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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Initial stages of ITO/Si interface formation: In situ x-ray photoelectron spectroscopy measurements upon magnetron sputtering and atomistic modelling using density functional theory

Initial stages of indium tin oxide (ITO) growth on a polished Si substrate upon magnetron sputtering were studied experimentally using in-situ x-ray photoelectron spectroscopy measurements. The presence of pure indium and tin, as well as Si bonded to oxygen at the ITO/Si interface were observed. The experimental observations were compared with several atomistic models of ITO/Si interfaces. A periodic model of the ITO/Si interface was constructed, giving detailed information about the local environment at the interface. Molecular dynamics based on density functional theory was performed, showing how metal-oxygen bonds are broken on behalf of silicon-oxygen bonds. These theoretical results support and provide an explanation for the present as well as previous ex-situ and in-situ experimental observations pointing to the creation of metallic In and Sn along with the growth of SiO{sub x} at the ITO/Si interface.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

(U) Validation and Optimization of a 1-Dimensional Quasi-Isentropic Compression Model Using a Functionally Graded Material Flyer Plate

The fields studying highly compressed materials have been around for many years. These fields have given birth to better understandings of the solar fusion cycle and the liquid-metallic core of Jupiter. The highest pressures achieved have been at the National Ignition Facility (NIF) and more recently, the Z-Machine. One method to achieve higher levels of compression is to use quasi-isentropic (QI) compression. In practice, this means minimizing the amount of temperature increase of the target material. In their paper, J.H. Nguyen et. al. manufactured a functionally graded material (FGM) in order to help them achieve QI compression. The aim of the study described in this paper is to validate a 1-dimensional (1D) FLAG model that uses an FGM flyer to compress a copper (Cu) target. Once validated, the density/composition profile of the FGM is varied and optimized using Markov Chain Monte Carlo, specifically using a Metropolis-Hastings algorithm to find the optimal FGM profile that minimizes the temperature increase in the copper.

36 MATERIALS SCIENCE↗
DOE OSTI2023

In Situ Raman Mapping of Si Island Electrodes and Stress Modeling as a Function of Lithiation and Size

Si is known for cracking and delamination during electrochemical cycling of a battery due to the large volume change associated with Li insertion and extraction. However, it has been found experimentally that patterned Si island electrodes that are 200 nm thick and less than 7 μm wide can deform in a purely elastic manner. Inspired by this, we performed in situ Raman stress characterization of model poly-crystalline Si island electrodes using an electrochemical cell coupled with an immersion objective lens and designed for a short working distance. A 5 μm wide Si island electrode showed a parabolic stress profile during lithiation, while for a 15 μm Si island electrode, a stress plateau in the center of the electrode was observed. A continuum model with coupled electro-chemo-mechanical (ECM) physics was established to understand the stress measurement. A qualitative agreement was reached between modeling and experimental data, and the critical size effect could be explained by the Li diffusive flux as governed by competition between the Li concentration and hydrostatic stress gradients. Below the critical size, the stress gradient drives Li toward the edges, where the electrode volume is free to expand, while above the critical size, the stress plateau inhibits Li diffusion to the edge and forces destructive stress relief by cracking. Furthermore, this work represents a promising methodology for in situ characterization of ECM coupling in battery electrodes, with suggestions provided for further improvement.

