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Results for “Structural Modeling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

X-ray spectroscopic study of amorphous and polycrystalline PbO films, α-PbO, and β-PbO for direct conversion imaging

We investigated the electronic structure of Lead Oxide (PbO) – one of the most promising photoconductor materials for direct conversion x-ray imaging detectors, using soft x-ray emission and absorption spectroscopy. Two structural configurations of thin PbO layers, namely the polycrystalline and the amorphous phase, were studied, and compared to the properties of powdered α-PbO and β-PbO samples. In addition, we performed calculations within the framework of density functional theory and found an excellent agreement between the calculated and the measured absorption and emission spectra, which indicates high accuracy of our structural models. Our work provides strong evidence that the electronic structure of PbO layers, specifically the width of the band gap and the presence of additional interband and intraband states in both conduction and valence band, depend on the deposition conditions. We tested several model structures using DFT simulations to understand what the origin of these states is. The presence of O vacancies is the most plausible explanation for these additional electronic states. Several other plausible models were ruled out including interstitial O, dislocated O and the presence of significant lattice stress in PbO.

42 ENGINEERING↗
DOE OSTI2016

Structure resolution by electron diffraction tomography of the complex layered iron-rich Fe-2234-type Sr{sub 5}Fe{sub 6}O{sub 15.4}

The crystal structure of the strontium ferrite Sr{sub 5}Fe{sub 6}O{sub 15.4}, was solved by direct methods on electron diffraction tomography data acquired on a transmission electron microscope. The refined cell parameters are a=27.4047(3) Å, b=5.48590(7) Å and c=42.7442(4) Å in Fm2m symmetry. Its structure is built up from the intergrowth sequence between a quadruple perovskite-type layer with a complex rock-salt (RS)-type block. In the latter iron atoms are found in two different environments : tetragonal pyramid and tetrahedron. The structural model was refined by Rietveld method based on the powder X-ray diffraction pattern. - Highlights: • Complex structure of Sr{sub 5}Fe{sub 6}O{sub 15.4} solved by electron diffraction tomography. • Observed Fourier maps allow determining missing oxygen atoms in the structure. • Structural model refined from powder X-ray diffraction data. • Intergrowth between quadruple perovskite layer with double rock-salt-type layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Modelica-based system modeling for studying control-related faults in chiller plants and boiler plants serving large office buildings

System modeling is critical when studying operation faults in chiller plants and boiler plants. However, current fault models have difficulties faithfully representing the operation of chiller plants and boiler plants under the effects of those faults, especially the control-related ones. In this study, we present a systematic method to develop high-fidelity models for approximating the behaviors of chiller plants and boiler plants under faulty conditions. Compared to existing ones, the resulting fault models have two advantages: first, they better characterize the dynamic patterns in the system operation. In those models, control architecture and control logic are faithfully implemented. Thus, they can be used to study control-related faults, such as incorrect staging control due to sensor bias and mistuned feedback control. Second, they are readily extensible and can support large-scale investigations to explore different faulty conditions/scenarios. Those models are established in a hierarchical structure while modules in each layer can be redeclared and parameterized at upper layers. In such a case, modifications to the models can be realized through model modifiers and the process can be easily streamlined with scripts. We applied the proposed models in a comprehensive fault impact evaluation of the 13 control-related faults of chiller and boiler plants. In this evaluation, the proposed plant model is coupled with the EnergyPlus thermal load model to study the impact of various faulty scenarios. Based on the evaluation results, we identified the faults that have the most significant impacts on the operation of the chiller and boiler plants, respectively. We also found that the relationship between the impacts of the studied faults and the severity level of the faults are highly non-linear

Huang, Sen↗
DOE OSTI2014

Adsorption of probe molecules in pillared interlayered clays: Experiment and computer simulation

In this paper we investigate the adsorption of various probe molecules in order to characterize the porous structure of a series of pillared interlayered clays (PILC). To that aim, volumetric and microcalorimetric adsorption experiments were performed on various Zr PILC samples using nitrogen, toluene, and mesitylene as probe molecules. For one of the samples, neutron scattering experiments were also performed using toluene as adsorbate. Various structural models are proposed and tested by means of a comprehensive computer simulation study, using both geometric and percolation analysis in combination with Grand Canonical Monte Carlo simulations in order to model the volumetric and microcalorimetric isotherms. On the basis of this analysis, we propose a series of structural models that aim at accounting for the adsorption experimental behavior, and make possible a microscopic interpretation of the role played by the different interactions and steric effects in the adsorption processes in these rather complex disordered microporous systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Ab Initio Modeling of Structure and Properties of Single and Mixed Alkali Silicate Glasses

