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At least 595 records · Page 33

Sensitivity of cellular automata grain structure predictions for high solidification rates

Understanding as-solidified grain structure development during constrained (G 0) alloy solidification conditions is a necessary component of understanding the larger process-microstructure relationships during additive manufacturing (AM) processing. This study applies a cellular automata (CA) model, for static solidification velocities and thermal gradients on the order of those expected in AM melt pools, to investigate grain shape development across ranges of input parameters governing temperature field evolution, nucleation, and growth. Variation in nucleated grain shape from columnar to equiaxed as a function of thermal gradient and nucleation density is modeled with CA and verified against the established transition model of Hunt and Gaumann. Furthermore, while thermal conditions and nucleation density are shown to have the largest roles on microstructure development, the sensitivity of grain structure was very unevenly distributed across parameter space. In particular, it was found that microstructure is very sensitive to mean nucleation undercooling and the interfacial response function in process space regimes near grain structure transitions, but entirely controlled by a combination of thermal gradient, solidification velocity, and nucleation density away from such transitions. The understanding of grain shape sensitivity obtained through CA modeling, particularly at large thermal gradient and nucleation density, will be necessary for accurate microstructure prediction during the extreme processing conditions and large input parameter uncertainty common to AM.

36 MATERIALS SCIENCE↗

Airship Model Tests in the Variable Density Wind Tunnel

This report presents the results of wind tunnel tests conducted to determine the aerodynamic characteristics of airship models. Eight Goodyear-Zeppelin airship models were tested in the original closed-throat tunnel. After the tunnel was rebuilt with an open throat a new model was tested, and one of the Goodyear-Zeppelin models was retested. The results indicate that much may be done to determine the drag of airships from evaluations of the pressure and skin-frictional drags on models tested at large Reynolds number.

Abbott, Ira H↗

Hydrodechlorination of 1,2-Dichloroethane on Platinum Catalysts: Insights from Reaction Kinetics Experiments, Density Functional Theory, and Microkinetic Modeling

Catalytic hydrodechlorination is a promising strategy for treating industrial 1,2-dichloroethane wastes, for which Pt and Pt-based alloy catalysts are widely used. Here, we performed a detailed mechanistic study for 1,2-dichloroethane hydrodechlorination on Pt using a synergistic approach combining density functional theory (DFT) calculations, reaction kinetics experiments, and microkinetic modeling. Using planewave DFT calculations, we evaluated the reaction energy and activation energy barrier of each elementary step involved in the reaction network on Pt(111). The calculated energetics were then incorporated into a comprehensive mean-field microkinetic model accounting for a total of 65 elementary steps. The model-predicted reaction rates were compared with the results from our reaction kinetics experiments on SiO2-supported Pt catalysts. Our results indicated that the hydrodechlorination of 1,2-dichloroethane on Pt(111) starts with a H-removal step; then, it proceeds through a sequence of alternating dechlorination and dehydrogenation steps until vinylidene (CH 2 C*) is formed; finally, CH 2 C* is hydrogenated to the final product, ethane, sequentially via vinyl (CH 2 CH*), ethylene, and ethyl (CH 3 CH 2 *) intermediates. After model parameter adjustments, we achieved good agreement between our theoretical model and experimental results; the adjustments to the calculated parameters are consistent with the typically anticipated coverage effects. Furthermore, our study offers valuable mechanistic insights, which are useful for improving catalysts for this chemistry.

