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At least 109 records · Page 6

A measurement of the Hubble constant from the X-ray properties and the Sunyaev-Zel'dovich effect of Abell 2218

The distance of the cluster of galaxies Abell 2218, and hence the value of the Hubble constant, has been measured by comparing the X-ray properties and the Sunyaev-Zel'dovich effect of the cluster. The result for the Hubble constant is H(sub zero) = 65 +/- 25 km/s/MPC, where the error includes the random and systematic errors, combined in quadrature, and the largest contributions to the overall error come from systematic errors in the Sunyaev-Zel'dovich effect data and in the X-ray spectrum of the cluster. The X-ray and Sunyaev-Zel'dovich effect data are consistent with the same model for the intergalactic medium in Abell 2218 (an isothermal Beta-model with Beta is about 0.65 and cluster core radius about 1.0 min). A prevous report of a smaller Hubble constant, found by applying the same method on the same cluster, is shown to be based on a model for the cluster gas that is inconsistent with the Einstein IPC data. The present result for the Hubble constant is consistent with the value found earlier for the cluster Abell 665: by combining the results of the method for both clusters we conclude that the value of the Hubble constant is H(sub zero) = 55 +/- 17 km/s/MPC.

Birkinshaw, M.↗

Porosity Area Fraction Analysis of Bonded Borosilicate Specimens From in-Situ Optical Imagery

Image segmentation methods are routinely used to analyze data derived in nondestructive testing scenarios. A typical problem in this area is to estimate porosity from X-ray Computed Tomography (CT) inspections. This investigation aims to understand the effectiveness of open-source image segmentation methods for porosity estimation from optical images in the context of strength analysis of bonded materials and provides a benchmark of performance against a standard commercial software package. The rank ordering of the specimens by porosity area fraction is consistent across both methods.

Porosity area fraction↗

In situ synchrotron diffraction and modeling of non-equilibrium solidification of a MnFeCoNiCu alloy

The solidification mechanism and segregation behavior of laser-melted Mn 35 Fe 5 Co 20 Ni 20 Cu 20 was firstly investigated via in situ synchrotron x-ray diffraction at millisecond temporal resolution. The transient composition evolution of the random solid solution during sequential solidification of dendritic and interdendritic regions complicates the analysis of synchrotron diffraction data via any single conventional tool, such as Rietveld refinement. Therefore, a novel approach combining a hard-sphere approximation model, thermodynamic simulation, thermal expansion measurement and microstructural characterization was developed to assist in a fundamental understanding of the evolution of local composition, lattice parameter, and dendrite volume fraction corresponding to the diffraction data. This methodology yields self-consistent results across different methods. Via this approach, four distinct stages were identified, including: (I) FCC dendrite solidification, (II) solidification of FCC interdendritic region, (III) solid-state interdiffusion and (IV) final cooling with marginal diffusion. It was found out that in Stage I, Cu and Mn were rejected into liquid as Mn 35 Fe 5 Co 20 Ni 20 Cu 20 solidified dendritically. During Stage II, the lattice parameter disparity between dendrite and interdendritic region escalated as Cu and Mn continued segregating into the interdendritic region. After complete solidification, during Stage III, the lattice parameter disparity gradually decreases, demonstrating a degree of composition homogenization. The volume fraction of dendrites slightly grew from 58.3 to 65.5%, based on the evolving composition profile across a dendrite/interdendritic interface in diffusion calculations. Postmortem metallography further confirmed that dendrites have a volume fraction of 64.7 ± 5.3% in the final microstructure.

36 MATERIALS SCIENCE↗

Comparative Analysis of Radial and Random Microstructures of Mesophase Pitch Carbon Fibers

Carbon fibers (CF) with radial and random microstructures are produced. Here, these fibers are subjected to identical treatment before being mechanically tested and analyzed with Weibull analysis, with the results revealing a statistically significant difference in tensile strengths of 2.23 GPa for random CF and 1.69 GPa for radial CF. Raman mapping probed the crystalline structure perpendicular to the fiber axis and found a uniform structure, while wide‐angle X‐ray diffraction showed a significant difference of 7.5 Å in the crystallites’ basal lengths parallel to the fiber. Small‐angle X‐ray scattering is completed parallel to the fiber for the first time. A cross‐section Guinier plot of the 1D azimuthal integration is generated assuming symmetric scattering, and the parallel scatterers are found to have a similar length scale to the crystallite's length, validating the testing method. Finally, transmission electron microscopy is completed on the longitudinal cross‐section of each fiber. The radial carbon fiber is found to have a core–shell structure, as evidenced further by fast Fourier transform images. Through all studies, it is shown that the structure developed during mesophase pitch spinning altered the microstructure, thus impacting the mechanical properties, confirming a direct relationship between processing, structure, and properties.

