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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Effect of Heat Treatment and Combination of Cold Rolling and Heat Treatment on Microstructure and Mechanical Properties of Titanium Alloy Ti6Al2V2Zr1.5Mo

The heat treatment and cold rolling combinations have been carried out on titanium alloy Ti6Al2V2Zr1.5Mo, and microstructure evolution and mechanical behavior have been studied. Solution treatment below the β-transus temperature, followed by air cooling, resulted in higher microhardness/strength as compared to the same with water quenching. A sudden drop in microhardness/strength is observed in sample solution heat-treated above β-transus temperature followed by air cooling. The former is attributed to the additional presence of fine secondary α-phase formed by dynamic aging during air cooling as compared to water-quenched samples which did not have fine secondary α-phase. Solution treatment above β-transus temperature resulted in Widmanstatten microstructure with no significant fine secondary α in air-cooled samples. Among the studied conditions of cold rolling (CR), gain in strength of the alloy from annealed condition is significant with first 15% reduction and thereafter it is marginal for 30% reduction. Initiation of cracks at the edges has been observed in 30% CR. The microstructure of cold-rolled samples confirms the fragmentation of α-plates with the presence of high dislocation density. Heat treatment of cold-rolled samples resulted in significant reduction in strength from the as-cold-rolled conditions. The marginally lower strength than the as-received (annealed) or heat-treated alloy samples is due to the recrystallization in CR samples and the formation of Widmanstatten microstructure in air-cooled samples. The alloy does not have fine secondary α or regions with large dislocation density in this condition. The microstructure in the samples heat-treated (with air cooling) below as well as above β-transus temperature (after CR) is similar to air-cooled samples (without prior CR) with heat treatment above β-transus temperature. This indicates the reduction in recrystallization temperature with cold working, which is substantiated with the reduction in strength as well.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Sensitive Targeted Quantification of ERK Phosphorylation Dynamics and Stoichiometry in Human Cells without Affinity Enrichment

Mass spectrometry-based targeted quantification is a promising technology for site-specific quantification of posttranslational modifications (PTMs). However, a major constraint of most targeted MS approaches is the limited sensitivity for quantifying low-abundance PTMs, requiring the use of affinity reagents to enrich specific PTMs. Herein, we demonstrate the direct site-specific quantification of ERK phosphorylation isoforms (pT, pY, pTpY) and their relative stoichiometries using a highly sensitive targeted MS approach termed high-pressure, high-resolution separations with intelligent selection and multiplexing (PRISM). PRISM provides effective enrichment of target peptides within a given fraction from complex biological matrix with minimal sample losses, followed by selected reaction monitoring (SRM) quantification. The PRISM-SRM approach enabled direct quantification of ERK phosphorylation in human mammary epithelial cells (HMEC) from as little as 25 µg tryptic peptides from whole cell lysates. Compared to immobilized metal-ion affinity chromatography, PRISM provided >10-fold improvement in signal intensities, presumably due to the better peptide recovery of PRISM for handling small size samples. This approach was applied to quantify ERK phosphorylation dynamics in HMEC treated by different doses of EGF at both the peak activation (10 min) and steady state (2 h). At 10 min, the maximal ERK activation was observed with 0.3 ng/mL dose, whereas the maximal steady state level of ERK activation at 2 h was at 3 ng/ml dose, corresponding to 1200 and 9000 occupied receptors, respectively. At 10 min, the maximally activated pTpY isoform represented ~40% of total ERK, falling to less than 10% at 2 h. The time course and dose-response profiles of individual phosphorylated ERK isoforms indicated that singly phosphorylated pT-ERK never increases significantly, while the increase of pY-ERK paralleled that of pTpY-ERK. This data supports for a processive, rather than distributed, model of ERK phosphorylation. The PRISM-SRM quantification of protein phosphorylation illustrates the potential for simultaneous quantification of multiple PTMs.

