Neural network assisted analysis of bimetallic nanocatalysts using X-ray absorption near edge structure spectroscopy
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99 GENERAL AND MISCELLANEOUS↗
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HT Lyn and IR Lyn: Two Semi-detached-type Near-contact Binaries with Stable Orbital Period
Abstract We presented the first photometric and orbital period investigations for two near-contact binaries: HT Lyn and IR Lyn. The light-curves solutions derived from both our ground-based and various surveys’ observations suggested that HT Lyn and IR Lyn are two semi-detached-type near-contact binaries with the secondary and primary components filling the Roche lobe. Combining the eclipse timings derived from several surveys’ data and our observations with those reported in the literature, we modified the orbital periods and revealed that their orbital periods were stable for the last two decades. The absolute physical parameters were well determined by using the empirical relations and the Gaia-distance-based method. Similar to other near-contact binaries, the primary components of HT Lyn and IR Lyn are evolving at the main-sequence stage, while their less-massive secondary components show the over-sized and over-luminosity features and should be more evolved than their primary ones. Combining the stable orbital period with the semi-detached configurations, we infer that the two near-contact binaries may be just located in the critical phase and evolving from the current semi-detached phase to the detached or contact one.
Astronomy & Astrophysics↗
Temperature and Water Levels Collectively Regulate Methane Emissions From Subtropical Freshwater Wetlands
Abstract Wetlands are the largest and most climate‐sensitive natural sources of methane. Accurately estimating wetland methane emissions involves reconciling inversion (“top‐down”) and process‐based (“bottom‐up”) models within the global methane budget. However, estimates from these two model types are inherently interdependent and often reveal substantial discrepancies. To enhance the reliability of both approaches, we need a comprehensive understanding of wetland methane emissions and an independent high‐resolution long‐term flux data set. Here, we employed a data‐driven random forest approach to identify key variables influencing methane emissions from subtropical freshwater wetlands in the Southeastern United States. The model‐estimated monthly mean methane fluxes fit well with measured methane fluxes ( R 2 = 0.67) at four representative FLUXNET‐CH4 wetland sites across the region. Variable importance analysis highlighted the sensitivity of subtropical freshwater wetland methane emissions to variations in both temperature and water levels. High temperatures facilitate methanogenesis by enhancing microbial activities, while elevated water levels maintain anaerobic conditions necessary for methane production. Notably, the response of methane emissions to water level fluctuations is contingent on temperature conditions, and vice versa. Moreover, we constructed the first high‐spatial‐resolution (∼1 km × 1 km) and long‐term (1982–2010) gridded regional wetland methane flux product for the Southeastern United States, estimating annual methane emissions from subtropical freshwater wetlands in the region at 4.93 ± 0.11 Tg CH 4 yr −1 for 1982–2010. This new benchmark product holds promise for validating and parameterizing uncertain wetland methane emission processes in bottom‐up models and provides improved prior information for top‐down models.
He, Keqi [Earth and Climate Sciences Nicholas Scho↗
Probing ferroelectric domain structures and their switching dynamics in SrBi2Ta2O9 by in-situ electric biasing in transmission electron microscopy
Abstract Lead-free SrBi 2 Ta 2 O 9 (SBT) has been a promising ferroelectric material for various applications such as electronics and data storage due to its outstanding ferroelectric properties including high fatigue endurance and low leakage current. However, the atomic-scale domain structure and switching dynamics of ferroelectric SBT remain elusive. This study reveals that spontaneous polarization arises from canted bismuth-cation displacements, forming 90° and Ising-type 180° domain walls. Interestingly, topological pairs of ferroelectric vortex and antivortex connect ferroelectric boundaries where three domain walls converge. In situ electrical biasing transmission electron microscopy (TEM) reveals the dominance of 180° switching over 90°, where oxygen octahedral connectivity is protected by ferroelastic energy in the 90° domain wall. Consequently, all 180° domain walls and (anti)vortices are removed, leaving only 90° domain walls in the electrically poled states. Chemical deterioration along domain walls highlights vulnerability of SBT to ferroelectric fatigue. This study provides insight into crucial aspects for practical applications of SBT.
