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Results for “compositional complexity”

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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Composition and structure of Mars' upper atmosphere - Results from the neutral mass spectrometers on Viking 1 and 2

The upper atmospheric mass spectrometers flown on Viking 1 and 2 are described, and results obtained for the composition and structure of Mars' upper atmosphere are summarized. Carbon dioxide is the major constituent of the atmosphere at all heights below 180 km. The thermal structure of the upper atmosphere is complex and variable with average temperatures below 200 K for both Viking 1 and 2. The atmosphere is mixed to heights in excess of 120 km. The isotopic composition of carbon and oxygen in the Martian atmosphere is similar to that in the terrestrial atmosphere: N-15 is enriched in Mars' atmosphere by a factor of 1.62 + or - 0.16.

Nier, A. O.↗
NASA NTRS2008

Oxidation of ZrB2 SiC TaSi2 Materials at Ultra High Temperatures

ZrB2 - 20v% SiC - 20v% TaSi2 was oxidized in stagnant air for ten minute cycles for times up to 100 minutes at 1627 C and 1927 C. The sample oxidized at 1627 C showed oxidation resistance better than that of the standard ZrB2 - 20v% SiC. The sample oxidized at 1927 C, however, showed evidence of liquid phase formation and complex oxidation products. The sample exposed at 1927 C was analyzed in detail by scanning electron microprobe and wavelength dispersive spectroscopy to understand the complex oxidation and melting reactions occurring during exposure. The as hot-pressed material shows the formation of a Zr(Ta)B2 phase in addition to the three phases in the nominal composition already noted. After oxidation, the TaSi2 in the matrix was completely reacted to form Ta(Zr)C. The layered oxidation products included SiO2, ZrO2, Ta2O5, and a complex oxide containing both Zr and Ta. Likely reactions are proposed based on thermodynamic phase stability and phase morphology.

Opila, E.↗
NASA NTRS2022

Compositional Measurements of Saturn's Upper Atmosphere and Rings From Cassini INMS: An Extended Analysis of Measurements From Cassini's Grand Finale Orbits

The Cassini spacecraft's final orbits sampled Saturn's atmosphere and returned surprisingly complex mass spectra from the Ion and Neutral Mass Spectrometer (INMS). Signal returned from the instrument included native Saturn species, as expected, as well as a significant amount of signal attributed to vaporized ices and higher mass organics believed to be owing into Saturn's atmosphere from the rings. In this paper, we present an in-depth compositional analysis of the mass spectra returned from Cassini's last few orbits. We use a mass spectral deconvolution algorithm designed specifically to handle the complexities involved with unit resolution spaceflight mass spectrometry data to determine the relative abundance of species detected in the observations. We calculate the downward external flux and mass deposition rates of ring volatile species into Saturn's atmosphere and conclude that during these observations ring material was being deposited into Saturn's equatorial region at a rate on the order of 10(exp 4) kg/s.

Saturn↗
NASA NTRS2022

Compositional Measurements of Saturn's Upper Atmosphere and Rings From Cassini INMS: An Extended Analysis of Measurements From Cassini's Grand Finale Orbits

The Cassini spacecraft's final orbits sampled Saturn's atmosphere and returned surprisingly complex mass spectra from the Ion and Neutral Mass Spectrometer (INMS). Signal returned from the instrument included native Saturn species, as expected, as well as a significant amount of signal attributed to vaporized ices and higher mass organics believed to be flowing into Saturn's atmosphere from the rings. In this paper, we present an in-depth compositional analysis of the mass spectra returned from Cassini's last few orbits. We use a mass spectral deconvolution algorithm designed specifically to handle the complexities involved with unit resolution spaceflight mass spectrometry data to determine the relative abundance of species detected in the observations. We calculate the downward external flux and mass deposition rates of ring volatile species into Saturn's atmosphere and conclude that during these observations ring material was being deposited into Saturn's equatorial region at a rate on the order of 10(exp 4) kg/s.

