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DOE OSTI2018

Comparison of the Optical Connectivity Method to X-Ray spray measurements in the near field of a diesel injector

For diesel sprays, the primary breakup processes are only rarely understood due to the high optical density and the resulting difficulties to measure them with extremely high spatial and sufficient temporal resolution. The Optical Connectivity Method (OCM) has been proposed in the last years to allow the determination of the breakup length of the connected liquid core, thus giving a measurement quantity of the primary breakup. In this research, an improved optical setup of the OCM is applied to a three-hole test injector nozzle where several measurement techniques are compared currently under well-defined conditions up to 100 MPa injection pressure. In this work, the direct comparison with X-Ray measurements done at the Advanced Photon Source of the Argonne National Laboratory will be described. This allows an evaluation of the OCM technique and a comparison of the different measurement quantities in the first 500 μm range of the spray. The structure of the spray is measured by X-Ray phase contrast imaging and the fuel mass distribution is measured by X-Ray absorption imaging. A detailed comparison of the two X-Ray techniques and the OCM technique has been possible for the first time. It is found that the measurement data of the spray near field are very congruent with all three methods. Due to this comparison, the measurement of the non-perturbed length, which describes the distance from the nozzle orifice up to the point where the formation of surface disturbances is starting, by the OCM is validated for the first time. Within this non-perturbed length of the spray, the OCM signal is weak before it starts to illuminate from the scattering of the perturbed surface. Hence, the OCM technique can deliver two characteristic length scales, the non-perturbed length and the breakup length , characterizing the primary spray breakup.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Speciation of Nanocatalysts Using X-ray Absorption Spectroscopy Assisted by Machine Learning

Structure and morphology of supported nanoparticle catalysts play important roles in many industrial reactions. Recent progress has identified key aspects of structure-activity relationships at nanoscale and novel methods to study the local environment of the active sites. X-ray absorption fine structure (XAFS) spectroscopy, despite being a leading technique for this purpose, is hampered significantly by its ensemble-averaging nature which often leads to a bias towards a single "representative" structure. Learning heterogeneous distributions of nanostructures at the inter- and intra-particle level from the average XAFS spectrum is a formidable challenge that can be overcome in some cases, described in this Perspective. Here we also discuss emerging machine learning techniques for extracting the information about heterogeneity of metal species from XAFS data.

36 MATERIALS SCIENCE↗

DOE OSTI2022

The Illumination of Thunderclouds by Lightning: 3. Retrieving Optical Source Altitude

Abstract Optical space‐based lightning sensors such as the Geostationary Lightning Mapper (GLM) detect and geolocate lightning by recording rapid changes in cloud top illumination. While lightning locations can be determined to within a pixel on the GLM imaging array, these instruments are not individually able to natively report lightning altitude. It has previously been shown that thunderclouds are illuminated differently based on the altitude of the optical source. In this study, we examine how altitude information can be extracted from the spatial distributions of GLM energy recorded from each optical pulse. We match GLM “groups” with Lightning Mapping Array (LMA) source data that accurately report the 3‐D positions of coincident Radio‐Frequency (RF) emitters. We then use machine learning methods to predict the mean LMA source altitudes matched to GLM groups using metrics from the optical data that describe the amplitude, breadth, and texture of the group spatial energy distribution. The resulting model can predict the LMA mean source altitude from GLM group data with a median absolute error of <1.5 km, which is sufficient to determine the location of the charge layer where the optical energy originated. This model is able to capture changes to the source altitude distribution in response to convective processes in the thunderstorm, and the GLM predictions can reveal the vertical structure of individual flashes ‐ enabling 3‐D flash geolocation with GLM for the first time. Future work will account for differences in thunderstorm charge/precipitation structures and viewing angle across the GLM Field of View.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Network Analysis of Academic Medical Center Websites in the United States

Healthcare resources are published annually in repositories such as the AHA Annual Survey Database TM . However, these data repositories are created via manual surveying techniques which are cumbersome in collection and not updated as frequently as website information of the respective hospital systems represented. Also, this resource is not widely available to patients in an easy-to-use format. Network analysis techniques have the potential to create topological maps which serve to aid in pathfinding for patients in their search for healthcare services. This study explores the topological structure of forty United States academic health center websites. Network analysis is utilized to analyze and visualize 48,686 webpages. Several elements of network structure are examined including basic network properties, and centrality measures distributions. The Louvain community detection algorithm is used to examine the extent to which these techniques allow identification of healthcare resources within networks. The results indicate that websites with related healthcare services tend to form observable clusters useful in mapping key resources within a hospital system.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Deciphering the 3D structure of the old galactic bulge from the OGLE RR Lyrae stars