36 MATERIALS SCIENCE↗
Automatic Detection and Classification of Radio Galaxy Images by Deep Learning
Abstract Surveys conducted by radio astronomy observatories, such as SKA, MeerKAT, Very Large Array, and ASKAP, have generated massive astronomical images containing radio galaxies (RGs). This generation of massive RG images has imposed strict requirements on the detection and classification of RGs and makes manual classification and detection increasingly difficult, even impossible. Rapid classification and detection of images of different types of RGs help astronomers make full use of the observed astronomical image data for further processing and analysis. The classification of FRI and FRII is relatively easy, and there are more studies and literature on them at present, but FR0 and FRI are similar, so it is difficult to distinguish them. It poses a greater challenge to image processing. At present, deep learning has made breakthrough progress in the field of image analysis and processing and has preliminary applications in astronomical data processing. Compared with classification algorithms that can only classify galaxies, object detection algorithms that can locate and classify RGs simultaneously are preferred. In target detection algorithms, YOLOv5 has outstanding advantages in the classification and positioning of small targets. Therefore, we propose a deep-learning method based on an improved YOLOv5 object detection model that makes full use of multisource data, combining FIRST radio with SDSS optical image data, and realizes the automatic detection of FR0, FRI, and FRII RGs. The innovation of our work is that on the basis of the original YOLOv5 object detection model, we introduce the SE Net attention mechanism, increase the number of preset anchors, adjust the network structure of the feature pyramid, and modify the network structure, thereby allowing our model to demonstrate galaxy classification and position detection effects. Our improved model produces satisfactory results, as evidenced by experiments. Overall, the mean average precision (mAP@0.5) of our improved model on the test set reaches 89.4%, which can determine the position (R.A. and decl.) and automatically detect and classify FR0s, FRIs, and FRIIs. Our work contributes to astronomy because it allows astronomers to locate FR0, FRI, and FRII galaxies in a relatively short time and can be further combined with other astronomically generated data to study the properties of these galaxies. The target detection model can also help astronomers find FR0s, FRIs, and FRIIs in future surveys and build a large-scale star RG catalog. Moreover, our work is also useful for the detection of other types of galaxies.
Astronomy & Astrophysics↗
Examining a hadronic γ-ray scenario for the radiative shell and molecular clouds of the old GeV supernova remnant G298.6−0.0
Abstract Based on the 13.7 yr Fermi-LAT data, Yeung, Bamba, and Sano (2023, PASJ, 75, 384) claimed detection of two γ-ray sources (namely Src-NE and Src-NW) associated with the supernova remnant (SNR) G298.6−0.0, and interpreted it as an old GeV SNR interacting with molecular clouds (MCs). In this follow-up study, we refine the flux measurements below 2 GeV with Fermi-LAT event types of better angular reconstruction. Then, we report our γ-ray spectral fittings and cosmic-ray phenomenology in a hadronic scenario, considering both the shell and MC regions of SNR G298.6−0.0. We confirm that the γ-ray spectra of both Src-NE and Src-NW exhibit spectral breaks, at $1.50_{-0.50}^{+0.60}$ and $0.68_{-0.11}^{+0.32}\:$GeV, respectively. Src-NW has a harder broad-band photon index than Src-NE, suggesting an appreciable difference between the physical separations of their respective emission sites from SNR G298.6−0.0. The cosmic-ray spectrum responsible for Src-NE starts with a minimum energy $E_\mathrm{CR,min}=1.38_{-0.16}^{+0.47}\:$GeV, and has a proton index $\Gamma _\mathrm{CR}=2.57_{-0.21}^{+0.18}$ below the exponential cutoff energy $E_\mathrm{CR,max}=240_{-150}^{+240}\:$GeV. Accordingly, we argue that Src-NE is dominated by the SNR shell, while only a minor portion of lower-energy emission is contributed by the MCs interacting with the SNR. The cosmic-ray population for Src-NW starts at a higher energy such that the ECR, min ratio of Src-NW to Src-NE is ≳2. The high ECR, min, as well as the high cosmic-ray energy density required (∼26 eV cm−3), supports the interpretation that Src-NW is predominantly the γ-ray emission from the farther MCs being bombarded by protons that had earlier escaped from SNR G298.6−0.0. By comparing the high-energy features of G298.6−0.0 with those of analogical SNRs, especially SNR W 28 and SNR W 44, we further constrain the age of SNR G298.6−0.0 to be 10–30 kyr, under the assumption of a purely hadronic scenario.