Saturn↗
DOE OSTI2024

Additive Manufacturing of Thermal Energy Storage Composites with Microencapsulated Phase Change Materials Supported in a Multi-Polymer Matrix

Advanced manufacturing techniques, such as additive manufacturing (AM), that can directly integrate phase change materials (PCMs) have garnered interest in recent years due to their potential for development of highly efficient thermal energy storage architectures. Complex, high surface area geometries embedded with PCMs that are only feasible with AM can improve thermal management with reduced material waste. Our work focuses on developing composite filaments with microencapsulated phase change materials (MEPCM) bound within a single or dual polymer matrix that can be processed through standard filament extruders and additively manufactured using off-the-shelf 3D printers. Polymer powders, rather than polymer pellets, were key to homogenously mixed filaments achieving high MEPCM loadings with no deterioration in thermal energy storage (TES) capability during extrusion. Composite filaments contain upwards of 60 wt% MEPCM and were printed without loss in feature resolution, print speed, or layer adhesion. Storage enthalpies of printed composites range from 100 - 130 kJ/kg, which were within 5% of the theoretical enthalpy based on weight fraction of MEPCM and maintained enthalpies within 1% over 500 thermal cycles. We can reliably manufacture low density, high surface area structures like 15% gyroid infill, along with dense, compact pucks at a 100% concentric infill. Prints were also scalable to a 900 cm3 honeycomb infill heat exchanger model that has an estimated energy storage capacity of 9 Wh.

3D printing↗
NASA NTRS2024

Filament Wound Composite Analysis Using the NASA Multiscale Analysis Tool (NASMAT) and Finite Element Analysis

Fiber reinforced composite materials, owing to their tailorable thermomechanical and functional properties, allow one to produce a structure that is stronger, stiffer, and lighter than its metal counterpart while performing the same function, yielding a more efficient structure. This not only allows for the improvement of current technologies like aircraft structures, but also enables new technologies like gaseous hydrogen storage for mobility applications, which are otherwise impractical when manufactured using traditional metals due to weight and space restrictions or material embrittlement. However, the use of composites imposes greater design and manufacturing challenges on an engineer, since they are heterogenous, having a distinct structure across multiple length scale, behave generally anisotropically at the structural level and require complex manufacturing and processing methods. Capturing this complex behavior requires detailed numerical simulations, including the modeling of microstructural features like undulations, voids, and fiber alignment. In this paper, multiple repeating unit cells (RUCs), representing filament wound composites, are developed (via a script provided in the Appendix) and analyzed. The refinement of these RUCs is varied, and the analyses are performed using both the Abaqus finite element software and the NASA Multiscale Analysis Tool (NASMAT). A study is undertaken to compare the predicted effective elastic properties of the wound RUC to a laminate representation of the wound RUC, which neglects the undulations. Additionally, two different sets of periodic boundary conditions (PBCs) have been examined. One approximates the real boundary conditions using a standard approach and the other represents the PBCs exactly through the use of an offset. Lastly, a comparison of the local elastic stress fields is made among the models and approaches. Since wound structures are often approximated as laminated structures, it is important to understand the degree to which this assumption is valid, namely by first comparing the elastic constants and local elastic fields. This will provide, on the one hand, information concerning the bulk mechanical behavior and, on the other hand, insights concerning local load distributions and likely damage initiation sites.

Composites↗
DOE OSTI2022

Fundamental Effects of Al and Ta on Microstructure and Phase Transformations in the Al–Cr–Mo–Ta–Ti Refractory Complex Concentrated Alloy System

The effect of aluminum and tantalum concentrations on a refractory metal complex concentrated alloy is reported, particularly with respect to their effect on microstructure and phase composition of the alloy in cast and annealed form. Alloys with an equiatomic composition, (AlCrMoTaTi), an aluminum-lean composition (Al 0.75 CrMoTaTi), and a tantalum-lean composition (AlCrMoTa 0.75 Ti) are produced via arc melting. The alloys exhibit multiphase structures, confirmed by X-ray diffraction, microstructural characterization, and thermal analysis. The minor off-equiatomic adjustments of aluminum and tantalum in this alloy system did not drastically alter the prevalence of the Cr–Ta-based Laves phase. Correlations between thermodynamic predictions and observed phase transformations via thermal analysis are improved upon refinement of calculations removing impractical intermediate phases. As a result, experimental findings provide information for the refinement of thermodynamic modeling and deliver additional insight into the optimization of alloy compositions within this five-component system.