Scherschel, Alexander [Univ. of Virginia, Charlott↗

Towards fast, accurate predictions of RF simulations via data-driven modeling: Forward and lateral models

Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. More accurate simulations with fast electron diffusion are even slower, requiring multiple hours of run time with parallel processing. The machine learning models use a database of 16,000+ GEN-RAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods implemented in πScope ensure that the database covers the range of 9 input parameters (n e0 , T e0 , I p , B t , R 0 , n ∥︀ , Z e f f , V loop , P LHCD ) with sufficient density in all regions of parameter space. The surrogate models reduce the computation time from minutes-hours to ms with high accuracy across the input parameter space. Data-driven surrogate models also allow for solving inverse and “lateral” problems. A surrogate model for the inverse problem maps from a desired current drive or power deposition profile to a set of input parameters that would result in such a profile, while a surrogate model for the lateral problem maps from a measured experimental quantity such as hard x-ray emission to a current drive or power deposition profile. In conclusion, the πScope database creation workflow is flexible and applicable to other RF simulation codes such as TORIC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Transport coefficient approach for characterizing nonequilibrium dynamics in soft matter

Nonequilibrium states in soft condensed matter require a systematic approach to characterize and model materials, enhancing predictability and applications. Among the tools, X-ray photon correlation spectroscopy (XPCS) provides exceptional temporal and spatial resolution to extract dynamic insight into the properties of the material. However, existing models might overlook intricate details. We introduce an approach for extracting the transport coefficient, denoted as $J(t)$, from the XPCS studies. This coefficient is a fundamental parameter in nonequilibrium statistical mechanics and is crucial for characterizing transport processes within a system. Our method unifies the Green–Kubo formulas associated with various transport coefficients, including gradient flows, particle–particle interactions, friction matrices, and continuous noise. We achieve this by integrating the collective influence of random and systematic forces acting on the particles within the framework of a Markov chain. We initially validated this method using molecular dynamics simulations of a system subjected to changes in temperatures over time. Subsequently, we conducted further verification using experimental systems reported in the literature and known for their complex nonequilibrium characteristics. The results, including the derived $J(t)$ and other relevant physical parameters, align with the previous observations and reveal detailed dynamical information in nonequilibrium states. This approach represents an advancement in XPCS analysis, addressing the growing demand to extract intricate nonequilibrium dynamics. Further, the methods presented are agnostic to the nature of the material system and can be potentially expanded to hard condensed matter systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Deterministic Linear Time for Maximal Poisson‐Disk Sampling using Chocks without Rejection or Approximation

Abstract We show how to sample uniformly within the three‐sided region bounded by a circle, a radial ray, and a tangent, called a “chock.” By dividing a 2D planar rectangle into a background grid, and subtracting Poisson disks from grid squares, we are able to represent the available region for samples exactly using triangles and chocks. Uniform random samples are generated from chock areas precisely without rejection sampling. This provides the first implemented algorithm for precise maximal Poisson‐disk sampling in deterministic linear time. We prove O(n · M(b) log b), where n is the number of samples, b is the bits of numerical precision and M is the cost of multiplication. Prior methods have higher time complexity, take expected time, are non‐maximal, and/or are not Poisson‐disk distributions in the most precise mathematical sense. We fill this theoretical lacuna.

Mitchell, Scott A.↗

Theory of radio occultation by Saturn's rings

The radio occultation technique, as applied to Saturn's rings, is developed as a new method for the study of the physical properties of planetary ring systems. The rings are treated as a Doppler-spread radar target composed of an ensemble of discrete scatterers. The mathematical formulation of the received signal as a random-phasor-sum process is carried out following a conventional radar theory approach, providing a convenient starting point for deriving coherent signal parameters. A classical result is rederived for the equivalent refractive index of the medium. The analysis is generalized to include ringlets of arbitrary width and it is shown that when the width is such that two adjacent rays are differentially perturbed in phase, ray bending that causes focusing of the coherent signal may result. The diffuse component is also treated in detail.

