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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Effect of annealing on the tribological behavior of Zr-based bulk metallic glass

Bulk Metallic Glasses (BMGs) are promising materials for several applications owing to their high elastic limit and resistance to permanent deformation. However, BMGs have lower wear resistance than their crystalline counterparts during dry sliding. The formation of a composite material with crystalline phases dispersed in the BMG matrix through devitrification and partial crystallization at elevated temperatures has recently been proposed as an effective way to improve the wear resistance. However, our understanding of the origin of the improved wear behavior of annealed BMGs is still elusive. Here, a systematic evaluation of the effect of annealing temperature (from temperatures lower than the BMG glass transition temperature to temperatures higher than the BMG recrystallization temperature) on the friction and wear response of a Zr-based BMG, namely Vit105 (Zr 52.5 Cu 17.9 Ni 14.6 Al 10 Ti 5 ), was performed. The results indicate that annealing Vit105 improves its wear resistance while also reducing the steady-state friction response when the annealing temperature is close to the glass transition temperature. Notably, the formation of a transfer film on the sapphire countersurface is highly dependent on the applied normal load and sliding time. Finally, the wear mechanism was found to be strongly dependent on the annealing temperature as a transition from a predominantly adhesive wear mechanism to an abrasive-dominated one was observed as the annealing temperature crossed the glass transition temperature. Altogether, the results of this work aid to our understanding of the tribological behavior of Zr-based BMGs in general, while also providing clues to strategies for the effective use of BMGs in tribological applications.

Lien, Hsu-Ming [Univ. of Texas, Austin, TX (United↗
DOE OSTI2024

Modeling Tungsten Boride Neutronics in ORIGEN for Z-Facility

ORIGEN is one of the main transmutation software packages used in nuclear engineering Modeling Tungsten Boride Neutronics in ORIGEN for Z-Facilityproblems. For the case of this study, tungsten borides are studied using a coupled framework between MCNP and the ORIGEN package of scale. The input used four compositions of tungsten boride: WB with natural boron- 10 abundance, WB with 80wt% B-10 per isotope of boron, WB4 with natural boron-10 abundance, and WB4 with 80wt% B-10 per isotope of boron. Isotopic inventories were produced for WB which show the time dependent change up to 2 years after a 6-Month irradiation. This will allow for further studies of the materials to assess things material composition changes, dose contribution, and waste management requirements.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Silicon-silicon oxide-carbon composites for lithium battery electrodes and methods for forming the composites

Composite silicon based materials are described that are effective active materials for lithium ion batteries. The composite materials comprise processed, e.g., high energy mechanically milled, silicon suboxide and graphitic carbon in which at least a portion of the graphitic carbon is exfoliated into graphene sheets. The composite materials have a relatively large surface area, a high specific capacity against lithium, and good cycling with lithium metal oxide cathode materials. The composite materials can be effectively formed with a two step high energy mechanical milling process. In the first milling process, silicon suboxide can be milled to form processed silicon suboxide, which may or may not exhibit crystalline silicon x-ray diffraction. In the second milling step, the processed silicon suboxide is milled with graphitic carbon. Composite materials with a high specific capacity and good cycling can be obtained in particular with balancing of the processing conditions.

Anguchamy, Yogesh Kumar↗
DOE OSTI2023

Methods for forming silicon-silicon oxide-carbon composites for lithium ion cell electrodes

Composite silicon based materials are described that are effective active materials for lithium ion batteries. The composite materials comprise processed, e.g., high energy mechanically milled, silicon suboxide and graphitic carbon in which at least a portion of the graphitic carbon is exfoliated into graphene sheets. The composite materials have a relatively large surface area, a high specific capacity against lithium, and good cycling with lithium metal oxide cathode materials. The composite materials can be effectively formed with a two-step high energy mechanical milling process. In the first milling process, silicon suboxide can be milled to form processed silicon suboxide, which may or may not exhibit crystalline silicon x-ray diffraction. In the second milling step, the processed silicon suboxide is milled with graphitic carbon. Composite materials with a high specific capacity and good cycling can be obtained in particular with balancing of the processing conditions.

