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At least 1,369 records · Page 76

Redetermination of the crystal structure of tetralithium octafluoridozirconate(IV), Li 4 ZrF 8 , from single-crystal X-ray data

Presented herein is the crystal-structure redetermination of Li 4 ZrF 8 from singlecrystal X-ray data. Alkali zirconium fluorides are important in nuclear-relevant technologies, and zirconium is commonly employed as an analogue for tetravalent f-block elements. The previous structure report of this species is based on powder X-ray data [Dugat et al. (1995). J. Solid State Chem. 120, 187– 196] but there has never been a refined structure model from single-crystal data. The octafluoridozirconate moieties are held together by electrostatic attraction to lithium ions without sharing of fluoride sites between zirconium(IV) ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A systematic comparison of machine learning methods for modeling of dynamic processes applied to combustion emission rate modeling

Ten established, data-driven dynamic algorithms are surveyed and a practical guide for understanding these methods generated. Existing Python programming packages for implementing each algorithm are acknowledged, and the model equations necessary for prediction are presented. A case study on a coal-fired power plant’s NO x emission rates is performed, directly comparing each modeling method’s performance on a mutual system. Each model is evaluated by its root mean squared error (RMSE) on out-of-sample future horizon predictions. Optimal hyperparameters are identified using either an exhaustive search or genetic algorithm. The top five model structures of each method are used to recursively predict future NO x emission rates over a 60-step time horizon. The RMSE at each future timestep is determined, and the recursive output prediction trends compared against measurements in time. The GRU neural network is identified as the best candidate for representing the system, demonstrating accurate and stable predictions across the future horizon by all considered models, while satisfactory performance was observed in several of the ARX/NARX formulations. Finally, these efforts have contributed 1) a concise resource of multiple proven dynamic machine learning methods, 2) a practical guide explaining the use of these methods, effectively lowering the “barrier-to-entry” of deploying such models in control systems, 3) a comparison study evaluating each method’s performance on a mutual system, 4) demonstration of accurate multi-timestep emissions modeling suitable for systems-level control, and 5) generalizable results demonstrating the suitability of each method for prediction over a multi-step future horizon to other complex dynamic systems.

42 ENGINEERING↗

Designing multicomponent hydrides with potential high T c superconductivity

While hydrogen-rich materials have been demonstrated to exhibit high T c superconductivity at high pressures, there is an ongoing search for ternary, quaternary, and more chemically complex hydrides that achieve such high critical temperatures at much lower pressures. First-principles searches are impeded by the computational complexity of solving the Eliashberg equations for large, complex crystal structures. Here, we adopt a simplified approach using electronic indicators previously established to be correlated with superconductivity in hydrides. This is used to study complex hydride structures, which are predicted to exhibit promisingly high critical temperatures for superconductivity. In particular, we propose three classes of hydrides inspired by the Fm$\overline{3}$ m RH 3 structures that exhibit strong hydrogen network connectivity, as defined through the electron localization function. The first class [RH 11 X 3 Y] is based on a Pm$\overline{3}$m structure showing moderately high T c , where the T c estimate from electronic properties is compared with direct Eliashberg calculations and found to be surprisingly accurate. The second class of structures [(RH 11 ) 2 X 6 YZ] improves on this with promisingly high density of states with dominant hydrogen character at the Fermi energy, typically enhancing T c . The third class [(R 1 H 11 )(R 2 H 11 )X 6 YZ] improves the strong hydrogen network connectivity by introducing anisotropy in the hydrogen network through a specific doping pattern. These design principles and associated model structures provide flexibility to optimize both T c and the structural stability of complex hydrides.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Geophysical data analysis and visualization using the Grid Analysis and Display System