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

Generalized correlation integral vectors: A distance concept for chaotic dynamical systems

Several concepts of fractal dimension have been developed to characterise properties of attractors of chaotic dynamical systems. Numerical approximations of them must be calculated by finite samples of simulated trajectories. In principle, the quantities should not depend on the choice of the trajectory, as long as it provides properly distributed samples of the underlying attractor. In practice, however, the trajectories are sensitive with respect to varying initial values, small changes of the model parameters, to the choice of a solver, numeric tolerances, etc. The purpose of this paper is to present a statistically sound approach to quantify this variability. We modify the concept of correlation integral to produce a vector that summarises the variability at all selected scales. The distribution of this stochastic vector can be estimated, and it provides a statistical distance concept between trajectories. Here, we demonstrate the use of the distance for the purpose of estimating model parameters of a chaotic dynamic model. The methodology is illustrated using computational examples for the Lorenz 63 and Lorenz 95 systems, together with a framework for Markov chain Monte Carlo sampling to produce posterior distributions of model parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Dynamic infrared gas analysis from longleaf pine fuel beds burned in a wind tunnel: observation of phenol in pyrolysis and combustion phases

Pyrolysis is the first step in a series of chemical and physical processes that produce flammable organic gases from wildland fuels that can result in a wildland fire. We report results using a new time-resolved Fourier transform infrared (FTIR) method that correlates the measured FTIR spectrum with an infrared thermal image sequence, enabling the identification and quantification of gases within different phases of the fire process. The flame from burning fuel beds composed of pine needles (Pinus palustris) and mixtures of sparkleberry, fetterbush, and inkberry plants was the natural heat source for pyrolysis. Extractive gas samples were analyzed and identified in both static and dynamic modes synchronized to thermal infrared imaging: a total of 29 gases were identified including small alkanes, alkenes, aldehydes, nitrogen compounds, and aromatics, most previously measured by FTIR in wildland fires. This study presents one of the first identifications of phenol associated with both pre-combustion and combustion phases using ca. 1 Hz temporal resolution. Preliminary results indicate ~2.5× greater phenol emissions from sparkleberry and inkberry compared to fetterbush, with differing temporal profiles.

09 BIOMASS FUELS↗
DOE OSTI2017

Effect of Multi-Walled Carbon Nanotubes on Viscoelastic Properties of PP/Reed Flour Composites

The objective of this investigation was to evaluate the influence of multi-wall carbon nanotubes (MWCNTs) on the dynamic mechanical properties of polypropylene (PP)/reed flour (RF) composites. The experimental samples were prepared through the melt mixing of PP/RF at 50% weight ratios, with various amounts of MWCNTs (0, 1, 2, 3 and 5 phr) in a twin-screw extruder, then the samples made by injection molding. The amount of maleic anhydride grafted polypropylene (PP-g-MA) as a coupling agent was fixed at 2 phr for all formulations. Dynamic mechanical analysis (DMA) tests were carried out to investigate the viscoelastic behavior of nanocomposites. The dynamic mechanical properties such as storage modulus (Eʹ), loss modulus (Eʺ), and damping coefficient (tan δ) of nanocomposites were investigated in the temperature range of −80 to 160 °C at a step of 5 °C and frequency of 1 Hz. The morphology of the specimens was characterized using field emission scanning electron microscope (FE-SEM) technique. Results indicated that the storage modulus of samples was found to increase with incorporation of MWCNTs while damping properties registered a decrease, owing to the reinforcing effect of CNTs into the composites. Moreover, CNTs addition leads to a positive shift in glass transition temperature (T{sub g}), which is explained on the molecular mobility of the polymer chains behavior. Additionally, the minimum adhesion factor is related to samples containing 2 phr MWCNTs which provides the best interaction between polymer and fibers. FE-SEM micrographs showed a predominantly homogeneous CNTs distribution through the composites; however, some aggregates were observed at higher CNTs fractions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2013

A direct dynamical measurement of the Milky Way's disk surface density profile, disk scale length, and dark matter profile at 4 kpc ≲ R ≲ 9 kpc

