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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 307 records · Page 17

Development and fabrication of high strength alloy fibers for use in metal-metal matrix composites

Metal fiber reinforced superalloys are being considered for construction of critical components in turbine engines that operate at high temperature. The problems involved in fabricating refractory metal alloys into wire form in such a manner as to maximize their strength properties without developing excessive structural defects are described. The fundamental principles underlying the development of such alloy fibers are also briefly discussed. The progress made to date in developing tungsten, tantalum and columbium base alloys for fiber reinforcement is reported and future prospects for alloy fiber development considered.

King, G. W.↗

Robotic and automatic welding development at the Marshall Space Flight Center

Welding automation is the key to two major development programs to improve quality and reduce the cost of manufacturing space hardware currently undertaken by the Materials and Processes Laboratory of the NASA Marshall Space Flight Center. Variable polarity plasma arc welding has demonstrated its effectiveness on class 1 aluminum welding in external tank production. More than three miles of welds were completed without an internal defect. Much of this success can be credited to automation developments which stabilize the process. Robotic manipulation technology is under development for automation of welds on the Space Shuttle's main engines utilizing pathfinder systems in development of tooling and sensors for the production applications. The overall approach to welding automation development undertaken is outlined. Advanced sensors and control systems methodologies are described that combine to make aerospace quality welds with a minimum of dependence on operator skill.

Jones, C. S.↗

Capability of Thermographic Imaging Defined for Detection in High-Temperature Composite Materials

Significant effort and resources are being expended to develop ceramic matrix (CMC), metal matrix (MMC), and polymer matrix (PMC) composites for high-temperature engine components and other parts in advanced aircraft. The objective of this NASA Lewis Research Center study was to evaluate the ability of a thermographic imaging technique for detecting artificially created defects (flat-bottom holes) of various diameters and depths in four composite systems (two CMC's, one MMC, and one PMC) of interest as high-temperature structural materials.

Roth, Don J.↗

Health Monitoring of a Rotating Disk Using a Combined Analytical-Experimental Approach

Rotating disks undergo rigorous mechanical loading conditions that make them subject to a variety of failure mechanisms leading to structural deformities and cracking. During operation, periodic loading fluctuations and other related factors cause fractures and hidden internal cracks that can only be detected via noninvasive types of health monitoring and/or nondestructive evaluation. These evaluations go further to inspect material discontinuities and other irregularities that have grown to become critical defects that can lead to failure. Hence, the objectives of this work is to conduct a collective analytical and experimental study to present a well-rounded structural assessment of a rotating disk by means of a health monitoring approach and to appraise the capabilities of an in-house rotor spin system. The analyses utilized the finite element method to analyze the disk with and without an induced crack at different loading levels, such as rotational speeds starting at 3000 up to 10 000 rpm. A parallel experiment was conducted to spin the disk at the desired speeds in an attempt to correlate the experimental findings with the analytical results. The testing involved conducting spin experiments which, covered the rotor in both damaged and undamaged (i.e., notched and unnotched) states. Damaged disks had artificially induced through-thickness flaws represented in the web region ranging from 2.54 to 5.08 cm (1 to 2 in.) in length. This study aims to identify defects that are greater than 1.27 cm (0.5 in.), applying available means of structural health monitoring and nondestructive evaluation, and documenting failure mechanisms experienced by the rotor system under typical turbine engine operating conditions.