Several problems posed by the rapidly growing volume of geophysical data are described, and a selected set of existing solutions to these problems is outlined. A recently developed desktop software tool called the Grid Analysis and Display System (GrADS) is presented. The GrADS' user interface is a natural extension of the standard procedures scientists apply to their geophysical data analysis problems. The basic GrADS operations have defaults that naturally map to data analysis actions, and there is a programmable interface for customizing data access and manipulation. The fundamental concept of the GrADS' dimension environment, which defines both the space in which the geophysical data reside and the 'slice' of data which is being analyzed at a given time, is expressed The GrADS' data storage and access model is described. An argument is made in favor of describable data formats rather than standard data formats. The manner in which GrADS users may perform operations on their data and display the results is also described. It is argued that two-dimensional graphics provides a powerful quantitative data analysis tool whose value is underestimated in the current development environment which emphasizes three dimensional structure modeling.

Doty, Brian E.↗

CuXASNet: Rapid and accurate prediction of copper L-edge x-ray absorption spectra using machine learning

In this work, we have developed CuXASNet, a dense neural network that predicts simulated Cu -edge x-ray absorption spectra (XAS) from atomic structures. Featurization of the Cu local environment is performed using a component of M3GNet, a graph neural network developed for predicting the potential energy surface. CuXASNet is trained on simulated spectra from FEFF9 at the multiple scattering level of theory, and can predict the and edges for Cu sites to quantitative accuracy. To validate our approach, we compare 14 experimental spectra extracted from the literature with the predictions of CuXASNet. The agreement of CuXASNet with experiments is shown by an average mean absolute error of 0.125 and an average Spearman's correlation coefficient of 0.891, which is comparable to FEFF9's values of 0.131 and 0.898 for the same metrics. As such, CuXASNet can rapidly predict a large number of -edge XAS spectra at the same accuracy as FEFF9 simulations. This can be used as a drop-in replacement for multiple scattering codes for fast screening of candidate atomic structure models of a measured system. This model establishes a general framework for Cu XAS prediction, and can be extended to more computationally expensive levels of theory and to other transition metal edges.

36 MATERIALS SCIENCE↗

Structure and stability of NaTaO 3 (001) and KTaO 3 (001) surfaces

In this work, we carried out first-principles slab calculations to investigate the structure, energetics, and electronic properties of the majority (001) surfaces of NaTaO 3 (NTO), a perovskite oxide with excellent photocatalytic properties, and KTaO 3 (KTO), a closely related but somewhat less active compound. Being polar, NTO(001) and KTO (001) require charge compensation to be stabilized.We examine a number of possible structural models for these surfaces by comparing their formation energies to those of the pure NaO/KO and TaO 2 terminations. Our results show that a “cation-exchange” reconstruction is energetically most favorable for NTO(001) under vacuum conditions, whereas for KTO(001) this reconstruction competes with a “striped” phase with equally exposed KO and TaO 2 terraces actually observed in recent experiments. NTO is found to exhibit enhanced structural flexibility and more effective charge compensation in comparison to KTO, which is attributed to the significantly smaller size of Na + relative to K + . Upon exposure to water, a (2 × 1) hydroxylated structure is by far most favorable for both NTO and KTO. This structure can thus provide a basis for the mechanistic understanding of photocatalytic processes on NTO and KTO surfaces.

36 MATERIALS SCIENCE↗

Thermal conductivity of crack-containing media: A numerical study

The present study aims to evaluate the effective thermal conduction behavior of crack-containing media through micromechanical modeling. Numerical analyses were performed using the finite element method, first using periodic arrays of elliptical pores and then reducing the elliptical minor axis to reach the crack limit. This parametric approach was seen to be able to capture the effect of discontinuity across the crack face in a straightforward manner. The overall thermal conductivity of the model structures, encompassing a range of crack densities and spatial distributions, was investigated. It was found that, for cracks with mixed orientations, the effective thermal conductivity is insensitive to the actual crack alignment and can be uniquely represented by the crack density. The mixed-orientation periodic crack configurations are also representative of random sizes, orientations, and spatial distributions of cracks, thus exhibiting a high degree of generality. The modeling analyses can also be used to determine simple empirical expressions for two- and three-dimensional media containing random cracks.