25 ENERGY STORAGE↗
DOE OSTI2014

Application of Gaussian Process Modeling to Analysis of Functional Unreliability

This paper applies Gaussian Process (GP) modeling to analysis of the functional unreliability of a “passive system.” GPs have been used widely in many ways [1]. The present application uses a GP for emulation of a system simulation code. Such an emulator can be applied in several distinct ways, discussed below. All applications illustrated in this paper have precedents in the literature; the present paper is an application of GP technology to a problem that was originally analyzed [2] using neural networks (NN), and later [3, 4] by a method called “Alternating Conditional Expectations” (ACE). This exercise enables a multifaceted comparison of both the processes and the results. Given knowledge of the range of possible values of key system variables, one could, in principle, quantify functional unreliability by sampling from their joint probability distribution, and performing a system simulation for each sample to determine whether the function succeeded for that particular setting of the variables. Using previously available system simulation codes, such an approach is generally impractical for a plant-scale problem. It has long been recognized, however, that a well-trained code emulator or surrogate could be used in a sampling process to quantify certain performance metrics, even for plant-scale problems. “Response surfaces” were used for this many years ago. But response surfaces are at their best for smoothly varying functions; in regions of parameter space where key system performance metrics may behave in complex ways, or even exhibit discontinuities, response surfaces are not the best available tool. This consideration was one of several that drove the work in [2]. In the present paper, (1) the original quantification of functional unreliability using NN [2], and later ACE [3], is reprised using GP; (2) additional information provided by the GP about uncertainty in the limit surface, generally unavailable in other representations, is discussed; (3) a simple forensic exercise is performed, analogous to the inverse problem of code calibration, but with an accident management spin: given an observation about containment pressure, what can we say about the system variables? References 1. For an introduction to GPs, see (for example) Gaussian Processes for Machine Learning, C. E. Rasmussen and C. K. I. Williams (MIT, 2006). 2. Reliability Quantification of Advanced Reactor Passive Safety Systems, J. J. Vandenkieboom, PhD Thesis (University of Michigan, 1996). 3. Z. Cui, J. C. Lee, J. J. Vandenkieboom, and R. W. Youngblood, “Unreliability Quantification of a Containment Cooling System through ACE and ANN Algorithms,” Trans. Am. Nucl. Soc. 85, 178 (2001). 4. Risk and Safety Analysis of Nuclear Systems, J. C. Lee and N. J. McCormick (Wiley, 2011). See especially §11.2.4.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

A Multi-Function AAA Algorithm Applied to Frequency Dependent Line Modeling

Modeling of power distribution system components that are valid for a wide range of frequencies are crucial for highly accurate modeling of electromagnetic transient (EMT) events. This has recently become of interest due to the improvements needed for the resilient operation of distribution systems. Vector fitting (VF) is a very popular and commonly used algorithm for wide band representations of power system components in EMT simulations. In this research, we present a new multi-input rational approximation algorithm (MIAAA) and illustrate its advantages with respect to VF using examples of approximations of admittance matrices discussed in the literature. We show that MIAAA not only outperforms VF in terms of achieving better accuracy using lesser number of poles, but also has no numerical issues achieving convergence. In contrast to VF, MIAAA is not sensitive to the location of input sample points and it does not require good estimates for the location of the desired approximation poles. The novelty of this research work is the use of recent mathematical results to solve existing challenges in distribution system modeling and to develop rational approximations for power system models that intend to be optimal in terms of accuracy and performance.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2024

Approaching periodic systems in ensemble density functional theory via finite one-dimensional models

Ensemble density functional theory (EDFT) is a generalization of ground-state DFT, which is based on an exact formal theory of finite collections of a system's ground and excited states. EDFT in various forms has been shown to improve the accuracy of calculated energy level differences in isolated model systems, atoms, and molecules, but it is not yet clear how EDFT could be used to calculate band gaps for periodic systems. We extend the application of EDFT toward periodic systems by estimating the thermodynamic limit with increasingly large finite one-dimensional 'particle in a box' systems, which approach the uniform electron gas (UEG). Using ensemble-generalized Hartree and local spin density approximation exchange-correlation functionals, we find that corrections go to zero in the infinite limit, as expected for a metallic system. However, there is a correction to the effective mass, with results comparable to other calculations on 1D, 2D, and 3D UEGs, which indicates promise for non-trivial results from EDFT on periodic systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Bond length and electric current oscillation of long linear carbon chains: Density functional theory, MpB model, and quantum spin transport studies

Carbon linear atomic chains attached to graphene have experimentally been produced. Motivated by these results, we study the nature of the carbon bonds in these nanowires and how it affects their electrical properties. In the present study we investigate chains with different numbers of atoms and we observe that nanowires with odd number of atoms present a distinct behavior than the ones with even numbers. Using graphene nanoribbons as leads, we identify differences in the quantum transport of the chains with the consequence that even and odd numbered chains have low and high electrical conduction, respectively. We also noted a dependence of current with the wire size. We study this unexpected behavior using a combination of first principles calculations and simple models based on chemical bond theory. From our studies, the electrons of carbon nanowires present a quasi-free electron behavior and this explains qualitatively the high electrical conduction and the bond lengths with unexpected values for the case of odd nanowires. Our study also allows the understanding of the electric conduction dependence with the number of atoms and their parity in the chain. In the case of odd number chains a proposed π-bond (MpB) model describes unsaturated carbons that introduce a mobile π-bond that changes dramatically the structure and transport properties of these wires. Our results indicate that the nature of bonds plays the main role in the oscillation of quantum electrical conduction for chains with even and odd number of atoms and also that nanowires bonded to graphene nanoribbons behave as a quasi-free electron system, suggesting that this behavior is general and it could also remain if the chains are bonded to other materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

