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At least 145 records · Page 8

Advanced EXAFS analysis techniques applied to the L -edges of the lanthanide oxides

The unique properties of the lanthanide (Ln) elements make them critical components of modern technologies, such as lasers, anti-corrosive films and catalysts. Thus, there is significant interest in establishing structure–property relationships for Ln-containing materials to advance these technologies. Extended X-ray absorption fine structure (EXAFS) is an excellent technique for this task considering its ability to determine the average local structure around the Ln atoms for both crystalline and amorphous materials. However, the limited availability of EXAFS reference spectra of the Ln oxides and challenges in the EXAFS analysis have hindered the application of this technique to these elements. The challenges include the limited k-range available for the analysis due to the superposition of L-edges on the EXAFS, multielectron excitations (MEEs) creating erroneous peaks in the EXAFS and the presence of inequivalent absorption sites. Herein, we removed MEEs to model the local atomic environment more accurately for light Ln oxides. Further, we investigated the use of cubic and non-cubic lattice expansion to minimize the fitting parameters needed and connect the fitting parameters to physically meaningful crystal parameters. The cubic expansion reduced the number of fitting parameters but resulted in a statistically worse fit. The non-cubic expansion resulted in a similar quality fit and showed non-isotropic expansion in the crystal lattice of Nd 2 O 3 . In total, the EXAFS spectra and the fits for the entire set of Ln oxides (excluding promethium) are included. The knowledge developed here can assist in the structural determination of a wide variety of Ln compounds and can further studies on their structure–property relationships.

36 MATERIALS SCIENCE↗

Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.

Huang, Norden E.↗

Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.

Huang, Norden E.↗

Accurate hydrodynamic force and torque correlations for prolate spheroids from Stokes regime to high Reynolds numbers

Detailed simulations of flow around various prolate spheroids are performed using multi-relaxation time lattice Boltzmann method (LBM). The simulations are performed in the Reynolds numbers range 0.1 ≤ Re ≤ 2000 at different incident angles 0°≤ φ ≤ 90° for various prolate spheroids of aspect ratios 1 ≤ λ ≤ 8. The Re is based on the volume equivalent sphere diameter. From the simulations, accurate correlations for average drag, lift and torque coefficients (C D , C L , and C T respectively) are proposed. The mean deviations between the correlations and the simulation data for C D , C L , and C T are 2%, 6.5%, and 4.7% respectively. Furthermore, the correlations are fitted with the physics in mind such that they can be extrapolated beyond the regimes simulated. The fits are designed such that correlations reduce to analytical (C D and C L ) solutions available for prolate spheroids in the limit Re ≈ 0. At high Re, the correlations mimic the asymptotic flattening of C D as for spheres and therefore, we expect the correlations to be valid until the critical Re (≈ 10 5 ). Furthermore, extensive comparison of our correlations with other high-fidelity simulations from literature demonstrate the accuracy of our work compared to other correlations from literature. This work enables researchers to perform accurate unresolved Euler-Lagrangian simulations for a wide range of elongated particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparing Machine Learning and Physics-Based Nanoparticle Geometry Determinations Using Far-Field Spectral Properties

Anisotropic metal nanostructures exhibit polarization-dependent light scattering, a property which has been widely studied and exploited to determine orientations of subwavelength structures using far-field microscopy. Here we explore the use of variational autoencoders (VAEs) to determine the geometries of gold nanorods (NRs) such as in-plane orientation and aspect ratio under linearly polarized dark-field illumination in an optical microscope. We enforce a shared latent space to connect two VAEs trained separately with polarized dark-field scattering spectra and electron microscopy images and achieve image prediction (shape, orientation, and size) of Au NRs using only polarized dark-field scattering spectra. We determine the geometrical parameters of orientational angle and aspect ratio quantitatively via both our dual-VAE and physics-based analysis on the input scattering spectra. We show that orientational angle prediction by dual-VAE performs well with only a small (~300 particle) training set, yielding a mean absolute error (MAE) of 14.4° and a concordance correlation coefficient (CCC) of 0.95. This performance is only marginally worse than the physics-based cos(2?) fitting approach between the scattering intensity and the polarizing angle, which achieves MAE of 8.78° and CCC of 0.99. Aspect ratio determination is also comparable for the dual-VAE and physics-based fitting comparison (MAE of 0.21 vs. 0.23 and CCC of 0.53 vs. 0.68). Here, this dual encoder-decoder architecture effectively exploits the structure-property relationships of plasmonic nanostructures to construct a cross-modal machine learning (ML) approach, providing a pathway to employ ML approaches to address other structure-property relationships in materials science.