We present and apply rigorous dynamical modeling with which we infer unprecedented constraints on the stellar and dark matter mass distribution within our Milky Way (MW), based on large sets of phase-space data on individual stars. Specifically, we model the dynamics of 16,269 G-type dwarfs from SEGUE, which sample 5 kpc < R{sub GC} < 12 kpc and 0.3 kpc ≲ |Z| ≲ 3 kpc. We independently fit a parameterized MW potential and a three-integral, action-based distribution function (DF) to the phase-space data of 43 separate abundance-selected sub-populations (MAPs), accounting for the complex selection effects affecting the data. We robustly measure the total surface density within 1.1 kpc of the mid-plane to 5% over 4.5 kpc < R{sub GC} < 9 kpc. Using metal-poor MAPs with small radial scale lengths as dynamical tracers probes 4.5 kpc ≲ R{sub GC} ≲ 7 kpc, while MAPs with longer radial scale lengths sample 7 kpc ≲ R{sub GC} ≲ 9 kpc. We measure the mass-weighted Galactic disk scale length to be R{sub d} = 2.15 ± 0.14 kpc, in agreement with the photometrically inferred spatial distribution of stellar mass. We thereby measure dynamically the mass of the Galactic stellar disk to unprecedented accuracy: M {sub *} = 4.6 ± 0.3 + 3.0 (R {sub 0}/ kpc – 8) × 10{sup 10} M {sub ☉} and a total local surface density of Σ{sub R{sub 0}}(Z=1.1 kpc)=68 ± 4 M{sub ⊙} pc{sup −2} of which 38 ± 4 M {sub ☉} pc{sup –2} is contributed by stars and stellar remnants. By combining our surface density measurements with the terminal velocity curve, we find that the MW's disk is maximal in the sense that V {sub c,} {sub disk}/V {sub c,} {sub total} = 0.83 ± 0.04 at R = 2.2 R{sub d} . We also constrain for the first time the radial profile of the dark halo at such small Galactocentric radii, finding that ρ{sub DM}(r; ≈R {sub 0})∝1/r {sup α} with α < 1.53 at 95% confidence. Our results show that action-based DF modeling of complex stellar data sets is now a feasible approach that will be fruitful for interpreting Gaia data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Anomalous neutron scattering `halo' observed in highly oriented pyrolytic graphite

Highly oriented pyrolytic graphite (HOPG) has been used as monochromators, analyzers and filters at neutron and X-ray scattering facilities for more than half a century. Interesting questions remain. In this work, the first observation of anomalous neutron `halo' scattering of HOPG is reported. The scattering projects a ring onto the detector with a half-cone angle of 12.4°, which surprisingly persists to incident neutron wavelengths far beyond the Bragg cutoff for graphite (6.71 Å). At longer wavelengths the ring is clearly a doublet with a splitting roughly proportional to wavelength. Sample tilting leads to the shift of the ring, which is wavelength dependent with longer wavelengths providing a smaller difference between the ring shift and the sample tilting. The ring broadens and weakens with decreasing HOPG quality. The lattice dynamics of graphite play a role in causing the scattering ring, as shown by the fact that the ring vanishes once the sample is cooled to 30 K. A possible interpretation by multiple scattering including elastic and inelastic processes is proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Predicting octane number from microscale flame dynamics

The standard method for measuring the octane number of fuels requires large sample volumes (~1L) and access to a Cooperative Fuel Research (CFR) engine. This method reliably quantifies the knock resistance of fuels in spark ignition engines, however the large sample volume requirement prevents testing of new experimental fuels (often produced in quantities of just ~1 mL), and the large equipment size impedes mobile, decentralized testing of remote fuel supplies. When direct measurements of octane number are impractical, other methods are needed. Micro flow reactors have shown promise in measuring ignition characteristics that are sensitive to octane number, and they are compact and operate on small volumes (~1 mL). This study uses simulations to demonstrate that measurements of the unsteady flame dynamics in a micro flow reactor can provide valuable data for accurate octane number predictions. Simulations of the flow reactor are used to obtain ignition characteristics for over 200 ethanol-toluene primary reference fuels (ETPRF) and 21 biofuel blends. A feed forward neural network is trained using the micro flow reactor ignition characteristics, fuel properties, and known research octane number (RON) and motor octane number (MON) for the ETPRF fuels. Here, the neural network is able to predict the RON and MON of the biofuel blends to within 2 octane number on average. Prediction results are compared to other methods available in the literature. Additional neural network models are trained that show improved prediction accuracy as additional fuel training data becomes available.

02 PETROLEUM↗
DOE OSTI2022

The Melampsora americana Population on Salix purpurea in the Great Lakes Region Is Highly Diverse with a Contributory Influence of Clonality

Shrub willows (Salix spp.) are emerging as a viable lignocellulosic, second-generation bioenergy crop with many growth characteristics favorable for marginal lands in New York State and surrounding areas. Willow rust, caused by members of the genus Melampsora, is the most limiting disease of shrub willow in this region and remains extremely understudied. In this study, genetic diversity, genetic structure, and pathogen clonality were examined in Melampsora americana over two growing seasons via genotyping-by-sequencing to identify single-nucleotide polymorphism markers. In conjunction with this project, a reference genome of rust isolate R15-033-03 was generated to aid in variant discovery. Sampling between years allowed regional and site-specific investigation into population dynamics, in the context of both wild and cultivated hosts within high-density plantings. This work revealed that this pathogen is largely panmictic over the sampled areas, with few sites showing moderate genetic differentiation. These data support the hypothesis of sexual recombination between growing seasons because no genotype persisted across the two years of sampling. Additionally, clonality was determined as a driver of pathogen populations within cultivated fields and single shrubs; however, there is also evidence of high genetic diversity of rust isolates in all settings. This work provides a framework for M. americana population structure in the Great Lakes region, providing crucial information that can aid in future resistance breeding efforts.

