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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Elucidating the Onset of Plasticity in Sliding Contacts Using Differential Computational Orientation Tomography

Abstract Depending on the mechanical and thermal energy introduced to a dry sliding interface, the near-surface regions of the mated bodies may undergo plastic deformation. In this work, we use large-scale molecular dynamics simulations to generate “differential computational orientation tomographs” (dCOT) and thus highlight changes to the microstructure near tribological FCC alloy surfaces, allowing us to detect subtle differences in lattice orientation and small distances in grain boundary migration. The analysis approach compares computationally generated orientation tomographs with their undeformed counterparts via a simple image analysis filter. We use our visualization method to discuss the acting microstructural mechanisms in a load- and time-resolved fashion, focusing on sliding conditions that lead to twinning, partial lattice rotation, and grain boundary-dominated processes. Extracting and laterally averaging the color saturation value of the generated tomographs allows us to produce quantitative time- and depth-resolved maps that give a good overview of the progress and severity of near-surface deformation. Corresponding maps of the lateral standard deviation in the color saturation show evidence of homogenization processes occurring in the tribologically loaded microstructure, frequently leading to the formation of a well-defined separation between deformed and undeformed regions. When integrated into a computational materials engineering framework, our approach could help optimize material design for tribological and other deformation problems. Graphic Abstract .

36 MATERIALS SCIENCE↗
DOE OSTI2021

Neutron Irradiation Induced Changes in Isotopic Abundance of 6Li and 3D Nanoscale Distribution of Tritium in LiAlO2 Pellets Analyzed by Atom Probe Tomography

Tritium, a radioactive isotope of hydrogen is produced by neutron irradiation of 6Li enriched LiAlO2 pellets in Tritium producing burnable absorber rods (TPBARs). Three-dimensional nanoscale mapping of Tritium in irradiated pellets is critical to understand its spatial variation and its association with various microstructural features in the pellets. Spatially resolved analysis of 6Li isotopic enrichment in such ceramic pellets before and after irradiation can provide insights to heterogeneities in Li isotopic distribution. However, Li being a light isotope, its spatially resolved compositional or isotopic analysis is a challenging task to most analytical methods. Here we used atom probe tomography, to evaluate the Li isotopic enrichment in both the LiAlO¬2 matrix and the Li deficient secondary phase LiAl5O8 before irradiation. These results were then compared with 6Li isotopic ratio measured by APT analysis of neutron irradiated pellets to clearly demonstrate the unique capability of APT to quantitatively analyze the isotopic enrichment of 6Li as well as for other light elements present in these materials. Evidence for heterogenous nanoscale distribution of 3H and O3H within irradiated pellet microstructure is also provided, which is attributed to 3H trapping in irradiation induced vacancy clusters or voids within the LiAlO2 matrix. The characterization results given here, now prove the feasibility for using APT for analyzing nanoscale spatially resolved isotopic enrichment of Li as well as other light elements such as Tritium in TPBARs. This work also paves way to adopt APT for analyzing light elements such as Li and tritium in materials used for nuclear fusion reactor applications, geochemistry, astrophysics as well as for energy storage applications.

Devaraj, Arun↗
DOE OSTI2026

A Bayesian inferencing framework for ultrasound wave speed measurements in metal additive manufacturing

Process-related changes during metal additive manufacturing introduce microstructural variability in the material properties of printed parts, directly affecting component reliability. Accurate estimation of these property variations with part performance are essential for quality assurance. Ultrasound testing offers a non-destructive means to estimate mechanical properties and detect defects; however, conventional analysis methods often neglect the influence of microstructural variability, limiting their effectiveness. Here, this research presents a Bayesian inference technique for quantifying wave speed uncertainty from ultrasound measurements of metal additive manufactured parts. By integrating prior ultrasound data with a Bayesian model, the proposed approach generates posterior density estimates of wave speed that systematically account for manufacturing-induced variability and uncertainty. The novelty of this research lies in applying a Bayesian framework to analyze experimental ultrasound measurements within the context of metal additive manufacturing variability. The method enhances the accuracy of wave speed estimation by 64%, defect position by 50% and increases confidence associated with wave speed variance by 30% across different porosity levels, thereby providing a robust foundation for improved decision-making and increased reliability in additively manufactured components.