MUTZ-3 derived Langerhans cells in human skin equivalents show differential migration and phenotypic plasticity after allergen or irritant exposure

After allergen or irritant exposure, Langerhans cells (LC) undergo phenotypic changes and exit the epidermis. In this study we describe the unique ability of MUTZ-3 derived Langerhans cells (MUTZ-LC) to display similar phenotypic plasticity as their primary counterparts when incorporated into a physiologically relevant full-thickness skin equivalent model (SE-LC). We describe differences and similarities in the mechanisms regulating LC migration and plasticity upon allergen or irritant exposure. The skin equivalent consisted of a reconstructed epidermis containing primary differentiated keratinocytes and CD1a{sup +} MUTZ-LC on a primary fibroblast-populated dermis. Skin equivalents were exposed to a panel of allergens and irritants. Topical exposure to sub-toxic concentrations of allergens (nickel sulfate, resorcinol, cinnamaldehyde) and irritants (Triton X-100, SDS, Tween 80) resulted in LC migration out of the epidermis and into the dermis. Neutralizing antibody to CXCL12 blocked allergen-induced migration, whereas anti-CCL5 blocked irritant-induced migration. In contrast to allergen exposure, irritant exposure resulted in cells within the dermis becoming CD1a{sup −}/CD14{sup +}/CD68{sup +} which is characteristic of a phenotypic switch of MUTZ-LC to a macrophage-like cell in the dermis. This phenotypic switch was blocked with anti-IL-10. Mechanisms previously identified as being involved in LC activation and migration in native human skin could thus be reproduced in the in vitro constructed skin equivalent model containing functional LC. This model therefore provides a unique and relevant research tool to study human LC biology in situ under controlled in vitro conditions, and will provide a powerful tool for hazard identification, testing novel therapeutics and identifying new drug targets. - Highlights: • MUTZ-3 derived Langerhans cells integrated into skin equivalents are fully functional. • Anti-CXCL12 blocks allergen-induced MUTZ-LC migration. • Anti-CCL5 blocks irritant-induced MUTZ-LC migration. • Irritant mediated MUTZ-LC trans-differentiation to macrophage-like cell in dermis. • Trans-differentiation of MUTZ-LC is IL-10 dependent.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Modeling pair distribution functions of rare-earth phosphate glasses using principal component analysis

The use of principal component analysis (PCA) to statistically infer features of local structure from experimental pair distribution function (PDF) data is assessed on a case study of rare-earth phosphate glasses (REPGs). Such glasses, co-doped with two rare-earth ions (R and R’) of different sizes and optical properties, are of interest to the laser industry. The determination of structure-property relationships in these materials is an important aspect of their technological development. Yet, realizing the local structure of co-doped REPGs presents significant challenges relative to their singly-doped counterparts; specifically, R and R’ are difficult to distinguish in terms of establishing relative material compositions, identifying atomic pairwise correlation profiles in a PDF that are associated with each ion, and resolving peak overlap of such profiles in PDFs. This study demonstrates that PCA can be employed to help overcome these structural complications, by statistically inferring trends in PDFs that exist for a restricted set of experimental data on REPGs, and using these as training data to predict material compositions and PDF profiles in unknown co-doped REPGs. The application of these PCA methods to resolve individual atomic pairwise correlations in t(r) signatures is also presented. The training methods developed for these structural predictions are pre-validated by testing their ability to reproduce known physical phenomena, such as the lanthanide contraction, on PDF signatures of the structurally simpler singly-doped REPGs. The intrinsic limitations of applying PCA to analyze PDFs relative to the quality control of source data, data processing, and sample definition, are also considered. Furthermore, while this case study is limited to lanthanide-doped REPGs, this type of statistical inference may easily be extended to other inorganic solid-state materials, and be exploited in large-scale data-mining efforts that probe many t(r) functions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Metagenome-assembled genome extraction and analysis from microbiomes using KBase

