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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 397 records · Page 22

Revealing the evolution of order in materials microstructures using multi-modal computer vision

The development of high-performance materials for microelectronics, energy storage, and extreme environments depends on our ability to describe and direct property-defining microstructural order. Our present understanding is typically derived from laborious manual analysis of imaging and spectroscopy data, which is difficult to scale, challenging to reproduce, and lacks the ability to reveal latent associations needed for mechanistic models. Here, we demonstrate a multi-modal machine learning (ML) approach to describe order from electron microscopy analysis of the complex oxide La 1−x Sr x FeO 3 . We construct a hybrid pipeline based on fully and semi-supervised classification, allowing us to evaluate both the characteristics of each data modality and the value each modality adds to the ensemble. We observe distinct differences in the performance of uni- and multi-modal models, from which we draw general lessons in describing crystal order using computer vision.

36 MATERIALS SCIENCE↗

Thermal spray processing

Thermal spray processing has been used for a number of years to cost-effecticely apply TBC's for a wide range of heat engine applications. In particular, bond coats are applied by plasma spray and HVOF techniques and partially-stabilized zirconia top coats are applied by plasma spray methods. Thermal spray involves melting and rapid transport of the molten particles to the substrate, where high-rate solidification and coating build-up occur. It is the very nature of this melt processing that leads to the unique layered microstructure, as well as the apparent imperfections, so readily identified with thermal spray. Modeling the process, process-induced residual stresses, and thermal conductivity will be discussed in light of a new understanding of porosity and its anisotropy. Microcracking can be understood using new approaches, allowing a fuller view of the processing-performance connection. Detailed electron microscopic, novel neutron diffraction and fracture analysis of the deposits can lead to a better understanding of how overall microstructure can be controlled to influence critical properties of the deposited TBC system.

Herman, H.↗

Theoretical analysis of Wolter/LSM X-ray telescope systems

A ray tracing analysis has been performed for the spectral slicing zoom X-ray telescope for configurations in which a convex layered synthetic microstructure (LSM) optic is placed in front of the prime focus or a concave LSM optic is placed behind the prime focus. The analysis has considered the geometrical shape of the LSM optic to be either a hyperboloid, sphere, ellipsoid or constant optical path aspheric element for two configurations of the glancing incidence X-ray telescope: the ATM Experimental S-056 Wolter I system and the Stanford/MSFC Wolter-Schwarzchild nested system. For the different systems the RMS blur circle radii, the point spread function (PSF), the full width half maximum (FWHM) of the PSF have been evaluated as a function of field angle and magnification of the secondary to determine resolution of the system. The effects of decentration and tilt of the selected LSM element on the performance of the system have been studied to determine mounting and alignment tolerances.

Shealy, D. L.↗

Creep Behavior of Friction Stir Processed Haynes 282

Haynes 282 is a nickel-based superalloy designed for use in hot sections of turbines for aircraft and power generation. In these applications, elevated temperature creep performance is critical. To that end, creep behavior of friction stir processed material was carried out to investigate the high-temperature performance of this alloy. Friction stir processing of Haynes 282 was successfully completed, and the processed region was found to be defect-free. Various mechanical property characterization approaches were carried out in post-heat treated condition. Transverse tensile samples repeatedly failed in the base metal indicating 100% joint efficiency. Creep property evaluation was completed at 760 °C and at various stress levels. The creep-rupture lifetime of the processed material was similar to the base metal. Detailed electron microscopy analysis of the failed sample was carried out to understand the microstructural evolution in various locations of the sample during creep.

creep↗

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗

Understanding interfacial crystallization dynamics on carbon fiber reinforced polypropylene composite manufacturing

Reinforcing polymers with discontinuous fibers improves mechanical properties, such as strength and stiffness, and in some cases achieve isotropic properties, rendering them suitable for various engineering applications. Matrix materials are generally highly engineered thermosets (e.g. crosslinked epoxies), bonded to the fiber periphery by proprietary surface and sizing chemistries. Semicrystalline thermoplastic matrices are less utilized due to poor fiber-matrix bonding resulting in inefficient interfacial load-transfer in reinforced composites. However, flexibility with melt-processing or molding conditions can be leveraged to promote non-covalent interfacial bonding between matrix and fiber via crystallization of the matrix onto fiber surface. In the present study, we utilize a co-mingle chopped carbon and isotactic polypropylene fibers to form isotropic composites, tailoring interfacial immobilized matrix or interphase morphology to optimize performance through precise control of thermal processing/molding windows. Calorimetry and optical microscopy were employed to investigate the impact of carbon fiber at various volume fractions (10, 20, and 30 %) on isotactic polypropylene crystallization and mechanical performance. Variations in mechanical properties correspond to the structural evolution of the interfacial region and are correlated to underlying microstructural attributes using wide-angle X-ray scattering, thermal analysis, and low-field nuclear magnetic resonance spectroscopy. These results provide a practical framework for the manufacturing of thermoplastic matrix composites. In conclusion, the results presented provide a guide for the strategic optimization of interphase design, showcasing tailorable tensile strengths which outperform any isotactic polypropylene carbon fiber composites previously reported in literature.