36 MATERIALS SCIENCE↗
DOE OSTI2018

MC Carbide Characterization in High Refractory Content Powder-Processed Ni-Based Superalloys

Carbide precipitates in Ni-based superalloys are considered to be desirable phases that can contribute to improving high-temperature properties as well as aid in microstructural refinement of the material; however, they can also serve as crack initiation sites during fatigue. To date, most of the knowledge pertaining to carbide formation has originated from assessments of cast and wrought Ni-based superalloys. As powder-processed Ni-based superalloys are becoming increasingly widespread, understanding the different mechanisms by which they form becomes increasingly important. Detailed characterization of MC carbides present in two experimental high Nb-content powder-processed Ni-based superalloys revealed that Hf additions affect the resultant carbide morphologies. This morphology difference was attributed to a higher magnitude of elastic strain energy along the interface associated with Hf being soluble in the MC carbide lattice. The composition of the MC carbides was studied through atom probe tomography and consisted of a complex carbonitride core, which was rich in Nb and with slight Hf segregation, surrounded by an Nb carbide shell. The characterization results of the segregation behavior of Hf in the MC carbides and the subsequent influence on their morphology were compared to density functional theory calculations and found to be in good agreement, suggesting that computational modeling can successfully be used to tailor carbide features.

Materials Science↗
DOE OSTI2018

Geometry-Induced Spatial Variation of Microstructure Evolution During Selective Electron Beam Melting of Rene-N5

High gamma prime (γ') nickel-based alloys produced by selective electron beam melting are of interest to the turbine industry which requires control of microstructure in relation to loading conditions within complex component geometry. Welding literature predicts cracking and microstructure evolution as a function of alloy composition and process parameters in this class of alloys. In addition, Additive manufacturing causes variations in the above conditions due to the interaction of geometry on processing and heat transfer. The influence of geometry on processing conditions was explored for alloy Rene N5 by characterizing the solidification grain microstructure and solid-state precipitation. A Semi-Analytical Heat Transfer Model was employed to explain the resulting variation in solidification grain morphology that occurred due to the part geometry. Finally, the as-built precipitation structure was found to vary as a function of build height and had no correlation to the solidification grain structure or the layer geometry.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Simulation of gas mixture dynamics in a pipeline network using explicit staggered-grid discretization

Here we develop an explicit staggered finite difference discretization scheme for simulating the transport of highly heterogeneous gas mixtures through pipeline networks. This study is motivated by the proposed blending of hydrogen into natural gas pipelines to reduce end use carbon emissions while using existing pipeline systems throughout their planned lifetimes. Our computational method accommodates an arbitrary number of constituent gases with very different physical properties that may be injected into a network with significant spatiotemporal variation. In this setting, the gas flow physics are highly location- and time- dependent, so that local composition and nodal mixing must be accounted for. The resulting conservation laws are formulated in terms of pressure, partial densities and flows, and volumetric and mass fractions of the constituents. We include non-ideal equations of state that employ linear approximations of gas compressibility factors, so that the pressure dynamics propagate locally according to a variable wave speed that depends on mixture composition and density. We derive compatibility relationships for network edge boundary values that are more complex than for a homogeneous gas. The simulation method is evaluated on initial boundary value problems for a single pipe and a small network, is cross-validated with a lumped element simulation, and used to demonstrate a local monitoring and control policy for maintaining allowable concentration levels.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

High-throughput validation of phase formability and simulation accuracy of Cantor alloys

High-throughput methods enable accelerated discovery of novel materials in complex systems such as high-entropy alloys, which exhibit intricate phase stability across vast compositional spaces. Computational approaches, including Density Functional Theory (DFT) and calculation of phase diagrams (CALPHAD), facilitate screening of phase formability as a function of composition and temperature. However, the integration of computational predictions with experimental validation remains challenging in high-throughput studies. In this work, we introduce a quantitative confidence metric to assess the agreement between predictions and experimental observations, providing a quantitative measure of the confidence of machine learning models trained on either DFT or CALPHAD input in accounting for experimental evidence. The experimental dataset was generated via high-throughput in-situ synchrotron X-ray diffraction on compositionally varied FeNiMnCr alloy libraries, heated from room temperature to ~1000 °C. Agreement between the observed and predicted phases was evaluated using either temperature-independent phase classification or a model that incorporates a temperature-dependent probability of phase formation. This integrated approach demonstrates where strong overall agreement between computation and experiment exists, while also identifying key discrepancies, particularly in FCC/BCC predictions at Mn-rich regions to inform future model refinement.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Jacobian-scaled K-means clustering for physics-informed segmentation of reacting flows

