Search NASA⌕ Search

SEARCH · Search NASA

Results for “Structural models”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Observing structural reorientations at solvent–nanoparticle interfaces by X-ray diffraction – putting water in the spotlight

Nanoparticles are attractive in a wide range of research genres due to their size-dependent properties, which can be in contrast to those of micrometre-sized colloids or bulk materials. This may be attributed, in part, to their large surface-to-volume ratio and quantum confinement effects. There is a growing awareness that stress and strain at the particle surface contribute to their behaviour and this has been included in the structural models of nanoparticles for some time. One significant oversight in this field, however, has been the fact that the particle surface affects its surroundings in an equally important manner. It should be emphasized here that the surface areas involved are huge and, therefore, a significant proportion of solvent molecules are affected. Experimental evidence of this is emerging, where suitable techniques to probe the structural correlations of liquids at nanoparticle surfaces have only recently been developed. The recent validation of solvation shells around nanoparticles has been a significant milestone in advancing this concept. Restructured ordering of solvent molecules at the surfaces of nanoparticles has an influence on the entire panoply of solvent–particle interactions during, for example, particle formation and growth, adhesion forces in industrial filtration, and activities of nanoparticle–enzyme complexes. This article gives an overview of the advances made in solvent–nanoparticle interface research in recent years: from description of the structure of bulk solids and liquids via macroscopic planar surfaces, to the detection of nanoscopic restructuring effects. Water–nanoparticle interfaces are given specific attention to illustrate and highlight their similarity to biological systems.

36 MATERIALS SCIENCE↗
DOE OSTI2014

SERIIUS-MAGEEP Visiting Scholars Program

Recent studies have assessed closed-loop supercritical carbon dioxide (s-CO 2 ) Brayton cycles to be a higher energy-density system in comparison to equivalent superheated steam Rankine systems. At turbine inlet conditions of 700°C and 20 MPa, a cycle thermal efficiency of ~50% can be achieved. Achieving these high efficiencies will help concentrating solar power (CSP) technologies to become a competitive alternative to current power generation methods. To incorporate an s-CO 2 Brayton power cycle in a solar power tower system, the development of a solar receiver capable of providing an outlet temperature of 700°C (at 20 MPa) is necessary. To satisfy the temperature requirements of an s-CO 2 Brayton cycle with recuperation and recompression, the s-CO 2 must undergo a temperature rise of ~200°C as it flows through the solar receiver. The main objective is to develop an optical-thermal-fluid and structural model to validate a tubular receiver that will receive a heat input ~0.33 MWth from the heliostat field at the National Solar Thermal Test Facility (NSTTF), Albuquerque, NM, USA. We also commenced the development of computational models and testing of air receivers being developed by the Indian Institute of Science (IISc) and the Indian Institute of Technology in Bombay (IIT-B). The helical tubular receiver is expected to counteract the effect of thermal expansion while using a cavity to reduce the radiative and convective losses. Initially, this receiver will be tested for a temperature range of 100-300°C under 1 MPa of pressurized air. The helical air receiver will be exposed to 10kWth to achieve a temperature rise of ~200°C. Preliminary tests to validate the modeling will be performed before the design and construction of a larger scale receiver. Lastly, I focused on the development of a new computational tool that would allow us to perform a nodal creep-fatigue analysis on the receivers and heat exchangers being developed. This tool was developed using MATLAB and is capable of processing the results obtained from ANSYS Fluent and Structural combined, which was limited when using commercial software. The main advantage of this code is that it can be modified to run in parallel making it more affordable and faster compared to commercial codes available. The code is in the process of validation and is currently being compared to nCode Design Life.

25 ENERGY STORAGE↗
DOE OSTI2012

Study of liquid gallium at high pressure using synchrotron x-ray

Liquid gallium has been studied at high pressure up to 2 GPa and ambient temperature in a diamond anvil cell using high energy synchrotron x-ray beam. The total x-ray scattering data of liquid gallium were collected up to Q = 12 A{sup -1} and analyzed using pair distribution functions (PDF). The results indicate that the first nearest neighbor peak and second nearest neighbor (shoulder) peak of PDF in liquid gallium does not change with pressure, whereas the higher order (i.e., third and fourth) nearest neighbor peaks shift towards shorter distance with increasing pressure. Reverse Monte Carlo modeling based on the observed data shows that the coordination number in the liquid gallium increases with pressure from 10.5 at 0.3 GPa to 11.6 at 2 GPa. An atomic arrangement similar to the crystalline phase of Ga(II) with coordination number of 12 is proposed for the locally dense-packed rigid unit in liquid gallium. The volume compression data derived from the structure modeling yield a bulk modulus of 12.1(6) GPa for liquid gallium.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

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↗
DOE OSTI2017

Deep learning for computational chemistry

The rise and fall of artificial neural networks is well documented in the scientific literature of both the fields of computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on “deep” neural networks. Within the last few years, we have seen the transformative impact of deep learning the computer science domain, notably in speech recognition and computer vision, to the extent that the majority of practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties as compared to traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including QSAR, virtual screening, protein structure modeling, QM calculations, materials synthesis and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non neural networks state-of-the-art models across disparate research topics, and deep neural network based models often exceeded the “glass ceiling” expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a useful tool and may grow into a pivotal role for various challenges in the computational chemistry field.