We have analyzed a sample of 27,258 fundamental-mode RR Lyrae variable stars (type RRab) detected recently toward the Galactic bulge by the Optical Gravitational Lensing Experiment (OGLE) survey. The data support our earlier claim that these metal-poor stars trace closely the barred structure formed of intermediate-age red clump giants. The distance to the Galactic center (GC) inferred from the bulge RR Lyrae stars is R{sub 0}=8.27±0.01(stat)±0.40(sys) kpc. We show that their spatial distribution has the shape of a triaxial ellipsoid with a major axis located in the Galactic plane and inclined at an angle of i=20{sup ∘}±3{sup ∘} to the Sun–GC line of sight. The obtained scale-length ratio of the major axis to the minor axis in the Galactic plane and to the axis vertical to the plane is 1:0.49(2):0.39(2). We do not see evidence for the bulge RR Lyrae stars forming an X-shaped structure. Based on the light curve parameters, we derive metallicities of the RRab variables and show that there is a very mild but statistically significant radial metallicity gradient. About 60% of the bulge RRab stars form two very close sequences on the period–amplitude (or Bailey) diagram, which we interpret as two major old bulge populations: A and B. Their metallicities likely differ. Population A is about four times less abundant than the slightly more metal-poor population B. Most of the remaining stars seem to represent other, even more metal-poor populations of the bulge. The presence of multiple old populations indicates that the Milky Way bulge was initially formed through mergers.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Crystal structure, homogeneity range and electronic structure of rhombohedral γ-Mn 5 Al 8

Here, the γ-region of the Mn–Al phase diagram between 45 and 70 at.% Al was re-investigated by a combination of powder and single crystal X-ray diffraction as well as EDS analysis to establish the distribution of Mn and Al atoms. Single crystals of γ-Mn 5–x Al 8+x were grown using Sn-flux at 650 °C. The crystal structure, atomic coordinates and site occupancy parameters of γ-Mn 5–x Al 8+x phases were refined from single crystal X-ray data. The γ-Mn 5-x Al 8+x phase adopts the rhombohedral Cr 5 Al 8 -type structure rather than a cubic γ-brass structure. The refined compositions from two crystals extracted from the Al-rich and Mn-rich sides are, respectively, Mn 4.76 Al 8.24(2) (I) and Mn 6.32 Al 6.68(2) (II). The structure was refined in the acentric R3m space group (No.160, Z=6), in order to compare with other reported rhombohedral γ-brasses. In addition, according to X-ray powder diffraction analysis, at the Al-rich side the γ-phase coexists with LT–Mn 4 Al 11 and, at the Mn-rich side, with a hitherto unknown phase. The refined lattice parameters from powder patterns fall in the range a=12.6814(7)–12.6012(5) Å and c=7.9444(2)–7.9311(2) Å from Al-rich to Mn-rich loadings, and the corresponding rhombohedral angles distorted from a pseudo-cubic cell were found to be 89.1(1)°–88.9(1)°. Magnetic susceptibility and magnetization studies of Mn 4.92 Al 8.08(2) are consistent with moment bearing Mn and suggest a spin glass state below 27 K. Tight-binding electronic structure calculations (LMTO-ASA with LSDA) showed that the calculated Fermi level for γ-“Mn 5 Al 8 ” falls within a pseudogap of the density of states, a result which is in accordance with a Hume-Rothery stabilization mechanism γ-brass type phases.

36 MATERIALS SCIENCE↗

DOE OSTI2019

HOOVER

HOOVER is a distributed framework for solving streaming/dynamic graph problems where the structure of a graph changes over time based on the state of its vertices.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Relative Permeability for Offshore Enhanced Oil Recovery

Relative permeability (kr ) is the description of multiphase transport through porous media that is most widely accepted and utilized to scale relationships up to the field scale through simulations. Previous research at NETL has shown a dependence of kr on the flow rates and porous media structure that is poorly captured in most descriptions of this process. Our project was originally scoped to be a 3-year project to (2019-2021): (1) determine if this poor literature description is true for offshore EOR; (2) collect data on the generation of relevant kr curves for offshore EOR; and (3) distribute this collected data, methodology and resultant curves.