Anguchamy, Yogesh Kumar↗
DOE OSTI2022

Systematic electronic structure in the cuprate parent state from quantum many-body simulations

The quantitative description of correlated electron materials remains a modern computational challenge. We demonstrate a numerical strategy to simulate correlated materials at the fully ab initio level beyond the solution of effective low-energy models and apply it to gain a detailed microscopic understanding across a family of cuprate superconducting materials in their parent undoped states. We uncover microscopic trends in the electron correlations and reveal the link between the material composition and magnetic energy scales through a many-body picture of excitation processes involving the buffer layers. Our work illustrates a path toward a quantitative and reliable understanding of more complex states of correlated materials at the ab initio many-body level.

Science & Technology - Other Topics↗
DOE OSTI2020

Volumetric analysis and mesh generation of real and artificial microstructural geometries

Producing a viable finite element mesh of realistic microstructural structural geometry is a critical step in analyzing the thermo-mechanical behavior of complex multi-material composites. Advancements in imaging technology such as micro computed tomography have allowed modelers to access high resolution mesoscale geometries for direct numerical simulation. However, converting from voxel based 3D images to usable finite element meshes has been challenging. A robust method including algorithms and software scripts for generating finite element meshes from 3D imaged microstructures is presented in this paper. It includes a routine for inserting cohesive elements around material interfaces to enable modeling of interface properties including delamination and damage. The algorithms and procedures presented in this method leverage currently available software packages for processing surface based geometry into volume based meshes. In addition to converting real geometry from physical imaging systems, algorithms for producing numerically generated and statistically equivalent microstructural geometry are also included. These artificial microstructures can be a valuable resource for modelers when physical specimens do not exist or are limited in quantity: Method establishes a workflow from voxel data to viable finite element mesh including interface information, and Includes a method for synthetic geometry generation based on metrics from real microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predictive coarse-grained (CG) modeling of morphologies in polymer nanocomposites with specific and directional intermolecular interactions (Final Report)

The overarching goal of the proposed work was to develop predictive models for investigating structure and dynamics in soft materials with chemistries that have specific and directional molecular interactions. The motivation behind studying materials with specific and directional interactions lies in the many desirable features these interactions provide when designing novel soft materials. Soft materials with specific and direction interactions (such as hydrogen bonds or H-bonds) can have a) thermally reversible phase behavior with different functions with varying temperature, b) precisely tuned nanostructure with desirable geometries that afford unique physical properties (e.g., color response, mechanical properties) and c) well-mixed/blended morphologies that are useful for variety of applications in energy field (e.g., materials for batteries require use of blended polymers where one domain gives superior mechanical properties and one domain promotes electrical conduction). Notably, biology makes extensive use of specific and directional interactions, in many cases based on H-bonds, to construct materials with precisely defined architectures and properties. Engineered soft materials with precisely tuned nanostructures and improved processiblity through thermoresponsive phase behavior are useful in numerous applications that are relevant to the Department of Energy (DOE) including high efficiency electronic devices, light-weight high-strength composite materials for batteries and fuel cells, and polymer membranes for separations, etc. While past computational studies have been tremendously useful in understanding molecular phenomena and guiding synthesis of new macromolecular soft materials for a wide variety of applications, the inability to capture small scale specific and directional interactions alongside macromolecular length and time scales represented a key limitation of most studies to date. Our work in this project addressed this grand challenge in computational materials chemistry, i.e., ability to model the anisotropic, directional, and specific interactions that govern the behavior of many macromolecular soft matter systems of interest, thus, has greatly expanded the predictive potential of simulations. Specifically the key outcomes were: successful development of new coarse-grained (CG) polymer models to study generic and specific polymer chemistries in which hydrogen-bonding interactions are dominant. These CG models were then used in molecular simulations to study structure and thermodynamics in polymer nanocomposites and blends; some studies were conducted in collaboration with experimentalists. We also published a perspective and a viewpoint which included some of the work we completed in this DOE project; we believe these perspective and viewpoint articles guide other researchers in the soft materials community on how to extend the computational approaches and models we have developed for the purposes of their studies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Rheological characterization of 3D printable geopolymers

