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DOE OSTI2022

Determination of Molecular Structure and Dynamics of Molten Salts by Advanced Neutron and X-ray Scattering Measurements and Computer Modeling

The design and development of fully functional Molten-Salt Reactors (MSR) require detailed knowledge of the molten salt properties in order to understand and predict the salt’s behavior. Fundamental properties of interest include molecular structure, speciation, and dynamics (such as diffusion coefficients) of salt components and dissolved corrosion and fission products. Computer modeling is necessary to predict changes in physical and chemical properties due to irradiation, burning of dissolved fuel, and corrosion. The modeling requires experimental data, and advanced neutron and x-ray scattering and spectroscopy provide the most reliable and direct determination of the structure (Pair-Distribution Functions, PDF), and dynamics of ions in the melt. This project dealt with both fluoride and chloride salts. The PDFs have been measured by a combination of neutron and x-ray diffraction. We utilized the techniques of isotope substitutions, a very powerful tool available for neutron-scattering, to extract the details of the liquid structure. Although similar measurements have been done before, modern advanced neutron and x-ray-scattering techniques allow collecting the data at much higher resolution and in a wider range of temperatures. Importantly, we were among the first to study fluoride salts by neutron scattering. The importance of impurities and their effects on salt properties have become apparent recently and so new methods of salt purification were developed. We took advantage of these developments to produce reliable data, which have been used for computer simulations of both clean salts and those with added fission and corrosion products most relevant for MSRs. Ab initio molecular dynamics simulations have been performed to understand the multi-component liquid solution, in particular solubility of impurities and thermodynamic interactions in relation to the ionic-cluster structure of the fluid. We applied machine learning to regress from the simulation and experimental data in order to develop a fast-acting model that can handle molten salt with an arbitrary (≥ 10) number of chemical elements and be able to predict chemical potential as a function of composition and temperature. This project resulted in a number of experimental and computer-simulation publications, a patent application, and numerous conference presentations (American Physical Society, American Chemical Society, and The Electrochemical Society among others). Multiple students and postdocs participated and collaborated on aspects of this project. This project seeded new collaborations between MIT and other institutions, such as the University of Massachusetts Lowell, the University of Illinois Urbana-Champaign, the University of California Berkeley, and Oak Ridge and Los Alamos National Labs. As such, this project has had a broad and lasting impact beyond its original scientific scope.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Bayesian inference for the seismic moment tensor using regional waveforms and a data-derived distribution of velocity models

The largest source of uncertainty in any source inversion is the velocity model used to construct the transfer function employed in the forward model that relates observed ground motion to the seismic moment tensor. However, standard inverse procedures often does not quantify uncertainty in the seismic moment tensor due to error in the Green’s functions from uncertain event location and Earth structure. We attempt to incorporate this uncertainty into an estimation of the seismic moment tensor using a distribution of velocity models calculated in a prior effort based on different and complementary data sets. The posterior distribution of velocity models is then used to construct Green’s functions for use in Bayesian inference of an unknown seismic moment tensor using regional waveform data. The combined likelihood is estimated using data-specific error models and the posterior of the seismic moment tensor is estimated and can be interpreted in terms of most-probable source-type.

58 GEOSCIENCES↗

DOE OSTI2020

The MolSSI QCArchive project: An open-source platform to compute, organize, and share quantum chemistry data

The Molecular Sciences Software Institute's (MolSSI) Quantum Chemistry Archive (QCArchive) project is an umbrella name that covers both a central server hosted by MolSSI for community data and the Python-based software infrastructure that powers automated computation and storage of quantum chemistry (QC) results. The MolSSI-hosted central server provides the computational molecular sciences community a location to freely access tens of millions of QC computations for machine learning, methodology assessment, force-field fitting, and more through a Python interface. Facile, user-friendly mining of the centrally archived quantum chemical data also can be achieved through web applications found at the website. The software infrastructure can be used as a standalone platform to compute, structure, and distribute hundreds of millions of QC computations for individuals or groups of researchers at any scale. The QCArchiveInfrastructure is open-source (BSD-3C), code repositories can be found at github, and releases can be downloaded via PyPI and Conda. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Software > Quantum Chemistry Data Science > Computer Algorithms and Programming