Astronomy & Astrophysics↗
Automatic detection of cataclysmic variables from SDSS images
Abstract Investigating rare and new objects have always been an important direction in astronomy. Cataclysmic variables (CVs) are ideal and natural celestial bodies for studying the accretion process of semi-detached binaries with accretion processes. However, the sample size of CVs must increase because a lager gap exists between the observational and the theoretical expanding CVs. Astronomy has entered the big data era and can provide massive images containing CV candidates. CVs as a type of faint celestial objects, are highly challenging to be identified directly from images using automatic manners. Deep learning has rapidly developed in intelligent image processing and has been widely applied in some astronomical fields with excellent detection results. YOLOX, as the latest YOLO framework, is advantageous in detecting small and dark targets. This work proposes an improved YOLOX-based framework according to the characteristics of CVs and Sloan Digital Sky Survey (SDSS) photometric images to train and verify the model to realise CV detection. We use the Convolutional Block Attention Module to increase the number of output features with the feature extraction network and adjust the feature fusion network to obtain fused features. Accordingly, the loss function is modified. Experimental results demonstrate that the improved model produces satisfactory results, with average accuracy (mean average Precision at 0.5) of 92.0%, Precision of 92.9%, Recall of 94.3%, and $F1-score$ of 93.6% on the test set. The proposed method can efficiently achieve the identification of CVs in test samples and search for CV candidates in unlabeled images. The image data vastly outnumber the spectra in the SDSS-released data. With supplementary follow-up observations or spectra, the proposed model can help astronomers in seeking and detecting CVs in a new manner to ensure that a more extensive CV catalog can be built. The proposed model may also be applied to the detection of other kinds of celestial objects.
Astronomy & Astrophysics↗
The Dark Energy Survey Supernova Program: Cosmological Biases from Host Galaxy Mismatch of Type Ia Supernovae
Abstract Redshift measurements, primarily obtained from host galaxies, are essential for inferring cosmological parameters from type Ia supernovae (SNe Ia). Matching SNe to host galaxies using images is nontrivial, resulting in a subset of SNe with mismatched hosts and thus incorrect redshifts. We evaluate the host galaxy mismatch rate and resulting biases on cosmological parameters from simulations modeled after the Dark Energy Survey 5 Yr (DES-SN5YR) photometric sample. For both DES-SN5YR data and simulations, we employ the directional light radius method for host galaxy matching. In our SN Ia simulations, we find that 1.7% of SNe are matched to the wrong host galaxy, with redshift differences between the true and matched hosts of up to 0.6. Using our analysis pipeline, we determine the shift in the dark energy equation of state parameter (Δ w ) due to including SNe with incorrect host galaxy matches. For SN Ia–only simulations, we find Δ w = 0.0013 ± 0.0026 with constraints from the cosmic microwave background. Including core-collapse SNe and peculiar SNe Ia in the simulation, we find that Δ w ranges from 0.0009 to 0.0032, depending on the photometric classifier used. This bias is an order of magnitude smaller than the expected total uncertainty on w from the DES-SN5YR sample of ∼0.03. We conclude that the bias on w from host galaxy mismatch is much smaller than the uncertainties expected from the DES-SN5YR sample, but we encourage further studies to reduce this bias through better host-matching algorithms or selection cuts.
79 ASTRONOMY AND ASTROPHYSICS↗
TYC 2990-127-1: An Algol-type SB2 binary system of subgiant and red giant with a probable ongoing mass-transfer
ABSTRACT We present a study of the spectroscopic binary TYC 2990-127-1 from the LAMOST survey. We use full-spectrum fitting to derive radial velocities and spectral parameters. The high mass ratio indicates that the system underwent mass transfer in the past. We compute the orbital solution and find that it is a very close sub-giant/red giant pair on circular orbit, slightly inclined to the sky-plane. Fitting of the TESS photometrical data confirms this and suggests an inclination of i ∼ 39.8°. The light curve and spectrum around Hα show signs of irregular variability, which supports ongoing mass transfer. The binary evolution simulations suggest that the binary may experience non-conservative mass transfer with accretion efficiency 0.3, and the binary will enter into common envelope (CE) phase in the subsequent evolution. The remnant product after the ejection of CE may be a detached double helium white dwarf (He WD) or a merger.