A density functional theory (DFT)-based ab initio molecular dynamics (AIMD) has been applied to simulate models of single and mixed alkali silicate glasses with two different molar concentrations of alkali oxides. The structural environments and spatial distributions of alkali ions in the 10 simulated models with 20% and 30% of Li, Na, K and equal proportions of Li–Na and Na–K are studied in detail for subtle variations among the models. Quantum mechanical calculations of electronic structures, interatomic bonding, and mechanical and optical properties are carried out for each of the models, and the results are compared with available experimental observation and other simulations. The calculated findings are in good agreement with the experimental data. We have used the novel concept of using the total bond order density (TBOD), a quantum mechanical metric, to characterize internal cohesion in these glass models. The mixed alkali effect (MAE) is visible in the bulk mechanical properties but not obvious in other physical properties studied in this paper. We demonstrate that Li doping deviates from expected trend due to the much stronger Li–O bonding than those of Na and K doping. Our method is in contrast with current studies in alkali-doped silicate glasses based only on geometric characterizations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

Significance We provide a method for population-based structure modeling of whole diploid genomes using Hi-C data. The method considers the stochastic nature of chromosome structures, which allows a detailed analysis of the dynamic landscape of genome organizations. We predict and experimentally validate the presence of chromosome-specific higher-order centromere clusters, which can play a key role in the spatial organization of the human genome, specifically influencing the overall chromosome positioning, as well as the preference of specific chromosome conformations. Our approach generate predictive structural models of diploid genomes from Hi-C data, which can provide insights into the guiding principles of 3D genome organizations.

3D genome organization↗
DOE OSTI2017

Gradient-Based Optimization of Wind Farms with Different Turbine Heights: Preprint

Turbine wakes reduce power production in a wind farm. Current wind farms are generally built with turbines that are all the same height, but if wind farms included turbines with different tower heights, the cost of energy (COE) may be reduced. We used gradient-based optimization to demonstrate a method to optimize wind farms with varied hub heights. Our study includes a modified version of the FLORIS wake model that accommodates three-dimensional wakes integrated with a tower structural model. Our purpose was to design a process to minimize the COE of a wind farm through layout optimization and varying turbine hub heights. Results indicate that when a farm is optimized for layout and height with two separate height groups, COE can be lowered by as much as 5%-9%, compared to a similar layout and height optimization where all the towers are the same. The COE has the best improvement in farms with high turbine density and a low wind shear exponent.

17 WIND ENERGY↗
DOE OSTI2023

Reducing uncertainty of high-latitude ecosystem models through identification of key parameters

Abstract Climate change is having significant impacts on Earth’s ecosystems and carbon budgets, and in the Arctic may drive a shift from an historic carbon sink to a source. Large uncertainties in terrestrial biosphere models (TBMs) used to forecast Arctic changes demonstrate the challenges of determining the timing and extent of this possible switch. This spread in model predictions can limit the ability of TBMs to guide management and policy decisions. One of the most influential sources of model uncertainty is model parameterization. Parameter uncertainty results in part from a mismatch between available data in databases and model needs. We identify that mismatch for three TBMs, DVM-DOS-TEM, SIPNET and ED2, and four databases with information on Arctic and boreal above- and belowground traits that may be applied to model parametrization. However, focusing solely on such data gaps can introduce biases towards simple models and ignores structural model uncertainty, another main source for model uncertainty. Therefore, we develop a causal loop diagram (CLD) of the Arctic and boreal ecosystem that includes unquantified, and thus unmodeled, processes. We map model parameters to processes in the CLD and assess parameter vulnerability via the internal network structure. One important substructure, feed forward loops (FFLs), describe processes that are linked both directly and indirectly. When the model parameters are data-informed, these indirect processes might be implicitly included in the model, but if not, they have the potential to introduce significant model uncertainty. We find that the parameters describing the impact of local temperature on microbial activity are associated with a particularly high number of FFLs but are not constrained well by existing data. By employing ecological models of varying complexity, databases, and network methods, we identify the key parameters responsible for limited model accuracy. They should be prioritized for future data sampling to reduce model uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Novel Method to Train Classification Models for Structure Detection in In Situ Spacecraft Data