36 MATERIALS SCIENCE↗

Formulation of full state feedback for infinite order structural systems

The estimation of exact displacement and displacement rate feedback kernels from finite dimensional control solutions based on finite element structural models is discussed. These kernels are then transformed to equivalent curvature and curvature rate feedback kernels. These curvature kernels are augmented with single point displacement and rotation feedback to account for rigid body motions. A growing class of sensors known as area-averaging sensors is used to measure the curvature and curvature rate state functions. The output of area-averaging sensors equals the convolution of all structural curvature states with the spatial sensitivity function of the sensors. Transforming the discrete feedback gains into continuous feedback kernels and employing area-averaging sensors make it possible to implement full state feedback for infinite order structural systems.

Miller, David W.↗

Modeling the Proton Radiation Belt With Van Allen Probes Relativistic Electron-Proton Telescope Data

An empirical model of the proton radiation belt is constructed from data taken during 2013-2017 by the Relativistic Electron-Proton Telescopes on the Van Allen Probes satellites. The model intensity is a function of time, kinetic energy in the range 18-600 megaelectronvolts, equatorial pitch angle, and L shell of proton guiding centers. Data are selected, on the basis of energy deposits in each of the nine silicon detectors, to reduce background caused by hard proton energy spectra at low L. Instrument response functions are computed by Monte Carlo integration, using simulated proton paths through a simplified structural model, to account for energy loss in shielding material for protons outside the nominal field of view. Overlap of energy channels, their wide angular response, and changing satellite orientation require the model dependencies on all three independent variables be determined simultaneously. This is done by least squares minimization with a customized steepest descent algorithm. Model uncertainty accounts for statistical data error and systematic error in the simulated instrument response. A proton energy spectrum is also computed from data taken during the 8 January 2014 solar event, to illustrate methods for the simpler case of an isotropic and homogeneous model distribution. Radiation belt and solar proton results are compared to intensities computed with a simplified, on-axis response that can provide a good approximation under limited circumstances.

Selesnick, R. S.↗

Stream Flow Prediction by Remote Sensing and Genetic Programming

A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

Chang, Ni-Bin↗

Comparison of Model Calculations of Biological Damage from Exposure to Heavy Ions with Measurements

The space environment consists of a varying field of radiation particles including high-energy ions, with spacecraft shielding material providing the major protection to astronauts from harmful exposure. Unlike low-LET gamma or X rays, the presence of shielding does not always reduce the radiation risks for energetic charged-particle exposure. Dose delivered by the charged particle increases sharply at the Bragg peak. However, the Bragg curve does not necessarily represent the biological damage along the particle path since biological effects are influenced by the track structures of both primary and secondary particles. Therefore, the ''biological Bragg curve'' is dependent on the energy and the type of the primary particle and may vary for different biological end points. Measurements of the induction of micronuclei (MN) have made across the Bragg curve in human fibroblasts exposed to energetic silicon and iron ions in vitro at two different energies, 300 MeV/nucleon and 1 GeV/nucleon. Although the data did not reveal an increased yield of MN at the location of the Bragg peak, the increased inhibition of cell progression, which is related to cell death, was found at the Bragg peak location. These results are compared to the calculations of biological damage using a stochastic Monte-Carlo track structure model, Galactic Cosmic Ray Event-based Risk Model (GERM) code (Cucinotta, et al., 2011). The GERM code estimates the basic physical properties along the passage of heavy ions in tissue and shielding materials, by which the experimental set-up can be interpreted. The code can also be used to describe the biophysical events of interest in radiobiology, cancer therapy, and space exploration. The calculation has shown that the severely damaged cells at the Bragg peak are more likely to go through reproductive death, the so called "overkill".