Computational Chemistry↗
DOE OSTI2021

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↗
DOE OSTI2024

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↗
DOE OSTI2025

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↗
DOE OSTI2014

Pf1 bacteriophage hydration by magic angle spinning solid-state NMR

High resolution two- and three-dimensional heteronuclear correlation spectroscopy ({sup 1}H–{sup 13}C, {sup 1}H–{sup 15}N, and {sup 1}H–{sup 13}C–{sup 13}C HETCOR) has provided a detailed characterization of the internal and external hydration water of the Pf1 virion. This long and slender virion (2000 nm × 7 nm) contains highly stretched DNA within a capsid of small protein subunits, each only 46 amino acid residues. HETCOR cross-peaks have been unambiguously assigned to 25 amino acids, including most external residues 1–21 as well as residues 39–40 and 43–46 deep inside the virion. In addition, the deoxyribose rings of the DNA near the virion axis are in contact with water. The sets of cross-peaks to the DNA and to all 25 amino acid residues were from the same hydration water {sup 1}H resonance; some of the assigned residues do not have exchangeable side-chain protons. A mapping of the contacts onto structural models indicates the presence of water “tunnels” through a highly hydrophobic region of the capsid. The present results significantly extend and modify results from a lower resolution study, and yield a comprehensive hydration surface map of Pf1. In addition, the internal water could be distinguished from external hydration water by means of paramagnetic relaxation enhancement. The internal water population may serve as a conveniently localized magnetization reservoir for structural studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

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↗
DOE OSTI2022

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↗
DOE OSTI2016

Characterization of DWARF14 Genes in Populus

Strigolactones are a new class of plant hormones regulating shoot branching and symbiotic interactions with arbuscular mycorrhizal fungi. Studies of branching mutants in herbaceous plants have identified several key genes involved in strigolactone biosynthesis or signaling. The strigolactone signal is perceived by a member of the α/β-fold hydrolase superfamily, known as DWARF14 (D14). However, little is known about D14 genes in the woody perennial plants. Here we report the identification of D14 homologs in the model woody plant Populus trichocarpa. We showed that there are two D14 homologs in P. trichocarpa, designated as PtD14a and PtD14b that are over 95% similar at the amino acid level. Expression analysis indicated that the transcript level of PtD14a is generally more abundant than that of PtD14b. However, only PtD14a was able to complement Arabidopsis d14 mutants, suggesting that PtD14a is the functional D14 ortholog. Amino acid alignment and structural modeling revealed substitutions of several highly conserved amino acids in the PtD14b protein including a phenylalanine near the catalytic triad of D14 proteins. Ultimately, we find this study lays a foundation for further characterization of strigolactone pathway and its functions in the woody perennial plants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Direct observation of electronic-liquid-crystal phase transitions and their microscopic origin in La 1/3 Ca 2/3 MnO 3

The ground-state electronic order in doped manganites is frequently associated with a lattice modulation, contributing to their many interesting properties. However, measuring the thermal evolution of the lattice superstructure with reciprocal-space probes alone can lead to ambiguous results with competing interpretations. Here, we provide direct observations of the evolution of the superstructure in La 1/3 Ca 2/3 MnO 3 in real space, as well as reciprocal space, using transmission electron microscopic (TEM) techniques. We show that the transitions are the consequence of a proliferation of dislocations plus electronic phase separation. The resulting states are well described by the symmetries associated with electronic-liquid-crystal (ELC) phases. Furthermore, our results resolve the long-standing controversy over the origin of the incommensurate superstructure and suggest a new structural model that is consistent with recent theoretical calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

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↗
DOE OSTI2018

Structural parameters of the nearest environment of ions in aqueous solutions of ytterbium chloride

The radial distribution functions (RDFs) of aqueous solutions of ytterbium chloride were calculated using previously collected X-ray diffraction data for a wide range of solution concentrations under ambient conditions. Different solution structure models were constructed. Theoretical RDFs were calculated for each model. The optimum models for all systems studied were chosen based on the best fit between the theoretical and experimental RDFs. Quantitative characteristics of the nearest environment of Yb{sup 3+} and Cl{sup –} ions in solutions, namely, the coordination number, interparticle distances, and types of ion pairs were determined. The average number of water molecules in the first coordination sphere of the cation decreases from 8.2 to 6.0 as the solution concentration increases. The structure of all systems investigated is governed by non-contact ion associates throughout the concentration range studied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

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↗