Plant Sciences↗
DOE OSTI2016

Novel covariance-based neutrality test of time-series data reveals asymmetries in ecological and economic systems

Systems as diverse as the interacting species in a community, alleles at a genetic locus, and companies in a market are characterized by competition (over resources, space, capital, etc) and adaptation. Neutral theory, built around the hypothesis that individual performance is independent of group membership, has found utility across the disciplines of ecology, population genetics, and economics, both because of the success of the neutral hypothesis in predicting system properties and because deviations from these predictions provide information about the underlying dynamics. However, most tests of neutrality are weak, based on static system properties such as species-abundance distributions or the number of singletons in a sample. Time-series data provide a window onto a system’s dynamics, and should furnish tests of the neutral hypothesis that are more powerful to detect deviations from neutrality and more informative about to the type of competitive asymmetry that drives the deviation. Here, we present a neutrality test for time-series data. We apply this test to several microbial time-series and financial time-series and find that most of these systems are not neutral. Our test isolates the covariance structure of neutral competition, thus facilitating further exploration of the nature of asymmetry in the covariance structure of competitive systems. Much like neutrality tests from population genetics that use relative abundance distributions have enabled researchers to scan entire genomes for genes under selection, we anticipate our time-series test will be useful for quick significance tests of neutrality across a range of ecological, economic, and sociological systems for which time-series data are available. Here, future work can use our test to categorize and compare the dynamic fingerprints of particular competitive asymmetries (frequency dependence, volatility smiles, etc) to improve forecasting and management of complex adaptive systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Isophote shapes of early-type galaxies in massive clusters at z ∼ 1 and 0

We compare the isophote shape parameter a{sub 4} of early-type galaxies (ETGs) between z ∼ 1 and 0 as a proxy for dynamics to investigate the epoch at which the dynamical properties of ETGs are established, using cluster ETG samples with stellar masses of log(M{sub ∗}/M{sub ⊙})⩾10.5 which have spectroscopic redshifts. We have 130 ETGs from the Hubble Space Telescope Cluster Supernova Survey for z ∼ 1 and 355 ETGs from the Sloan Digital Sky Survey for z ∼ 0. We have developed an isophote shape analysis method, which can be used for high-redshift galaxies and has been carefully compared with published results. We have applied the same method for both the z ∼ 1 and 0 samples. We find similar dependence of the a{sub 4} parameter on the mass and size at z ∼ 1 and 0; the main population of ETGs changes from disky to boxy at a critical stellar mass of log(M{sub ∗}/M{sub ⊙})∼11.5 with the massive end dominated by boxy. The disky ETG fraction decreases with increasing stellar mass both at z ∼ 1 and 0, and is consistent between these redshifts in all stellar mass bins when the Eddington bias is taken into account. Although uncertainties are large, the results suggest that the isophote shapes and probably dynamical properties of ETGs in massive clusters are already in place at z > 1 and do not significantly evolve in z < 1, despite significant size evolution in the same galaxy population. The constant disky fraction favors less violent processes than mergers as the main cause of the size and morphological evolution of intermediate mass ETGs in z < 1.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Improving the Accuracy of Atomistic Simulations of the Electrochemical Interface

Atomistic simulation of the electrochemical double layer is an ambitious undertaking, requiring quantum mechanical description of electrons, phase space sampling of liquid electrolytes, and equilibration of electrolytes over nanosecond time scales. All models of electrochemistry make different trade-offs in the approximation of electrons and atomic configurations, from the extremes of classical molecular dynamics of a complete interface with point-charge atoms to correlated electronic structure methods of a single electrode configuration with no dynamics or electrolyte. Here, we review the spectrum of simulation techniques suitable for electrochemistry, focusing on the key approximations and accuracy considerations for each technique. Additionally, we discuss promising approaches, such as enhanced sampling techniques for atomic configurations and computationally efficient beyond density functional theory (DFT) electronic methods, that will push electrochemical simulations beyond the present frontier.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

