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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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Laser microprobe facility is effective in the elemental analysis of small areas of heterogeneous samples. The instrument uses the focused beam of a pulsed laser to evaporate a small volume of material from a relatively massive sample.
Oxidation of cold-pressed and sintered Si3N4 containing 15 wt% Y2O3 and 2, 4, 6, and 8% Al2O3 is observed at temperatures as low as 1000 C with IR reflection spectroscopy. Concentrations of Al2O3 in excess of 4% greatly retard the rate of oxidation and alter the mechanism of surface attack by promoting formation of a glassy layer on the surface containing mixed oxynitride bonds. The glassy layer retards heterogeneous attack and reduces the effect of an oxidation transition temperature between 1000 and 1100 C for these materials.
Development of lightweight, high specific stiffness engineered materials has been the long term goal of many investigators. Recently, this quest has focused on discontinuously reinforced aluminum metal matrix composites. This paper reviews the fabrication of powder metallurgy discontinuously reinforced metal matrix composites. Emphasis is given to the differences in heat treatment response reported between unreinforced and reinforced powder metallurgy materials. It is proposed that these observations can be rationalized by considering the effects of pre-existing heterogeneous nucleation sites, i.e., the dislocation substructure developed during rapid cooling of discontinuously reinforced aluminum metal matrix composites, on precipitation in reinforced aluminum alloys.
The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition, after investigating various methods, a Smoothed Particle Hydrodynamics Model (SPH Model) was developed to model wire feeding process. Its computational efficiency and simple architecture makes it more robust and flexible than other models. More research on material properties may be needed to realistically model the AAM processes. A microscale model was developed to investigate heterogeneous nucleation, dendritic grain growth, epitaxial growth of columnar grains, columnar-to-equiaxed transition, grain transport in melt, and other properties. The orientations of the columnar grains were almost perpendicular to the laser motion's direction. Compared to the similar studies in the literature, the multiple grain morphology modeling result is in the same order of magnitude as optical morphologies in the experiment. Experimental work was conducted to validate different models. An infrared camera was incorporated as a process monitoring and validating tool to identify the solidus and mushy zones during deposition. The images were successfully processed to identify these regions. This research project has investigated multiscale and multiphysics of the complex AAM processes thus leading to advanced understanding of these processes. The project has also developed several modeling tools and experimental validation tools that will be very critical in the future of AAM process qualification and certification.
The economic evaluation of natural resources depends on the accuracy of resource distribution estimates. On Earth such estimates are necessary in making decisions about opening new mines or in planning future investment for operating mines or industrial deposits. A frequently discussed lunar resource is water ice, however, we are only at the first stages of understanding its potential as a resource. In particular, we currently do not have a sufficient understanding of the distribution of water or its form at the scales it would be extracted and processed, that is, the “working scale”. Here the “working scale” is defined to be the scales at which sufficient material can be processed to meet some basic demand (for example, 100s of square meters), and the anticipated heterogeneity in the water distribution across those scales (scales <5 - 10s of meters). Several mission concepts have been developed to better understand lunar water, motivated by both scientific and exploration goals. This paper provides an analysis of the number and distribution of observations needed to provide the necessary next steps in lunar water ISRU. We use a combination of Monte Carlo studies and classic geostatistical approaches to go from the exploration goal of “understand the distribution of water” to quantification of specific mission sampling requirements.