Uncultivated Bacteria and Archaea account for the vast majority of species on Earth, but obtaining their genomes directly from the environment, using shotgun sequencing, has only become possible recently. In order to realize the hope of capturing Earth’s microbial genetic complement and to facilitate the investigation of the functional roles of specific lineages in a given ecosystem, technologies that accelerate the recovery of high-quality genomes are necessary. We present a series of analysis steps and data products for the extraction of high-quality metagenome-assembled genomes (MAGs) from microbiomes using the U.S. Department of Energy Systems Biology Knowledgebase (KBase) platform (http://www.kbase.us/). Overall, these steps take about a day to obtain extracted genomes when starting from smaller environmental shotgun read libraries, or up to about a week from larger libraries. In KBase, the process is end-to-end, allowing a user to go from the initial sequencing reads all the way through to MAGs, which can then be analyzed with other KBase capabilities such as phylogenetic placement, functional assignment, metabolic modeling, pangenome functional profiling, RNA-Seq and others. While portions of such capabilities are available individually from other resources, the combination of the intuitive usability, data interoperability and integration of tools in a freely available computational resource makes KBase a powerful platform for obtaining MAGs from microbiomes. While this workflow offers tools for each of the key steps in the genome extraction process, it also provides a scaffold that can be easily extended with additional MAG recovery and analysis tools, via the KBase software development kit (SDK).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Prebiotic RNA Polymerisation: Energetics of Nucleotide Adsorption and Polymerisation on Clay Mineral Surfaces

We measured the binding energy and bonding parameters between model nucleotide functional groups and model clay mineral surfaces in solutions of acidic pH. We demonstrate that basal surfaces of clay minerals interact most strongly with nucleobases and show that the adsorption of the phosphate group to clay edges could facilitate polymerisation. Our results suggest that Al- and Fe-rich edge sites behave similarly in nucleotide polymerisation through change of the phosphodiester bond strength. We present an internally consistent set of thermodynamic parameters that represent the nucleotide–clay mineral system.

Jelavic, Stanislov↗
DOE OSTI2024

Solving the Orszag–Tang vortex magnetohydrodynamics problem with physics-constrained convolutional neural networks

We study the 2D Orszag–Tang vortex magnetohydrodynamics (MHD) problem through the use of physics-constrained convolutional neural networks (PCNNs) for forecasting the density, ρ, and the magnetic field, B, as well as the prediction of B given the velocity field v of the fluid. In addition to translation equivariance from the convolutional architecture, other physics constraints were embedded: absence of magnetic monopoles, non-negativity of ρ, use of only relevant variables, and the periodic boundary conditions of the problem. The use of only relevant variables and the hard constraint of non-negative ρ were found to facilitate learning greatly. The divergenceless condition ∇·B=0 was implemented as a hard constraint up to machine precision through the use of a magnetic potential to define B=∇×A. Residual networks and data augmentation were also used to improve performance. This allowed for some of the residual models to function as surrogate models and provide reasonably accurate simulations. For the prediction task, the PCNNs were evaluated against a physics-informed neural network, which had the ideal MHD induction equation as a soft constraint. Several models were able to generate highly accurate fields, which are visually almost indistinguishable and have low mean squared error. Only methods with built-in hard constraints produced physical fields with ∇·B=0. The use of PCNNs for MHD has the potential to produce physically consistent real-time simulations to serve as virtual diagnostics in cases where inferences must be made with limited observables.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Optical fields in porous polylactide matrices

Optical fields induced by laser light inside porous polymer matrices (scaffolds) under stimulating effect on cells are investigated. The spectra of light scattering coefficients and anisotropy factors of porous polylactide scaffolds in the visible and near-IR ranges are determined by numerical simulation based on experimental data obtained using a double integrating sphere. Studies are conducted for dry and wet scaffolds fabricated by supercritical fluid foaming and surface-selective laser sintering. The Monte Carlo method is used to calculate the fluence rate distribution under the assumptions of the Henyey – Greenstein phase scattering function and the model phase function of scattering on spherical cavities. It is shown that th e fluence rate distribution mainly depends on the scattering coefficient and the mean cosine of the deflection angle (g-factor). The results obtained are of great practical importance for tissue engineering based on the use of polymeric porous scaffolds with cells to replace tissue defects; they can be used to determine the dose range for laser stimulation of cells. (paper)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Seeing red in M32: Constraints on the stellar content from near- and mid-infrared observations and applications for studies of more distant galaxies {sup ,} {sup ,}