UQpy: A general purpose Python package and development environment for uncertainty quantification

In this paper, we present the UQpy software toolbox, an open-source Python package for general uncertainty quantification (UQ) in mathematical and physical systems. The software serves as both a user-ready toolbox that includes many of the latest methods for UQ in computational modeling and a convenient development environment for Python programmers advancing the field of UQ. The paper presents an introduction to the software's architecture and existing capabilities, divided in the code in a set of modules centered around different UQ tasks such as sampling methods, generation of random processes and random fields, probabilistic inverse modeling, reliability analysis, surrogate modeling, and active learning. The paper also highlights the importance of the RunModel module, which is used to drive simulations in the uncertainty analyses performed in UQpy. This module conveniently allows the user to define computational models directly in Python, or to run simulations from a third-party software in serial or in parallel. To illustrate the various capabilities, two examples are tracked throughout the paper and analyzed repeatedly for various UQ tasks. The first is a Python model solving a nonlinear structural dynamics problem, used to illustrate UQpy's capabilities in sampling and forward propagation of high dimensional random vectors (stochastic processes), and probabilistic inference. The second model is a third-party Abaqus finite element model solving the thermomechanical response of a beam structure. This example is used to illustrate UQpy's capabilities in variance reduction sampling techniques, reliability analysis, surrogate modeling and active learning techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

An interface for the direct coupling of small liquid samples to AMS

We describe the moving wire interface attached to the 1-MV AMS system at LLNL’s Center for Accelerator Mass Spectrometry for the analysis of nonvolatile liquid samples as either discrete drops or from the direct output of biochemical separatory instrumentation, such as high-performance liquid chromatography (HPLC). Discrete samples containing at least a few 10 s of nanograms of carbon and as little as 50 zmol 14 C can be measured with a 3–5% precision in a few minutes. The dynamic range of our system spans approximately 3 orders in magnitude. Sample to sample memory is minimized by the use of fresh targets for each discrete sample or by minimizing the amount of carbon present in a peak generated by an HPLC containing a significant amount of 14 C. As a result, liquid sample AMS provides a new technology to expand our biomedical AMS program by enabling the capability to measure low-level biochemicals in extremely small samples that would otherwise be inaccessible.

14C↗
DOE OSTI2015

Time-Resolved Phase Transition Kinetics STL-03-15, Year 1 of 1

Presentation describes shock compression experiments performed to measure the dynamic reflectance of light from the surface of tin samples shocked through the β to BCT (body centered tetragonal) solid-solid polymorphic phase transition near 9 GPa, using a technique that extrapolates the low- and high-pressure behavior of reflectance through the mixed phase, allowing researchers to infer the value of the mixed-phase fraction.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Developing new alkaline ceramics as possible CO 2 chemisorbents at high temperatures: The lithium and sodium yttriates (LiYO 2 and NaYO 2 ) cases

In this work, lithium and sodium yttriates (LiYO 2 and NaYO 2 ) were synthesized, characterized and tested as possible carbon dioxide (CO 2 ) captors. All the experimental syntheses and analyses were supported by the theoretical thermodynamic calculations, showing that both ceramics would be able to chemisorb CO 2 in a wide temperature range. Therefore, both ceramics were prepared by solid-state reaction and structurally characterized. In fact, the structural characterization evidenced that sodium atoms are located in a octahedral close-packed structure, while lithium ions are not so packed. The lithium ions are, indeed, in a highly distorted tetrahedron, tending to square-planar coordination. Then, based on the theoretical and structural analysis, LiYO 2 and NaYO 2 samples were investigated for the CO 2 capture process through dynamic and isothermal thermogravimetric experiments. All these experiments showed that LiYO 2 has better CO 2 capture properties than NaYO 2 , which was further correlated with the crystal structures of each ceramic. Furthermore, both ceramics presented similar CO 2 capture efficiencies regardless of the CO 2 concentration. Finally, LiYO 2 sample was tested for cyclic CO 2 chemisorption-desorption processes. The obtained results showed that the CO 2 capture efficiency is maintained high at least through 10 cycles. Therefore, these alkaline yttriates seem to present interesting alternatives as high and moderate temperature CO 2 captors, applicable for post-combustion industrial capture processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