1,2-dichloroethane↗

Nonconventional NMR Spin-Coupling Constants in Oligosaccharide Conformational Modeling: Structural Dependencies Determined from Density Functional Theory Calculations

Nonconventional NMR spin-coupling constants were investigated to determine their potential as conformational constraints in MA’AT modeling of the O-glycosidic linkages of oligosaccharides. Four ( 1 J C1',H1' , 1 J C1',C2' , 2 J C1',H2' , and 2 J C2',H1' ) and eight ( 1 J C4,H4 , 1 J C3,C4 , 1 J C4,C5 , 2 J C3,H4 , 2 J C4,H3 , 2 J C5,H4 , 2 J C4,H5 , and 2 J C3,C5 ) spin-couplings in methyl β-d-galactopyranosyl-(1→4)-β-d-glucopyranoside (methyl β-lactoside) were calculated using density functional theory (DFT) to determine their dependencies on O-glycosidic linkage C–O torsion angles, $\phi$ and ψ, respectively. Long-range 4 J H1',H4 was also examined as a potential conformational constraint of either $\phi$ or ψ. Secondary effects of exocyclic (hydroxyl) C–O bond rotation within or proximal to these coupling pathways were investigated. Based on the findings of methyl β-lactoside, analogous J-couplings were studied in five additional two-bond O-glycosidic linkages [βGlcNAc-(1→4)-βMan, 2-deoxy-βGlc-(1→4)-βGlc, αMan-(1→3)-βMan, αMan-(1→2)-αMan, and βGlcNAc(1→2)-αMan] to determine whether the coupling behaviors observed in methyl β-lactoside were more broadly observed. Of the 13 nonconventional J-couplings studied, 7 exhibit properties that may be useful in future MA’AT modeling of O-glycosidic linkages, none of which involve coupling pathways that include the linkage C–O bonds. The findings also provide new insights into the general effects of exocyclic C–O bond conformation on the magnitude of experimental spin-couplings in saccharides and other hydroxyl-containing molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Generative Adversarial Networks and Mixture Density Networks-Based Inverse Modeling for Microstructural Materials Design

Abstract There are two broad modeling paradigms in scientific applications: forward and inverse. While forward modeling estimates the observations based on known causes, inverse modeling attempts to infer the causes given the observations. Inverse problems are usually more critical as well as difficult in scientific applications as they seek to explore the causes that cannot be directly observed. Inverse problems are used extensively in various scientific fields, such as geophysics, health care and materials science. Exploring the relationships from properties to microstructures is one of the inverse problems in material science. It is challenging to solve the microstructure discovery inverse problem, because it usually needs to learn a one-to-many nonlinear mapping. Given a target property, there are multiple different microstructures that exhibit the target property, and their discovery also requires significant computing time. Further, microstructure discovery becomes even more difficult because the dimension of properties (input) is much lower than that of microstructures (output). In this work, we propose a framework consisting of generative adversarial networks and mixture density networks for inverse modeling of structure–property linkages in materials, i.e., microstructure discovery for a given property. The results demonstrate that compared to baseline methods, the proposed framework can overcome the above-mentioned challenges and discover multiple promising solutions in an efficient manner.

36 MATERIALS SCIENCE↗

On Ba(+) production in the CRIT 2 experiment

Analysis of partical data from the CRIT 2 experiment, studying Alfven's critical ionization velocity (CIV) effect, shows that the density of newly created ions (presumably Ba(+) from the shaped-charge beam) is consistent with the increase in total plasma density measured by the independent RF plasma probe on board (Swenson et al., 1990) at the most active time period. We model this ion production using the measured electron flux data and the neutral barium model of Stenbaek-Nielsen et al. (1990a). To identify the main source mechanisms which may contribute most to the barium ionization, a simple model for the barium ion density at the payload location is developed based on Liouvilles theorem. We estimate that the electron impact ionization is responsible for 90% of the barium ion production observed by CRIT 2 in the first release and up to 45% in the second release. By employing a two-state approximation calculation (Rapp and Francis, 1962), the Ba-O(+) charge exchange cross section is found to range from about 2.0 X 10(exp -17) sq cm at a velocity of 4 km/s to 2.0 X 10(exp -15) sq cm at a velocity of 20 km/s. This result suggests that the Ba-O(+) charge exchange is probably dominant among all the non-CIV ionization processes. By considering the charge exchange process in our density model, the barrium ion densities are calculated for the two releases on CRIT II. The comparison between the model results and the observed data is found to be resonably consistent if the cross sections, as calculated above, are multiplied by 0.3 for the first release and 1.0 for the second release. Our result suggests that the charge exchange process could be the most important non-CIV ionization mechanism in the CRIT II experiment and it should be considered carefully case by case in CIV experiments.