Dark-field scattering↗

Shape memory polymer foams for endovascular therapies

A system for occluding a physical anomaly. One embodiment comprises a shape memory material body wherein the shape memory material body fits within the physical anomaly occluding the physical anomaly. The shape memory material body has a primary shape for occluding the physical anomaly and a secondary shape for being positioned in the physical anomaly.

59 BASIC BIOLOGICAL SCIENCES↗

Shape memory polymer foams for endovascular therapies

A system for occluding a physical anomaly. One embodiment comprises a shape memory material body wherein the shape memory material body fits within the physical anomaly occluding the physical anomaly. The shape memory material body has a primary shape for occluding the physical anomaly and a secondary shape for being positioned in the physical anomaly.

59 BASIC BIOLOGICAL SCIENCES↗

Potential origin of the state-dependent high-energy tail in the black hole microquasar Cygnus X-1 as seen with INTEGRAL

Context. 0.1–10 MeV observations of the black hole microquasar Cygnus X-1 have shown the presence of a spectral feature in the form of a power law in addition to the standard black body (0.1–10 keV) and Comptonization (10–200 keV) components observed by INTEGRAL in several black-hole X-ray binaries. This so-called “high-energy tail” was recently shown to be strong in the hard spectral state of Cygnus X-1, and, in this system, has been interpreted as the high-energy part of the emission from a compact jet. Aims. This result was nevertheless obtained from a data set largely dominated by hard state observations. In the soft state, only upper limits on the presence and hence the potential parameters of a high-energy tail could be derived. Using an extended data set, we aim to obtain better constraints on the properties of this spectral component in both states. Methods. We make use of data obtained from about 15 years of observations with the INTEGRAL satellite. The data set is separated into the different states and we analyze stacked state-resolved spectra obtained from the X-ray monitors, the gamma-ray imager, and the gamma-ray spectrometer (SPI) onboard. Results. A high-energy component is detected in both states, confirming its earlier detection in the hard state and its suspected presence in the soft state with INTEGRAL, as seen in a much smaller SPI data set. We first characterize the high-energy tail components in the two states through a model-independent, phenomenological analysis. We then apply physical models based on hybrid Comptonization (eqpair and belm). The spectra are well modeled in all cases, with a similar goodness of the fits. While in the semi-phenomenological approach the high-energy tail has similar indices in both states, the fits with the physical models seem to indicate slightly different properties. Based on this approach, we discuss the potential origins of the high-energy components in both the soft and hard states, and favor an interpretation where the high-energy component is due to a compact jet in the hard state and hybrid Comptonization in either a magnetized or nonmagnetized corona in the soft state.

accretion↗

The Thermal and Kinematic Sunyaev–Zeldovich Effect in Galaxy Clusters and Filaments Using Multifrequency Temperature Maps of the Cosmic Microwave Background: A399–A401 Cluster Pair Case Study

We present a multifrequency and multi-instrument methodology to study the physical properties of galaxy clusters and cosmic filaments using cosmic microwave background observations. Our approach enables simultaneous measurement of both the thermal (tSZ) and kinematic Sunyaev–Zeldovich (kSZ) effects, incorporates relativistic corrections, and models astrophysical foregrounds such as thermal dust emission. We do this by jointly fitting a single physical model across multiple maps from multiple instruments at different frequencies, rather than fitting a model to a single Compton-y map. We demonstrate the success of this method by fitting the A399–A401 galaxy cluster pair and filament system using archival data from the Planck satellite and new, targeted deep data from the Atacama Cosmology Telescope, covering 11 different frequencies over 14 maps from 30 GHz to 545 GHz. Our tSZ results are consistent with previous work using Compton-y maps. We measure the line-of-sight peculiar velocities of the cluster–filament system using the kSZ effect and find statistical uncertainties on individual cluster peculiar velocities of ≲600 km s −1 , which are competitive with current state-of-the-art measurements. Additionally, we measure the optical depth of the filament component with a signal-to-noise of 8.5σ and reveal hints of its morphology. This modular approach is well-suited for application to future instruments across a wide range of millimeter and submillimeter wavebands.