Abdul-Aziz, Ali↗

Smart Process Planning for Automated Fiber Placement

Many industries, including aerospace, automotive, wind energy, maritime, and sporting goods, rely on strong, lightweight materials called composites. These materials are made by layering fibers, which can come in the form of narrow strips or wider sheets, and setting them in a polymer matrix. One of the most advanced ways to make these parts is through automated fiber placement, where a machine lays down the fibers in precise patterns. This method can create very efficient and strong designs, but it is complex, expensive, and often depends heavily on the experience of skilled engineers. Today, the design, manufacturing, and inspection stages of composite production are usually handled separately. This separation means that important information, such as how a part will be built or what defects might occur, is not always shared between stages. As a result, parts may not be as lightweight, strong, or defect-free as possible, and the process can take longer and cost more. This research develops a smart process planning system that connects design, manufacturing, and inspection into one continuous process. Built as software that works with existing tools, the system can automatically plan how the fibers are placed, predicting and reducing defects while improving both manufacturability and strength. The system optimizes not only individual layers but also how defects are distributed across all layers, preventing them from stacking up in ways that weaken the final part. It also uses inspection results from completed parts to improve future designs, creating a feedback loop where each stage informs the others. The system was tested by designing a composite panel using this new approach and comparing it to a panel made with state-of-the-art manual planning methods. The results showed that the system could intentionally control where defects appeared and increase the efficiency of the planning process. By unifying design, manufacturing, and inspection, this research shows a way to make advanced composite manufacturing more efficient, consistent, and cost-effective. This approach lowers the barrier to using automated fiber placement and opens the door for its wider adoption not only in aerospace but also in industries such as automotive, wind energy, maritime, and sporting goods, where strong and lightweight structures are essential.

Computer-Aided Process Planning↗

Telecom-Wavelength Single-Photon Emitters in Multilayer InSe

The development of robust and efficient single-photon emitters (SPEs) at telecom wavelengths is critical for advancements in quantum information science. Two-dimensional (2D) materials have recently emerged as promising sources for SPEs, owing to their high photon extraction efficiency, facile coupling to external fields, and seamless integration into photonic circuits. In this study, we demonstrate the creation of SPEs emitting in the 1000–1550 nm near-infrared range by coupling 2D indium selenide (InSe) with strain-inducing nanopillar arrays. The emission wavelength exhibits a strong dependence on the number of layers. Hanbury Brown and Twiss experiments conducted at 10 K reveal clear photon antibunching, confirming the single-photon nature of the emissions. In conclusion, density-functional-theory calculations and scanning-tunneling-microscopy analyses provide insights into the electronic structures and defect states, elucidating the origins of the SPEs.

2D Material↗

Anomaly Detection in Materials Digital Twins with Multiscale ICME for Additive Manufacturing

Detecting anomaly in fatigue and fracture experimental materials science is an interesting yet challenging topic. The reasons are threefold. First, the anomalous microstructure feature that gives rise to structural failure is small, sometimes in the order of 10 -7 of the interrogated volume. This, in turn, results in a highly imbalanced classification problem in machine learning (ML). Second, the consequence is high, in the sense that the test specimen is destructed in such case. Third, the convolution between microstructure stochasticity and the small probability of void nucleation, growth, and coalescence makes failure and fracture a hard-to-predict and challenging problem in materials science due to its irreproducibility, even experimentally. In this paper, we developed a materials digital twin and applied anomaly detection methods to detect voids and anomaly in additive manufacturing (AM). The materials digital twin is driven by two integrated computational materials engineering (ICME) models, which are kinetic Monte Carlo (kMC) and crystal plasticity finite element method (CPFEM). In conclusion, we demonstrated that by using anomaly detection, it is possible to detect voids and other defects in materials digital twin, which paves way for future research in integrating materials digital twin with its physical counterpart.

ICME↗

Radiation damage in tungsten under high-energy He-ion irradiation

Tungsten (W) is a primary candidate for plasma-facing components (PFCs) in fusion reactors and hybrid fission-fusion reactors. However, W suffers from severe microstructural damage under Helium (He) ion irradiation in operation conditions. Key irradiation parameters, including incident ion energy, fluence, and irradiation temperature, are known to determine the formation of He bubbles and dislocation loops, which ultimately lead to the degradation of mechanical properties, such as radiation hardening and ductile-to-brittle transition temperature (DBTT) shifts. Various strategies, for instance, interface engineering and alloying, have been developed to enhance He irradiation tolerance in W to address these challenges. Studies in the recent two decades have enhanced the understanding of the underlying mechanisms that drive defect evolution and mechanical performance degradation, thereby offering more insights into the design of more resilient W-based materials for extreme environments.