This study demonstrates a two-step approach that enables quantification of concrete printability through dynamics mode rheological measurements; I) modeling shearing history during extrusion; II) monitoring the hardening evolution of deposited material by applying a strain smaller than the critical strain. It is shown that the shearing history of the material is removed by imposing a pre-shearing above the critical strain, and zero value yield stress is measured for all specimens. At step II, a linear extrapolation of the green strength development can quantify the static yield stress at the origin, which we used to quantify the material printability. As far as this yield stress surpasses the stress level that exists in the printed structure, the material retains its shape stability. We show the performance of the model on a series of geopolymer mortars with a wide range of rheological properties as a function of material composition, aging, and pre-shearing consequences.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Fused Deposition Modeling Additive Manufacturing of Carbonized Structures via Waste-Enhanced Filaments

This report details the development, characterization, and use of coal-enhanced composite materials in additive manufacturing applications. High coal loading formulations—containing up to 70 wt.% coal—were successfully extruded and processed using commercially available 3D printers. Extensive experimental testing was conducted to assess the mechanical, thermal, and microstructural properties of the composites. In parallel, multi-scale computational modeling was employed to elucidate atomistic interactions and evaluate the effects of printing-induced defects on structural performance. Large-scale printability trials demonstrated the feasibility of fabricating complex components for tooling and construction applications, including wind turbine blade molds and modular wall sections. Techno-economic analyses demonstrated the cost-effectiveness and scalability of coal-enhanced composites for large-scale additive manufacturing applications such as wind turbine blade tooling.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Bimodal Visualization of Industrial X-Ray and Neutron Computed Tomography Data

Advanced manufacturing creates increasingly complex objects with material compositions that are often difficult to characterize by a single modality. Our collaborating domain scientists are going beyond traditional methods by employing both X-ray and neutron computed tomography to obtain complementary representations expected to better resolve material boundaries. However, the use of two modalities creates its own challenges for visualization, requiring either complex adjustments of bimodal transfer functions or the need for multiple views. Together with experts in nondestructive evaluation, we designed a novel interactive bimodal visualization approach to create a combined view of the co-registered X-ray and neutron acquisitions of industrial objects. Using an automatic topological segmentation of the bivariate histogram of X-ray and neutron values as a starting point, the system provides a simple yet effective interface to easily create, explore, and adjust a bimodal visualization. Here, we propose a widget with simple brushing interactions that enables the user to quickly correct the segmented histogram results. Our semiautomated system enables domain experts to intuitively explore large bimodal datasets without the need for either advanced segmentation algorithms or knowledge of visualization techniques. We demonstrate our approach using synthetic examples, industrial phantom objects created to stress bimodal scanning techniques, and real-world objects, and we discuss expert feedback.

image segmentation↗
DOE OSTI2024

Physical origin of enhanced electrical conduction in aluminum-graphene composites

In this study, the electronic and transport properties of aluminum-graphene composite materials were investigated using the ab initio plane wave density functional theory. The interfacial structure is reported for several configurations. In some cases, the face-centered aluminum (111) surface relaxes in a nearly ideal registry with graphene, resulting in a remarkably continuous interface structure. The Kubo–Greenwood formula and space-projected conductivity were employed to study electronic conduction in aluminum single- and double-layer graphene-aluminum composite models. The electronic density of states at the Fermi level is enhanced by the graphene for certain aluminum–graphene interfaces, thus improving electronic conductivity. In double-layer graphene composites, conductivity varies non-monotonically with temperature, showing an increase between 300 and 400 K at short aluminum-graphene distances, unlike the consistent decrease in single-layer composites.

