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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

X-ray vector radiography imaging for biomedical applications

The non-invasive estimation of fracture risk in osteoporosis remains a challenge in the clinical routine and is mainly based on an assessment of bone density by dual X-ray absorption (DXA) although bone micro-architecture is known to play an important role for bone fragility. Here we report on 'X-ray vector Radiography' measurements able to provide a direct bone microstructure diagnostics on human bone samples, which we compare qualitatively and quantitatively with numerical analysis of high resolution radiographs.

60 APPLIED LIFE SCIENCES↗
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 OSTI2018

Microstructure and Performance of Nano-WC Particle-Strengthened Ni Coatings by Electro-brush Plating

Nano-WC particle-strengthened Ni composite coatings were prepared by electro-brush plating. A series of artificial neural network models was developed for the analysis and prediction of the coating performance. The microstructure and phase structure were studied with SEM, XRD and EDS. Nano-WC particles as the hard phase were distributed evenly and dispersed in the coatings, which was conducive to the hardness enhancement of the coatings. Additionally, nano-WC particles as microballs inserted in the coatings could reduce the friction when wear of the coating surface occurred. Furthermore, the addition of nano-WC particles delayed the time of crack initiation and propagation in the coatings, which increased the service lifetime when they worked in a thermal shock environment.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
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 OSTI2018

Effects of Copper Content and Mold Temperature on the Hot Tearing Susceptibility of Mg-7Zn-xCu-0.6Zr Alloys

The effects of copper (Cu) content and mold temperature on the hot tearing susceptibility (HTS) of Mg-7Zn-xCu-0.6Zr (x = 0, 1, 2) alloys were investigated experimentally using a T-type hot tearing mold. The crack volumes were measured by paraffin permeation method, and the solidification process was analyzed by thermal analysis and by using the Clyne and Davies model. The microstructure and morphology of the crack zone of Mg-7Zn-xCu-0.6Zr alloys were characterized by scanning electron microscopy, and the composition of alloys was analyzed by X-ray diffraction. The results showed the formation of a new phase of MgZnCu in the alloys with Cu addition. Moreover, addition of Cu also led to the refinement of microstructures of Mg-7Zn-xCu-0.6Zr alloys. The HTS of Mg-7Zn-xCu-0.6Zr alloys decreased with the increase in both the content of Cu and the mold temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Data-driven reduced-order models for rank-ordering the high cycle fatigue performance of polycrystalline microstructures

Computationally efficient estimation of the fatigue response of polycrystalline materials is critical for the development of next generation materials in application domains such as transportation, health, security, and energy industries. This is non-trivial for fatigue of polycrystalline metals since the initiation and growth of fatigue cracks depends strongly on attributes of the microstructure, such as the sizes, shapes, orientations, and neighbors of individual grains. Furthermore, regions of microstructure most likely to initiate cracks correspond to the tails of the distributions of the microstructure features. This requires the execution of large numbers of experiments or simulations to capture the response of the material in a statistically meaningful manner. In this work, a linkage is described to connect polycrystalline microstructures to the statistically signified driving forces controlling the high cycle fatigue (HCF) responses. This is achieved through protocols that quantify these microstructures using 2-pt spatial correlations and represent them in a reduced-dimensional space using principal component analysis. Reduced-order relationships are then constructed to link microstructures to performance characteristics related to their HCF responses. As a result, these protocols are demonstrated for α-titanium, which exhibits heterogeneous microstructure features along with significant elastic and inelastic anisotropies at both the microscale and the macroscale.

2-point correlations↗
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 OSTI2015

Fire performance, microstructure and thermal degradation of an epoxy based nano intumescent fire retardant coating for structural applications

Intumescent fire retardant coating (IFRC) is a passive fire protection system which swells upon heating to form expanded multi-cellular char layer that protects the substrate from fire. In this research work, IFRC’s were developed using different flame retardants such as ammonium polyphosphate, expandable graphite, melamine and boric acid. These flame retardants were bound together with the help of epoxy binder and cured together using curing agent. IFRC was then reinforced with nano magnesium oxide and nano alumina as inorganic fillers to study their effect towards fire performance, microstructure and thermal degradation. Small scale fire test was conducted to investigate the thermal insulation of coating whereas fire performance was calculated using thermal margin value. Field emission scanning electron microscopy was used to examine the microstructure of char obtained after fire test. Thermogravimetric analysis was conducted to investigate the residual weight of coating. Results showed that the performance of the coating was enhanced by reinforcement with nano size fillers as compared to non-filler based coating. Comparing both nano size magnesium oxide and nano size alumina; nano size alumina gave better fire performance with improved microstructure of char and high residual weight.

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 OSTI2015

Benefits of utilizing CellProfiler as a characterization tool for U–10Mo nuclear fuel

Automated image processing techniques have the potential to aid in the performance evaluation of nuclear fuels by eliminating judgment calls that may vary from person-to-person or sample-to-sample. Analysis of in-core fuel performance is required for design and safety evaluations related to almost every aspect of the nuclear fuel cycle. This study presents a methodology for assessing the quality of uranium–molybdenum fuel images and describes image analysis routines designed for the characterization of several important microstructural properties. The analyses are performed in CellProfiler, an open-source program designed to enable biologists without training in computer vision or programming to automatically extract cellular measurements from large image sets. The quality metric scores an image based on three parameters: the illumination gradient across the image, the overall focus of the image, and the fraction of the image that contains scratches. The metric presents the user with the ability to ‘pass’ or ‘fail’ an image based on a reproducible quality score. Passable images may then be characterized through a separate CellProfiler pipeline, which enlists a variety of common image analysis techniques. The results demonstrate the ability to reliably pass or fail images based on the illumination, focus, and scratch fraction of the image, followed by automatic extraction of morphological data with respect to fission gas voids, interaction layers, and grain boundaries. - Graphical abstract: Display Omitted - Highlights: • A technique is developed to score U–10Mo FIB-SEM image quality using CellProfiler. • The pass/fail metric is based on image illumination, focus, and area scratched. • Automated image analysis is performed in pipeline fashion to characterize images. • Fission gas void, interaction layer, and grain boundary coverage data is extracted. • Preliminary characterization results demonstrate consistency of the algorithm.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Dynamic microstructural evolution of an Al–Zn–Mg–Cu alloy (7075) during continuous heating and the influence on the viscoelastic response

Highlights: • A TEM/HRTEM, FIB-SEM and APT analysis of an Al–Zn–Mg–(Cu) alloy is performed. • Microstructural evolution is analyzed during constant heating rate heat-treatment. • Composition, size, number density and vol. fraction of present phases are reported. • Vol. fraction and kinetic data from rate equations in the literature are validated. • Viscoelastic behavior of the alloy is associated to microstructural transformations. - Abstract: The microstructural evolution of an Al–Zn–Mg–Cu alloy under continuous heating over the temperature range of 298 to 648 K (25 to 375 °C) is characterized by focused ion beam-scanning electron microscopy, transmission electron microscopy, and atom probe tomography. The chemical composition, dimensions, number density, and volume fraction of precipitates are measured comprehensively. Quantitative measurements of Guinier-Preston zones volume fraction and η′/η phase volume fraction are correlated to the viscoelastic response of the Al–Zn–Mg–Cu alloy with temperature in the studied range. This provides valuable evidence indicating that observed variations in the viscoelastic behavior of the Al–Zn–Mg–Cu alloy may be associated with phase transformations involving Guinier-Preston zones and phases η′ and η.

36 MATERIALS SCIENCE↗