79 ASTRONOMY AND ASTROPHYSICS↗
On the intermediate Jacobian of M5-branes
Abstract We study Euclidean M5-branes wrapping vertical divisors in elliptic Calabi-Yau fourfold compactifications of M/F-theory that admit a Sen limit. We construct these Calabi-Yau fourfolds as elliptic fibrations over coordinate flip O3/O7 orientifolds of toric hypersurface Calabi-Yau threefolds. We devise a method to analyze the Hodge structure (and hence the dimension of the intermediate Jacobian) of vertical divisors in these fourfolds, using only the data available from a type IIB compactification on the O3/O7 Calabi-Yau orientifold. Our method utilizes simple combinatorial formulae (that we prove) for the equivariant Hodge numbers of the Calabi-Yau orientifolds and their prime toric divisors, along with a formula for the Euler characteristic of vertical divisors in the corresponding elliptic Calabi-Yau fourfold. Our formula for the Euler characteristic includes a conjectured correction term that accounts for the contributions of pointlike terminal ℤ 2 singularities corresponding to perturbative O3-planes. We check our conjecture in a number of explicit examples and find perfect agreement with the results of direct computations.
Physics↗
The Calar Alto Legacy Integral Field Area survey: extended and remastered data release
ABSTRACT This paper describes the extended data release (eDR) of the Calar Alto Legacy Integral Field Area (CALIFA) survey. It comprises science-grade quality data for 895 galaxies obtained with the Potsdam Multi Aperture Spectograph/PPak instrument at the 3.5-m telescope at the Calar Alto Observatory along the last 12 yr, using the V500 setup [3700–7500 Å, 6 Å/full-width at half-maximum (FWHM)] and the CALIFA observing strategy. It includes galaxies of any morphological type, star formation stage, a wide range of stellar masses (∼107–1012 M⊙), at an average redshift of ∼0.015 (90 per cent within 0.005 < z < 0.05). Primarily selected based on the projected size and apparent magnitude, we demonstrate that it can be volume corrected resulting in a statistically limited but representative sample of the population of galaxies in the nearby Universe. All the data were homogeneous re-reduced, introducing a set of modifications to the previous reduction. The most relevant is the development and implementation of a new cube-reconstruction algorithm that provides with an (almost) seeing-limited spatial resolution (FWHMPSF ∼ 1.0 arcsec). To illustrate the usability and quality of the data, we extracted two aperture spectra for each galaxy (central 1.5 arcsec and fully integrated), and analyse them using pyFIT3D. We obtain a set of observational and physical properties of both the stellar populations and the ionized gas, that have been compared for the two apertures, exploring their distributions as a function of the stellar masses and morphologies of the galaxies, comparing with recent results in the literature.
Sánchez, S. F. (ORCID:0000000164449307)↗
H2 Materials Compatibility of Low Cost, High Pressure, Polymer H2 Dispensing Hoses
NanoSonic was recently awarded a DOE Phase IIB SBIR program for the commercialization of an innovative metal-free polymer based H2 dispensing hose to make H2 an economically viable fuel alternative to gasoline. During the Phase I and Phase II base programs, NanoSonic's H2 hose demonstrated ultra-high hydrostatic burst strength values > 31,000 psi where failure occurred due to fitting slippage, rather than hose burst. Additionally, our hoses survived > 51,000 pressure impulse cycles at 12,000 psi over a thermal cycle of -40 °C to 85 °C. These hoses also failed due to fitting slippage. Thus, our Phase IIB program is centralized on the addition of a new fitting, polymer hose refinement, and validation of a complete hose and fitting system certified for use with H2. While NanoSonic has partnered with the National Renewable Energy Laboratory (NREL) to test our hose on their robotic H2 dispensing system, we are also seeking durability with the H2 environment at the molecular level. Here, NanoSonic proposes a CRADA with Pacific Northwest National Laboratory (PNNL), who has expertise in H2 polymer materials compatibility. Together, we will determine the lifetime of our H2 hose polymer and composite constituents via: 1) time-temperature superposition (TTS) studies via dynamic mechanical analysis (DMA) under H2, 2) friction and wear resistance under in situ H2 tribometry, and 3) multi-axis strain testing under cryogenic conditions. PNNL has the unique test equipment essential to gain this type of insight and lifetime prediction data. Importantly, the work conducted under the proposed CRADA will increase the safety and reliability of our H2 hoses while expanding the market for use of our low H2 permeation polymers and durable cryogenic composites to realize the H2@Scale objectives to reduce the cost of H2.