Crandall, Dustin↗

DOE OSTI2025

Distinguishing isotropic and anisotropic signals for X-ray total scattering using machine learning

Understanding structure–property relationships is essential for advancing technologies based on thin films. X-ray pair distribution function (PDF) analysis can access relevant atomic structure details spanning local-, mid- and long-range structure. While X-ray PDF has been adapted for thin films on amorphous substrates, measurements on single-crystal substrates are necessary to accurately determine structure origins for some thin film materials, especially those for which the substrate changes the accessible structure and properties. However, when measuring films on single-crystal substrates, high-intensity anisotropic Bragg spots saturate 2D detector images, overshadowing the thin films' isotropic scattering signal. This renders previous data processing methods for films on amorphous substrates unsuitable for films on single-crystal substrates. To address this measurement need, we developed IsoDAT2D, an innovative data processing approach using unsupervised machine learning algorithms. The program combines dimensionality reduction and clustering algorithms to separate thin film and single-crystal substrate X-ray scattering signals. We use SimDAT2D , a program we developed to generate simulated thin film data, to validate IsoDAT2D . Here we also use IsoDAT2D to isolate X-ray total scattering signal from a thin film on a single-crystal substrate. The resulting PDF data are compared with similar data processed using previous methods, especially substrate subtraction for single-crystal and amorphous substrates. PDF data from IsoDAT2D -identified X-ray total scattering data are significantly better than from single-crystal substrate subtraction, but not as reliable as PDF data from amorphous substrate subtraction. With IsoDAT2D , there are new opportunities to expand PDF to a wider variety of thin films, including those on single-crystal substrates, with which new structure–property relationships can be elucidated to enable fundamental understanding and technological advances.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Modeling the role of local crystallographic correlations in microstructures of Ti-6Al-4V using a correlated structure visco-plastic self-consistent polycrystal plasticity formulation

This paper presents a multi-level crystal plasticity-based simulation framework for modeling mechanical response and microstructure evolution of Ti-6Al-4V with α-lath/lamellar microstructures. Here, the model is a correlated structure visco-plastic self-consistent (CS-VPSC) formulation linking three scales: a single crystals micro-scale, a lath/lamellar colony meso-scale, and a lath/lamellar aggregate macro-scale. A selected hardening law for the evolution of critical resolved shear stress per slip system used in CS-VPSC is phenomenological. However, it adjusts the resistances of basal and prismatic slip systems based on the geometry of slip transfer between adjacent lamellae. Consistent with experimental evidences, the resolved shear stress on the pyramidal slip planes is dependent not only on the stress in the direction of slip but also on the two orthogonal shear stress components and the three normal stress components (non-Schmid effects). Electron backscatter diffraction (EBSD) data in conjunction with a procedure relying on α→β phase transformation is used to construct paired variants of α-laths/lamellae satisfying their local crystallographic correlations. The procedure fits volume fractions of individual laths/lamellae with the experimental EBSD data and selects a distribution of habit planes between adjacent variants with respect to the loading direction. The simulation framework is applied to interpret the deformation behavior in tension and compression along two sample directions of Ti-6Al-4V fabricated via laser powder bed fusion. Moreover, the model is used to simulate texture evolution during rolling of the material to large strains. It is demonstrated that the model is capable of predicting plastic anisotropy/asymmetry and the concomitant texture evolution. While the model reveals a significant effect of habit plane inclination with respect to the loading direction on yield stress, the comparison of the data and model predictions shows that a random distribution of habit planes fits the flow response. It is further inferred that the tension-compression asymmetry arises from the non-Schmid effects.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Studies on the compositional dependent structural and electrical properties of CaTiO3-modified K0.5Na0.5NbO3 piezoelectric system

Lead-free piezoelectric ceramics of (1 − x)K0.5Na0.5NbO3-xCaTiO3 were fabricated, and their crystal structure, microstructure, and electrical properties were systematically studied. Rietveld refinement of the x-ray diffraction data and Raman spectroscopic analyses revealed a composition-dependent structural phase transition: three phase transitions, namely, from a pure orthorhombic phase for x ≤ 0.02 to a mixed phase of orthorhombic and tetragonal phases (0.03 ≤ x ≤ 0.08) and finally another mixed phase of tetragonal + cubic for x = 0.10 and 0.15 at room temperature (RT). The morphological study reveals a decrease in grain size along with a more uniform distribution of grains as the concentration of CaTiO3 (CT) increases; notably, a homogeneous distribution of grains is observed for x = 0.05. The temperature-dependent dielectric properties show two phase transitions, from orthorhombic to tetragonal (TO-T) and tetragonal to cubic (TC), for unmodified K0.5Na0.5NbO3 (KNN). However, both the phase transition temperatures (TO-T and TC) decrease, and the transition peaks broaden with an increase in CT substitution, and for x > 0.06, the TO-T shifted below RT. The broadening of the transition peak at TO-T may be due to the relaxation behavior. Among the prepared samples, the 5 mol. % CT-modified KNN shows the optimum electrical properties (d33 = 114 pC/N, ɛr = 412, and 2Pr = 15.25 μC/cm2) at RT. The enhanced electrical properties for x = 0.05 are due to the coexistence of orthorhombic and tetragonal phases, facilitating easy polarization rotation and flattening of the free energy profile. A phase diagram has been constructed based on the information gathered from the temperature-dependent dielectric measurements, RT x-ray diffraction, and Raman spectroscopy data and is discussed in detail.

