A crystallographic approach to the short-range ordering problem in V[subscript 1;#8722;x]Mo[subscript x]O[subscript 2] (0.50 ;#8804; x ;#8804; 0.60)
Abstract not provided
Davenport, Matthew A.↗
SEARCH · Engineering Papers
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Bond dissociation energies of low-valent lanthanide hydroxides: lower limits from ion–molecule reactions and comparisons with fluorides
Despite that bond dissociation energies (BDEs) are among the most fundamental and relevant chemical properties they remain poorly characterized for most elementary lanthanide hydroxides and halides. Lanthanide ions Ln + = Eu + , Tm + and Yb + are here shown to react with H 2 O to yield hydroxides LnOH + . Additionally, under low-energy conditions such reactions must be exothermic, which implies a lower limit of 499 kJ mol -1 for the Ln + –OH BDEs. This limit is significantly higher than previously reported for YbOH + and is unexpectedly similar to the BDE for Yb + –F. To explain this apparent anomaly, it is considered feasible that the inefficient hydrolysis reactions observed here in a quadrupole ion trap mass spectrometer may actually be endothermic. More definitive and broad-based evaluations and comparisons require additional and more reliable BDEs and ionization energies for key lanthanide molecules, and/or energies for ligand-exchange reactions like LnF + OH ↔ LnOH + F. The hydroxide results motivated an assessment of currently available lanthanide monohalide BDEs. Among several intriguing relationships is the distinctively higher BDE for neutral LuF versus cationic LuF + , though quantifying this comparison awaits a more accurate value for the anomalously high ionization energy of LuF.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Structure of water-in-salt and water-in-bisalt electrolytes
We report a systematic diffraction study of two “water-in-salt” electrolytes and a “water-in-bisalt” electrolyte combining high-energy X-ray diffraction (HEXRD) with polarized and unpolarized neutron diffraction (ND) on both H 2 O and D 2 O solutions. The measurements provide three independent combinations of correlations between the different pairs of atom types that reveal the short- and intermediate-range order in considerable detail. The ND interference functions show pronounced peaks around a scattering vector Q ~ 0.5 Å -1 that change dramatically with composition, indicating significant rearrangements of the water network on a length scale around 12 Å. The experimental results are compared with two sets of Molecular Dynamics (MD) simulations, one including polarization effects and the other based on a non-polarizable force field. The two simulations reproduce the general shapes of the experimental structure factors and their changes with concentration, but differ in many detailed respects, suggesting ways in which their force fields might be modified to better represent the actual systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Developing a microwave-driven reactor for ammonia synthesis: insights into the unique challenges of microwave catalysis
Rapid development of new ammonia (NH 3 ) synthesis techniques that enable modular, intermittent production is essential to actualizing NH 3 's potential as a clean energy carrier, since contemporary methods are configured to centralized, continuous production methods with high emissions and are incompatible with renewable sources. Here, in this mission, microwave-driven catalysis is promising for its ability to enhance reaction kinetics and apply targeted heating for efficient energy use. However, owing to an incomplete understanding of the interaction between microwave fields and catalyst beds, the development of such microwave-catalysis systems remains underexplored and challenging. This paper investigates the 10× scale-up of a microwave-based NH 3 synthesis reactor using numerical and experimental approaches, achieving the largest reported microwave-driven NH 3 reactor to date. Results elucidate phenomena unique to microwave processes that are only predictable through numerical modeling, including how a catalyst's dielectric properties influence microwave field distribution by affecting penetration depth and how energy utilization can be poor even with sufficient attenuation. These dynamics change with scale, constrain reactor geometry, and potentially hamper performance. Nonetheless, we demonstrate a production rate of 56.6 g NH$_3$ per day, the highest reported NH 3 synthesis rate for laboratory-scale alternative techniques; correspondingly, the benchmark energy efficiency achieved in this paper (45.6 g NH$_3$ kW h -1 ) is the highest reported for such reactors of sufficient scale. Even with this exemplary energy efficiency, energy losses were found in excess of 50%, an issue resolvable through scale and reactor design. The efficiencies imparted by microwaves were key in these achievements, warranting further investigation toward development of microwave-driven NH 3 systems.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Size distribution of polycyclic aromatic hydrocarbons in space: an old new light on the 11.2/3.3 μm intensity ratio