Marouf, E. A.↗

Low-energy enhancement in the magnetic dipole γ-ray strength functions of heavy nuclei

A low-energy enhancement (LEE), which was observed experimentally in the gamma-ray strength function (γSF) describing the decay of compound nuclei, would have profound effects on r-process nucleosynthesis if it persists in heavy neutron-rich nuclei. The LEE was shown to be a feature of the magnetic dipole (M1) strength function in configuration-interaction shell-model calculations in medium-mass nuclei. However, its existence in heavy open-shell nuclei remains an open question. Here, using a combination of many-body methods, we identify a LEE in the M1 γSFs of heavy samarium nuclei. In particular, we use the static-path plus random-phase approximation (SPA+RPA), which includes static and small-amplitude quantal fluctuations beyond the mean field. Using the SPA+RPA strength as a prior, we apply the maximum-entropy method (MEM) to obtain finite-temperature M1 γSFs from exact imaginary-time response functions calculated with the shell model Monte Carlo (SMMC) method. We find that the slope of the LEE in samarium isotopes is roughly independent of the average initial energy over a wide range below the neutron separation energy. As the neutron number increases, strength transfers to a low-energy excitation, which we interpret as the scissors mode built on top of excited states.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Binary pseudo-random array (BPRA) for inspection and calibration for cylindrical wavefront interferometry

High-accuracy metrology is vitally important in manufacturing ultra-high-quality free-form mirrors designed to manipulate X-ray light with nanometer-scale wavelengths. However, surface topography measurements are instrument dependent, and without the knowledge of how the instrument performs under the practical usage conditions, the measured data contain some degree of uncertainty. Binary Pseudo Random Array (BPRA) “white noise” artifact are effective and useful for characterizing the Instrument Transfer Function (ITF) of surface topography metrology tools and wavefront measurement instrument. BPRA artifact contains features with all spatial frequencies in the instrument bandpass with equal weight. As a result, power spectral density of the patterns has a deterministic white-noise-like character that allows direct determination of the ITF with uniform sensitivity over the entire spatial frequency range. The application examples include electron microscopes, x-ray microscopes, interferometric microscopes, and large field-of-view Fizeau Interferometers. Furthermore, we will introduce the application of BPRA method to characterizing the ITF of Cylindrical Wavefront Interferometry (CWI), by developing the BPRA artifact which matches the radius of curvature of the cylindrical wavefront. The data acquisition and analysis procedures for different applications of the ITF calibration technique developed are also discussed.

Munechika, K↗

A comparison of machine learning methods to classify radioactive elements using prompt-gamma-ray neutron activation data

The detection of illicit radiological materials is critical to establishing a robust second line of defence in nuclear security. Neutron-capture prompt-gamma activation analysis (PGAA) can be used to detect multiple radioactive materials across the entire Periodic Table. However, long detection times and a high rate of false positives pose a significant hindrance in the deployment of PGAA-based systems to identify the presence of illicit substances in nuclear forensics. In the present work, six different machine-learning algorithms were developed to classify radioactive elements based on the PGAA energy spectra. The model performance was evaluated using standard classification metrics and trend curves with an emphasis on comparing the effectiveness of algorithms that are best suited for classifying imbalanced datasets. We analyse the classification performance based on Precision, Recall, F1-score, Specificity, Confusion matrix, ROC-AUC curves, and Geometric Mean Score (GMS) measures. The tree-based algorithms (Decision Trees, Random Forest and AdaBoost) have consistently outperformed Support Vector Machine and K-Nearest Neighbours. Based on the results presented, AdaBoost is the preferred classifier to analyse data containing PGAA spectral information due to the high recall and minimal false negatives reported in the minority class.

97 MATHEMATICS AND COMPUTING↗

Emergence of high piezoelectricity from competing local polar order-disorder in relaxor ferroelectrics

Relaxor ferroelectrics are known for outstanding piezoelectric properties, finding a broad range of applications in advanced electromechanical devices. Decoding the origins of the enhanced properties, however, have long been complicated by the heterogeneous local structures. Here, we employ the advanced big-box refinement method by fitting neutron-, X-ray-based total scattering, and X-ray absorption spectrum simultaneously, to extract local atomic polar displacements and construct 3D polar configurations in the classical relaxor ferroelectric Pb(Mg 1/3 Nb 2/3 )O 3 –PbTiO 3 . Our results demonstrate that prevailing order-disorder character accompanied by the continuous rotation of local polar displacements commands the composition-driven global structure evolution. The omnidirectional local polar disordering appears as an indication of macroscopic relaxor characteristics. Combined with phase-field simulations, it demonstrates that the competing local polar order-disorder between different states with balanced local polar length and direction randomness leads to a flattening free-energy profile over a wide polar length, thus giving rise to high piezoelectricity. Our work clarifies that the critical structural feature required for high piezoelectricity is the competition states of local polar rather than relaxor.