Liou, K.↗

Structure of chalcogen overlayers on Au(111): Density functional theory and lattice-gas modeling

Ordering of different chalcogens, S, Se, and Te, on Au(111) exhibit broad similarities but also some distinct features, which must reflect subtle differences in relative values of the long-range pair and many-body lateral interactions between adatoms. We develop lattice-gas (LG) models within a cluster expansion framework, which includes about 50 interaction parameters. These LG models are developed based on density functional theory (DFT) analysis of the energetics of key adlayer configurations in combination with the Monte Carlo (MC) simulation of the LG models to identify statistically relevant adlayer motifs, i.e., model development is based entirely on theoretical considerations. The MC simulation guides additional DFT analysis and iterative model refinement. Given their complexity, development of optimal models is also aided by strategies from supervised machine learning. The model for S successfully captures ordering motifs over a broader range of coverage than achieved by previous models, and models for Se and Te capture the features of ordering, which are distinct from those for S. More specifically, the modeling for all three chalcogens successfully explains the linear adatom rows (also subtle differences between them) observed at low coverages of ~0.1 monolayer. The model for S also leads to a new possible explanation for the experimentally observed phase with a (5 × 5)-type low energy electron diffraction (LEED) pattern at 0.28 ML and to predictions for LEED patterns that would be observed with Se and Te at this coverage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tip‐Enhanced Imaging and Control of Infrared Strong Light‐Matter Interaction

Optical antenna resonators enable control of light‐matter interactions on the nano‐scale via electron–photon hybrid states in strong coupling. Specifically, mid‐infrared (MIR) nano‐antennas coupled to saturable intersubband transitions in multi‐quantum‐well (MQW) semiconductor heterostructures allow for the coupling strength to be tuned through antenna resonance and field intensity. Here, in this study, tip‐enhanced nano‐scale variation of antenna‐MQW coupling across the antenna is demonstrated, with a spatially‐dependent coupling strength $g_{\textrm{aq}}$ varying from 73 (strong coupling) to 24 cm -1 (weak coupling). This behavior is modeled based on the spatially dependent local constructive and destructive interference between tip and antenna fields. Using a quantum‐mechanical density‐matrix model of the MQW system with its designed values of transition dipole moment, doping density, and population decay time, the picosecond IR pulse coupling to intersubband transitions and the associated tip induced strong‐field saturation effects are described. These results present a new regime of nonlinear IR light‐matter control based on the dynamic manipulation of quantum hybrid states on the nanoscale and in the infrared, with a perspective regarding extension to molecular vibrations.

Wang, Yueying↗

Role of ripples in altering the electronic and chemical properties of graphene

Ripples of graphene are known to manipulate electronic and hydrogenation properties of graphitic materials. More detailed work is needed to elucidate the structure–property relationship of these systems. In this work, the density functional theory is used to compute the energy and electronic structure of the graphene models with respect to variable curvatures and hydrogen adsorption sites. The magnitude of finite bandgap opening depends on the orientation of ripples, and the hydrogen adsorption energy depends on the local curvature of graphene. An adsorbed hydrogen alters the local curvature, resulting in relatively weakened adsorption on the neighboring three sites, which gives a rationale to experimentally observed dynamic equilibrium stoichiometry (H:C = 1:4) of hydrogenated graphene. The surface diffusion transition state energy of adsorbed hydrogen is computed, which indicates that the Eley–Rideal surface recombination mechanism may be important to establish the dynamic equilibrium, instead of the commonly assumed Langmuir–Hinshelwood mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In Quest of Calibration Density and Consistency in Hydrologic Modeling: Distributed Parameter Calibration against Streamflow Characteristics