We present a method for creating spacecraft-like data which can be used to train Machine Learning (ML) models to detect and classify structures in in situ spacecraft data. First, we use the Grad-Shafranov equation to numerically solve for several magnetohydrostatic equilibria which are variations on a known analytic equilibrium. These equilibria are then used as the initial conditions for Particle-In-Cell simulations in which the structures of interest are observed and labeled. We then take one-dimensional slices through the simulations to replicate what a spacecraft collecting data from the simulation would observe. This sliced data then can be used as training data for the initial training of ML models intended for use on spacecraft data. We demonstrate the method applied to the problem of detecting small-scale plasmoids in the magnetotail, which is important for understanding complex magnetotail reconnection dynamics. The simple 1D classifier we train is able to detect more than 70% of the plasmoid points in the data set but also produces a large number of false positives. Our further work on this example problem is detailed, and further potential uses of the method are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Integrative Analysis of Metabolic Models – from Structure to Dynamics

The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the context of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Resolving Atomic-Scale Structure and Chemical Coordination in High-Entropy Alloy Electrocatalysts for Structure–Function Relationship Elucidation

The recent breakthrough in confining five or more atomic species in nanocatalysts, referred to as high-entropy alloy nanocatalysts (HEAs), has revealed the possibilities of multielemental interactions that can surpass the limitations of binary and ternary electrocatalysts. The wide range of potential surface configurations in HEAs, however, presents a significant challenge in resolving active structural motifs, preventing the establishment of structure-function relationships for rational catalyst design and optimization. Here, we present a methodology for creating sub-5 nm HEAs using an aqueous-based peptide-directed route. Using a combination of pair distribution function and X-ray absorption spectroscopy, HEA structure models are constructed from reverse Monte Carlo modeling of experimental data sets and showcase a clear peptide-induced influence on atomic-structure and chemical miscibility. Coordination analysis of our structure models facilitated the construction of structure-function correlations applied to electrochemical methanol oxidation reactions, revealing the complex interplay between multiple metals that leads to improved catalytic properties. Our results showcase a viable strategy for elucidating structure-function relationships in HEAs, prospectively providing a pathway for future materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Mapping the three-dimensional “x-shaped structure” in models of the Galactic bulge

Numerical simulations have shown that the X-shaped structure in the Milky Way bulge can naturally arise from bar instability and buckling instability. To understand the influence of buckling amplitude on the morphology of the X-shape, we analyze three self-consistent numerical simulations of barred galaxies with different buckling amplitudes (strong, intermediate, and weak). We derive the three-dimensional density using an adaptive kernel smoothing technique. The face-on isodensity surfaces are all elliptical, while in the edge-on view, the morphology of buckled bars transitions with increasing radius from a central boxy core to a peanut bulge and then to an extended, thin bar. Based on these isodensity surfaces at different density levels, we find no clear evidence for a well-defined structure shaped like the letter X. The X-shaped structure is more peanut-like, the visual perception of which is probably enhanced by the pinched inner concave isodensity contours. The peanut bulge can reproduce qualitatively the observed bimodal distributions that were used as evidence for the discovery of the X-shape. The central boxy core is shaped like an oblong tablet, extending ∼500 pc above and below the Galactic plane (|b|∼4{sup ∘}). From the solar perspective, lines of sight passing through the central boxy core do not show bimodal distributions. This generally agrees with the observations that double peaks merge at |b| ∼ 4°–5° from the Galactic plane, indicating the presence of a possibly similar structure in the Galactic bulge.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Oxygen Defect Configurations in Single-Phase UO 2.15

Hyperstoichiometric UO 2.15 was characterized by neutron total scattering at high temperature in the single-phase UO 2+x region of the U/O phase diagram. The diffraction data confirmed a single-phase fluorite structure at high temperature. Analysis of the short-range data showed that the same structural model does not fit the pair distribution functions well. Instead, structural models containing specific configurations of oxygen defect clusters best represent the local atomic arrangement. In conclusion, prevalent defect clusters previously proposed were fit to the experimental data, and moderately distorted oxygen cuboctahedra hypothesized by recent molecular dynamics simulations fit the data most accurately.

neutron pair-distribution function analysis↗
DOE OSTI2024

High throughput, accurate gene annotation through AI and HPC-enabled structural analysis

With the advances in next generation sequencing technologies, the number of sequenced genomes is growing exponentially, resulting in a technology bottleneck for the translation of sequence information into usable hypotheses about the function of each gene. We have proposed leveraging our leadership high-performance computing (HPC) resources to help break this annotation bottleneck. Here we design an HPC-based framework to infer gene function from gene sequence by incorporating information about protein structure and interactions predicted by deep learning approaches. Accurate functional prediction and gene annotation using computational methods will facilitate breakthroughs in the genomic sciences essential to understanding and harnessing life processes in bacteria, fungi and plants. The development and applications of the state-of-the-art deep neural networks to protein structural modeling, interaction prediction, sequence comparison, and quality assessment of protein structural models will be made possible by leadership computational resources. These HPC-enabled bioinformatics and molecular modeling tools will provide powerful insights into molecular functions of genes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Surface termination structure of α-Ga{sub 2}O{sub 3} film grown by mist chemical vapor deposition