The intensity ratio of the 11.2/3.3 μm emission bands is considered to be a reliable tracer of the size distribution of polycyclic aromatic hydrocarbons (PAHs) in the interstellar medium (ISM). This paper describes the validation of the calculated intrinsic infrared (IR) spectra of PAHs that underlie the interpretation of the observed ratio. The comparison of harmonic calculations from the NASA Ames PAH IR spectroscopic database to gas-phase experimental absorption IR spectra reveals a consistent underestimation of the 11.2/3.3 μm intensity ratio by 34%. IR spectra based on higher level anharmonic calculations, on the other hand, are in very good agreement with the experiments. While there are indications that the 11.2/3.3 μm ratio increases systematically for PAHs in the relevant size range when using a larger basis set, it is unfortunately not yet possible to reliably calculate anharmonic spectra for large PAHs. Based on these considerations, we have adjusted the intrinsic ratio of these modes and incorporated this in an interstellar PAH emission model. This corrected model implies that typical PAH sizes in reflection nebulae such as NGC 7023 – previously inferred to be in the range of 50 to 70 carbon atoms per PAH are actually in the range of 40 to 55 carbon atoms. The higher limit of this range is close to the size of the C 60 fullerene (also detected in reflection nebulae), which would be in line with the hypothesis that, under appropriate conditions, large PAHs are converted into the more stable fullerenes in the ISM.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Deep learning potential of mean force between polymer grafted nanoparticles
Grafting polymer chains on the surfaces of nanoparticles is a well-known route to control their self-assembly and distribution in a polymer matrix. A wide variety of self-assembled structures are achieved by changing the grafting patterns on the surface of an individual nanoparticle. However, an accurate estimation of the effective potential of mean force between a pair of grafted nanoparticles that determines their assembly and distribution in a polymer matrix is an outstanding challenge in nanoscience. We address this problem via deep learning. As a proof of concept, here we report a deep learning framework that learns the interaction between a pair of single-chain grafted spherical nanoparticles from their molecular dynamics trajectory. Subsequently, we carry out the deep learning potential of mean force-based molecular simulation that predicts the self-assembly of a large number of single-chain grafted nanoparticles into various anisotropic superstructures, including percolating networks and bilayers depending on the nanoparticle concentration in three-dimensions. The deep learning potential of mean force-predicted self-assembled superstructures are consistent with the actual superstructures of single-chain polymer grafted spherical nanoparticles. This deep learning framework is very generic and extensible to more complex systems including multiple-chain grafted nanoparticles. Finally, we expect that this deep learning approach will accelerate the characterization and prediction of the self-assembly and phase behaviour of polymer-grafted and unfunctionalized nanoparticles in free space or a polymer matrix.
36 MATERIALS SCIENCE↗
Resolving a structural issue in cerium-nickel-based oxide: a single compound or a two-phase system?
Preparation of CeNiO 3 in order to elucidate the actual crystal structure with the aim of establishing a structure–property relationship. Three different structural models were proposed accompanied by detailed structural analysis.
Chemistry↗
Determination of the vacancy distribution over Al cation sites in γ-Al 2 O 3
Although gamma-alumina (γ-Al 2 O 3 ) is an extensively used material with wide-ranging applications due to its inherently high surface area and acidity, its atomic structure is still not fully understood. γ-Al 2 O 3 is described as having a spinel-like structure, where the O sublattice has a face-centered cubic (FCC) arrangement and Al cations are placed in the spinel tetrahedral and octahedral interstitial sites. Achieving the correct stoichiometry of Al 2 O 3 , however, requires the introduction of Al vacancies into some of the interstitial sites. Despite the importance of accurately describing the structure of γ-Al 2 O 3 , the distribution of vacancies between tetrahedral and octahedral sites remains unclear, in part because of the usually poor crystalline quality of γ-Al 2 O 3 that has often been used in previous studies. To determine the actual cation distribution in γ-Al 2 O 3 , single-crystalline γ-Al 2 O 3 was investigated using a correlative approach of experimental and simulated selected-area electron diffraction (SAED) and high-resolution electron energy-loss spectroscopy (EELS). Comparison of the reflection intensities in single-crystal SAED to simulated SAED from models with varied vacancy distributions revealed that vacancies exist primarily on tetrahedral sites, contrary to the placement of vacancies on octahedral sites proposed in several common models. Comparison of EELS spectra—acquired with the highest energy resolution reported so far for γ-Al 2 O 3 —with ab initio multiple scattering EELS simulations confirmed the distribution of vacancies on tetrahedral sites. These results enable more accurate modeling of γ-Al 2 O 3 to better predict its properties in existing and future applications.