36 MATERIALS SCIENCE↗

Review of SiC material development for nuclear fusion applications: Cross-cutting research and emerging opportunities

The SiC-based materials, particularly SiC-fiber-reinforced SiC matrix (SiC/SiC) composites, show strong potential for structural and functional applications in future fusion power plants because they can operate at high temperatures with a range of coolants and breeders, thereby enabling higher energy conversion efficiency. Here, this paper presents recent advancements in the development of SiC-based materials, focusing on processing techniques and material performance and resistance under fusion-relevant environments. The processing activities have emphasized near-net-shape fabrication and the joining of SiC subcomponents, with processing methods and material compositions informed by previous irradiation experiments on various grades of SiC. Research on irradiation effects has remained focused on degradation mechanisms and the microstructural optimization of SiC/SiC composites irradiated to high neutron damage levels. Analysis of irradiation defects in SiC has advanced via the application of cutting-edge characterization methods, among which Raman spectroscopy is becoming a common tool to assess atomic-scale chemical disorder. Fusion–fission crosscutting irradiation research has explored combined effects in SiC/SiC composites with application-relevant geometries, including bowing of SiC/SiC composite channels under neutron flux gradients, stress evolution in SiC/SiC composite tubes under through-thickness temperature gradients, and irradiation-enhanced corrosion in SiC. Finally, research opportunities for component testing and assessment under fusion-relevant conditions, in support of emerging concepts from the private fusion sector, are discussed.

Advanced manufacturing↗

PyCMG-based Simulation of Volumetric Concrete Microstructure

Concrete is a complex, heterogeneous material with a microstructure composed of aggregates, cement paste, and pores spanning multiple length scales. Understanding this microstructure is critical for advancing the performance, durability, and modeling of concrete-based systems. While experimental imaging such as X-ray computed tomography (XCT) provides valuable insights, generating large datasets with detailed ground truth annotations is both costly and labor-intensive due to challenges in segmenting similar phases, such as aggregates and cement paste, that often share similar attenuation properties. To address this, we developed a pipeline to simulate realistic 3D concrete microstructures using the open-source Python package PyCMG. This simulation effort focuses on generating high-fidelity, annotated microstructures that can serve as training or benchmarking datasets for image analysis, segmentation algorithms, and machine learning models, particularly in scenarios where experimental data is scarce.

Ziabari, Amir [Oak Ridge National Laboratory; ORNL↗

An e.s.c.a. study of atomic oxygen interactions with phosphazene-coated polyimide films

Metallic as well as most nonmetallic materials experience oxidation and mass loss via surface erosion in low earth orbit as shown in previous Space Shuttle flights. This study is an evaluation of select polyphosphazene polymers and their resistance to atomic oxygen attack. Electron spectroscopy for chemical analysis examinations of the surfaces of polyphosphazene coatings were monitored for microstructural changes induced during exposures to atomic oxygen. Sample exposures in oxygen plasmas and O(3P) beam were compared as to their effect on surface compositional changes in the polyphosphazene coating. High resolution line scans revealed rearrangements in the polymer backbone and scissioning reactions involving fluorocarbon units of long chain fluoroalkoxy pendant groups. Atom percents and peak areas of all species provided a detailed profile of the microstructural changes induced in phosphazene polymers as a result of exposures to atomic oxygen.

Fewell, Larry L.↗

Proceedings of the Second Annual Symposium for Nondestructive Evaluation of Bond Strength

Ultrasonics, microwaves, optically stimulated electron emission (OSEE), and computational chemistry approaches have shown relevance to bond strength determination. Nonlinear ultrasonic nondestructive evaluation methods, however, have shown the most effectiveness over other methods on adhesive bond analysis. Correlation to changes in higher order material properties due to microstructural changes using nonlinear ultrasonics has been shown related to bond strength. Nonlinear ultrasonic energy is an order of magnitude more sensitive than linear ultrasound to these material parameter changes and to acoustic velocity changes caused by the acoustoelastic effect when a bond is prestressed. Signal correlations between non-linear ultrasonic measurements and initialization of bond failures have been measured. This paper reviews bond strength research efforts presented by university and industry experts at the Second Annual Symposium for Nondestructive Evaluation of Bond Strength organized by the NDE Sciences Branch at NASA Langley in November 1998.