Kim, Myung-Hee Y.↗

Actinide 5f Occupations: The Case of PuO 2

In actinide chemistry, the formal number of open-shell 5f electrons, n open , is a well-defined quantity with an integer value. The effective 5f occupation, n f , additionally takes donation and back-donation into account, generally has a non-integer value, and has varying numerical definitions. The present study explores the important distinction between n f and n open in actinide chemistry with the example of PuO2, by using electronic structure methods with a relativistic Hamiltonian in combination with experimental Pu M 5 -edge high-energy-resolution X-ray absorption and emission spectroscopic data. The total donation to the metal in PuO 2 is between 3.1 and 2.4 electrons, depending on the type of calculation, most of which is to the Pu 6d and 5f shells. The donation into 5f is sensitive to the approximations in the electronic structure model but likely amounts to 1.6/0.8 electrons when the diffuse regions of the 5f shell are included/excluded. Valence band resonant inelastic X-ray scattering experiments demonstrate that Pu 5f electron density is present in the valence band; thus, there is a clear experimental signature of covalent bonding in PuO 2 . Pu M 5 -edge and M 3 -edge high-energy-resolution X-ray absorption near-edge structures for Pu 3+ and Pu 4+ in an aqueous solution are compared to PuO 2 , showing that Pu in PuO 2 has an nf closer to Pu 4+ (aq).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aeroelastic loads and stability investigation of a full-scale hingeless rotor

An analytical investigation was conducted to study the influence of various parameters on predicting the aeroelastic loads and stability of a full-scale hingeless rotor in hover and forward flight. The CAMRAD/JA (Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics, Johnson Aeronautics) analysis code is used to obtain the analytical predictions. Data are presented for rotor blade bending and torsional moments as well as inplane damping data obtained for rotor operation in hover at a constant rotor rotational speed of 425 rpm and thrust coefficients between 0.0 and 0.12. Experimental data are presented from a test in the wind tunnel. Validation of the rotor system structural model with experimental rotor blade loads data shows excellent correlation with analytical results. Using this analysis, the influence of different aerodynamic inflow models, the number of generalized blade and body degrees of freedom, and the control-system stiffness at predicted stability levels are shown. Forward flight predictions of the BO-105 rotor system for 1-G thrust conditions at advance ratios of 0.0 to 0.35 are presented. The influence of different aerodynamic inflow models, dynamic inflow models and shaft angle variations on predicted stability levels are shown as a function of advance ratio.

Peterson, Randall L.↗

Thermodynamic re-modelling of the Cu–Nb–Sn system: Integrating the nausite phase

Currently available Cu–Nb–Sn phase diagrams lack the recently discovered nausite phase (Cu,Nb)Sn 2 , which is an important intermediate in the course of thermal processing of superconducting Nb 3 Sn wires. Processing decisively determines the resulting microstructure of Nb 3 Sn and, thus, its superconducting properties. Lack of suitable and complete phase diagrams, however, obstructs rational design of such thermal processing procedures. To close this gap and to obtain valid knowledge of homogeneity and stability range of nausite, various Cu–Nb–Sn samples, which are heat-treated between 300 °C and 500 °C, are investigated. By means of energy-dispersive X-ray spectroscopy (EDX), a temperature-dependent homogeneity range of nausite is observed, which covers average mole fractions of Cu between 0.09 and 0.15. This is correlated with a change in the mean atomic volume and can be seen in the lattice parameters determined by X-ray diffraction (XRD). Additionally performed first-principles calculations on different CuSn 2 and NbSn 2 model structures confirm this trend. Furthermore, the peritectic decomposition of nausite to NbSn 2 and liquid at 586 °C is determined by means of in situ XRD and differential scanning calorimetry (DSC). By using the CALPHAD (CALculation of PHase Diagrams) approach, all these findings are used to extend a previous thermodynamic description of the Cu–Nb–Sn system by including the nausite as an additional phase. Finally, with this noteworthy integration, the updated modelling of the Cu–Nb–Sn system can be used for optimizing the multistage heat-treatment steps during processing superconducting Nb 3 Sn wires.