36 MATERIALS SCIENCE↗
Exploring the mobility of Cu in bimetallic nanocrystals to promote atomic-scale transformations under a reactive gas environment
Bimetallic nanocrystals (NCs) often show improved catalytic activities compared to their monometallic counterparts, but to optimize the performance it is crucial to understand how they behave under actual reaction conditions, i.e. in gas environments. Here, in this study, we use powder X-ray diffraction (PXRD), total scattering (TS) with pair distribution function (PDF) analysis and in situ high-resolution transmission electron microscopy (HR-TEM) to provide new insights into the atomic-scale behaviour of NC catalysts under a reactive gas environment. By investigating Au, Cu, Pd, PdCu, AuPd and AuCu NCs, we observe that the properties of bimetallic NCs differ significantly from their monometallic counterparts. While metal oxide phases formed for monometallic Pd and Cu under O 2 -exposure, bimetallic PdCu and AuCu NCs showed loss of metallic Cu in the crystalline phases after exposure to O 2 . However, upon introducing the bimetallic NCs to a reducing atmosphere, the Cu was found to reappear and reincorporate into a crystalline phase, forming the initial bimetallic structures. By combining TS, PDF analysis and in situ HR-TEM, we saw that Cu segregates to the NC surfaces or forms small CuO domains under O 2 -exposure. Our results thus indicate that the Cu mobility promotes segregation and formation of CuO along with the formation of a monometallic phase, which ultimately changes the resulting active surface sites of the nanocatalyst. Understanding the dynamical structure–property relations of nanocatalysts is key to enable rational design of efficient and robust catalysts for controlled catalytic reactions.
36 MATERIALS SCIENCE↗
Unraveling the myths and mysteries of photon avalanching nanoparticles
Photon avalanching (PA) nanomaterials exhibit some of the most nonlinear optical phenomena reported for any material, allowing them to push the frontiers of applications ranging from nanoscale imaging and sensing to optical computing. But PA remains shrouded in mystery, with its underlying physics and limitations misunderstood. Photon avalanching is not, in fact, an avalanche of photons, at least not in the same way that snowballs beget more snowballing in an actual avalanche. In this focus article, we dispel these and other common myths surrounding PA in lanthanide-based nanoparticles and unravel the mysteries of this unique nonlinear optical effect. We hope that removing the misconceptions surrounding avalanching nanoparticles will inspire new interest and applications that harness the giant nonlinearity of PA across a broad range of scientific fields.
Skripka, Artiom↗
Uranium particle age dating, aggregation, and model age best estimators
We present important aspects of uranium particle age dating by Large-Geometry Secondary Ion Mass Spectrometry (LG-SIMS) that can introduce bias and increase model age uncertainties, especially for small, young, and/or low-enriched particles. This metrology is important for applications related to International Nuclear Safeguards. We explore influential factors related to model age estimation, including the effects of evolving surface chemistry on inter-element measurements of particles (e.g., Th and U), detector background, and aggregation methods using simulated and actual particle samples. We introduce a new model age estimator, called “mid68”, that supplements 95% confidence intervals, providing a “best estimate” and uncertainty about the most likely age. The mid68 estimator can be calculated using the Feldman and Cousins method or Bayesian methods and provides a value with a symmetric uncertainty that can be used for calculations and approximate aggregation of processed model age values when the raw data and correction factors are not available. For particles yielding low 230 Th counts amidst nonzero detector background, their underlying model age probability distributions are asymmetric, so the mid68 estimator provides additional robust information regarding the underlying model age likelihood. This study provides a comprehensive and timely examination of critical aspects of uranium particle age dating as more laboratories establish particle chronometry capabilities.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Building workflows for an interactive human-in-the-loop automated experiment (hAE) in STEM-EELS
Exploring the structural, chemical, and physical properties of matter on the nano- and atomic scales has become possible with the recent advances in aberration-corrected electron energy-loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). However, the current paradigm of STEM-EELS relies on the classical rectangular grid sampling, in which all surface regions are assumed to be of equal a priori interest. However, this is typically not the case for real-world scenarios, where phenomena of interest are concentrated in a small number of spatial locations, such as interfaces, structural and topological defects, and multi-phase inclusions. One of the foundational problems is the discovery of nanometer- or atomic-scale structures having specific signatures in EELS spectra. Herein, we systematically explore the hyperparameters controlling deep kernel learning (DKL) discovery workflows for STEM-EELS and identify the role of the local structural descriptors and acquisition functions in experiment progression. In agreement with the actual experiment, we observe that for certain parameter combinations the experiment path can be trapped in the local minima. We demonstrate the approaches for monitoring the automated experiment in the real and feature space of the system and knowledge acquisition of the DKL model. Based on these, we construct intervention strategies defining the human-in-the-loop automated experiment (hAE). This approach can be further extended to other techniques including 4D STEM and other forms of spectroscopic imaging. The hAE library is available on Github at https://github.com/utkarshp1161/hAE/tree/main/hAE.
