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At least 991 records · Page 55

Assessment of Machine Learning Wall Modeling Approaches for Large Eddy Simulation of Gas Turbine Film Cooling Flows: An a Priori Study

Here, in this work, a priori analysis of machine learning (ML) strategies is carried out with the goal of data-driven wall modeling for large eddy simulation (LES) of gas turbine film cooling flows. High-fidelity flow datasets are extracted from wall-resolved LES (WRLES) of flow over a flat plate interacting with the coolant flow supplied by a single row of 7-7-7 shaped cooling holes inclined at 30 degrees with the flat plate at different blowing ratios (BR). The WRLES are performed using the high-order Nek5000 spectral element computational fluid dynamics (CFD) solver. Light gradient boosting machine (LightGBM) is employed as the ML algorithm for the data-driven wall model. Parametric tests are conducted to systematically assess the influence of a wide range of input flow features (velocity components, velocity gradients, pressure gradients, and fluid properties) on the accuracy of ML wall model with respect to prediction of wall shear stress. In addition, the use of spatial stencil and time delay is also explored within the ML wall modeling framework. It is shown that features associated with gradients of the streamwise and spanwise velocity components have a major impact on the prediction fidelity of wall model, while the effect of gradients of wall-normal velocity component is found to be negligible. Moreover, adding flow feature information from an x-y-z spatial stencil significantly improves the ML model accuracy and generalizability compared to just using local flow features from the matching location. Overall, highest prediction accuracy is achieved when both spatial stencil and time delay features are incorporated within the data-driven wall modeling paradigm.

33 ADVANCED PROPULSION SYSTEMS↗

Quantifying Polaron Mole Fractions and Interpreting Spectral Changes in Molecularly Doped Conjugated Polymers

Molecular doping of conjugated polymers causes bleaching of the neutral absorbance and results in new polaron absorbance transitions in the mid and near infrared. In this report the concentration dependent changes in the spectra for a series of molecularly doped diketopyrrolopyrrole (DPP) co-polymers with a series of ultra-high electron affinity cyanotrimethylenecyclopropane-based dopants is analyzed. With these strong dopants the polaron mole fraction (Θ) reaches saturation. Analysis of the full spectrum enables separation of neutral and polaron signals and quantification of the polaron mole fraction using a simple noninteracting site model. The peak ratios for both neutral and polaron peaks change systematically with increasing polaron mole fraction for all measured polymers. Analysis of the spectral changes indicates that the polaron mole fraction can be quantified to within 5%. While the total change in the absorbance spectrum with increasing polaron mole fraction is linear, the lowest energy polaron peak (P1) grows nonlinearly, which indicates increased polarization/delocalization. Molecular doping of polymers that form either H- or J-aggregates shows systematically different spectral changes in the vibronic peak ratios of the neutral spectra and provides insights into the polymer configuration at undoped sites in the film.

36 MATERIALS SCIENCE↗

Charge Movement and Structural Changes in the Gas-Phase Unfolding of Multimeric Protein Complexes Captured by Native Top-Down Mass Spectrometry

The extent to which noncovalent protein complexes retain native structure in the gas phase is highly dependent on experimental conditions. Energetic collisions with background gas can cause structural changes ranging from unfolding to subunit dissociation. Additionally, recent studies have highlighted the role of charge in such structural changes, but the mechanism is not completely understood. In this study, native top down (native TD) mass spectrometry was used to probe gas-phase structural changes of alcohol dehydrogenase (ADH, 4mer) under varying degrees of in-source activation. Changes in covalent backbone fragments produced by electron capture dissociation (ECD) or 193 nm ultraviolet photodissociation (UVPD) were correlated to structural changes of the ADH 4mer. ECD fragments indicated unfolding started at the N-terminus, and the charge states of UVPD fragments enabled monitoring of charge migration to the unfolded regions. Interestingly, UVPD fragments also indicated that the charge at the “unfolding” N-terminus of ADH decreased at high in-source activation energies after the initial increase. We proposed a possible “refolding-after-unfolding” mechanism, as further supported by monitoring hydrogen elimination from radical a-ions produced by UVPD at the N-terminus of ADH. However, “refolding-after-unfolding” with increasing in-source activation was not observed for charge-reduced ADH, which likely adopted compact structures that are resistant to both charge migration and unfolding. Combined, these results support a charge-directed unfolding mechanism for protein complexes. Overall, an experimental framework was outlined for utilizing native TD to generate structure-informative mass spectral signatures for protein complexes that complement other structure characterization techniques, such as ion mobility spectrometry and computational modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Water–Hydrocarbon Interactions in Anionic Pyrene Monohydrate