36 MATERIALS SCIENCE↗
DOE OSTI2021

MADE3D: Enabling the next generation of high-torque density wind generators by additive design and 3D printing

Direct-drive wind turbine generators are increasing in popularity, thanks to recent project developments—especially offshore, where reliability and efficiency are major cost drivers. Yet, high capital costs are forcing many original equipment manufacturers to consider lightweight, high-torque density generators for next-generation multi-megawatt turbines that may be difficult to realize by traditional design or manufacturing methods. In this study, we present a new design framework enabled by advanced machine learning and multimaterial additive manufacturing to perform a magnetic topology optimization that maximizes the torque per rotor active mass for a 15-megawatt direct-drive permanent magnet wind generator. A comparison of the proposed approach against conventional topology optimization demonstrated a significant increase in computational efficiency and accuracy in performance predictions. Results using single and multimaterial compositions for rotor core and magnets identify a wider choice of 3D printable designs for a given specification. A hybrid combination of sintered and dysprosium-free polymer-bonded magnets shows good potential for torque performance by saving material costs up to 8.75%. More than 30% improvement in rotor torque densities is identified which can marginally improve the overall generator torque density. With the rapid evolution of multipowder deposition technolgies, this study can greatly inspire a new paradigm for design-driven manufacturing with novel material compositions and lightweight, low-cost, high-strength multimaterial geometries that were previously unexplored for direct-drive generators.

17 WIND ENERGY↗
DOE OSTI2022

Supercurrent decay in ballistic magnetic Josephson junctions

We investigate transport properties of ballistic magnetic Josephson junctions and establish that suppression of supercurrent is an intrinsic property of the junctions, even in absence of disorder. By studying the role of ferromagnet thickness, magnetization, and crystal orientation we show how the supercurrent decays exponentially with thickness and identify two mechanisms responsible for the effect: (i) large exchange splitting may gap out minority or majority carriers leading to the suppression of Andreev reflection in the junction, (ii) loss of synchronization between different modes due to the significant dispersion of the quasiparticle velocity with the transverse momentum. Our results for Nb/Ni/Nb junctions are in good agreement with recent experimental studies. Our approach combines density functional theory and the Bogoliubov-de Gennes model and opens a path for material composition optimization in magnetic Josephson junctions and superconducting magnetic spin valves.

36 MATERIALS SCIENCE↗
DOE OSTI2021

MADE3D: Enabling the Next-Generation High-Torque- Density Wind Generators by Additive Design and 3D Printing

Direct-drive wind turbine generators are increasing in popularity, thanks to recent project developments - especially offshore, where reliability and efficiency are major cost drivers. Yet, high capital costs are forcing many original equipment manufacturers to consider lightweight, high-torque density generators for next-generation multi-megawatt turbines that may be difficult to realize by traditional design or manufacturing methods. In this study, we present a new design framework enabled by advanced machine learning and multimaterial additive manufacturing to perform a magnetic topology optimization that maximizes the torque per rotor active mass for a 15-megawatt direct-drive permanent magnet wind generator. A comparison of the proposed approach against conventional topology optimization demonstrated a significant increase in computational efficiency and accuracy in performance predictions. Results using single and multimaterial compositions for rotor core and magnets identify a wider choice of 3D printable designs for a given specification. A hybrid combination of sintered and dysprosium-free polymer-bonded magnets shows good potential for torque performance by saving material costs up to 8.75%. More than 30% improvement in rotor torque densities is identified which can marginally improve the overall generator torque density. With the rapid evolution of multipowder deposition technologies, this study can greatly inspire a new paradigm for design-driven manufacturing with novel material compositions and lightweight, low-cost, high-strength multimaterial geometries that were previously unexplored for direct-drive generators.