Pratiush, Utkarsh [Univ. of Tennessee, Knoxville, ↗
Deep learning model to detect various synchrophasor data anomalies
High-density synchrophasors provide valuable information for power grid situational awareness, operation and control. Unfortunately, due to factors including communication instability and hardware failure, their data quality can be greatly deteriorated by anomalies. Since the anomalies can impact the performance of the synchrophasor applications, it is of paramount significance to propose a model to detect anomalies in synchrophasor. In this study, a convolutional neural network model is established to detect and classify the anomalies in the synchrophasor measurements. Additionally, four types of anomalies observed in actual synchrophasors including erroneous patterns, random spikes, missing points and high-frequency interferences are considered in this study. The proposed model is extensively evaluated via field-collected measurements from the synchrophasor network in Jiangsu grid, China. The superior performance of the proposed model indicates the great potential of using deep learning for the detection of abnormal synchrophasor measurements.
42 ENGINEERING↗
Phase curves of small bodies from the SLOAN Moving Objects Catalog
Extensive photometric surveys continue to produce enormous stores of data on small bodies. These data are typically sparsely obtained at arbitrary (or unknown) rotational phases. Therefore, new methods for processing such data need to be developed to make the most of these vast catalogs. We aim to produce a method of recreating the phase curves of small bodies by considering the uncertainties introduced by the nominal errors in the magnitudes and the effect introduced by rotational variations. Here, we use the SLOAN Moving Objects Catalog data as a benchmark to construct phase curves of all small bodies in u', g', r', i', and z' filters. From the phase curves, we obtain the absolute magnitudes and we use them to set up the absolute colors, which are the colors of the asteroids that are not affected by changes in the phase angle. We selected objects with ≥3 observations taken in at least one filter and spanning over a minimum of 5 degrees in the phase angle. We developed a method that combines Monte Carlo simulations and Bayesian inference to estimate the absolute magnitudes using the HG 12 * photometric system. We obtained almost 15 000 phase curves, with about 12 000 of these including all five filters. The absolute magnitudes and absolute colors are compatible with previously published data that support our method. The method we developed is fully automatic and well suited for a run based on large amounts of data. Moreover, it includes the nominal uncertainties in the magnitudes and the whole distribution of possible rotational states of the objects producing what are possibly less precise values, that is, larger uncertainties, but more accurate, namely, closer to the actual value. To our knowledge, this work is the first to include the effect of rotational variations in such a manner.