Interactions between water and polycyclic aromatic hydrocarbons are essential in many aspects of chemistry, from interstellar and atmospheric processes to interfacial hydrophobicity and wetting phenomena. Despite their growing importance, the intermolecular potentials of the water-hydrocarbon interactions are underdeveloped compared to water-water potentials, and there are similarly few experimental probes that are sensitive to the details of the water-hydrocarbon potential. We present a combined experimental and computational study of anionic pyrene monohydrate, one of the simplest water/hydrocarbon clusters. The action spectrum in the OH region of the mass-selected cluster ion provides a rigorous benchmark for intermolecular potentials and computational methodologies. We identify missing intermolecular interactions and shortcomings in conventional dynamics calculations by comparing experimental data to density functional theory and classical molecular dynamics calculations. Kinetic trapping is prevalent, even for one water molecule and one pyrene molecule, leading to slow equilibration in conventional molecular dynamics calculations, even on nanosecond timescales and at low temperatures (50 K). At constant energy, temperature fluctuations for the pair of molecules are substantial. Immersing the system in a bath of soft spheres and employing parallel tempering alleviates kinetic trapping and dampens temperature fluctuations, bringing the system closer to the thermodynamic limit. With such augmented sampling, a simple, flexible water model reproduces the linewidth and the asymmetric broadening of the symmetric OH stretching mode, which we assign to spectral diffusion. In the OH stretching region, dynamics calculations predict a more intense antisymmetric peak than experiments observe but do not predict the bimodal split symmetric peak that the experiments show. Furthermore, our work suggests that electronic polarization, missing in the empirical force field, is responsible for the first discrepancy and that quantum nuclear effects, captured neither in density functional theory nor in classical dynamics, may be responsible for the second.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ultrafast Optical Nanoscopy of Carrier Dynamics in Silicon Nanowires

Carrier distribution and dynamics in semiconductor materials often govern their physical properties that are critical to functionalities and performance in industrial applications. The continued miniaturization of electronic and photonic devices calls for tools to probe carrier behavior in semiconductors simultaneously at the picosecond time and nanometer length scales. Here, in this paper, we report pump–probe optical nanoscopy in the visible-near-infrared spectral region to characterize the carrier dynamics in silicon nanostructures. By coupling experiments with the point-dipole model, we resolve the size-dependent photoexcited carrier lifetime in individual silicon nanowires. We further demonstrate local carrier decay time mapping in silicon nanostructures with a sub-50 nm spatial resolution. Our study enables the nanoimaging of ultrafast carrier kinetics, which will find promising applications in the future design of a broad range of electronic, photonic, and optoelectronic devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

MolDiscovery: learning mass spectrometry fragmentation of small molecules

Identification of small molecules is a critical task in various areas of life science. Recent advances in mass spectrometry have enabled the collection of tandem mass spectra of small molecules from hundreds of thousands of environments. To identify which molecules are present in a sample, one can search mass spectra collected from the sample against millions of molecular structures in small molecule databases. The existing approaches are based on chemistry domain knowledge, and they fail to explain many of the peaks in mass spectra of small molecules. Here, we present molDiscovery, a mass spectral database search method that improves both efficiency and accuracy of small molecule identification by learning a probabilistic model to match small molecules with their mass spectra. A search of over 8 million spectra from the Global Natural Product Social molecular networking infrastructure shows that molDiscovery correctly identify six times more unique small molecules than previous methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spectrum and extension of the inverse-Compton emission of the Crab Nebula from a combined Fermi -LAT and H.E.S.S. analysis