3D printing↗
DOE OSTI2024

Emerging continuous SiC fibers for high-temperature applications

Silicon carbide (SiC) fibers are responsible for the ultimate strength and toughness of SiC-fiber reinforced composites in harsh environments. The development of a new generation of continuous SiC fibers continues to advance the mechanical properties of composite materials. Tyranno™ SA4 fiber was recently released as a successor of Tyranno™ SA3 fiber. Laser-driven chemical vapor deposition (LCVD) has been adopted as an alternative fiber processing route to synthesizing high-strength SiC fiber with tailorable small diameters and chemical compositions. Both Tyranno™ SA4 and laser-driven CVD fibers show very high tensile strength, about 4 GPa in the as-fabricated condition. The degradation of thermal stability and strength due to annealing in an inert environment were similar for Tyranno™ SA3 and SA4 fibers because of their similar carbon-rich, crystalline microstructure. Silicon-rich fibers produced by LCVD possessed heterogeneous crystallinity, which was attributed to laser power distribution and showed microstructural instability at 1500 °C and above. Finally, the new SiC fibers demonstrated an increase in as-fabricated strength but faced the same challenges in environmental resistance as the traditional SiC fibers do.

36 MATERIALS SCIENCE↗
DOE OSTI2023

CRADA Number NFE-20-08283 with Actinic LLC (CRADA Final Report)

Significant advances have been made in the additive manufacturing (AM) of thermoplastics and optically cured thermosets; however, AM of thermally cured thermosets has lagged. Materials belonging to this class of thermosets, such as silicone rubbers and polyurethanes, are not well represented in the AM space despite their widespread use in medical, defense, and other fields. Ideally, a solution would enable AM of current commercially viable thermally cured thermosets with a speed that is comparable to those already realized for thermoplastics and optically cured thermosets. Realizing this goal will provide several benefits, including: 1. Make thermally cured thermoset designs impossible via casting. 2. Iteration of part designs without investment in new molds. 3. Devices and personal protection equipment, custom-fit to the end-user. 4. Ability to print multifunctional composite materials. 5. Rapid production ability for DoD personnel deployed at forward locations. 6. Simplify supply chains and replace multiple parts with a single raw material. These benefits motivate the development of a commercially viable 3D printer for thermally cured thermosets, based on the technique of photothermal curing. This project further developed a printer capable of printing composites containing commercially available thermally cured polydimethylsiloxane (PDMS), directly yielding cured parts such as boxes, walls, and free-standing overhangs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Benchtop Autonomous Electrochemical Characterization System for Combinatorial Thin-Film Solid Oxide Electrodes

The design of materials for electrochemical energy conversion is complicated by a vast search space of candidate materials and multifaceted property requirements: multicarrier conductivity, stability, and catalytic activity are all necessary but rarely intersect. Although self-driving laboratories are rapidly rising to address such material optimization problems, the required infrastructure for integrated, large-scale robotic facilities can be cost-prohibitive. Here we develop and evaluate a closed-loop measurement system for efficient screening of proton-conducting oxide electrodes for ceramic fuel cells and electrolyzers, building on top of an existing benchtop instrument and integrating techniques for rapid impedance measurement and automated analysis. This system exemplifies a “minimum viable” self-driving implementation that can deliver substantial benefits with relatively simple infrastructure. Combinatorial thin-film microelectrode libraries are characterized with a recently developed joint time-domain and frequency-domain impedance measurement technique, which provides an order-of-magnitude acceleration relative to conventional impedance spectroscopy. The distribution of relaxation times is extracted from impedance data and analyzed without human intervention. These results feed an active learning and Bayesian optimization process that learns to predict electrochemical impedance as a function of material composition, measurement temperature, oxygen partial pressure, and electrical bias, which further reduces the screening time by tenfold with optimized experimental sequences. We apply this system to Ba⁡(Co,Fe,Zr,Y)⁢O 3−𝛿 combinatorial libraries and evaluate its effectiveness for learning material property trends and optimizing expensive-to-evaluate properties such as activation energy. This offers insights into key methodological aspects of practical autonomous experimentation, including surrogate model validation, cost-aware acquisition functions, and high-throughput data interpretation. Our results demonstrate the efficacy of the system for rapidly gathering information, but also highlight real-world experimental challenges of thin-film degradation and numerical instability in surrogate models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