is rapidly convergent and requires only about half the number of shape parameters as a general Fourier representation in the pedestal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Rapid approach for structural design of the tower and monopile for a series of 25 MW offshore turbines

The goal of further reducing the Levelized Cost of Energy (LCOE) has driven the investigation of large-scale wind turbines. This work presents a simple, rapid and detailed approach for the structural design of the tower and monopile without a controller, but with frequency and high fidelity structural verification. The approach uses an optimization to reduce the mass of the structures while meeting strength, buckling and geometric constraints by using analytical equations. A verification of frequency constraints is performed with BModes, and ANSYS Mechanical APDL is used for high fidelity verification of stress and buckling. The approach is applied to study the design space of three 25 MW offshore wind turbines with different rotor diameters and cone angles, and to evaluate the nacelle center of mass fore-aft location effect. Results obtained show that the tower and monopile are more susceptible to changes in the rotor thrust than the overturning moment even for designs with high pre-cone angle and large distance of the nacelle center of mass from the tower axis. But it is possible to obtain structurally feasible tower and monopile designs for the three 25 MW turbines studied while not exceeding diameter and wall thickness limits. However, mass penalties can be decreased by 0.8-14%, to further reduce the cost of energy, by increasing the diameter limit which may require manufacturing technology development. The approach applied and studies serve to understand the design space of the tower and monopile for a 25 MW turbine, and provide baseline designs that can be used in the development of a controller and evaluation of a full suite of design load cases.

17 WIND ENERGY↗

Rapidly changing high-latitude seasonality: implications for the 21st century carbon cycle in Alaska

Seasonal variations in high-latitude terrestrial carbon (C) fluxes are predominantly driven by air temperature and radiation. At present, high-latitude net C uptake is largest during the summer. Recent observations and modeling studies have demonstrated that ongoing and projected climate change will increase plant productivity, microbial respiration, and growing season lengths at high-latitudes, but impacts on high-latitude C cycle seasonality (and potential feedbacks to the climate system) remain uncertain. Here we use ecosys, a well-tested and process-rich mechanistic ecosystem model that we evaluate further in this study, to explore how climate warming under an RCP8.5 scenario will shift C cycle seasonality in Alaska throughout the 21st century. The model successfully reproduced recently reported large high-latitude C losses during the fall and winter and yet still predicts a high-latitude C sink, pointing to a resolution of the current conflict between process-model and observation-based estimates of high-latitude C balance. We find that warming will result in surprisingly large changes in net ecosystem exchange (NEE; defined as negative for uptake) seasonality, with spring net C uptake overtaking summer net C uptake by year 2100. This shift is driven by a factor of 3 relaxation of spring temperature limitation to plant productivity that results in earlier C uptake and a corresponding increase in magnitude of spring NEE from –19 to –144 gC m –2 season –1 by the end of the century. Although a similar relaxation of temperature limitation will occur in the fall, radiation limitation during those months will limit increases in C fixation. Additionally, warmer soil temperatures and increased carbon inputs from plants lead to combined fall and winter C losses (163 gC m –2 ) that are larger than summer net uptake (123 gC m –2 season –1 ) by year 2100. However, this increase in microbial activity leads to more rapid N cycling and increased plant N uptake during the fall and winter months that supports large increases in spring NPP. Due to the large increases in spring net C uptake, the high-latitude atmospheric C sink is projected to sustain throughout this century. Our analysis disentangles the effects of key environmental drivers of high-latitude seasonal C balances as climate changes over the 21st century.

54 ENVIRONMENTAL SCIENCES↗

TEQUILA: a platform for rapid development of quantum algorithms

Variational quantum algorithms are currently the most promising class of algorithms for deployment on near-term quantum computers. In contrast to classical algorithms, there are almost no standardized methods in quantum algorithmic development yet, and the field continues to evolve rapidly. As in classical computing, heuristics play a crucial role in the development of new quantum algorithms, resulting in a high demand for flexible and reliable ways to implement, test, and share new ideas. In this paper, inspired by this demand, we introduce TEQUILA, a development package for quantum algorithms in PYTHON, designed for fast and flexible implementation, prototyping and deployment of novel quantum algorithms in electronic structure and other fields. TEQUILA operates with abstract expectation values which can be combined, transformed, differentiated, and optimized. On evaluation, the abstract data structures are compiled to run on state of the art quantum simulators or interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