The properties of asymptotic giant branch (AGB) stars in the Local Group galaxy M32 are investigated using ground- and space-based observations that span the 1-8 μm wavelength interval, with the goal of demonstrating the utility of infrared observations as probes of stellar content. Comparisons with isochrones indicate that the brightest resolved stars in M32 have ages of a few gigayears and are younger on average than AGB stars with the same intrinsic brightness in the outer disk of M31. Accounting for stellar variability is shown to be essential for modeling AGB luminosity functions (LFs). Model LFs that assume the star-forming history measured by Monachesi et al. and the variability properties of Galactic AGB stars match both the K and [5.8] LFs of M32. Models also suggest that the slope of the [5.8] LF between M{sub [5.8]} = –8.5 and –10.0 is sensitive to the mix of stellar ages, and a sizeable fraction of the stars in M32 must have an age older than 7 Gyr in order to match the [5.8] LF. The structural properties of M32 in the infrared are also investigated. The effective radii that are computed from near-infrared and mid-infrared isophotes are similar to those measured at visible wavelengths, suggesting that the stellar content of M32 is well mixed. However, isophotes at radii >16'' (>60 pc) in the near- and mid-infrared are flatter than those at visible wavelengths. The coefficient of the fourth-order cosine term in the Fourier expansion of isophotes changes from 'boxy' values at r < 16'' to 'disky' values at r > 48''in [3.6] and [4.5]. The mid-infrared colors near the center of M32 do not vary systematically with radius, providing evidence of a well mixed stellar content in this part of the galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Late day measurement of excised branches results in uncertainty in the estimation of two stomatal parameters derived from response curves in Populus deltoides Bartr. x Populus nigra L.

Many terrestrial biosphere models depend on an understanding of the relationship between stomatal conductance and photosynthesis. However, unlike the measurement of photosynthetic parameters, such as the maximum carboxylation capacity, where standard methods (e.g., CO 2 response or ACi curves) are widely accepted, a consensus method for empirically measuring parameters representing stomatal response has not yet emerged. Most models of stomatal response to environment represent stomatal conductance as being bounded by a lower intercept parameter (g 0 ), and linearly scaled based on a multivariate term described by the stomatal slope parameter (g 1 ). Here we employ the widely used Unified Stomatal Optimization model, to test whether g 1 and g 0 parameters are impacted by the choice of measurement method, either on an intact branch, or a cut branch segment stored in water. We measured paired stomatal response curves on intact and excised branches of a hybrid poplar clone (Populus deltoides Bartr. x Populus nigra L. OP367), measured twice over a diurnal period. We found that predawn branch excision did not significantly affect measured g 0 and g 1 when measured within 4 h of excision. Measurement in the afternoon resulted in significantly higher values of g 1 and lower values of g0, with values changing by 55% and 56% respectively. Excision combined with afternoon measurement resulted in a marked effect on parameter estimates, with g1 increasing 89% from morning to afternoon and a 25% lower g 1 for cut branches than those measured in situ. We also show that in hybrid poplar the differences in parameter estimates obtained from plants measured under different conditions can directly impact models of canopy function, reducing modeled transpiration by 18% over a simulated 12.5-hour period. While these findings are only for a single isohydric woody species, our findings suggest that stomatal optimality parameters may not remain constant throughout the day.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Accuracy of ghost rotationally invariant slave-boson and dynamical mean field theory as a function of the impurity-model bath size

Here, we compare the accuracy of the ghost rotationally invariant slave-boson (g-RISB) theory and dynamical mean field theory (DMFT) on the single-band Hubbard model, as a function of the number of bath sites in the embedding impurity Hamiltonian. Our benchmark calculations confirm that the accuracy of g-RISB can be systematically improved by increasing the number of bath sites, similar to DMFT. With a few bath sites, we observe that g-RISB is systematically more accurate than DMFT for the ground-state observables. On the other hand, the relative accuracy of these methods is generally comparable for the quasiparticle weight and the spectral function. As expected, we observe that g-RISB satisfies the variational principle in infinite dimensions, as the total energy decreases monotonically towards the exact value as a function of the number of bath sites, suggesting that the g-RISB wave function may approach the exact ground state in infinite dimensions. Our results suggest that the g-RISB is a promising method for first-principles simulations of strongly correlated matter, which can capture the behavior of both static and dynamical observables, at a relatively low computational cost.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