Roberts, Mark J.↗

Application of Nonstandard Analysis to the Study of the Shock Structure in a Viscous Heat Conducting Fluid

The study of the shock structure in a viscous heat conducting fluid is an old problem. We study this problem from a novel mathematical point of view. A new class of generalized functions is defined where multiplication of any two functions is allowed with the usual properties. A Heaviside function in this class has the unit jump at occurring on an infinitesimal interval of the nonstandard analysis (NSA) in the halo of . This jump has a smooth microstructure over the infinitesimal interval . From this point of view, we have a new class of Heaviside functions, and their derivatives the Dirac delta functions, which are equivalent when viewed as continuous linear functionals over the test function space of Schwartz. However, they differ in their microstructures which in applications are determined from physics of the problem as shown in our presentation.

F. Farassat↗

Effect of a growth hormone treatment on bone orthotropic elasticity in dwarf rats

A refinement of the current ultrasonic elasticity technique was used to measure the orthotropic elastic properties of rat cortical bone as well as to quantify changes in elastic properties, density, and porosity of the dwarf rat cortex after a treatment with recombinant human growth hormone (rhGH). The ultrasonic elasticity technique was refined via optimized signal management of high-frequency wave propagation through cubic cortical specimens. Twenty dwarf rats (37 days old) were randomly assigned to two groups (10 rats each). The dwarf rat model (5-10% of normal GH) was given subcutaneous injections of either rhGH or saline over a 14-day treatment period. Density was measured using Archimedes technique. Porosity and other microstructural characteristics were also explored via scanning electron microscopy and image analysis. Statistical tests verified significant decreases in cortical orthotropic Young's (-26.7%) and shear (-16.7%) moduli and density (-2.42%) concomitant with an increase in porosity (+125%) after rhGH treatments to the dwarf model (p < 0.05). A change in material symmetry from orthotropy toward planar isotropy within the radial-circumferential plane after GH treatments was also noted. These results demonstrate some alteration in bone properties at this time interval. Structural implications of these changes throughout physiological loading regimens should be explored.

NASA Discipline Musculoskeletal↗

Additive Manufacturing and Characterization of Polylactic Acid (PLA) Composites Containing Metal Reinforcements

Additive manufacturing of polymeric systems using 3D printing has become quite popular recently due to rapid growth and availability of low cost and open source 3D printers. Two widely used 3D printing filaments are based on polylactic acid (PLA) and acrylonitrile butadiene styrene (ABS) systems. PLA is much more environmentally friendly in comparison to ABS since it is made from renewable resources such as corn, sugarcane, and other starches as precursors. Recently, polylactic acid-based metal powder containing composite filaments have emerged which could be utilized for multifunctional applications. The composite filaments have higher density than pure PLA, and the majority of the materials volume is made up of polylactic acid. In order to utilize functionalities of composite filaments, printing behavior and properties of 3-D printed composites need to be characterized and compared with the pure PLA materials. In this study, pure PLA and composite specimens with different metallic reinforcements (Copper, Bronze, Tungsten, Iron, etc) were 3D printed at various layer heights and resulting microstructures and properties were characterized. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) behavior of filaments with different reinforcements were studied. The microscopy results show an increase in porosity between 3-D printed regular PLA and the metal composite PLA samples, which could produce weaker mechanical properties in the metal composite materials. Tensile strength and fracture toughness behavior of specimens as a function of print layer height will be presented.

brass↗

Metallurgical characterization of the fracture of several high strength aluminum alloys

The fracture behavior for structural aluminum alloys (2024, 6061, 7075, and 7178) was examined in selected heat treatments. The investigation included tensile, shear, and precracked notch-bend specimens fractured at ambient temperature under monotonic loading. Specimens were obtained from thin sheets and thick plates and were tested in longitudinal and transverse orientations at different strain rates. Microstructures of alloys were examined using the optical microscope and the scanning electron microscope with associated energy dispersive X ray chemical analysis. Several different types of second phase particles, some not reported by other investigators, were identified in the alloys. Fracture morphology was related to microstructural variables, test variables, and type of commercial product. Specimen orientation examined in the present investigation had little effect on fracture morphology. Test strain rate changes resulted in some change in shear fracture morphology, but not in fracture morphology of tensile specimens.

