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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Annual report for DOE VTO

Carbon fiber (CF)/polymer composites are a transformative class of high-performance, lightweight material, where high aspect-ratio CFs reinforce a polymer matrix and exceed the strength of steel alloys at a fraction of the density. Despite the advantages of such a class of material, the broader implementation of CF composites in a range of automotive, aerospace, and energy applications is hindered by limitations of current manufacturing methods. These current techniques (e.g., hand lay-up, wet filament winding) are costly and impose severe limitations on fiber placement, orientation, and angle, and thus a composite’s ultimate properties. Today’s CF composites are expensive to manufacture, limited in form factor, and utilize costly and sub-optimal continuous filament CF. Advanced additive manufacturing (AM) processes, combined with computational design optimization and new approaches to resin development, offer alternative design and manufacturing paradigms that have the realistic potential to lift these constraints. Such integrated AM approaches could thus help to realize the full potential of CF composite materials. One relevant application of CF composite materials where manufacturing constraints limit the cost-benefit ratio is in the manufacture of high-performance composite pressure vessels for onboard compressed natural gas (CNG) storage. Current CNG storage vessels (Types 3–5) are made from load-bearing filament-wound carbon-fiber composite and are ~3.5 times as expensive as an all-metallic Type-1 vessel. This cost is invariably tied to the complex and labor-intensive nature of conventional filament winding processes and the large volumes of expensive high tensile-strength CF tow feedstock required in manufacture. Our proposed approach to CNG storage vessel manufacture is based on a combination of AM technologies for CF composite printing and design optimization tools that were pioneered at Lawrence Livermore National Laboratory (LLNL), with advances in resin/composite formulation enabled by chemical and nano-material modification. Through the successful development of this technology, LLNL seeks to demonstrate the capability for advanced CNG storage vessel manufacture at reduced cost with no reduction in performance versus the most advanced, extant Type-5 designs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Elucidating the Interfacial Barriers in Lanthanide Back-Extraction: From Water to Oil and Back Again

Recovery of critical rare earth elements from complex mixtures has long been realized via solvent extraction, where ions in an aqueous phase are separated into an organic phase using amphiphilic ligands. While a great deal of effort has been placed on understanding this forward reaction, substantial knowledge gaps in the back-extraction process remain. This includes the mechanism of interfacial dissociation and transport back into a highly acidic aqueous phase for further processing. In this work, we connect back-extraction kinetics made in realistic solvent extraction systems to salient interfacial chemistry and structure that represent bottlenecks in the back-extraction of lanthanide ions. We show that the interface between the two liquid phases varies dramatically based on the composition of both phases. Water stretching signals are shown to report on the population of lingering interfacial complexes and are thus used as a reporter of competitive adsorption from excess free ligands in solution for limited interfacial vacancies. We show that excess free ligands, often used to improve forward extractions, set up interfacial blockades inhibiting back-extraction both kinetically and thermodynamically. In conclusion, this insight opens up avenues to tune interfacial properties to facilitate a more dynamic, exchangeable interface to speed up back-extractions while using less energy intensive chemical swings.

Interfaces↗
DOE OSTI2022

Bone: An Outstanding Composite Material

Bone is an outstanding, well-designed composite. It is constituted by a multi-level structure wherein its properties and behavior are dependent on its composition and structural organization at different length scales. The combination of unique mechanical properties with adaptive and self-healing abilities makes bone an innovative model for the future design of synthetic biomimetic composites with improved performance in bone repair and regeneration. However, the relation between structure and properties in bone is very complex. In this review article, we intend to describe the hierarchical organization of bone on progressively greater scales and present the basic concepts that are fundamental to understanding the arrangement-based mechanical properties at each length scale and their influence on bone’s overall structural behavior. The need for a better understanding of bone’s intricate composite structure is also highlighted.

Rosa, Natacha (ORCID:0000000199008851)↗
DOE OSTI2018

Revealing structural involvement of chromophores in algal light harvesting complexes using symmetry-adapted perturbation theory

The attribution of quantum beats observed in the time-resolved spectroscopy of photosynthetic light-harvesting antennae to nontrivial quantum coherences has sparked a flurry of research activity beginning a decade ago. Even though investigations into the functional aspects of photosynthetic light-harvesting were supported by X-ray crystal structures, the non-covalent interactions between pigments and their local protein environment that drive such function has yet to be comprehensively explored. Using symmetry-adapted perturbation theory (SAPT), we have comprehensively determined the magnitude and compositions of these non-covalent interactions involving light-harvesting chromophores in two quintessential photosynthetic pigment-protein complexes — peridinin chlorophyll-a protein (PCP) from dinoflagellate Amphidinium carterae and phycocyanin 645 (PC645) from cryptophyte Chroomonas mesostigmatica. In PCP, the chlorophylls are dispersion-bound to the peridinins, which in turn are electrostatically anchored to the protein scaffold via their polar terminal rings. This might be an evolutionary design principle in which the relative orientation of the carotenoids towards the aqueous environment determines the arrangement of the other chromophores in carotenoid-based antennas. On the other hand, electrostatics dominate the non-covalent interactions in PC645. As a result, our ab initio simulations also suggest full protonation of the PC645 chromophores in physiological conditions, and that changes to their protonation states result in their participation as switches between folded and unfolded conformations.

59 BASIC BIOLOGICAL SCIENCES↗
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↗
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↗
DOE OSTI2020

Trends and drivers of marine fish landings in Portugal since its entrance in the European Union

Abstract Marine landings in Portugal have decreased at a higher rate than fishing effort in the last 20 years. Identifying the variables driving the quantity and composition of landings is pivotal to understand the dynamics of the fisheries sector, which entails complex social and environmental aspects. In this study, we investigate the main drivers of marine fish landings in continental Portugal between 1989 and 2014. To identify common trends in time series, and quantify the importance of environmental factors, we applied a dynamic factor analysis considering four regions and three types of gear (trawling, purse-seine, and a multi-gear fishery). Our results show the importance of fishing effort as the most relevant factor driving marine landings in Portugal, both at the long and short terms. In addition, the effect of environmental factors such as the winter river discharge and the spring East Atlantic Teleconnection index should not be neglected, probably through mechanisms affecting coastal productivity. We provide a comprehensive amount of information that permits to improve our understanding of the trends of the most important commercial species in Portugal during the period of study.

Bueno-Pardo, Juan↗