Physics↗

DOE OSTI2017

Merging single-shot XFEL diffraction data from inorganic nanoparticles: a new approach to size and orientation determination

X-ray free-electron lasers (XFELs) provide new opportunities for structure determination of biomolecules, viruses and nanomaterials. With unprecedented peak brilliance and ultra-short pulse duration, XFELs can tolerate higher X-ray doses by exploiting the femtosecond-scale exposure time, and can thus go beyond the resolution limits achieved with conventional X-ray diffraction imaging techniques. Using XFELs, it is possible to collect scattering information from single particles at high resolution, however particle heterogeneity and unknown orientations complicate data merging in three-dimensional space. Using the Linac Coherent Light Source (LCLS), synthetic inorganic nanocrystals with a core–shell architecture were used as a model system for proof-of-principle coherent diffractive single-particle imaging experiments. To deal with the heterogeneity of the core–shell particles, new computational methods have been developed to extract the particle size and orientation from the scattering data to assist data merging. The size distribution agrees with that obtained by electron microscopy and the merged data support a model with a core–shell architecture.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Broad Distribution of Local Polar States Generates Large Electrothermal Properties in Pb-Free Relaxor Ferroelectrics

Electrothermal energy conversion provides attractive solutions for global energy management, such as energy harvesting from waste heat using pyroelectric energy conversion (PEC) and efficient cooling of portable electronics or data servers using the electrocaloric effect. Relaxor ferroelectrics are attractive for electrothermal energy conversion because of their large pyroelectric coefficients over a wide temperature range. Although Pb-based relaxors are well-known, toxicity concerns have mandated the intense search for Pb-free alternatives. Here, we engineered (Ba,Ca)TiO 3 -based relaxors based on a multisite doping strategy, which show promising electrothermal performance, viz. a maximum PEC efficiency of 14% and electrocaloric refrigeration capacity of 115 J/kg. Using local-scale structural analysis, we provide an atomistic model for large electrothermal properties in the newly designed Pb-free ferroelectrics, whereby a temperature-independent continuous distribution of cation displacement directions creates easy pathways for microscopic polarization reorientation. This research provides key structural insight for future atomic-scale engineering of environmentally sustainable ferroelectrics in energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

X-ray fluorescence at nanoscale resolution for multicomponent layered structures: A solar cell case study

The study of a multilayered and multicomponent system by spatially resolved X-ray fluorescence microscopy poses unique challenges in achieving accurate quantification of elemental distributions. This is particularly true for the quantification of materials with high X-ray attenuation coefficients, depth-dependent composition variations and thickness variations. A widely applicable procedure for use after spectrum fitting and quantification is described. This procedure corrects the elemental distribution from the measured fluorescence signal, taking into account attenuation of the incident beam and generated fluorescence from multiple layers, and accounts for sample thickness variations. Deriving from Beer–Lambert's law, formulae are presented in a general integral form and numerically applicable framework. Here, the procedure is applied using experimental data from a solar cell with a Cu(In,Ga)Se 2 absorber layer, measured at two separate synchrotron beamlines with varied measurement geometries. This example shows the importance of these corrections in real material systems, which can change the interpretation of the measured distributions dramatically.