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Feature Extraction for Pipeline Defects Inspection Based Upon Distributed Acoustic Fiber Optic Sensing Data

Fiber-optic distributed acoustic sensing (DAS) is becoming an increasingly important tool for real-time monitoring of energy and civil infrastructure structural health such as pipelines. We present a systematic theoretical study of the potential for DAS to be directly coupled with guided ultrasonic waves typically used in conventional acoustic non-destructive evaluation (NDE) methods for real-time pipeline health monitoring. We are referring to this innovative new NDE technique as ultrasonic guided wave and optical fiber sensor fusion. In the practical application of DAS coupled with guided ultrasonic waves, the structural design of (1) the specific guided waves excited, (2) the physical installation of the acoustic transducers and the fiber optic sensors, and (3) the functional performance specifications (gauge length, sensitivity, Etc.) of fiber optic DAS have an important influence on overall capabilities of the monitoring system. Meanwhile, physics-based analysis of acoustic waves is still a challenge due to the complex nature of the Lamb wave when it propagates, scatters, and disperses in the presence of structural defects. In this work, we simulate carbon steel pipes relevant for oil and gas pipeline applications with diameters of approximately 6-12” and wall thickness of 0.5” as the objects to be monitored. By establishing and implementing these capabilities, we seek to pursue an in-depth study on structural parameter optimization of DAS network, measurement range, and signal processing with an ultimate goal of increasing the sensitivity and efficacy of DAS to defect identification for various modes of corrosion expected in practice. To study the characteristics of scattered acoustic waves and performance of DAS for defect identification, we simulated the response of DAS for multiple pipe structures, defect types, and DAS sensor network configuration using finite element software Ansys, then the properties of signal response are extracted to construct defect-sensitive features. The raw data simulated, and the associated features extracted can ultimately be utilized as annotated training data to benchmark various designs for DAS applications, guided acoustic excitation sources, and learning model parameters to enhance early detection of potentially problematic defects.

Pipeline Defects Inspection, Fiber-optic sensors, ↗

DOE OSTI2018

Development of boron oxide potentials for computer simulations of multicomponent oxide glasses

Molecular dynamics and related atomistic computer simulations are effective ways in studying the structures and structure–property relations of glass materials. However, simulations of boron oxide (B 2 O 3 )-containing oxide glasses pose a challenge due to the lack of reliable empirical potentials. This paper reports development of a set of partial charge pairwise composition-dependent potentials for boron-related interactions that enable simulations of multicomponent borosilicate glasses, together with some of the existing parameters. This set of potentials was tested in sodium borate glasses and sodium borosilicate glasses and it is shown capable to describe boron coordination change with glass composition in wide composition ranges. Structure features such as boron N 4 value, density, Q n species distribution, fraction of non-bridging oxygen around boron and silicon, total correlation function, and bond angle distribution function were calculated and compared with available experimental data. Mechanical properties of the simulated glasses calculated with the new potential also show good agreement with experiments. Therefore, this new set of potential can be used to simulate boron oxide-containing multicomponent glasses including those with wide industrial and technology applications.

nuclear, defects, corrosion↗

DOE OSTI2018

Influence of CdTe Deposition Temperature and Window Thickness on CdTe Grain Size and Lifetime After CdCl 2 Recrystallization