The Crab Nebula is a unique laboratory for studying the acceleration of electrons and positrons through their non-thermal radiation. Observations of very-high-energy γ rays from the Crab Nebula have provided important constraints for modelling its broadband emission. We present the first fully self-consistent analysis of the Crab Nebula’s γ-ray emission between 1 GeV and ∼100 TeV, that is, over five orders of magnitude in energy. Using the open-source software package GAMMAPY, we combined 11.4 yr of data from the Fermi Large Area Telescope and 80 h of High Energy Stereoscopic System (H.E.S.S.) data at the event level and provide a measurement of the spatial extension of the nebula and its energy spectrum. We find evidence for a shrinking of the nebula with increasing γ-ray energy. Furthermore, we fitted several phenomenological models to the measured data, finding that none of them can fully describe the spatial extension and the spectral energy distribution at the same time. Especially the extension measured at TeV energies appears too large when compared to the X-ray emission. Our measurements probe the structure of the magnetic field between the pulsar wind termination shock and the dust torus, and we conclude that the magnetic field strength decreases with increasing distance from the pulsar. We complement our study with a careful assessment of systematic uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗

Machine learning on neutron and x-ray scattering and spectroscopies

Neutron and x-ray scattering represent two classes of state-of-the-art materials characterization techniques that measure materials structural and dynamical properties with high precision. These techniques play critical roles in understanding a wide variety of materials systems from catalysts to polymers, nanomaterials to macromolecules, and energy materials to quantum materials. In recent years, neutron and x-ray scattering have received a significant boost due to the development and increased application of machine learning to materials problems. This article reviews the recent progress in applying machine learning techniques to augment various neutron and x-ray techniques, including neutron scattering, x-ray absorption, x-ray scattering, and photoemission. We highlight the integration of machine learning methods into the typical workflow of scattering experiments, focusing on problems that challenge traditional analysis approaches but are addressable through machine learning, including leveraging the knowledge of simple materials to model more complicated systems, learning with limited data or incomplete labels, identifying meaningful spectra and materials representations, mitigating spectral noise, and others. We present an outlook on a few emerging roles machine learning may play in broad types of scattering and spectroscopic problems in the foreseeable future.

Chen, Zhantao↗

Machine Learning–Augmented Laser-Induced Breakdown Spectroscopy for Spectral Discrimination of Iron Oxalates

Enhanced characterization and phase identification of post-PUREX Pu Oxalates (PuOXA) are pivotal for nonproliferation and pre-detonation nuclear forensics. Despite significant advances in the characterization of PuO 2 samples, little is known about the impact of both the chemical structure and oxidation states of PuOXA (i.e., Pu(III) and Pu(IV)) have on optical emission signatures. Here, we demonstrate the analytical capabilities of laser-induced breakdown spectroscopy (LIBS) applied to Fe(II) and Fe(III) oxalate samples as surrogates for PuOXA, highlighting the discriminating features in the LIBS emission spectra arising from differences in the oxidation states within mixed FeOXA samples. We report the enhancement of spectral feature selection using Principal Component Analysis (PCA), which enables the analytical superiority of machine learning algorithms such as Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Random Forest Regression (RFR) over conventional univariate techniques for phase discrimination and chemometric analysis. Cluster analysis revealed how both matrix effects and laser ablation influence cluster separability by introducing spectral artifacts that misdirect the maximization of variance. PCA-selected emission lines were used in the regression models, demonstrating that both univariate and multivariate linear regression models (i.e., PLSR and SVR) can achieve acceptable performance, with machine learning models outperforming conventional calibration regressions. Furthermore, the application of non-linearly activated PCA-selected emission lines illustrates how simplifying the data while retaining captured variance enables the use of less complex and more computationally efficient models. Furthermore, this is particularly evident in the underperformance of RFR, which suffers from increased computational costs and overfitting owing to its high complexity.