Additive manufacturing↗
NASA NTRS1986

Solidification of Nb-Ge alloys in long drop tubes

The 30-m and 100 m-long drop tubes at the Marshall Space Flight Center have been used to obtain large undercooling in Nb-Ge alloys. Electron beam melting has been used to obtain drops approximately 2.5 mm in diam. In the 30-m tube, many specimens fell the length of the tube without solidifying, and were ultimately liquid-quenched in oil. The amount of undercooling prior to the quench was usually around 0.13 T(m). In the 100-m tube, freezing generally initiated during free fall, and the maximum undercooling was around 0.22 T(m). Microstructures were characterized by a combination of X-ray diffraction, optical microscopy, and scanning electron microscopy with energy dispersive analysis by X-rays. A variety of interesting microstructures was observed.

Bayuzick, R. J.↗
NASA NTRS1978

Metallurgical analysis of skylab M552 and M557 samples

The anomalous microstructures on the basis of phase equilibria, liquid/liquid phase separation, and liquid/solid segregation for the Skylab M557 and M552 flight samples were studied. All of the unknown diffraction spectra have been identified. The previously unknown crystal structure of the Zn3Sb2 phase the M577B Experiment was determined. Previously unreported effects due to the near-absence of the hydrostatic pressure head are documented for the M557C samples.

Larson, D. J., Jr.↗
NASA NTRS2014

A Technique for Mapping Characteristic Lengths to Preserve Energy Dissipated via Strain Softening in a Multiscale Analysis

It is often advantageous to account for the microstructure of the material directly using multiscale modeling. For computational tractability, an idealized repeating unit cell (RUC) is used to capture all of the pertinent features of the microstructure. Typically, the RUC is dimensionless and depends only on the relative volume fractions of the different phases in the material. This works well for non-linear and inelastic behavior exhibiting a positive-definite constitutive response. Although, once the material exhibits strain softening, or localization, a mesh objective failure theories, such as smeared fracture theories, nodal and element enrichment theories (XFEM), cohesive elements or virtual crack closure technique (VCCT), can be utilized at the microscale, but the dimensions of the RUC must then be defined. One major challenge in multiscale progressive damage modeling is relating the characteristic lengths across the scales in order to preserve the energy that is dissipated via localization at the microscale. If there is no effort to relate the size of the macroscale element to the microscale RUC, then the energy that is dissipated will remain mesh dependent at the macroscale, even if it is regularized at the microscale. Here, a technique for mapping characteristic lengths across the scales is proposed. The RUC will be modeled using the generalized method of cells (GMC) micromechanics theory, and local failure in the matrix constituent subcells will be modeled using the crack band theory. The subcell characteristic lengths used in the crack band calculations will be mapped to the macroscale finite element in order to regularize the local energy in a manner consistent with the global length scale. Examples will be provided with and without the regularization, and they will be compared to a baseline case where the size and shape of the element and RUC are coincident (ensuring energy is preserved across the scales).

softening↗
DOE OSTI2023

Microstructurally driven self-sharpening mechanism in beaver incisor enamel facilitates their capacity to fell trees

Beavers ( Castor ) stand out among mammals for their unique capacity to fell trees using their large, ever-growing incisors. This routine consumption of resistant fodder induces prodigious wear in the lower incisors, despite this blunting effect the incisors maintain a remarkably sharp cutting edge. Notably, the enamel edges of their incisors show a highly complex two-part microstructure of which the biomechanical import is unknown. Here, using fracture analysis, nanoindentation, and wear testing on North American beaver ( C. canadensis ) incisors we test the microstructure's possible contribution to maintaining incisal sharpness. Although comparable in hardness, the inner enamel preferentially fails and readily wears at 2.5 times the rate of the outer enamel. The outer microstructure redirects all fractures in parallel, decreasing fracture coalescence. Conversely, the inner microstructure facilitates crack coalescence increasing the wear rate by isolating layers of enamel prisms that readily fragment. Together these two architectures form a microstructurally driven self-sharpening mechanism contained entirely within the thin enamel shell. Here, our results demonstrate that enamel microstructures exposed at the occlusal surface can markedly influence both enamel crest shape and surface texture in wearing dentitions. The methods introduced here open the door to exploring the biomechanical functionality and evolution of enamel microstructures throughout Mammalia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Failure analysis of solid oxide fuel cells nickel-yttria stabilized zirconia anode under siloxane contamination