Catalytic fast pyrolysis (CFP) is a versatile technology platform to convert biomass into fungible hydrocarbon transportation fuels and chemical co-products. Key technical barriers to reaching this goal include increasing the product yields and achieving the desired fuel properties for gasoline, diesel, and jet range fuels or blendstocks that would be suitable for introduction into existing refinery unit operations. Overcoming these barriers will require durable catalysts that are effective at upgrading and stabilizing biomass pyrolysis vapors. Towards these goals, this CRADA leveraged NREL experience as a leader in biomass pyrolysis research and Johnson Matthey's (JM) experience as a leader in the production of advanced catalytic materials. The scope spanned CFP catalyst development, characterization, multi-scale reaction testing, and computational modeling. CRADA benefits to DOE, Participant, and U.S. Taxpayer: Assists laboratory in achieving programmatic scope, Uses the laboratory’s core competencies. The purpose of this CRADA was to develop and deploy catalysts for biomass CFP to help achieve cost-competitive biofuels and bio-based products. This was accomplished through a close collaboration between biomass conversion researchers at NREL and catalyst development researchers at JM. Summary of Research Results: Focus Area 1. Foundational research on catalytic conversion and deactivation: Key interactions between pyrolysis vapors and heterogeneous catalysts were probed through catalyst characterization, model compound reaction testing, and atomistic-scale computational modeling. Catalyst development focused on multifunctional materials, which include zeolites, oxides, carbides, and nitrides. Computational modeling identified reaction mechanisms and elucidated surface chemistry to test hypotheses regarding mechanisms of deoxygenation, coupling, cracking, dehydration, coke formation, hydrogen transfer, and aromatic ring reactions. This information was used to design multifunctional catalysts to increase product yields, control product selectivity, and reduce deactivation during CFP and downstream processing steps. The results served to increase fundamental understanding of key catalyst attributes and durability features for the upgrading of biomass pyrolysis vapors. Model compound experiments confirmed the importance of metal-acid bifunctionality for the deoxygenation of lignin-derived phenolic species under hydrodeoxygenation conditions. This insight led to the development of catalysts such as Pt/TiO2 and Mo2C, which were confirmed as high-performing materials during subsequent bench-scale experiments using biomass-derived pyrolysis vapors. This focus area also led to the identification of important catalyst deactivation mechanisms associated with the deposition of inorganic contaminants such as potassium. The molecular-level insight from model compound experiments and computational modeling, shown in Figure 1, informed the development of regeneration procedures that have been shown to be effective for restoration of > 90% of initial catalyst activity. This understanding has subsequently been translated to other catalyst systems, including zeolite materials that can be operated without requirements for co-fed hydrogen.
In this report two plutonium oxides were prepared as unique reference materials for measurement of actinide elements present as trace constituents. Each reference material unit is approximately 200 mg of PuO 2 powder in a quartz glass bottle. Characterized attributes of the oxides included mass fractions of plutonium, americium, neptunium, and uranium. Isotope-amount ratios were also determined for plutonium and uranium, but neptunium and americium were observed to be monoisotopic 237 Np and 241 Am. Measurements for characterization and verification of the attributes show that plutonium and trace actinides are homogeneous with the exception of limited heterogeneity for uranium, primarily observed for the 238 U isotope. Model purification ages calculated from measured americium and uranium attribute values are consistent with material histories and indicate that these impurities are predominantly due to the decay of plutonium isotopes.
Ni-based superalloys are promising materials for high-temperature molten salt (MS) energy generation and storage. Studying morphological and chemical evolution of pure Ni in MS provides fundamental knowledge for MS technologies and corrosion mitigation. Here, in this study, real-time 3D morphological changes of Ni microparticles in molten KCl-MgCl 2 were studied by operando synchrotron X-ray nano-tomography at 700°C. Rapid Ni particle agglomeration occurred, without significant chemical reactions, such as oxide or chloride formation. The morphological growth evolved differently from classical coarsening or sintering behaviors and occurred nonuniformly, with other regions showing slight dissolution of Ni. Ni nanoparticles were found to be dispersed in many areas of the samples, either from microparticle dissolution or other radiation-induced nanoparticle formation mechanisms. This study discusses important factors, i.e., thermal gradient, amounts of salt and metals, and radiation effect, that influence morphological changes of materials in MS, critical for fundamental understanding of material–MS interactions as well as for practical applications.
Completely or partially ordered intermetallic compounds possess unique geometric ensembles, electronic structure and chemical bonding scenarios, establishing them as an emergent class of catalytic materials for selective hydrogenation reactions.