08 HYDROGEN↗
Progressive transfer learning for advancing machine learning-based reduced-order modeling
Abstract To maximize knowledge transfer and improve the data requirement for data-driven machine learning (ML) modeling, a progressive transfer learning for reduced-order modeling (p-ROM) framework is proposed. A key concept of p-ROM is to selectively transfer knowledge from previously trained ML models and effectively develop a new ML model(s) for unseen tasks by optimizing information gates in hidden layers. The p-ROM framework is designed to work with any type of data-driven ROMs. For demonstration purposes, we evaluate the p-ROM with specific Barlow Twins ROMs (p-BT-ROMs) to highlight how progress learning can apply to multiple topological and physical problems with an emphasis on a small training set regime. The proposed p-BT-ROM framework has been tested using multiple examples, including transport, flow, and solid mechanics, to illustrate the importance of progressive knowledge transfer and its impact on model accuracy with reduced training samples. In both similar and different topologies, p-BT-ROM achieves improved model accuracy with much less training data. For instance, p-BT-ROM with four-parent (i.e., pre-trained models) outperforms the no-parent counterpart trained on data nine times larger. The p-ROM framework is poised to significantly enhance the capabilities of ML-based ROM approaches for scientific and engineering applications by mitigating data scarcity through progressively transferring knowledge.
97 MATHEMATICS AND COMPUTING↗
Conversions between gas-phase metallicities in MaNGA
ABSTRACT We present polynomial conversions between each of 11 different strong line gas-phase metallicity calibrations, each based on ∼1.1 million star-forming spaxels in the public Sloan Digital Sky Survey (SDSS) Data Release 15 (DR15) Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. For this sample, which is ∼20 times larger than previous works, we present fifth-order polynomial fits for each of 110 possible calibration conversions, for both Small Magellanic Cloud-type and Milky Way-type dust corrections. The typical 2σ scatter around our polynomial fits is 0.1 dex; we present the range over which the metallicities are valid. Conversions between metallicities which rely on the same set of line ratios, or a heavily shared set of emission lines, have reduced scatter in their conversions relative to those conversions with little overlap in required emission lines. Calibration conversions with less consistent sets of emission lines also have increased galaxy-to-galaxy variability, and this variability can account for up to 35 per cent of the total scatter. We also compare our conversions to previous work with the single fibre SDSS DR7 spectra along with higher spatial resolution data from the TYPHOON Integral Field Spectroscopy survey, resulting in comparison samples with spatial resolutions from several kpc down to ∼100 pc. Our metallicity conversions, obtained with the large sample of MaNGA, are robust against the influence of diffuse ionized gas, redshift, effective radius, and spatial blurring, and are therefore consistent across both integrated spectra and the high-resolution integral field spectroscopy data.
79 ASTRONOMY AND ASTROPHYSICS↗
Transcript and metabolite network perturbations in lignin biosynthetic mutants of Arabidopsis
Abstract Lignin, one of the most abundant polymers in plants, is derived from the phenylpropanoid pathway, which also gives rise to an array of metabolites that are essential for plant fitness. Genetic engineering of lignification can cause drastic changes in transcription and metabolite accumulation with or without an accompanying development phenotype. To understand the impact of lignin perturbation, we analyzed transcriptome and metabolite data from the rapidly lignifying stem tissue in 13 selected phenylpropanoid mutants and wild-type Arabidopsis (Arabidopsis thaliana). Our dataset contains 20,974 expressed genes, of which over 26% had altered transcript levels in at least one mutant, and 18 targeted metabolites, all of which displayed altered accumulation in at least one mutant. We found that lignin biosynthesis and phenylalanine supply via the shikimate pathway are tightly co-regulated at the transcriptional level. The hierarchical clustering analysis of differentially expressed genes (DEGs) grouped the 13 mutants into 5 subgroups with similar profiles of mis-regulated genes. Functional analysis of the DEGs in these mutants and correlation between gene expression and metabolite accumulation revealed system-wide effects on transcripts involved in multiple biological processes.