Conventional basin-by-basin approaches to calibrate hydrologic models are limited to gauged basins and typically result in spatially discontinuous parameter fields. Moreover, the consequent low calibration density in space falls seriously behind the need from present-day applications like high resolution river hydrodynamic modeling. In this study we calibrated three key parameters of the Variable Infiltration Capacity (VIC) model at every 1/8° grid-cell using machine learning-based maps of four streamflow characteristics for the conterminous United States (CONUS), with a total of 52,663 grid-cells. This new calibration approach, as an alternative to parameter regionalization, applied to ungauged regions too. A key difference made here is that we tried to regionalize physical variables (streamflow characteristics) instead of model parameters whose behavior may often be less well understood. The resulting parameter fields no longer presented any spatial discontinuities and the patterns corresponded well with climate characteristics, such as aridity and runoff ratio. The calibrated parameters were evaluated against observed streamflow from 704/648 (calibration/validation period) small-to-medium-sized catchments used to derive the streamflow characteristics, 3941/3809 (calibration/validation period) small-to-medium-sized catchments not used to derive the streamflow characteristics as well as five large basins. Comparisons indicated marked improvements in bias and Nash-Sutcliffe efficiency. Model performance was still poor in arid and semiarid regions, which is mostly due to both model structural and forcing deficiencies. Although the performance gain was limited by the relative small number of parameters to calibrate, the study and results here served as a proof-of-concept for a new promising approach for fine-scale hydrologic model calibrations.

54 ENVIRONMENTAL SCIENCES↗

Predictability of upper-atmospheric density and composition

Empirical models of upper-atmospheric density and composition are employed in a number of areas, ranging from basic research in atmospheric and ionospheric physics to practical applications in satellite ephemeris prediction. Such models are based on various kinds of data sets and have varying levels of complexity, strengths, and weaknesses. The characteristics of several of the widely used models are described and studies in which the predictions of these models were compared with observational data are reviewed. The relative advantages and limitations of the models in current use are discussed as well as ways in which the models might be improved.

Straus, J. M.↗

Level density of the sd-nuclei—Statistical shell-model predictions

Accurate knowledge of the nuclear level density is important both from a theoretical viewpoint as a powerful instrument for studying nuclear structure and for numerous applications. For example, astrophysical reactions responsible for the nucleosynthesis in the universe can be understood only if we know the nuclear level density. We use the configuration-interaction nuclear shell model to predict nuclear level density for all nuclei in the sd-shell, both total and for individual spins (only with positive parity). To avoid the diagonalization in large model spaces we use the moments method based on statistical properties of nuclear many-body systems. In the cases where the diagonalization is possible, the results of the moments method practically coincide with those from the shell-model calculations. Using the computed level densities, we fit the parameters of the Constant Temperature phenomenological model, which can be used by practitioners in their studies of nuclear reactions at excitation energies appropriate for the sd-shell nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Transition heating rates obtained on a matted and isolated 0.006 scale model (41-OT) space shuttle orbiter and external tank in the NASA/LaRC variable density hypersonic tunnel (IH17)

Model information and data obtained from wind tunnel tests performed on a 0.006 scale model of the Rockwell International space shuttle orbiter and external tank in the 18 inch Variable Density Hypersonic Wind Tunnel (VDHT) at NASA Langley Research Center are presented. Tests were performed at a Mach number of 8.0 over a Reynolds Number range from 0.1 to 10.0 million per foot at 0 deg and -5 deg angle of attack and 0 deg sideslip angle. Transition heating rates were determined using thin skin thermocouples located at various locations on the orbiter and ET. The test was conducted in three stages: orbiter plus external tank (mated configuration); orbiter alone, and external tank alone. The effects of boundary layer trips were also included in the test sequence. The plotted results presented show the effect of configuration interference on the orbiter lower surface and on the ET. Tabulated data are given.

Cummings, J.↗