Possible interpretations of the results of the Viking Biology Experiments suggest that greater than 1 ppm of a thermally labile oxidant, perhaps H2O2, and about 10 ppm of a thermally stable oxidant are present in the martian soil. We reexamine these results and discuss implications for future missions, the search for organics on Mars, and the possible health and engineering effects for human exploration. We conclude that further characterization of the reactivity of the martian regolith materials is warrented-although if our present understanding is correct the oxidant does not pose a hazard to humans. There are difficulties in explaining the reactivity of the Martian soil by oxidants. Most bulk phase compounds that are capable of oxidizing H2O to O2 per the Gas Exchange Experiment (GEx) are thermally labile or unstable against reduction by atmospheric CO2. Models invoking trapped O2 or peroxynitrates (NOO2(-)) require an unlikely geologic history for the Viking Lander 2 site. Most suggested oxidants, including H2O2, are expected to decompose rapidly under martian UV. Nonetheless, we conclude that the best model for the martian soil contains oxidants produced by heterogeneous chemical reactions with a photochemically produced atmospheric oxidant. The GEx results may be due to catalytic decomposition of an unstable oxidizing material by H2O. We show that interfacial reaction sites covering less than 1% of the available soil surfaces could explain the Viking Biology Experiments results.
Fluid flow through fractures is intimately linked to the fracture surfaces that define the void geometry through which fluids flow. Thus, an understanding of what controls fracture surface roughness is essential to the development of models for predicting fluid transport through fractured rock. The difficulty in predicting surface roughness arises from the complexity of rock which is inherently heterogeneous and nonuniform in composition, fabric, and structural components, even when samples are acquired from the same rock mass. Here, a benchmarked-simulation approach motivated from geo-architected 3D printed synthetic gypsum rocks is used to provide insight into the competing contributions from fabric and layering on fracture roughness formation. Simulation results from a discrete element model (Particle Flow Code, Itasca Consulting Group, Inc.) clearly indicate that the relative orientation between mineral layers and in-layer mineral fabric, and the variability in mineral bonding strengths determine whether anisotropic corrugated surfaces or isotropic surfaces are formed. Weak mineral layers oriented perpendicular to the applied load resulted in strong roughness anisotropy. Peak failure loads were found to vary up to 30% depending on the strength of the mineral fabric at the location of fracture initiation, which provides insight into the observed high variability in strength values of natural rock. The uniqueness of induced fracture roughness and peak failure load is intimately linked to layering, mineral fabric, and their distribution in the rock. These findings have important implications for any architected material fabricated through serial printing of layers with local compositional heterogeneity.
The boundary element method is utilized in this study to conduct thermal analysis of functionally graded composites, materials in which the internal microstructure or properties are explicitly tailored in order to obtain an optimal response, on the micromechanical (constituent) scale. A unique feature of the boundary element formulations used here is the use of circular shape functions to convert the two-dimensional integrations of the composite fibers to one dimensional integrations. Using the computer code BEST-CMS, the through the thickness temperature profiles are computed for a representative material with varying numbers of fibers and fiber spacing in the thickness direction. The computed temperature profiles are compared to those obtained using an alternate analytical theory which explicitly couples the heterogeneous microstructure to the global analysis. The boundary element results compared favorably to the analytical calculations, with discrepancies that are explainable based on the boundary element formulation. The results serve both to demonstrate the ability of the boundary element method to analyze these types of materials, and to verify the accuracy of the analytical theory.
The degradation of nickel-rich cathode materials for lithium-ion batteries upon prolonged electrochemical cycling features a complicated interplay among electronic structure, lattice configuration, and micro-morphology. The underlying mechanism for such an entanglement of different material properties at nano- to mesoscales is fundamental to the battery performance but not well-understood yet. Here we investigate the correlation between the local redox reaction and lattice mismatch through a nano-resolution synchrotron spectro-microscopy study of LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM 811) cathode particles. With assistance from a machine-learning-based data classification method, we identify local regions that demonstrate a strain–redox decoupling effect, which can be attributed to different side reactions. Overall, our results highlight the mesoscale reaction heterogeneity in the battery cathode and suggest that particle structure engineering could be a viable approach to mitigate the chemomechanical degradation of cathode materials.