Liu, Yinghang [Purdue University]↗

Expression of a Bacterial Trehalose 6-Phosphate Synthase Gene otsA in Camelina sativa Seeds Promotes the Channelling of Carbon Towards Oil Accumulation

Improving seed oil yield is essential for developing Camelina sativa as a sustainable biofuel crop. Fatty acid synthesis depends on the production of acetyl-CoA from photosynthetically derived sugars. Trehalose 6-phosphate (T6P), a proxy for sucrose availability, can link sugar status to plant growth and development. Synthesised by trehalose 6-phosphate synthase (TPS) from UDP-glucose and glucose-6-phosphate, T6P plays a regulatory role in metabolism. Our previous studies on Arabidopsis transgenic lines constitutively expressing the E. coli otsA (encoding TPS) showed increased T6P levels and seed triacylglycerol, along with stunted growth. In the present study we express otsA in camelina under the control of a seed-specific Phaseolin promoter. Seeds of the resulting transgenic lines accumulated high levels of T6P, and a 15%–20% increase in total fatty acids and triacylglycerol compared to wild-type. Molecular analysis showed the transgenic seeds had reduced SnRK1 activity, elevated WRI1 protein levels, and increased the levels of WRI1 and its target genes, along with enhanced rates of fatty acid synthesis that increased seed weights relative to wild type. Notably, the increase in oil did not affect seed protein levels but did reduce the soluble metabolite fraction. Crucially, seed-specific expression of otsA mitigated the growth defects associated with constitutive otsA expression, and the transgenic lines showed normal seed development and germination. These findings demonstrate that targeted T6P modulation via seed-specific otsA expression is an effective metabolic engineering strategy to boost oil production in camelina and potentially in other oilseed crops and bioenergy crops such as energycane, sorghum and miscanthus.

59 BASIC BIOLOGICAL SCIENCES↗

Defect diffusion graph neural networks (d2gnn)

SAND2025-01004O Defect Diffusion Graph Neural Networks (d2gnn) is a software tool that assists in the discovery of new materials for high-temperature, clean-energy applications. It uses advanced graph neural networks to model the relationship between material structures and their defect properties. The application helps predict how materials will behave under different conditions and accelerates the development of innovative materials. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Witman, Matthew [Sandia National Lab. (SNL-CA), Li↗

A Scalable & Non-Destructive Characterization Strategy to Study Semiconductor/Dielectric Interfaces and Predict Wafer-Level Device Performance

The defect density present at the dielectric-semiconductor interface in an MOS structure directly influences the channel carrier characteristics in semiconductor devices, especially in wide bandgap material systems used in power devices. While these trap defects are typically quantified through electrical characterization of MOS-capacitor test structures, this treatment offers very little insight into the physical nature of interface defects. Such shortcomings demand a physical characterization strategy to guide fabrication optimization. X-ray photoelectron spectroscopy (XPS) is suggested as a viable technique to determine chemical data for dielectric interfaces formed using atomic layer deposition (ALD) on GaN substrates. Previously, 1-D XPS characterization has confirmed the presence of a Ga x O y interlayer between ALD dielectrics and the GaN substrate. In this work, XPS data is serially collected to form 2-D images of an ALD-Al 2 O 3 /GaN interface as a proof-of-concept experiment for in-situ XPS quality monitoring during ALD processing. The information provided by this work reveals some of the challenges for incorporating XPS characterization as an in-situ strategy during fabrication of GaN-based devices. Separately, electrical mapping of a 2-D array of ALD-Al 2 O 3 /GaN MOS-capacitor devices provide a means to quantify the spatial variations in interface quality across a single wafer. Physical characterization techniques, such as time-of-flight secondary ion mass spectroscopy, provide additional chemical information about the Al 2 O 3 /Ga x O y /GaN structure that complement the electrical mapping results. This analysis shows that a higher Ga x O y content correlates with higher interface state defects for trap energies deep in the band gap.

42 ENGINEERING↗

Environmental and high strain rate effects on composites for engine applications

The complex environmental and loading conditions experienced by many turbine engine components impose severe durability and damage tolerance requirements for component materials. Programs are being conducted to establish the structural performance of composite materials under anticipated engine operating environments. A description is presented of the results obtained in connection with several of these programs. A comparison of predicted and measured hygrothermal effects is considered along with hygrothermal effects on defect growth, high strain rate effects on composite mechanical properties, dynamic stress intensity factors for composites, and the indentation laws for composite impact analysis.