79 ASTRONOMY AND ASTROPHYSICS↗
The eROSITA Final Equatorial-Depth Survey (eFEDS)
The eROSITA Final Equatorial Depth Survey (eFEDS), completed in survey mode during the calibration and performance verification phase of the eROSITA instrument on Spectrum Roentgen Gamma, delivers data at and beyond the final depth of the 4-yr eROSITA all-sky survey (eRASS:8), f 0.5–2 keV = 1.1 × 10 –14 erg s –1 cm –2 , over 140 deg 2 . It provides the first view of normal galaxy X-ray emission from X-ray binaries (XRBs) and the hot interstellar medium at the full depth of eRASS:8. We used the Heraklion Extragalactic Catalogue (HECATE) of galaxies to correlate with eFEDS X-ray sources and identify X-ray detected normal galaxies. This flux-limited X-ray survey is relatively free from selection effects and enables the study of integrated normal galaxy X-ray emission and its relation to galaxy parameters such as the stellar mass, star formation rate (SFR), and metallicity. We cross-correlated 32 646 eFEDS X-ray sources to 1181 HECATE normal galaxies and obtained 94 matches. We classified galaxies as star-forming, early-type, composite, and active galactic nuclei (AGN) using Sloan Digital Sky Survey (SDSS) and Six-degree Field (6dF) optical spectroscopy. The eFEDS field harbours 37 normal galaxies: 36 late-type (star-forming) galaxies and one early-type galaxy. There are 1.9 times as many normal galaxies as predicted by scaling relations via simulations, with an overabundance of late-type galaxies and a dearth of early-type galaxies. When compared with empirical relations, eFEDS dwarf galaxies with a high specific SFR have elevated L X /SFR at a fixed specific SFR and metallicity, indicating an increase in XRB emission due to low metallicity. We expect that eRASS:8 will detect 12 500 normal galaxies, the majority of which will be star-forming, with the caveat that there are unclassified sources in eFEDS and galaxy catalogue incompleteness issues that could increase the actual number of detected galaxies over these current estimates. eFEDS observations detected a rare population of galaxies – the metal-poor dwarf starbursts – that do not follow known scaling relations. eRASS is expected to discover significant numbers of these high-redshift analogues, which are important for studying the heating of the intergalactic medium at high redshift. Further investigation of the hot gas emission from normal galaxies and stochastic effects in the dwarf galaxy population are required to constrain their X-ray output.
79 ASTRONOMY AND ASTROPHYSICS↗
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↗
Towards a self-consistent model of the convective core boundary in upper main sequence stars: I. 2.5D and 3D simulations
There is strong observational evidence that the convective cores of intermediate-mass and massive main sequence stars are substantially larger than those predicted by standard stellar-evolution models. However, it is unclear what physical processes cause this phenomenon or how to predict the extent and stratification of stellar convective boundary layers. Convective penetration is a thermal-timescale process that is likely to be particularly relevant during the slow evolution on the main sequence. We use our low-Mach-number S EVEN -L EAGUE H YDRO code to study this process in 2.5D and 3D geometries. Starting with a chemically homogeneous model of a 15 M ⊙ zero-age main sequence star, we construct a series of simulations with the luminosity increased and opacity decreased by the same factor, ranging from 10 3 to 10 6 . After reaching thermal equilibrium, all of our models show a clear penetration layer; its thickness becomes statistically constant in time and it is shown to converge upon grid refinement. The penetration layer becomes nearly adiabatic with a steep transition to a radiative stratification in simulations at the lower end of our luminosity range. This structure corresponds to the adiabatic ‘step overshoot’ model often employed in stellar-evolution calculations. The simulations with the highest and lowest luminosity differ by less than a factor of two in the penetration distance. The high computational cost of 3D simulations makes our current 3D data set rather sparse. Depending on how we extrapolate the 3D data to the actual luminosity of the initial stellar model, we obtain penetration distances ranging from 0.09 to 0.44 pressure scale heights, which is broadly compatible with observations.
79 ASTRONOMY AND ASTROPHYSICS↗
Boosting RDataFrame performance with transparent bulk event processing
RDataFrame is ROOT’s high-level interface for Python and C++ data analysis. Since it first became available, RDataFrame adoption has grown steadily and it is now poised to be a major component of analysis software pipelines for LHC Run 3 and beyond. Thanks to its design inspired by declarative programming principles, RDataFrame enables the development of highperformance, highly parallel analyses without requiring expert knowledge of multi-threading and I/O: user logic is expressed in terms of self-contained, small computation kernels tied together by a high-level API. This design completely decouples analysis logic from its actual execution, and opens several interesting avenues for workflow optimization. In particular, in this work we explore the benefits of moving internal data processing from an event-by-event to a bulkby-bulk loop. This refactoring dramatically reduces the framework’s runtime overheads; in collaboration with the I/O layer it improves data access patterns; it exposes information that optimizing compilers might use to auto-vectorize the invocation of user-defined computations; finally, while existing user-facing interfaces remain unaffected, it becomes possible to additionally offer interfaces that explicitly expose bulks of events, useful e.g. for the injection of GPU kernels into the analysis workflow. In order to inform similar future R&D, design challenges will be presented, as well as an investigation of the relevant timememory trade-off backed by novel performance benchmarks.
Guiraud, Enrico↗