Oxalates↗

Development and preliminary results of 270 GHz microwave forward scattering diagnostic system on the experimental advanced superconducting tokamak (EAST)

To measure localized (intermediate, high) poloidal wavenumber electron density fluctuations, a tangential millimeter-wave collective scattering system has been designed and successfully developed on the experimental advanced superconducting tokamak (EAST). This innovative system employs a 270 GHz mm-wave probe beam, emitted from the mid-plane of Port K and directed towards Port P after passing through a combination of two in-vessel mirrors. Here these two ports are located on the EAST device’s midplane and are 110° apart. The downward scattered signals pass through two in-vessel mirrors, and exit through the P window. The received multi-channel separated scattering signals are arranged along the poloidal direction. This optical arrangement makes the monitored turbulent wave number is poloidal dominant and up to 40 cm −1 . The tangential microwave scattering scheme enables this diagnostic to monitor local density fluctuations, with typically a radial spatial resolution △ R = 5 cm, and a wavenumber resolution of △ k = 0.4 cm −1 . The scattering system underwent comprehensive laboratory testing in 2023, with installation finalized in 2024. The system features steerable launch and receiver optics, allowing remote control to position the scattering volume from normalized radius ρ –0 to the pedestal region on a shot-by-shot basis. Effective experimental data, characterized by distinct off-center spectral peaks, have been successfully obtained in neutral beam-heated plasmas on EAST. The beam tracing forward modeling has been employed for experimental data interpretation. The advanced millimeter-wave scattering system provides fluctuation measurement capability from ion temperature gradient to electron temperature gradient scale on low field side. Preliminary experimental density fluctuation data have been successfully obtained in neutral beam-heated plasmas on EAST. The localized measurement will be used for kinetic turbulence transport numerical simulation validation.

high-k collective scattering↗

Radio AGN selection in LoTSS DR2

ABSTRACT The wide-area component of the LOFAR Two-Metre Sky Survey (LoTSS) is currently the largest radio survey ever carried out, and a large fraction of the 4.5 million radio sources it contains have been optically identified with galaxies or quasars with spectroscopic or photometric redshifts. Identification of radio-luminous active galactic nucleus (AGN) from this LoTSS source catalogue is not only important from the point of view of understanding the accretion history of the universe, but also enables a wide range of other science. However, at present the vast majority of the optical identifications lack spectroscopic information or well-sampled spectral energy distributions. We show that colour and absolute magnitude information from the Wide-Field Infrared Survey Explorer (WISE) allows for the robust and efficient selection of radio AGN candidates, generating a radio AGN candidate sample of around 600 000 objects with flux density $> 1.1$ mJy, spanning 144-MHz luminosities between $10^{21}$ and $10^{29}$ W Hz$^{-1}$. We use the catalogue to constrain the total sky density of radio-luminous AGN and the evolution of their luminosity function between $z=0$ and $z\approx 1$, and show that the typical mass of their host galaxies, around $10^{11} {\rm M}_\odot$, is essentially independent of radio luminosity above around $L_{144} \approx 10^{24}$ W Hz$^{-1}$. Combining with Very Large Array Sky Survey (VLASS) data, we show that the core prominences, radio spectral indices and variability of extended sources from the sample are qualitatively consistent with the expectations from unified models. A catalogue of the radio AGN candidates is released with this paper.

Hardcastle, M. J. (ORCID:0000000342231117)↗

Particle production as a function of charged-particle flattenicity in 𝑝⁢𝑝 collisions at $\sqrt{s}$ = 13 TeV