Bhandarkar, M. D.↗

An Efficient Implementation of the GMC Micromechanics Model for Multi-Phased Materials with Complex Microstructures

An efficient implementation of the generalized method of cells micromechanics model is presented that allows analysis of periodic unidirectional composites characterized by repeating unit cells containing thousands of subcells. The original formulation, given in terms of Hill's strain concentration matrices that relate average subcell strains to the macroscopic strains, is reformulated in terms of the interfacial subcell tractions as the basic unknowns. This is accomplished by expressing the displacement continuity equations in terms of the stresses and then imposing the traction continuity conditions directly. The result is a mixed formulation wherein the unknown interfacial subcell traction components are related to the macroscopic strain components. Because the stress field throughout the repeating unit cell is piece-wise uniform, the imposition of traction continuity conditions directly in the displacement continuity equations, expressed in terms of stresses, substantially reduces the number of unknown subcell traction (and stress) components, and thus the size of the system of equations that must be solved. Further reduction in the size of the system of continuity equations is obtained by separating the normal and shear traction equations in those instances where the individual subcells are, at most, orthotropic. The reformulated version facilitates detailed analysis of the impact of the fiber cross-section geometry and arrangement on the response of multi-phased unidirectional composites with and without evolving damage. Comparison of execution times obtained with the original and reformulated versions of the generalized method of cells demonstrates the new version's efficiency.

Pindera, Marek-Jerzy↗

Analysis of Polder Polarization Measurements During Astex and Eucrex Experiments

Polarization is more sensitive than intensity to cloud microstructure such as the particle size and shape, and multiple scattering does not wash out features in polarization as effectively as it does in the intensity. Polarization measurements, particularly in the near IR, are potentially a valuable tool for cloud identification and for studies of the microphysics of clouds. The POLDER instrument is designed to provide wide field of view bidirectional images in polarized light. During the ASTEX-SOFIA campaign on June 12th, 1992, over the Atlantic Ocean (near the Azores Islands), images of homogeneous thick stratocumulus cloud fields were acquired. During the EUCREX'94 (April, 1994) campaign, the POLDER instrument was flying over the region of Brittany (France), taking observations of cirrus clouds. This study involves model studies and data analysis of POLDER observations. Both models and data analysis show that POLDER can be used to detect cloud thermodynamic phases. Model results show that polarized reflection in the Lamda =0.86 micron band is sensitive to cloud droplet sizes but not to cloud optical thickness. Comparison between model and data analysis reveals that cloud droplet sizes during ASTEX are about 5 microns, which agrees very well with the results of in situ measurements (4-5 microns). Knowing the retrieved cloud droplet sizes, the total reflected intensity of the POLDER measurements then can be used to retrieve cloud optical thickness. The close agreement between data analysis and model results during ASTEX also suggests the homogeneity of the cloud layer during that campaign.

Chen, Hui↗

Surface chemistry, microstructure and friction properties of some ferrous-base metallic glasses at temperatures to 750 C

X-ray photoelectron spectroscopy analysis, transmission electron microscopy, diffraction studies, and sliding friction experiments were conducted with ferrous-base metallic glasses in sliding contact with aluminum oxide at temperatures from room to 750 C in a vacuum of 30 nPa. The results indicate that there is a significant temperature influence on the friction properties, surface chemistry, and microstructure of metallic glasses. The relative concentrations of the various constituents at the surface of the sputtered specimens were very different from the normal bulk compositions. Contaminants can come from the bulk of the material to the surface upon heating and impart boric oxide and silicon oxide at 350 C and boron nitride above 500 C. The coefficient of friction increased with increasing temperature to 350 C. Above 500 C the coefficient of friction decreased rapidly. The segregation of contaminants may be responsible for the friction behavior.

Miyoshi, K.↗

A comparative analysis of YOLOv8 and U-Net image segmentation approaches for transmission electron micrographs of polycrystalline thin films

Metallic thin films offer a platform to experimentally study the dynamics of microstructural evolution, but the required transmission electron microscopy (TEM)-based imaging generates complex images that are challenging to segment and quantify. This work provides a comparative analysis of a new YOLOv8 model and an established U-Net model for bright-field TEM images of polycrystals, employing a framework leveraging physical observables to evaluate performance against two hand-traced benchmark datasets. This methodology obviates the comparison of large, diversely structured, and manually labeled datasets that are required to assess performance on a per-image/per-pixel basis. It is found that the YOLOv8 model, adapted for real-time instance segmentation, has up to 43× faster inferencing (NVIDIA GeForce RTX 4090) compared to U-Net and reconstructs hand-traced grain size distributions (GSDs) with excellent fidelity, finding mean diameter within 3% for grains near an optimal magnification; for grains that deviate from the optimal pixel-diameter, the size of small- (large)-diameter grains is systematically over- (under)-estimated. This is partially mitigated by including scale-aware augmentations during training. Moreover, when the bias is corrected post-inference by a rigid shift in distribution, the YOLOv8 model reproduces ground truth GSDs with exceptional fidelity, with statistical tests indicating <5% probability that the distributions are distinct. Based on ground truth data, calibration curves pertaining to this shift can be constructed for a given model. This issue is not present in the U-Net model’s results, indicating that for quantitative measurements where the true size of objects is of interest, special procedures must be implemented for YOLO-based models.

36 MATERIALS SCIENCE↗