Grain structure influences both transport and recombination in CdTe solar cells. Larger grains generally are obtained with higher deposition temperatures, but commercially it is important to avoid softening soda-lime glass. Furthermore, depositing at lower temperatures can enable different substrates and reduced cost in the future. We examine how initial deposition temperatures and morphology influence grain size and lifetime after CdCl 2 recrystallization. Techniques are developed to estimate grain distribution quickly with low-cost optical microscopy, which compares well with electron backscatter diffraction data providing corroborative assessments of exposed CdTe grain structures. Average grain size increases as a function of CdCl 2 temperature. For lower temperature close-spaced sublimation CdTe depositions, there can be more stress and grain segregation during recrystallization. However, the resulting lifetimes and grain sizes are similar to high-temperature CdTe depositions. The grain structures and lifetimes are largely independent of the presence and/or interdiffusion of Se at the interface, before and after the CdCl 2 treatment.

14 SOLAR ENERGY↗

DOE OSTI2021

Atomic arrangements in an amorphous CoFeB ribbon extracted via an analysis of radial distribution functions

Here we discuss the atomic structure of amorphous ferromagnetic FeCoB alloys, which are used widely in spintronics applications. Specifically, we obtain the pair-distribution functions for various atomic pairs based on high-energy x-ray diffraction data taken from an amorphous Co 20 Fe 61 B 19 specimen. We start our reverse Monte Carlo cycles to determine the disordered structure with a two-phase model in which a small amount of cobalt is mixed with Fe 23 B 6 as a second phase. The structure of the alloy is found to be heterogeneous, where the boron atoms drive disorder through the random occupation of the atomic network. Our analysis also indicates the presence of small cobalt clusters that are embedded in the iron matrix and percolating the latter throughout the structure. This morphology can explain the enhanced spin polarization observed in amorphous magnetic materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Deep learning as a tool for neural data analysis: Speech classification and cross-frequency coupling in human sensorimotor cortex

A fundamental challenge in neuroscience is to understand what structure in the world is represented in spatially distributed patterns of neural activity from multiple single-trial measurements. This is often accomplished by learning a simple, linear transformations between neural features and features of the sensory stimuli or motor task. While successful in some early sensory processing areas, linear mappings are unlikely to be ideal tools for elucidating nonlinear, hierarchical representations of higher-order brain areas during complex tasks, such as the production of speech by humans. Here, we apply deep networks to predict produced speech syllables from a dataset of high gamma cortical surface electric potentials recorded from human sensorimotor cortex. We find that deep networks had higher decoding prediction accuracy compared to baseline models. Having established that deep networks extract more task relevant information from neural data sets relative to linear models (i.e., higher predictive accuracy), we next sought to demonstrate their utility as a data analysis tool for neuroscience. We first show that deep network's confusions revealed hierarchical latent structure in the neural data, which recapitulated the underlying articulatory nature of speech motor control. We next broadened the frequency features beyond high-gamma and identified a novel high-gamma-to-beta coupling during speech production. Finally, we used deep networks to compare task-relevant information in different neural frequency bands, and found that the high-gamma band contains the vast majority of information relevant for the speech prediction task, with little-to-no additional contribution from lower-frequency amplitudes. Together, these results demonstrate the utility of deep networks as a data analysis tool for basic and applied neuroscience.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Local order of orthorhombic weberite-type Y 3 TaO 7 as determined by neutron total scattering and density functional theory calculations

Weberite-type oxides are a family of oxides with A 3 BO 7 stoichiometry that can adopt different space groups depending on chemical composition. There is a discrepancy in previous studies as to whether Y 3 TaO 7 is the orthorhombic C222 1 or the Ccmm space group. Here, we describe the short- and long-range structural properties of weberite-type Y 3 TaO 7 using neutron total scattering data, which has a high sensitivity to the oxygen sublattice. Simultaneous analysis of both short- and long-range structural data via conventional Rietveld and small box modelling demonstrates that Y 3 TaO 7 is best modeled as C222 1 . While the Ccmm describes equally well the long-range structure, pair distribution function analysis revealed that the local atomic configuration can be best modelled as C222 1 . This is corroborated by first-principles calculations that confirm the energetic preference of the C222 1 over Ccmm. Further, neutron total scattering data are reported for the first time for the Y 3 TaO 7 weberite-type ceramics.