42 ENGINEERING↗

Multiframe point-projection radiography imaging based on hybrid X-pinch

This paper demonstrates the possibility of using a new configuration of the hybrid X-pinch to produce a set of spatially and temporarily separate x-ray bursts that could be used for the radiography of dynamic events. To achieve this, a longer than normal wire is placed between the conical electrodes of the hybrid X-pinch, and a set of small spacers (fishing weights) is placed along the wire. Each subsection of the wire then acts as a unique X-pinch, producing its own radiation burst from a small (~3 µm) spot. The timing between bursts is 20–50 ns, and each is <2 ns in duration. For comparison, if a longer wire is simply employed without spacers, hotspots of radiation occur in random positions and the time between any two bursts does not exceed 20 ns. Examples of two and three frame point-projection radiography of solid-state and plasma test objects are given.

47 OTHER INSTRUMENTATION↗

Protein coating composition targets nanoparticles to leaf stomata and trichomes

Plant nanobiotechnology has the potential to revolutionize agriculture. However, the lack of effective methods to deliver nanoparticles (NPs) to the precise locations in plants where they are needed impedes these technological innovations. Here, model gold nanoparticles (AuNP) were coated with citrate, bovine serum albumin (BSA) as a protein control, or LM6-M, an antibody with an affinity for functional groups unique to stomata on leaf surfaces to deliver the AuNPs to stomata. One-month-old Vicia faba leaves were exposed via drop deposition to aqueous suspensions of LM6-M-coated AuNPs and allowed to air dry. After rinsing, Au distribution on the leaf surface was investigated by enhanced dark-field microscopy and X-ray fluorescence mapping. While citrate-coated AuNPs randomly covered the plant leaves, LM6M-AuNPs strongly adhered to the stomata and remained on the leaf surface after rinsing, and BSA-AuNPs specifically targeted trichome hairs. To the authors’ knowledge, this is the first report of active targeting of live leaf structures using NPs coated with molecular recognition molecules. Finally, this proof-of-concept study provides a strategy for future targeted nanopesticide delivery research.

60 APPLIED LIFE SCIENCES↗

Evidence of the beam pattern concept of subsonic jet noise emission

The methods and results are described of an approach toward positively identifying the apparent location and strength of the sound source in a subsonic jet. The Green's function technique is applied to regenerate the three-dimensional distribution of the acoustic far field from measured data on a two-dimensional plane. The apparent sound-source location is also determined by using geometrical ray acoustics. The results revealed a number of features of the subsonic jet noise mechanisms; they show that the apparent sound source is highly localized within the jet flow and that the spontaneous noise emission from such a compact source volume is in the fashion of a narrow beam with random directions. These observable properties of the sound field offer the basis for a beam pattern concept of subsonic jet noise radiation. A powerful and accurate technique of aerodynamic noise measurement is verified. This technique is expected to have important applications in the development of jet noise reduction technology.

Pao, S. P.↗

Method for conducting in situ high-temperature digital image correlation with simultaneous synchrotron measurements under thermomechanical conditions

This work presents a novel method of obtaining in situ strain measurements at high temperature by simultaneous digital image correlation (DIC), which provides the total strain on the specimen surface, and synchrotron x-ray diffraction (XRD), which provides lattice strains of crystalline materials. DIC at high temperature requires specialized techniques to overcome the effects of increased blackbody radiation that would otherwise overexpose the images. The technique presented herein is unique in that it can be used with a sample enclosed in an infrared heater, remotely and simultaneously with synchrotron XRD measurements. The heater included a window for camera access, and the light of the heater lamps is used as illumination. High-temperature paint is used to apply a random speckle pattern to the sample to allow the tracking of displacements and the calculation of the DIC strains. An inexpensive blue theatrical gel filter is used to block interfering visible and infrared light at high temperatures. This technique successfully produces properly exposed images at 870 °C and is expected to perform similarly at higher temperatures. The average strains measured by DIC were validated by an analytical calculation of the theoretical strain. Simultaneous DIC and XRD strain measurements of Inconel 718 (IN718) tensile test specimens were performed under thermal and mechanical loads and evaluated. Finally, this approach uses the fact that with DIC, the total strain is measured, including plastic strain, while with XRD, only elastic strain is captured. The observed differences were discussed with respect to the effective deformation mechanisms.