Gill, Ajay S. [National Research Council of Canada↗

The Thermal and Kinematic Sunyaev–Zeldovich Effect in Galaxy Clusters and Filaments Using Multifrequency Temperature Maps of the Cosmic Microwave Background A399–A401 Cluster Pair Case Study

We present a multifrequency and multi-instrument methodology to study the physical properties of galaxy clusters and cosmic filaments using cosmic microwave background observations. Our approach enables simultaneous measurement of both the thermal (tSZ) and kinematic Sunyaev–Zeldovich (kSZ) effects, incorporates relativistic corrections, and models astrophysical foregrounds such as thermal dust emission. We do this by jointly fitting a single physical model across multiple maps from multiple instruments at different frequencies, rather than fitting a model to a single Compton-y map. We demonstrate the success of this method by fitting the A399–A401 galaxy cluster pair and filament system using archival data from the Planck satellite and new, targeted deep data from the Atacama Cosmology Telescope, covering 11 different frequencies over 14 maps from 30 GHz to 545 GHz. Our tSZ results are consistent with previous work using Compton-y maps. We measure the line-of-sight peculiar velocities of the cluster–filament system using the kSZ effect and find statistical uncertainties on individual cluster peculiar velocities of ≲600 km s −1 , which are competitive with current state-of-the-art measurements. Additionally, we measure the optical depth of the filament component with a signal-to-noise of 8.5σ and reveal hints of its morphology. This modular approach is well-suited for application to future instruments across a wide range of millimeter and submillimeter wavebands.

Ajay S Gill↗

A generalized power-law criterion for rocks based on Mohr failure theory

Nonlinearity of Mohr envelopes confirmed by past laboratory test data can be of considerable importance in theoretical interpretation of rock strength behaviors and many practical applications. Current nonlinear failure criteria are introduced with parameters to empirically fit test data, and the physical and mechanical meanings of these fitting parameters are often not known. Predicted strengths by theoretical criteria (e.g., Griffith criterion) generally do not agree well with test data. Considering the nonlinear properties of a Mohr envelope, a nonlinear failure criterion in a generalized power-law form is derived in this paper based on strength magnitude coefficient (a) and failure envelope curvature coefficient (n) which are expressed in terms of uniaxial tensile strength, uniaxial compressive strength, and angle of internal friction. Test data on granite, marble, dolomite, and andesite from published literature were chosen to test the performance of the proposed criterion along with Griffith and Hoek-Brown criteria. Statistical analysis was performed to evaluate the application of different criteria in predicting the strength of rocks. In addition, some Griffith-typed criteria are mathematically shown to be the special cases of the proposed criterion. The proposed and Hoek-Brown criteria have similar power-law forms with a significant difference in the coefficient functions that govern the shear strength magnitude of rock. The different tensile and compressive failure mechanisms are also investigated from the perspective of the relationship between the uniaxial tension Mohr circle and the proposed failure envelope.

58 GEOSCIENCES↗

NASA Computational Case Study: Spectral Energy Distribution Fitting

The need for faster, more efficient algorithms is an important aspect of scientific computing. Generally, scientists are only exposed to computational issues that arise in their field. Thus, collaboration between a numerical analyst and a scientist is becoming necessary for scientific computing. The purpose of this case study is to expose computer scientists to processes that an astronomer would use to obtain useful results from raw data. For example, astronomers are interested in determining the properties of galaxies and measuring changes in those properties as a function of time throughout cosmic history. To do so, they use certain models that are designed and refined over time via observations at different wavelengths of the light spectrum. The process of matching these models with observed data from studying celestial bodies is referred to as Spectral Energy Distribution (SED) fitting. In this case study, we learn how to perform the SED fit. This process requires knowledge of both the astronomical and computational issues involved when fitting flux, the total energy from a source as seen from Earth, to a set of physical templates. Once a fit is complete, one can classify the source and estimate a number of physical parameters. The goal is to demonstrate how the computer science skill set can be used in the scientific community and to possibly improve one or more of the computational aspects of this problem. The following provides some background on the astronomy issues, including information on the spectral energy distribution and related physical parameters, and the computational issues, including the fitting procedure..

modeling↗

Bayesian Active Learning for Scanning Probe Microscopy: From Gaussian Processes to Hypothesis Learning

Recent progress in machine learning methods and the emerging availability of programmable interfaces for scanning probe microscopes (SPMs) have propelled automated and autonomous microscopies to the forefront of attention of the scientific community. However, enabling automated microscopy requires the development of task-specific machine learning methods, understanding the interplay between physics discovery and machine learning, and fully defined discovery workflows. This, in turn, requires balancing the physical intuition and prior knowledge of the domain scientist with rewards that define experimental goals and machine learning algorithms that can translate these to specific experimental protocols. Here, we discuss the basic principles of Bayesian active learning and illustrate its applications for SPM. We progress from the Gaussian process as a simple data-driven method and Bayesian inference for physical models as an extension of physics-based functional fits to more complex deep kernel learning methods, structured Gaussian processes, and hypothesis learning. These frameworks allow for the use of prior data, the discovery of specific functionalities as encoded in spectral data, and exploration of physical laws manifesting during the experiment. Here, the discussed framework can be universally applied to all techniques combining imaging and spectroscopy, SPM methods, nanoindentation, electron microscopy and spectroscopy, and chemical imaging methods and can be particularly impactful for destructive or irreversible measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Steady surficial core motions - An alternate method