36 MATERIALS SCIENCE↗

DOE OSTI2018

A Design and New Functionality of Antiwaveguiding Vertical-Cavity Surface-Emitting Lasers for a Wavelength of 850 nm

Vertical-cavity surface-emitting lasers (VCSELs) with an aperture limited by an oxide and a resonance cavity based on GaAlAs with high Al content provide a maximum γ factor (λ/2 design) and suppression of optical power beyond the aperture. A VCSEL with two coupled cavities provides additional sharp growth of the loss of high-order lateral modes by leakage to the oxidized region and provides single-mode laser generation for an aperture diameter of up to 5 μm. Single-mode antiwaveguiding VCSELs provide ultrafast data transmission with a rate of up to 160 Gbit/s. The structure in which the active medium is placed in the lower distributed Bragg reflector and the cavity and the upper distributed Bragg reflector are dielectric, reducing the temperature shift of the radiation wavelength by a factor of 2 (to ∼0.03 nm/K).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Total X-ray scattering and big-box modeling of pressure-induced local disorder and partial amorphization in CsPbBr 3

The mechanisms governing pressure-induced amorphization and its reversibility in halide perovskites are not yet fully understood, particularly the contribution of local disorder. We performed high-pressure synchrotron total X-ray scattering and reverse Monte Carlo (RMC) big-box modeling using CsPbBr 3 as a model system to investigate short-range structural evolution in both the ordered and partially amorphous phases. While diffraction data indicate that long-range order persists up to 2 GPa, pair distribution function (PDF) analysis reveals significant local distortions, including PbBr 6 octahedral tilting and Cs displacement, which influence the bandgap through a complex interplay between bond compression and angular tilting. Beyond 2 GPa, CsPbBr 3 undergoes partial amorphization, with significant disordering of Cs and Br, while the Pb sublattice remains preserved, allowing for structural recovery upon decompression. Our work, accounting for both short- and long-range structural evolution through RMC modeling, successfully captures how disorder shapes the structural response of halide perovskites under pressure.

critical phenomena↗

DOE OSTI2021

Geographic patterns of genomic diversity and structure in the C4 grass Panicum hallii across its natural distribution

Abstract Geographic patterns of within-species genomic diversity are shaped by evolutionary processes, life history and historical and contemporary factors. New genomic approaches can be used to infer the influence of such factors on the current distribution of infraspecific lineages. In this study, we evaluated the genomic and morphological diversity as well as the genetic structure of the C4 grass Panicum hallii across its complex natural distribution in North America. We sampled extensively across the natural range of P. hallii in Mexico and the USA to generate double-digestion restriction-associated DNA (ddRAD) sequence data for 423 individuals from 118 localities. We used these individuals to study the divergence between the two varieties of P. hallii, P. hallii var. filipes and P. hallii var. hallii as well as the genetic diversity and structure within these groups. We also examined the possibility of admixture in the geographically sympatric zone shared by both varieties, and assessed distribution shifts related with past climatic fluctuations. There is strong genetic and morphological divergence between the varieties and consistent genetic structure defining seven genetic clusters that follow major ecoregions across the range. South Texas constitutes a hotspot of genetic diversity with the co-occurrence of all genetic clusters and admixture between the two varieties. It is likely a recolonization and convergence point of populations that previously diverged in isolation during fragmentation events following glaciation periods.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Reduced Order Description of Experimental Two-Phase Pipe Flows: Characterization of Flow Structures and Dynamics via Proper Orthogonal Decomposition