36 MATERIALS SCIENCE↗

The HHV-6B U20 glycoprotein binds ULBP1, masking it from recognition by NKG2D and interfering with natural killer cell activation

Human Herpesvirus 6B (HHV-6B) impedes host immune responses by downregulating class I MHC molecules (MHC-I), hindering antigen presentation to CD8+ T cells. Downregulation of MHC-I disengages inhibitory receptors on natural killer (NK) cells, resulting in activation and killing of the target cell if NK cell activating receptors such as NKG2D have engaged stress ligands upregulated on the target cells. Previous work has shown that HHV-6B downregulates three MHC-like stress ligands MICB, ULBP1, and ULBP3, which are recognized by NKG2D. The U20 glycoprotein of the related virus HHV-6A has been implicated in the downregulation of ULBP1, but the precise mechanism remains undetermined. We set out to investigate the role of HHV-6B U20 in modulating NK cell activity. We used HHV-6B U20 expressed as a recombinant protein or transduced into target cells, as well as HHV-6B infection, to investigate binding interactions with NK cell ligands and receptors and to assess effects on NK cell activation. Small-angle X-ray scattering was used to align molecular models derived from machine-learning approaches. We demonstrate that U20 binds directly to ULBP1 with sub-micromolar affinity. Transduction of U20 decreases NKG2D binding to ULBP1 at the cell surface but does not decrease ULBP1 protein levels, either at the cell surface or in toto. HHV-6B infection and soluble U20 have the same effect. Transduction of U20 blocks NK cell activation in response to cell-surface ULBP1. Structural modeling of the U20 – ULBP1 complex indicates some similarities to the m152-RAE1γ complex.

60 APPLIED LIFE SCIENCES↗

Representing Small Commercial Building Faults in EnergyPlus, Part I: Model Development

Small commercial buildings (those with less than approximately 1000 m2 of total floor area) often do not have access to cost-effective automated fault detection and diagnosis (AFDD) tools for maintaining efficient building operations. AFDD tools based on machine-learning algorithms hold promise for lowering cost barriers for AFDD in small commercial buildings; however, such algorithms require access to high-quality training data that is often difficult to obtain. To fill the gap in this research area, this study covers the development (Part I) and validation (Part II) of fault models that can be used with the building energy modeling software EnergyPlus® and OpenStudio® to generate a cost-effective training data set for developing AFDD algorithms. Part I (this paper) presents a library of fault models, including detailed descriptions of each fault model structure and their implementation with EnergyPlus. This paper also discusses a case study of training data set generation, representing an actual building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

GRAIL Refinements to Lunar Seismic Structure

Gravity field measurements are perhaps the most numerous of the indirect observations relevant to the Moon's internal structure. Multiple recent missions have mapped the global lunar gravity field, each one improving upon the resolution of the last. The details of the Moon's deepest structure, including the parameters that define the lunar core, however, were still largely unaddressed by pre-GRAIL gravity measurements, which were not high enough resolution to resolve the tidal coefficients at a sufficient degree of accuracy. Current constraints on core size and state arise from other indirect measurements, including lunar laser ranging, magnetic induction studies, and analyses of elemental abundances in depth-derived mare basalts. These inferences vary widely, but when considered together with structure models derived from the seismic data gathered during the Apollo missions, a schematic of the lunar interior containing a partially molten deepest mantle layer overlying molten outer and solid inner core layers was obtained. Seismology provides the most direct constraints on the variables that govern the dynamic properties of the body. However, the GRAIL mission's high-resolution measurements of the lunar gravity field are being used to constrain the interior structure of the Moon using a "crust to core" approach. GRAIL's constraints on crustal thickness, mantle structure, core radius and stratification, and core state (solid vs. molten) therefore complement seismic investigations. This work focuses on expanding our knowledge of the Moon's internal structure using joint gravity and seismic analyses, which will improve constraints on the deep lunar mantle and core.

Weber, Renee C.↗