This work introduces Jacobian-scaled K-means (JSK-means) clustering, which is a physicsinformed clustering strategy centered on the K-means framework. The method allows for the injection of underlying physical knowledge into the clustering procedure through a distance function modification: instead of leveraging conventional Euclidean distance vectors, the JSKmeans procedure operates on distance vectors scaled by matrices obtained from dynamical system Jacobians evaluated at the cluster centroids. The goal of this work is to show how the JSKmeans algorithm - without modifying the input dataset - produces clusters that capture regions of dynamical similarity, in that the clusters are redistributed towards high-sensitivity regions in phase space and are described by similarity in the source terms of samples instead of the samples themselves. The algorithm is demonstrated on a complex reacting flow simulation dataset (a channel detonation configuration), where the dynamics in the thermochemical composition space are known through the highly nonlinear and stiff Arrhenius-based chemical source terms. Interpretations of cluster partitions in both physical space and composition space reveal how JSK-means shifts clusters produced by standard K-means towards regions of high chemical sensitivity (e.g., towards regions of peak heat release rate near the detonation reaction zone). Furthermore, the findings presented here illustrate the benefits of utilizing Jacobian-scaled distances in clustering techniques, and the JSK-means method in particular displays promising potential for improving former partition-based modeling strategies in reacting flow (and other multi-physics) applications.

Clustering↗
DOE OSTI2020

Microwave-Based Synthesis of Functional Morphological Variants and Carbon Nanotube-Based Composites of VS 4 for Electrochemical Applications

A novel facile, fast, and efficient microwave-assisted method was developed to synthesize a number of diverse nanostructured motifs (ranging from nanorods to nanoflowers) of VS 4 along with its associated composite heterostructures, VS 4 /multi-walled carbon nanotube (MWNT; i.e., multi-walled carbon nanotubes). Specifically, we have probed and correlated the effects of a number of specific experimental variables, including primarily precursor, solvent, temperature, and time. We noted that nanorods formed more readily with VO(acac) 2 as the vanadium precursor and n-methyl-2-pyrrolidone (NMP) as a polar reaction solvent. By contrast, we determined that hierarchical three-dimensional (3D) nanoflower-like assemblies, ranging in size from 100 to 200 nm in average diameter, could be controllably synthesized by using Na 3 VO 4 as the vanadium precursor and an aqueous water: polar solvent mixture as the reaction medium. We also observed that VS 4 disintegrates, when in the presence of either air, solution, or a combination of these environments, and established that the extent of VS4 nanorod decomposition could be almost fully prevented by storage under nitrogen. From an application’s perspective, our VS 4 is electrochemically active and shows behavior, consistent with the literature. In particular, as compared with pristine VS 4 nanorods alone, we observed enhanced electrochemical activity with (i) 3D hierarchical flower-like motifs, (ii) unique necklace-like VS 4 nanorod–MWNT composites, and (iii) samples in which as-prepared VS4 nanorods had been annealed. Moreover, we found that the rational application of specific physical and chemical processing treatments, such as (i) thermal annealing to improve crystallinity, (ii) the addition of MWNTs to form conductive composites, and (iii) the evolution of morphology from one-dimensional (1D) nanorods to more complex 3D nanoflowers, was favorable to the resulting electrochemical performance with respect to increasing stability and reversibility.

25 ENERGY STORAGE↗
DOE OSTI2023

Installing Controlled Stereo-Defects Yields Semicrystalline and Biodegradable Poly(3-Hydroxybutyrate) with High Toughness and Optical Clarity

Stereo-defects present in stereo-regular polymers often diminish thermal and mechanical properties, and hence suppressing or eliminating them is a major aspirational goal for achieving polymers with optimal or enhanced properties. Here, we accomplish the opposite by introducing controlled stereo-defects to semicrystalline biodegradable poly(3-hydroxybutyrate) (P3HB), which offers an attractive biodegradable alternative to semicrystalline isotactic polypropylene but is brittle and opaque. We enhance the specific properties and mechanical performance of P3HB by drastically toughening it and also rendering it with the desired optical clarity while maintaining its biodegradability and crystallinity. This toughening strategy of stereo-microstructural engineering without changing the chemical compositions also departs from the conventional approach of toughening P3HB through copolymerization that increases chemical complexity, suppresses crystal-lization in the resulting copolymers, and is thus undesirable in the context of polymer recycling and performance. More specifically, syndio-rich P3HB (sr-P3HB), readily synthesized from the eight-membered meso-dimethyl diolide, has a unique set of stereo-microstructures comprising enriched syndiotactic [rr] and no isotactic [mm] triads but abundant stereo-defects randomly distributed along the chain. This sr-P3HB material is characterized by high toughness (UT = 96 MJ/m 3 ) as a result of its high elongation at break (>400%) and tensile strength (34 MPa), crystallinity (T m = 114 degrees C), optical clarity (due to its submicron spherulites), and good barrier properties, while it still biodegrades in freshwater and soil.