Multiphase pipe flow is investigated using proper orthogonal decomposition for tomographic X-ray data, where holdup, cross-sectional phase distributions and phase interface characteristics within the pipe are obtained. Six cases of stratified and mixed flow with water content of 10%, 30% and 80% are investigated to gain insight into effects of velocity and proportion of water on the flow fields. Dispersed and slug flows are separately analyzed to consider the added interface complexity of the flow fields. These regimes are also highly applicable to industry operational flows. Instantaneous and fluctuating phase fractions of the four flow regime are analyzed and reduced order dynamical descriptions are generated. Stratified flow cases display coherent structures that highlight the liquid-liquid interface location while the mixed flow cases show minimal coherence of the eigenmodes. The dispersed flow displays coherent structures for the first few modes near the horizontal center of the pipe, representing the liquid-liquid interface location while the slug flow case shows coherent structures that correspond to the cyclical formation and break up of the slug in the first 5 modes. The low order descriptions of the high water content, stratified flow field indicates that main characteristics can be captured with minimal degrees of freedom. Reconstructions of the dispersed flow and slug flow cases indicate that dominant features are observed in the low order dynamical description utilizing less than 1%of the full order model. POD temporal coefficients a1, a2 and a3 show a high level of interdependence for the slug flowcase. The coefficients also describe the phase fraction holdup as a function of time for both dispersed and slug flow. The second coefficient, a2, and the centerline holdup profile show a mean percent difference below 9% between the two curves. The mathematical description obtained from the decomposition will deepen the understanding of multiphase flow characteristics and is applicable to long distance multiphase transport pipelines, fluidized beds, hydroelectric power and nuclear processes to name a few.

Viggiano, Bianca↗

DOE OSTI2019

The sea of quarks and antiquarks in the nucleon

The quark and gluon structure of the proton has been under intense experimental and theoretical investigation for five decades. Even for the distributions of the well-studied valence quarks, challenges such as the value of the down quark to up quark ratio at high fractional momenta remain. Much of the sea of quark-antiquark pairs emerges from the splitting of gluons and is well described by perturbative evolution in quantum chromodynamics. However, experiments confirm that there is a non-perturbative component to the sea that is not well understood and hitherto has been difficult to calculate with ab initio non-perturbative methods. This non-perturbative structure shows up, perhaps most directly, in the flavor dependence of the sea antiquark distributions. Even though some of the general trends can be reproduced by models, there are features of the data that do not seem to be well described. Conclusively, this article discusses the experimental situation, the status of calculations and models, and the directions where these studies will progress in the near future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Effects of threshold resummation for large-x PDF in large momentum effective theory

Parton distribution functions (PDFs) at large x are challenging to extract from experimental data, yet they are essential for understanding hadron structure and searching for new physics beyond the Standard Model. Within the framework of the large momentum P z expansion of lattice quasi-PDFs, we investigate large x PDFs, where the matching coefficient is factorized into the hard kernel, related to the active quark momentum xP z , and the threshold soft function, associated with the spectator momentum (1 − x)P z . The renormalization group equation of the soft function enables the resummation of the threshold double logarithms α k ln 2k (1 − x), which is crucial for a reliable and controllable calculation of large x PDFs. Our analysis with pion valence PDFs indicates that perturbative matching breaks down when the spectator momentum (1 − x)P z approaches Λ QCD , but remains valid when both xP z and (1 − x)P z are much larger than Λ QCD . Additionally, we incorporate leading renormalon resummation within the threshold framework, demonstrating good perturbative convergence in the region where both spectator and active quark momenta are perturbative scales.

factorization↗

DOE OSTI2021

Crystal Structure of Moganite and Its Anisotropic Atomic Displacement Parameters Determined by Synchrotron X-ray Diffraction and X-ray/Neutron Pair Distribution Function Analyses