This paper reports the first measurement of the transverse momentum (𝑝 T ) spectra of primary charged pions, kaons, (anti)protons, and unidentified particles as a function of the charged-particle flattenicity in pp collisions at $\sqrt{s}$ =13 TeV. Flattenicity is a novel event shape observable that is measured in the pseudorapidity intervals covered by the V0 detector, 2.8 < 𝜂 < 5.1 and −3.7 < 𝜂 < −1.7. According to QCD-inspired phenomenological models, it shows sensitivity to multiparton interactions and is less affected by biases toward larger 𝑝 T due to local multiplicity fluctuations in the V0 acceptance than multiplicity. The analysis is performed in minimum-bias (MB) as well as in high-multiplicity events up to 𝑝 T = 20 GeV/⁢𝑐. The event selection requires at least one charged particle produced in the pseudorapidity interval |𝜂| < 1. The measured 𝑝 T distributions, average 𝑝 T , kaon-to-pion and proton-to-pion particle ratios, presented in this paper, are compared to model calculations using pythia 8 based on color strings and EPOS LHC. The modification of the 𝑝 T -spectral shapes in low-flattenicity events that have large event activity with respect to those measured in MB events develops a pronounced peak at intermediate 𝑝 T (2 < 𝑝 T < 8 GeV/𝑐), and approaches the vicinity of unity at higher 𝑝 T . The results are qualitatively described by pythia, and they show different behavior than those measured as a function of charged-particle multiplicity based on the V0M estimator.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

CERES MODIS Cloud Product Retrievals for Edition 4--Part I: Algorithm Changes

The Edition 2 (Ed2) cloud property retrieval algorithm system was upgraded and applied to the MODerate-resolution Imaging Spectroradiometer (MODIS) data for the Clouds and the Earth's Radiant Energy System (CERES) Edition 4 (Ed4) products. New calibrations for solar channels and the use of the 1.24-μm channel for cloud optical depth (COD) over snow improve the daytime consistency between Terra and Aqua MODIS retrievals. Use of additional spectral channels and revised logic enhanced the cloud-top phase retrieval accuracy. A new ice crystal reflectance model and a CO₂-channel algorithm retrieved higher ice clouds, while a new regional lapse rate technique produced more accurate water cloud heights than in Ed2. Ice cloud base heights are more accurate due to a new cloud thickness parameterization. Overall, CODs increased, especially over the polar (PO) regions. The mean particle sizes increased slightly for water clouds, but more so for ice clouds in the PO areas. New experimental parameters introduced in Ed4 are limited in utility, but will be revised for the next CERES edition. As part of the Ed4 retrieval evaluation, the average properties are compared with those from other algorithms and the differences between individual reference data and matched Ed4 retrievals are explored. Part II of this article provides a comprehensive, objective evaluation of selected parameters. More accurate interpretation of the CERES radiation measurements has resulted from the use of the Ed4 cloud properties.

54 ENVIRONMENTAL SCIENCES↗

Introductory guide to backgrounds in XPS spectra and their impact on determining peak intensities

Photoelectron and Auger peaks are central to most of the important uses of x-ray photoelectron spectroscopy (XPS), and thus, they receive the most attention in many types of analysis. Quantitative chemical analysis using XPS requires the assessment of the intensities of the photoemission peaks of the elements detected. Determination of peak intensities requires separation of the photoelectron peak signals from the background on which the peaks rest. For the determination of peak area intensities, the background is subtracted from overall signal intensity. The spectral background is also critical when peak fitting is used to determine intensities of overlapping peaks, and the model of background used in this process can impact the results. In addition to the impact on quantitative analysis, information about the depth distribution of elements in the near surface region can often be obtained by visual inspection of the background and quantified using appropriate modeling. Here, this introductory guide provides some basic information about backgrounds in the XPS analysis, describes the types of background models that are commonly used, suggests some of their strengths and weaknesses, and provides examples of their use and misuse. Although the fundamental nature of some components of the background signals in XPS is not understood, indicating that none of the models in use are fully correct and the area is subject to active research, appropriate good practices have been established for most routine analysis. The guide describes good practices, identifies errors that frequently appear in the literature, and uses examples to demonstrate the impacts of background selections on determinations of peak intensities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-efficiency, single-stage tunable optical parametric amplifier for visible photocathode applications

In this work we present a single-stage optical parametric amplifier (OPA) with an average conversion efficiency up to 38%, tunable between 1.01 and 1.18 µm. The OPA seed is produced by a gain-managed nonlinear fiber amplifier. Numerical modeling of the seed pulse generation shows a linear chirp, a smoothly broadened redshifted spectrum, and a high spectral energy density. When up-converted to the visible through second-harmonic generation, the signal pulses are suitable for visible photocathode excitation.