In this study, the failure process of the solid oxide fuel cell (SOFC) Ni-yttria-stabilized zirconia (YSZ) anode is investigated with D4 siloxane (octamethylcyclotetrasiloxane) contamination. In order to evaluate the influence of the electrochemical reaction on the siloxane deposition process, the SOFC experiments were operated at open circuit voltage (OCV) and 50 mA cm -2 conditions at 800°C. During the failure process, electrochemical, morphology and exhaust gas component analysis testing are conducted at the critical points. An equivalent circuit model and corresponding microstructure parameter calculations for separated physicochemical processes were utilized for the quantitative analysis of the failure process. Further, the results confirm the siloxane chemical adsorption deposition mechanism proposed in previous work. As a result, the failure of the anode was attributed to the gas diffusion blockage by dense silicon dioxide layer formation. The anode failure process with siloxane contamination is faster when the anode is operated under polarization.

25 ENERGY STORAGE↗
DOE OSTI2020

Topological analysis of X-ray CT data for the recognition and trending of subtle changes in microstructure under material aging

X-ray computed tomography (CT) is an established non-destructive tool for 3D imaging of multiphasic composites. Numerous applications of X-ray CT in medical diagnosis and materials characterization have been reported, many involving field-specific innovations in the imaging technology itself. Yet, quantitative summarization to link image features to properties of interest has been rare. Here we address this issue by employing state-of-the-art technics in scalar field topology for the summarization of X-ray CT images of an example biphasic system. By varying processing-parameters we create different microstructures, evolve them through accelerated thermal aging, CT-image them pre- and post-aged, and demonstrate the ability of our image summarization method to systematically track process- and age-related changes, which can often be very subtle. A novel aspect of the algorithm involves recognition over multiple resolution levels, which provides deeper insight into the pattern relationship between grain-like features and their neighbors. The method is general, adaptable to diverse image reconstruction methods and materials systems, and particularly useful in applications where practical constraints on the sample-size limits the reliable use of more complex models, e.g., convolutional neural networks.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Correlative electron and ion beam analysis of the electrochemical performances of LiV 3 O 8 cathode films as a function of microstructures

Degradation mechanisms in LiV 3 O 8 cathode films (~500 nm) with different initial microstructures i.e., globular nanocrystals in amorphous matrix and needle-like nanocrystals, synthesized by annealing the cathodes at 150 °C and 300 °C for 6 h are studied by Transmission Electron Microscopy (TEM) and Auger Electron Spectroscopy (AES). In addition, a unique in-situ combination of TEM and Secondary Ion Mass Spectrometry (SIMS) imaging techniques, namely Parallel Ion and Electron beam Spectrometry (PIES) is carried out to measure the 3D distribution of V and Li with nanoscale resolution. These characterization studies focus on correlating the pre- and post-cycling microstructure to observed electrochemical performance. The LiV 3 O 8 cathode film with needle-like nanocrystals (300 °C) shows a higher initial capacity but it degrades rapidly compared to the film with globular nanocrystals embedded in amorphous matrix (150 °C). We observed that LiV 3 O 8 films with needle-like nanocrystals are more susceptible to cathode decohesion and vanadium dissolution than the films with globular nanocrystals embedded in amorphous matrix, explaining the differences in their electrochemical performance. The findings from this study have relevance to the development of thin film electrode microstructures for high capacity and cyclic stability.

25 ENERGY STORAGE↗
DOE OSTI2022

Prediction of grain structure after thermomechanical processing of U-10Mo alloy using sensitivity analysis and machine learning surrogate model

Abstract Hot rolling and annealing are critical intermediate steps for controlling microstructures and thickness variations when fabricating uranium alloyed with 10% molybdenum (U-10Mo), which is highly relevant to worldwide nuclear non-proliferation efforts. This work proposes a machine-learning surrogate model combined with sensitivity analysis to identify and predict U-10Mo microstructure development during thermomechanical processing. Over 200 simulations were collected using physics-based microstructure models covering a wide range of thermomechanical processing routes and initial alloy grain features. Based on the sensitivity analysis, we determined that an increase in rolling reduction percentage at each processing pass has the strongest effect in reducing the grain size. Multi-pass rolling and annealing can significantly improve recrystallization regardless of the reduction percentage. With a volume fraction below 2%, uranium carbide particles were found to have marginal effects on the average grain size and distribution. The proposed stratified stacking ensemble surrogate predicts the U-10Mo grain size with a mean square error four times smaller than a standard single deep neural network. At the same time, with a significant speedup (1000×) compared to the physics-based model, the machine learning surrogate shows good potential for U-10Mo fabrication process optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss

Advanced manufacturing research and development is typically small-scale, owing to costly experiments associated with these novel processes. Deep learning techniques could help accelerate this development cycle but frequently struggle in small-data regimes like the advanced manufacturing space. While prior work has applied deep learning to modeling visually plausible advanced manufacturing microstructures, little work has been done on data-driven modeling of how microstructures are affected by heat treatment, or assessing the degree to which synthetic microstructures are able to support existing workflows. We propose to address this gap by using invertible neural networks (normalizing flows) to model the effects of heat treatment, e.g., tempering. The model is developed using scanning electron microscope imagery from samples produced using shear-assisted processing and extrusion (ShAPE) manufacturing. This approach not only produces visually and topologically plausible samples, but also captures information related to a sample’s material properties or experimental process parameters. We also demonstrate that topological data analysis, used in prior work to characterize microstructures, can also be used to stabilize model training, preserve structure, and improve downstream results. We assess directions for future work and identify our approach as an important step towards end-to-end deep learning system for accelerating advanced manufacturing research and development.

Howland, Sylvia↗
DOE OSTI2024

A Gaussian process autoregressive model capturing microstructure evolution paths in a Ni–Mo–Nb alloy

Additive manufacturing is increasingly being employed to produce components of complex geometries in structural alloys because of the expected energy savings associated with the near-net-shape capability and the ability to build in novel internal features that are not possible with many conventional manufacturing approaches. However, because of the extreme thermal conditions encountered, the non-equilibrium microstructures produced during powder bed-based additive manufacturing processes must be subjected to custom post-heat treatment processes to recover the target mechanical properties. Phase-field models and simulation techniques have matured to a state where the microstructure evolution paths, and the morphologies of the resulting precipitate phases can be predicted reasonably accurately, considering alloy-specific thermodynamic and kinetic aspects of the nucleation and growth processes. However, phase-field simulations are computationally intensive, which precludes the ability to apply the simulations directly to the length scale of the entire component. Therefore, it is highly desirable to develop low-computational-cost surrogate models that effectively capture the physics at the microstructural length scale, while facilitating the design of optimized processing conditions resulting in location-specific targeted microstructures at the component scale. The work presented here demonstrates the application of the materials knowledge system framework to develop a surrogate model that effectively captures the microstructural path during annealing of a Ni–Mo–Nb alloy containing different Mo and Nb compositions known to segregate during solidification under additive manufacturing conditions. Specifically, the surrogate model built in this work is based on a Gaussian process autoregressive model informed by statistical representation of simulated microstructures using two-point correlations and dimensionality reduction through principal component analysis. In conclusion, this surrogate model is shown to capture the bifurcation of the microstructural path during precipitation, which yields a microstructure dominated by the $\gamma^{\prime\prime}$ phase at high Nb concentrations and the $\delta$ phase at low Nb concentrations.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Nondestructive ultrasonic characterization of a triple-weld-bead wire arc additively manufactured ER70S-6 S-curved wall

Understanding build-scale microstructural variation in wire arc additive manufacturing (WAAM) of low-carbon steels is essential for ensuring consistent structure–property relationships throughout large components. Conventional destructive characterization techniques, such as scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD), are time-intensive and limited to localized regions, making comprehensive evaluation of large WAAM structures challenging. In this study, a nondestructive ultrasonic approach was employed to characterize a 252 mm tall ER70S-6 S-curved WAAM wall produced using a triple-bead deposition strategy. Optical and SEM analysis revealed a repeating dual-region microstructure consisting of uniform polygonal ferrite at melt pool centers and heterogeneous ferrite with coarse and fine grains near melt pool boundaries, attributed to cyclic thermal conditions. Longitudinal ultrasonic backscatter imaging was used to evaluate the continuity of this periodicity along the full build height. The ultrasonic response exhibited a consistent repeating pattern that correlated with the observed layer-wise microstructural variation. X-ray computed tomography confirmed the absence of detectable porosity, indicating that ultrasonic contrast is primarily governed by grain morphology. Overall, the results indicate that longitudinal backscatter ultrasound is a promising nondestructive characterization technique for validating microstructural variations along the s-curved WAAM wall, with significant potential for microstructure optimization and process control.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiscale investigation of thermomechanical and compositional developments in Ni alloy 718 under laser processing