Plant Sciences↗
Development of data‐driven exponential integrators with application to modeling of delay photocurrents
Abstract Radiation‐induced photocurrent effects represent a threat to microelectronic components operating in space, manmade and terrestrial radiation environments. Analysis of these threats by circuit simulations requires accurate and computationally efficient compact models. Most existing compact models are based on closed form analytic solutions of the governing equations and require empirical assumptions and idealizations that can limit their validity. In this paper we formulate an alternative numerical, data‐driven approach that learns a compact model from data representative of the type of measurements one can obtain in an experimental facility. To develop the model we start from a generic discrete‐time dynamical system and then use physics knowledge to refine its structure. Numerical studies demonstrate the potential of the model and establish some empirical guidelines for its training.
Bochev, Pavel↗
High‐Pressure Phase Stability and Thermoelastic Properties of Iron Carbonitrides and Nitrogen in the Deep Earth
Abstract Iron‐dominant metallic phases are likely the primary hosts for nitrogen in the reduced deep Earth, hence the storage of nitrogen in the lower mantle and the core is governed by the behavior of the Fe‐N‐C system at high temperatures and pressures. In this study, phase transitions and thermoelastic properties of iron carbonitrides were investigated at high pressure‐temperature conditions by diamond anvil cell experiments and first‐principles calculations. Experimental data revealed no phase transition in ε ‐type Fe 4 (N 0.6 C 0.4 ) or Fe 7 (N 0.75 C 0.25 ) 3 up to 60 GPa at room temperature. At high temperature, Fe 7 (N 0.75 C 0.25 ) 3 transforms into the Fe 3 C‐type phase at ∼27 GPa, and then into the Fe 7 C 3 ‐type phase at ∼45 GPa, which is also corroborated by our theoretical calculations. We found that the phase stability of iron carbonitrides mainly depends on the N/C ratio, and the elastic properties of iron carbonitrides are dominantly affected by the Fe/(N+C) ratio. Iron carbonitrides with diverse structures may be the main host for nitrogen in the deep mantle. Some iron carbonitride inclusions in lower mantle diamonds could be the residue of the primordial mantle or originate from subducted nitrogen‐bearing materials, rather than iron‐enriched phases of the outer core. In addition, our experiments confirmed the existence of Fe 7 C 3 ‐type Fe 7 C 3 ‐Fe 7 N 3 solid solutions above 40 GPa. Fe 7 C 3 ‐type Fe 7 (C, N) 3 has comparable density and thermoelastic properties to its isostructural endmembers and may be a promising candidate constituent of the Earth's inner core.
Huang, Shengxuan↗
Data-driven electron-diffraction approach reveals local short-range ordering in CrCoNi with ordering effects
Abstract The exceptional mechanical strength of medium/high-entropy alloys has been attributed to hardening in random solid solutions. Here, we evidence non-random chemical mixing in a CrCoNi alloy, resulting from short-range ordering. A data-mining approach of electron nanodiffraction enabled the study, which is assisted by neutron scattering, atom probe tomography, and diffraction simulation using first-principles theory models. Two samples, one homogenized and one heat-treated, are observed. In both samples, results reveal two types of short-range-order inside nanoclusters that minimize the Cr–Cr nearest neighbors (L1 2 ) or segregate Cr on alternating close-packed planes (L1 1 ). The L1 1 is predominant in the homogenized sample, while the L1 2 formation is promoted by heat-treatment, with the latter being accompanied by a dramatic change in dislocation-slip behavior. These findings uncover short-range order and the resulted chemical heterogeneities behind the mechanical strength in CrCoNi, providing general opportunities for atomistic-structure study in concentrated alloys for the design of strong and ductile materials.
36 MATERIALS SCIENCE↗