47 OTHER INSTRUMENTATION↗

Interconnected Nanoporous Polysulfone by the Self-Assembly of Randomly Linked Copolymer Networks and Linear Multiblocks

Porous materials have attracted considerable attention due to their versatile applications, especially in water purification. Interconnected nanoporous structures are distinguished by their high degree of porosity and resistance to clogging, as well as their insensitivity to nanostructural orientation. Previous works on randomly linked copolymer systems have shown that they can effectively produce disordered cocontinuous nanostructures, which upon removal of one component yield interconnected nanoporous materials. However, the cocontinuous nanomaterials previously developed using polystyrene (PS) and poly(d,l-lactic acid) (PLA) strands, and the resulting interconnected nanoporous PS monoliths, were far too brittle to enable practical use as membranes. Here, we study the self-assembly of randomly linked copolymer networks prepared using blocks of the engineering polymer polysulfone (PSU). A wide cocontinuous regime (spanning 40 wt %) was found for randomly end-linked copolymer networks (RECNs) constructed from PSU and PLA strands, via a combination of mechanical testing, gravimetry, small-angle X-ray scattering, and scanning electron microscopy. The PSU/PLA cocontinuous nanomaterial with symmetric composition showed 2.4 times higher Young’s modulus and ~100 times greater toughness than the corresponding PS/PLA sample. The interconnected nanoporous PSU fabricated after etching of PLA even exhibited 1.6 times greater toughness than PS/PLA prior to PLA removal. To facilitate the production of thin films of cocontinuous nanomaterials, we applied solution-processable randomly linked linear PSU/PLA multiblock polymers onto ultrafiltration membranes. Here, the interconnected nanoporous PSU thin film generated by etching PLA was found to effectively reject 50 nm diameter particles without significantly compromising permeability. This discovery presents a valuable addition to the existing techniques used to fabricate PSU membranes. In contrast to traditional methods, which are sensitive to processing conditions, produce a wide range of pore sizes, and offer limited adjustability of pore size, the current technique is anticipated to enable interconnected PSU membranes with more uniform and tailorable porosity.

36 MATERIALS SCIENCE↗

A spatially regularized detector for emergent/re-emergent disease outbreaks

Early detection of outbreaks caused by emergent pathogens, using epidemiological surveillance data i.e., daily case counts, is difficult. This is because the data tend to be noisy during the early epoch of the outbreak. In contrast, the spread-rate of the disease tends to be well-behaved, as it depends only on the mixing patterns of the population and the characteristics of the pathogen, neither of which behave erratically in space-time. In this report, we explore whether the spread-rate can be used for epidemiological surveillance, conditional on case count data. Estimating the spread-rate from case count data allows us to exploit exogenous information, e.g., incubation period distributions etc., which can considerably smooth out any erratic temporal behavior. Further, epidemiological dynamics are spatially correlated, and if case counts are available for multiple areal units e.g., counties, these correlations could potentially be used to suppress noise in the early epoch data. These exogenous information and structure are not exploited by conventional syndromic surveillance detectors to extract a well-behaved latent variable for monitoring purposes. The technical challenge lies in the estimation of the spread-rate field jointly over a collection of areal units; further, the spread-rate varies over time. We develop a method based on mean-field variational inference to approximately estimate the spread-rate field, using a Gaussian Random Field Model for spatial regularization. The method is tested on the estimation of spread-rate in the thirty-three counties of New Mexico and detect the arrival of the Fall 2020 COVID-19 wave in September 2020. We find that the method is scalable, but underestimates the uncertainty in the estimated spread-rate field. We detect the arrival of the Fall 2020 wave a week ahead of conventional syndromic surveillance algorithms, but our simplistic detection algorithm, based on simple anomaly detection, suffers from a high false positive rate, similar to conventional detectors.

59 BASIC BIOLOGICAL SCIENCES↗