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

Fast predictions of liquid-phase acid-catalyzed reaction rates using molecular dynamics simulations and convolutional neural networks

The rates of liquid-phase, acid-catalyzed reactions relevant to the upgrading of biomass into high-value chemicals are highly sensitive to solvent composition and identifying suitable solvent mixtures is theoretically and experimentally challenging. We show that the complex atomistic configurations of reactant–solvent environments generated by classical molecular dynamics simulations can be exploited by 3D convolutional neural networks to enable accurate predictions of Brønsted acid-catalyzed reaction rates for model biomass compounds. We develop a 3D convolutional neural network, which we call SolventNet, and train it to predict acid-catalyzed reaction rates using experimental reaction data and corresponding molecular dynamics simulation data for seven biomass-derived oxygenates in water–cosolvent mixtures. We show that SolventNet can predict reaction rates for additional reactants and solvent systems an order of magnitude faster than prior simulation methods. This combination of machine learning with molecular dynamics enables the rapid, high-throughput screening of solvent systems and identification of improved biomass conversion conditions.

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

High throughput exploration of the oxidation landscape in high entropy alloys

We report high entropy alloys (HEAs) have gained interest for structural applications in extreme environments. With a potentially vast chemical and phase space, there are significant opportunities to discover superior performing alloys. Crucial for most high-temperature applications is understanding and mitigating the oxidation behavior of these chemically complex alloys. Most experimental and computational HEA studies have focused on a limited set of compositions and only a fraction these compositions have been characterized for oxidation. We present a high-throughput framework that utilizes density-functional theory (DFT) in concert with a combined machine-learning model and grand-canonical linear programming for assessing phase stability, phase-fraction, chemical activity and high-temperature survivability of arbitrary HEAs. This framework considers temperature dependent contributions to the Gibbs energy of the competing phases arising from short-range order and vibrational entropy. We demonstrate the effectiveness of the framework by assessing the thermodynamic stability, oxidation behavior, chemical activity, and phase decomposition of body-centered cubic Mo-W-Ta-Ti-Zr refractory HEAs. A total of 51 compositions were analyzed and ranked in order of their survivability based on the Pareto-front analysis. Oxidation was performed at 1373 K on fours samples in air showing the difference in oxidation behavior determined experimentally through scale thickness and their mass changes. The insights on oxidation behavior presented in this work will enable the fast assessment of technologically useful HEAs needed for future structural application in extreme conditions

36 MATERIALS SCIENCE↗
DOE OSTI2017

A coarse-grained computational model of the nuclear pore complex predicts Phe-Gly nucleoporin dynamics

The phenylalanine-glycine–repeat nucleoporins (FG-Nups), which occupy the lumen of the nuclear pore complex (NPC), are critical for transport between the nucleus and cytosol. Although NPCs differ in composition across species, they are largely conserved in organization and function. Transport through the pore is on the millisecond timescale. Here, to explore the dynamics of nucleoporins on this timescale, we use coarse-grained computational simulations. These simulations generate predictions that can be experimentally tested to distinguish between proposed mechanisms of transport. Our model reflects the conserved structure of the NPC, in which FG-Nup filaments extend into the lumen and anchor along the interior of the channel. The lengths of the filaments in our model are based on the known characteristics of yeast FG-Nups. The FG-repeat sites also bind to each other, and we vary this association over several orders of magnitude and run 100-ms simulations for each value. The autocorrelation functions of the orientation of the simulated FG-Nups are compared with in vivo anisotropy data. We observe that FG-Nups reptate back and forth through the NPC at timescales commensurate with experimental measurements of the speed of cargo transport through the NPC. Our results are consistent with models of transport where FG-Nup filaments are free to move across the central channel of the NPC, possibly informing how cargo might transverse the NPC.

59 BASIC BIOLOGICAL SCIENCES↗