Tetrahedral liquids exhibit intriguing thermodynamic and transport properties because of the various ways tetrahedra can be packed and connected. Recently, an unusual temperature dependence of the stretching exponent β in a model tetrahedral liquid ZnCl 2 from T m + 85 K to T m + 35 K has been reported using neutron-spin echo spectroscopy. This discovery stands in sharp contrast to other glass-forming liquids. In this study, we conducted neural network force field driven molecular dynamic simulations of ZnCl 2 . We found a non-monotonic temperature dependence of β from liquid to supercooled liquid temperatures. Further structural decomposition and dynamic analysis suggest that this unusual dynamic behavior is a result of the competition between the decrease in the diversity of tetrahedra motifs (structural heterogeneity) and the increase in glassy dynamic heterogeneity. Furthermore, this result may contribute to new understandings of the structural relaxation of other network liquids.
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Materials databases generated by high-throughput computational screening, typically using density functional theory (DFT), have become valuable resources for discovering new heterogeneous catalysts, though the computational cost associated with generating them presents a crucial roadblock. Hence there is a significant demand for developing descriptors or features, in lieu of DFT, to accurately predict catalytic properties, such as adsorption energies. Here, we demonstrate an approach to predict energies using a convolutional neural network-based machine learning model to automatically obtain key features from the electronic density of states (DOS). The model, DOSnet, is evaluated for a diverse set of adsorbates and surfaces, yielding a mean absolute error on the order of 0.1 eV. In addition, DOSnet can provide physically meaningful predictions and insights by predicting responses to external perturbations to the electronic structure without additional DFT calculations, paving the way for the accelerated discovery of materials and catalysts by exploration of the electronic space.
This Perspective builds upon insights from the National Institute of Standards and Technology (NIST)-organized workshop, “Materials and Metrology Needs for Advanced Semiconductor Packaging Strategies,” held at the 35th annual Electronics Packaging Symposium in Binghamton, NY, on September 5, 2024. It outlines critical challenges and opportunities related to polymer-based “soft” materials in advanced semiconductor packaging, with emphasis on polymer science, measurement science (metrology), and the strategic development of Research-Grade Test Materials (RGTMs). These efforts, led by the NIST CHIPS team, aim to advance the fundamental understanding of structure-property-processing relationships, promote standardized guidelines and innovative methods for material characterization, and accelerate the development, qualification, and adoption of next-generation packaging materials. The Perspective also distills key insights from the panel discussion with industry experts, emphasizing the need for close collaboration among materials scientists, process engineers, and metrology experts to enable a holistic strategy, further highlighting the importance of cross-sector partnerships among industry, academia, and government to address pressing challenges in packaging materials and processes.
Understanding the particle-scale dynamics of granular materials during rapid compaction and flow is of fundamental importance for manufacturing, planetary science, geology, and defense applications. Time-resolved 2D radiography and static 3D x-ray tomography are powerful in situ tools for studying particle-scale dynamics but provide detail only in 2D or with significant time-scale limitations, respectively. Here, we introduce a new method that uses 2D in situ x-ray imaging for determining time-resolved 3D particle-scale dynamics in rapidly compressed granular materials. The method employs initial particle packing structures obtained from x-ray tomography, a 2D x-ray image generation algorithm, and an optimization algorithm. We first describe and validate the method using finite element simulations. Furthermore, we then apply the technique to x-ray phase-contrast images obtained during rapid compaction of granular materials with varying particle morphology and sample thickness. The depth-resolved particle-scale dynamics reveal complex velocity and porosity fields evolving heterogeneously along and perpendicular to the compaction direction. We characterize these features, their fluctuations near the compaction front, and the compaction front thickness. Our technique can be applied to understanding granular dynamics during rapid compaction events, and rearrangements during slower, but non-quasi-static, flows.