14 SOLAR ENERGY↗

DOE OSTI2016

Solvation structures of water in trihexyltetradecylphosphonium-orthoborate ionic liquids

Atomistic molecular dynamics simulations have been performed to investigate effective interactions of isolated water molecules dispersed in trihexyltetradecylphosphonium-orthoborate ionic liquids (ILs). The intrinsic free energy changes in solvating one water molecule from gas phase into bulk IL matrices were estimated as a function of temperature, and thereafter, the calculations of potential of mean force between two dispersed water molecules within different IL matrices were performed using umbrella sampling simulations. The systematic analyses of local ionic microstructures, orientational preferences, probability and spatial distributions of dispersed water molecules around neighboring ionic species indicate their preferential coordinations to central polar segments in orthoborate anions. The effective interactions between two dispersed water molecules are partially or totally screened as their separation distance increases due to interference of ionic species in between. These computational results connect microscopic anionic structures with macroscopically and experimentally observed difficulty in completely removing water from synthesized IL samples and suggest that the introduction of hydrophobic groups to central polar segments and the formation of conjugated ionic structures in orthoborate anions can effectively reduce residual water content in the corresponding IL samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Learning energy-based representations of quantum many-body states

Efficient representation of quantum many-body states on classical computers is a problem of practical importance. An ideal representation of a quantum state combines a succinct characterization informed by the structure and symmetries of the system along with the ability to predict the physical observables of interest. Several machine-learning approaches have been recently used to construct such classical representations, which enable predictions of observables and account for physical symmetries. However, the structure of a quantum state typically gets lost unless a specialized is employed based on prior knowledge of the system. Moreover, most such approaches give no information about what states are easier to learn in comparison with others. Here, we propose a generative energy-based representation of quantum many-body states derived from Gibbs distributions used for modeling the thermal states of classical spin systems. Based on the prior information on a family of quantum states, the energy function can be specified by a small number of parameters using an explicit low-degree polynomial or a generic parametric family such as neural nets and can naturally include the known symmetries of the system. Our results show that such a representation can be efficiently learned from data using exact algorithms in a form that enables the prediction of expectation values of physical observables. Importantly, the structure of the learned energy function provides a natural explanation for the difficulty of learning an energy-based representation of a given class of quantum states when measured in a certain basis. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Selecting XFEL single-particle snapshots by geometric machine learning

A promising new route for structural biology is single-particle imaging with an X-ray Free-Electron Laser (XFEL). This method has the advantage that the samples do not require crystallization and can be examined at room temperature. However, high-resolution structures can only be obtained from a sufficiently large number of diffraction patterns of individual molecules, so-called single particles. Here, we present a method that allows for efficient identification of single particles in very large XFEL datasets, operates at low signal levels, and is tolerant to background. This method uses supervised Geometric Machine Learning (GML) to extract low-dimensional feature vectors from a training dataset, fuse test datasets into the feature space of training datasets, and separate the data into binary distributions of “single particles” and “non-single particles.” As a proof of principle, we tested simulated and experimental datasets of the Coliphage PR772 virus. We created a training dataset and classified three types of test datasets: First, a noise-free simulated test dataset, which gave near perfect separation. Second, simulated test datasets that were modified to reflect different levels of photon counts and background noise. These modified datasets were used to quantify the predictive limits of our approach. Third, an experimental dataset collected at the Stanford Linear Accelerator Center. The single-particle identification for this experimental dataset was compared with previously published results and it was found that GML covers a wide photon-count range, outperforming other single-particle identification methods. Moreover, a major advantage of GML is its ability to retrieve single particles in the presence of structural variability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

High-Fidelity Analysis of ULF Wave Mode Structure Following Interplanetary Shock Compression of the Dayside Magnetopause Using MMS Multi-Point Observations

During the 9 March 2018 event with two consecutive interplanetary shocks compressing the dayside magnetosphere, the azimuthal mode structure and frequency spectrum of ultra low frequency magnetic pulsations are resolved using a cross-spectral analysis based on high-fidelity multi-probe Magnetospheric Multiscale Mission (MMS) magnetometer data. The results based on the MMS 4 and MMS 3 pair of measurements show that shock arrival leads to low mode (|m| ≤ 3) magnetic fluctuations in the Pc4-5 regimes, and smaller spatial scale fluctuations implied by the dominant high mode numbers are observed after both shock signatures hit and passed the magnetosphere. Detailed evolution of the mode structure is also shown for the first shock to reveal the development of high mode structure from a bump-on-tail distribution at m≈20 to a dominant peak at m≈50 in about 10 min. In addition, an interesting change of sign in m from negative to positive is observed as MMS crosses ~11 MLT pre-noon, which is consistent with the picture of wave generation by dayside magnetopause compression and then anti-sunward propagation. Finally, for both shocks, the contribution of higher frequency waves (Pc-4 range compared with Pc-5) to the total wave power is found to be negligible before and after the shock impact, but it becomes more significant during the shock impact.

79 ASTRONOMY AND ASTROPHYSICS↗