The crystal structure of moganite from the Mogán formation on Gran Canaria has been re-investigated using high-resolution synchrotron X-ray diffraction (XRD) and X-ray/neutron pair distribution function (PDF) analyses. Our study for the first time reports the anisotropic atomic displacement parameters (ADPs) of a natural moganite. Rietveld analysis of synchrotron XRD data determined the crystal structure of moganite with the space group I2/a. The refined unit-cell parameters are a = 8.7363(8), b = 4.8688(5), c = 10.7203(9) Å, and β = 90.212(4)°. The ADPs of Si and O in moganite were obtained from X-ray and neutron PDF analyses. The shapes and orientations of the anisotropic ellipsoids determined from X-ray and neutron measurements are similar. The anisotropic ellipsoids for O extend along planes perpendicular to the Si-Si axis of corner-sharing SiO4 tetrahedra, suggesting precession-like movement. Neutron PDF result confirms the occurrence of OH over some of the tetrahedral sites. We postulate that moganite nanomineral is stable with respect to quartz in hypersaline water. The ADPs of moganite show a similar trend as those of quartz determined by single-crystal XRD. In short, the combined methods can provide high-quality structural parameters of moganite nanomineral, including its ADPs and extra OH position at the surface. This approach can be used as an alternative means for solving the structures of crystals that are not large enough for single-crystal XRD measurements, such as fine-grained and nanocrystalline minerals formed in various geological environments.

58 GEOSCIENCES↗

DOE OSTI2024

First Sagittarius A* Event Horizon Telescope Results. VII. Polarization of the Ring

Abstract The Event Horizon Telescope observed the horizon-scale synchrotron emission region around the Galactic center supermassive black hole, Sagittarius A* (Sgr A*), in 2017. These observations revealed a bright, thick ring morphology with a diameter of 51.8 ± 2.3 μas and modest azimuthal brightness asymmetry, consistent with the expected appearance of a black hole with mass M ≈ 4 × 106 M ⊙. From these observations, we present the first resolved linear and circular polarimetric images of Sgr A*. The linear polarization images demonstrate that the emission ring is highly polarized, exhibiting a prominent spiral electric vector polarization angle pattern with a peak fractional polarization of ∼40% in the western portion of the ring. The circular polarization images feature a modestly (∼5%–10%) polarized dipole structure along the emission ring, with negative circular polarization in the western region and positive circular polarization in the eastern region, although our methods exhibit stronger disagreement than for linear polarization. We analyze the data using multiple independent imaging and modeling methods, each of which is validated using a standardized suite of synthetic data sets. While the detailed spatial distribution of the linear polarization along the ring remains uncertain owing to the intrinsic variability of the source, the spiraling polarization structure is robust to methodological choices. The degree and orientation of the linear polarization provide stringent constraints for the black hole and its surrounding magnetic fields, which we discuss in an accompanying publication.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Challenges in solving structures from radiation-damaged tomograms of protein nanocrystals assessed by simulation

Structure-determination methods are needed to resolve the atomic details that underlie protein function. X-ray crystallography has provided most of our knowledge of protein structure, but is constrained by the need for large, well ordered crystals and the loss of phase information. The rapidly developing methods of serial femtosecond crystallography, micro-electron diffraction and single-particle reconstruction circumvent the first of these limitations by enabling data collection from nanocrystals or purified proteins. However, the first two methods also suffer from the phase problem, while many proteins fall below the molecular-weight threshold required for single-particle reconstruction. Cryo-electron tomography of protein nanocrystals has the potential to overcome these obstacles of mainstream structure-determination methods. Here, a data-processing scheme is presented that combines routines from X-ray crystallography and new algorithms that have been developed to solve structures from tomograms of nanocrystals. This pipeline handles image-processing challenges specific to tomographic sampling of periodic specimens and is validated using simulated crystals. The tolerance of this workflow to the effects of radiation damage is also assessed. The simulations indicate a trade-off between a wider tilt range to facilitate merging data from multiple tomograms and a smaller tilt increment to improve phase accuracy. Since phase errors, but not merging errors, can be overcome with additional data sets, these results recommend distributing the dose over a wide angular range rather than using a finer sampling interval to solve the protein structure.

59 BASIC BIOLOGICAL SCIENCES↗