The surface structure of α-Ga{sub 2}O{sub 3}(0001) grown on an α-Al{sub 2}O{sub 3}(0001) substrate by mist chemical vapor deposition was studied by coaxial impact-collision ion scattering spectroscopy (CAICISS) and atomic force microscopy (AFM). The minimum step height observed in the AFM image was 0.21 ± 0.01 nm, coinciding with the height of three atomic layers of α-Ga{sub 2}O{sub 3}(0001). It was revealed by CAICISS analysis that the surface of α-Ga{sub 2}O{sub 3}(0001) is terminated by a Ga layer followed by an O layer, which is consistent with the surface termination of α-Al{sub 2}O{sub 3}(0001). A structural model taking surface relaxation into account was also constructed by fitting the simulated curve for the azimuth angle dependence of the Ga intensity to the experimental dependence. The resultant structural model is similar to the model of an α-Al{sub 2}O{sub 3}(0001) surface, which indicates analogous behavior in corundum crystals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

The Use of Raman Spectroscopy and Methods of Quantum Chemistry for Assessing the Relative Concentration of Triglycerides of Oleic and Linoleic Acids in a Mixture of Olive Oil and Sunflower Seed Oil

The Raman spectra of five samples of sunflower seed oil and five samples of cold-pressed olive oil of various brands are recorded in the range of 500–2000 cm{sup –1}. Within the framework of the B3LYP/6-31G(d)/6-31G(d,p)/6-31+G(d,p)/6-311G(d)/6-311G(d, p)/6-311+G(d,p) methods, the structural models of eight fatty acids (oleic, linoleic, palmitic, stearic, α-linolenic, arachidonic, eicosapentaenoic, and docosahexaenoic) are constructed, and also within the framework of the B3LYP/6-31G(d) method, the structural models of triglycerides of the first four of the above acids are obtained. The vibrational wavenumbers and intensities in the IR and Raman spectra are calculated. The Raman spectra of olive oil and sunflower seed oil were simulated by using the supermolecular approach. We investigated the dependence of the relative intensity of the vibrational bands ν{sub exp} = 1660 and 1445 cm{sup –1} on the concentration of triglycerides in oils of oleic and linoleic acids and the dependence of the intensity of these bands on the degree of saturation of fatty acids. Experimental and empirical dependences are constructed to estimate the relative concentration of triglycerides of oleic and linoleic acids in a mixture of olive oil and sunflower seed oil. The applicability of the density functional theory together with the vibrational spectroscopy for the identification of mixtures of vegetable oils is discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

A Review on Lignin Liquefaction: Advanced Characterization of Structure and Microkinetic Modeling

Lignin liquefaction microkinetics is a move toward a more first principles (i.e., ab initio) based understanding at the molecular level in reaction engineering. While the microkinetic modelling of reactions to obtain kinetic rate parameters of chemical reactions have been widely used in the field of gas phase combustion and heterogeneous catalysis, this approach has not been as thoroughly developed in the area of biomass thermochemical reactions (e.g., lignin pyrolysis, hydrothermal liquefaction). The difficulties in establishing the structure of complex heterogeneous materials, like lignin, is perhaps the main challenge in developing rational microkinetic descriptions of biomass thermochemical reactions. In this manuscript we review the current state of the art and the challenges to develop microkinetic models for lignin liquefaction technologies (e.g., pyrolysis, hydrothermal liquefaction, solvolysis). A general strategy for the development of microkinetic models for lignin liquefaction technologies is discussed. Here, the first hurdle is to obtain sufficiently rich experimental data of lignin underlying polymeric structure and methodologies to use this data to build realistic lignin structural representations. Some analytical techniques for lignin structural characterization and their associated data, as well as a correlation for calculating the degree of macromolecular lignin branching are discussed. The presence of small lignin oligomeric structures and the role of these structures in lignin pyrolysis is also addressed. The ways in which elementary deconstruction and repolymerization reactions occur within this structure to form a liquid intermediate, and how these deconstruction products continue to interact with each other until they are removed from the liquid intermediate is thoroughly discussed. Further, experimental work with model compounds and the effect of reaction parameters (e.g., temperature, pressure, vapor residence time) are reviewed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