A new method for deriving steady surficial core motions from geomagnetic field models is presented and applied. The original method determines the steady velocity field at the top of a frozen-flux core which best fits, in both the spatial and temporal linear least squares sense, a model of the large scale geomagnetic secular variation (SV) at the base of a source-free mantle (Voorhies, 1986). New method is based upon the same physical assumptions, but fits SV at earth's surface instead of the core-mantle boundary (CMB). The newly derived flow differs somewhat from prior solutions, and shows but slight westward drift; however, other key global properties are virtually unchanged. Over a 15 year interval the new method provides a better fit to the time-varying geomagnetic field at earth's surface than does the old.

Voorhies, Coerte V.↗

Photoionization Modeling of Oxygen K Absorption in the Interstellar Medium: The Chandra Grating Spectra of XTE J1817-330

We present detailed analyses of oxygen K absorption in the interstellar medium (ISM) using four high-resolution Chandra spectra towards the X-ray low-mass binary XTE J1817-330. The 11-25 A broadband is described with a simple absorption model that takes into account the pileup effect and results in an estimate of the hydrogen column density. The oxygen K-edge region (21-25 A) is fitted with the physical warmabs model, which is based on a photoionization model grid generated with the XSTAR code with the most up-to-date atomic database. This approach allows a benchmark of the atomic data which involves wavelength shifts of both the K lines and photoionization cross sections in order to fit the observed spectra accurately. As a result we obtain: a column density of N(sub H) = 1.38 +/- 0.01 x 10(exp 21) cm(exp -2); ionization parameter of log xi = .2.70 +/- 0.023; oxygen abundance of A(sub O) = 0.689(exp +0.015./-0.010); and ionization fractions of O I/O = 0.911, O II/O = 0.077, and O III/O = 0.012 that are in good agreement with previous studies. Since the oxygen abundance in warmabs is given relative to the solar standard of Grevesse and Sauval (1998), a rescaling with the revision by Asplund et al. (2009) yields A(sub O) = 0.952(exp +0.020/-0.013, a value close to solar that reinforces the new standard. We identify several atomic absorption lines.K-alpha , K-beta, and K-gamma in O I and O II; and K-alpha in O III, O VI, and O VII--last two probably residing in the neighborhood of the source rather than in the ISM. This is the first firm detection of oxygen K resonances with principal quantum numbers n greater than 2 associated to ISM cold absorption.

Gatuzz, E.↗

Photoionization Modeling of Oxygen K Absorption in the Interstellar Medium:

We present detailed analyses of oxygen K absorption in the interstellar medium (ISM) using four high-resolution Chandra spectra toward the X-ray low-mass binary XTE J1817-330. The 11-25 Angstrom broadband is described with a simple absorption model that takes into account the pile-up effect and results in an estimate of the hydrogen column density. The oxygen K-edge region (21-25 Angstroms) is fitted with the physical warmabs model, which is based on a photoionization model grid generated with the xstar code with the most up-to-date atomic database. This approach allows a benchmark of the atomic data which involves wavelength shifts of both the K lines and photoionization cross sections in order to fit the observed spectra accurately. As a result we obtain a column density of N(sub H) = 1.38 +/- 0.01 × 10(exp 21) cm(exp −2); an ionization parameter of log xi = −2.70 +/- 0.023; an oxygen abundance of A(sub O) = 0.689 (+0.015/−0.010); and ionization fractions of O(sub I)/O = 0.911, O(sub II)/O = 0.077, and O(sub III)/O = 0.012 that are in good agreement with results from previous studies. Since the oxygen abundance in warmabs is given relative to the solar standard of Grevesse & Sauval, a rescaling with the revision by Asplund et al. yields A(sub O) = 0.952(+0.020/−0.013), a value close to solar that reinforces the new standard.We identify several atomic absorption lines-K(alpha), K(beta), and K(gamma) in O(sub I) and O(sub II) and K(alpha) in O(sub III), O(sub VI), and O(sub VII)-the last two probably residing in the neighborhood of the source rather than in the ISM. This is the first firm detection of oxygen K resonances with principal quantum numbers n greater than 2 associated with ISM cold absorption.

oxygen↗

Surface fitting with biharmonic and harmonic models

The physical and geometric interpretation of a surface fitting technique, multiquadric equations (MQ), is discussed. The relation of this method and its reciprocal form to biharmonic and harmonic techniques respectively, is pointed out. In both forms the solutions may be viewed as being numerical approximations of an integral equation in which an unknown density function is the physical source for disturbing potential (reciprocal-MQ) or elastic displacement (MQ).

Hardy, R. L.↗