14 SOLAR ENERGY↗

Hierarchical model reduction driven by a proper orthogonal decomposition for parametrized advection-diffusion-reaction problems

This work combines the Hierarchical Model (HiMod) reduction technique with a standard Proper Orthogonal Decomposition (POD) to solve parametrized partial differential equations for the modeling of advection-diffusion-reaction phenomena in elongated domains (e.g., pipes). This combination leads to what we define as HiPOD model reduction, which merges the reliability of HiMod reduction with the computational efficiency of POD. Two HiPOD techniques are presented and assessed by an extensive numerical verification.

97 MATHEMATICS AND COMPUTING↗

Visual Orbits of Spectroscopic Binaries with the CHARA Array. III. HD 8374 and HD 24546

We present the visual orbits of two long-period spectroscopic binary stars, HD 8374 and HD 24546, using interferometric observations acquired with the CHARA Array and the Palomar Testbed Interferometer. We also obtained new radial velocities from echelle spectra using the APO 3.5 m and Fairborn 2.0 m telescopes. By combining the visual and spectroscopic observations, we solve for the full, three-dimensional orbits and determine the stellar masses and distances to within 3% uncertainty. We then estimate the effective temperature and radius of each component star through Doppler tomography and spectral energy distribution analyses, in order to compare the observed stellar parameters to the predictions of stellar evolution models. For HD 8374, we find masses of M {sub 1} = 1.636 ± 0.050M {sub ⊙} and M {sub 2} = 1.587 ± 0.049M {sub ⊙}, radii of R {sub 1} = 1.84 ± 0.05R {sub ⊙} and R {sub 2} = 1.66 ± 0.12R {sub ⊙}, temperatures of T{sub eff1}=7280±110 K and T{sub eff2}=7280±120 K, and an estimated age of 1.0 Gyr. For HD 24546, we find masses of M {sub 1} = 1.434 ± 0.014M {sub ⊙} and M {sub 2} = 1.409 ± 0.014M {sub ⊙}, radii of R {sub 1} = 1.67 ± 0.06R {sub ⊙} and R {sub 2} = 1.60 ± 0.10R {sub ⊙}, temperatures of T{sub eff1}=6790±120 K and T{sub eff2}=6770±90 K, and an estimated age of 1.4 Gyr. HD 24546 is therefore too old to be a member of the Hyades cluster, despite its physical proximity to the group.

79 ASTRONOMY AND ASTROPHYSICS↗

Global X-Ray Properties of the Vela and Puppis A Supernova Remnants

The Vela and Puppis A supernova remnants (SNRs) comprise a large emission region of ∼8° diameter in the soft X-ray sky. The HaloSat CubeSat mission provides the first soft X-ray (0.4–7 keV) observation of the entire Vela SNR and Puppis A SNR region with a single pointing and moderate spectral resolution. HaloSat observations of the Vela SNR are best fit with a two-temperature thermal plasma model consisting of a cooler component with kT{sub 1}=0.19{sub −0.01}{sup +0.01} keV in collisional ionization equilibrium and a hotter component with kT{sub 2}=1.06{sub −0.27}{sup +0.45} keV in nonequilibrium ionization. Observations of the Puppis A SNR are best fit with a single-component plane-parallel shocked plasma model with kT=0.86{sub −0.05}{sup +0.06} keV in nonequilibrium ionization. For the first time, we find the total X-ray luminosities of both components of the Vela SNR spectrum in the 0.5–7 keV energy band to be L{sub X}=4.4{sub −1.4}{sup +1.4}×10{sup 34} erg s{sup −1} for the cooler component and L{sub X}=4.1{sub −1.5}{sup +1.8}×10{sup 34} erg s{sup −1} for the hotter component. We find the total X-ray luminosities of the Vela and Puppis A SNRs to be L{sub X}=8.4×10{sup 34} erg s{sup −1} and L{sub X}=6.7{sub −0.9}{sup +1.1}×10{sup 36} erg s{sup −1}.

79 ASTRONOMY AND ASTROPHYSICS↗