Laser processing has been widely employed in various applications due to its exceptional spatial resolution. However, the rapid temperature gradients generated in localized areas present significant challenges for experimental characterization using conventional instruments. To characterize Ni alloy 718 during laser processing, we employed in-situ synchrotron X-ray diffraction with a high-speed detector, a method particularly well-suited for probing processes with high temporal and spatial resolution. Through a series of in-situ experiments, we investigated the local variations in the evolution of microstructures and thermomechanical behaviors within a keyhole mode melt pool. The in situ macroscopic thermomechanical behaviors were quantified using an empirical model derived from diffraction patterns, with experimental results showing reasonable agreement with finite element analysis. Various laser parameters were tested to assess their influences on the residual strains in the melt pools. The results revealed that the residual strain in the keyhole mode melt pool is relatively insensitive to variations in the parameters and is smaller than that in the melt pool created under conduction mode laser scanning. Additionally, we analyzed the shapes of individual diffraction spots, providing insights into the plastic behaviors and compositional developments in the resolidified alloy. The analysis confirmed that compositional variations in a dendritic microstructure manifest as asymmetric broadening of the diffraction spots.

Ni alloy 718↗
DOE OSTI2023

Iridescence from Total Internal Reflection at 3D Microscale Interfaces: Mechanistic Insights and Spectral Analysis

An experimental investigation and the optical modeling of the structural coloration produced from total internal reflection interference within 3D microstructures are described. Ray-tracing simulations coupled with color visualization and spectral analysis techniques are used to model, examine, and rationalize the iridescence generated for a range of microgeometries, including hemicylinders and truncated hemispheres, under varying illumination conditions. An approach to deconstruct the observed iridescence and complex far-field spectral features into its elementary components and systematically link them to ray trajectories that emanate from the illuminated microstructures is demonstrated. The results are compared with experiments, wherein microstructures are fabricated with methods such as chemical etching, multiphoton lithography, and grayscale lithography. Microstructure arrays patterned on surfaces with varying orientation and size lead to unique color-traveling optical effects and highlight opportunities for how total internal reflection interference can be used to create customizable reflective iridescence. The findings herein provide a robust conceptual framework for rationalizing this multibounce interference mechanism and establish approaches for characterizing and tailoring the optical and iridescent properties of microstructured surfaces.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Microstructure Of A SIC/(Ti/V/Cr/Sn/Al) Composite

NASA technical memorandum reports on analysis of composite material made of SiC fibers in matrix of 0.76 Ti/0.15 V/0.03 Cr/0.03 Sn/0.03 Al (parts by weight) alloy. Purposes of study to investigate suitability of some metallographic techniques for use on composite materials in general and to obtain information about macrostructure and microstructure of this specific composite to provide guidance for experimental and theoretical studies of more advanced composites.

Lerch, Bradley A.↗
DOE OSTI2023

Microstructure Evolution of a Multimodal Gamma-Prime Ni-Based Superalloy Characterized by In Situ Diffraction

The relationship between the evolution of microstructure, deformation micromechanisms and mechanical properties is difficult to establish in multimodal size distribution $_γ$$'$ superalloys, as the microstructure evolves with both temperature and time, and multiple strengthening mechanisms across each size distribution contribute to mechanical performance. In situ X-ray scattering can offer unparalleled insight regarding microstructure evolution at the temperatures and stresses of importance to gas-turbine applications; however, in situ X-ray diffraction has not been applied to the study of multimodal $_γ$$'$ distribution superalloys. Herein, lattice parameter evolution of secondary and tertiary $_γ$$'$ precipitates in a representative superalloy, Nimonic 115, is determined between 750 °C and 950 °C and correlated to room-temperature SEM and microhardness values. A large positive lattice parameter misfit of secondary $_γ$$'$ induces precipitate splitting, and the tertiary $_γ$$'$ goes into dissolution at ~ 800 °C, but with little apparent change in hardness values. The volume fraction of $_γ$$'$ decreases above 900 °C and precipitate-matrix coherency is lost, and there is a corresponding decrease in microhardness values. Importantly, the diffraction analysis demonstrates the capability to determine critical microstructural parameters of both precipitate size distributions in situ, representing an additional tool for determining microstructure-mechanical property relationships of multimodal superalloys.

36 MATERIALS SCIENCE↗