Chamis, C. C.↗

Sizing Up the Situation

Hailstorm damage to the Space Shuttle's External Tank inspired a NASA innovation with extensive photography applications. In order to measure the defects caused by the storm, Kennedy Space Center used telephoto lenses to zoom in on the tank and view the damage clearly. However, since there was no reference object in the image, the engineers could not determine the scale of the damage. In photographic situations similar to this, an object, such as a ruler, is placed within the field of view. This allows a person to look at a photograph and have a visual indication of the scale of the objects in it. In the External Tank situation, however, this procedure was not possible. As a solution, Kennedy developed the Scaling and Measurement Device for Photographic Images, which provides a non-intrusive means of adding a scale to a photograph. In addition to meeting Kennedy's needs, scaling images is extremely important in crime and accident scene investigations, oil and chemical tank monitoring, and aerial photography. The innovation consists of a tool that attaches directly to a camera or charge coupled device using a standard screw. Two lasers fitted to the device provide parallel beams that are set 1 inch apart. These lasers enable the device to project a pattern into the field of view. When a photograph is taken, the image of the laser pattern appears, along with the image of the object under investigation, allowing the viewer quantifiable information as to the size of the object. The laser beams are accurate to approximately 200 feet. Windows-based software was developed to work with the scaling device tool. The software provides further techniques to measure objects in photographs and digital images. By using the software, any object in the image can be measured diagonally, vertically, and horizontally. The device and its software enable the user to determine two-dimensional measurements within a photograph.

Source record↗

Methodology for Physics and Engineering of Reliable Products

Physics of failure approaches have gained wide spread acceptance within the electronic reliability community. These methodologies involve identifying root cause failure mechanisms, developing associated models, and utilizing these models to inprove time to market, lower development and build costs and higher reliability. The methodology outlined herein sets forth a process, based on integration of both physics and engineering principles, for achieving the same goals.

failure analysis electronics reliability PACT (pre↗

Exep: Environmental Testing of High-Actuator-Count Mems Deformable Mirrors for Space-Based Applications

Coronagraph instruments on future space telescopes will rely on deformable mirrors to create high contrast images for the direct detection of exoplanets. As part of the NASA Exoplanet Explorations Program’s coronagraph technology development efforts, two sets of Micro-electro-mechanical systems (MEMS) deformable mirrors manufactured by Boston Micromachines Corporation were exposed to vibration and thermal cycles representative of launch conditions. The first set were 952-actuator Kilo-DMs that successfully demonstrated 100% actuator survival and achieved ~1e-8 contrast after the environment test. The second round used an engineering-grade 2048-actuator deformable mirror on which few changes were identified after the environmental test. However, each actuator that changed behavior was flagged as anomalous beforehand or was directly adjacent to a defective actuator. From this result, we hypothesized that typical actuators on a science grade deformable mirror are robust to environmental testing. A third set of 2048-actuator deformable mirror have been procured for a planned test to characterize the deformable mirrors using interferometric measurements, contrast results on a new in-air coronagraph testbed, and infrared microscopy on the internal structure of the MEMS devices.

Lam, Charlie↗

Automating Bug Report Classification with Few Shot Learning

Orthogonal defect classification (ODC) is a method used to categorize software defects, providing valuable insights into the development process. This study focuses on automating the classification of software bug reports into different ODC defect types using few shot learning, a machine learning approach that requires minimal labeled data. Previous research has manually classified bug reports or used traditional machine learning algorithms like linear support vector machine, achieving limited success. Our approach uses few shot learning to improve classification accuracy and efficiency. The results show a harmonic mean of recall and precision (i.e., the F1 score) of around 0.6 which is a performance improvement over previous methods. The results highlight the potential benefit of few shot learning techniques and their application in enhancing the safety and reliability of nuclear digital instrumentation and control (DI&C) systems. Future work will explore incorporating advanced techniques to supplement the model's training data and achieve better results.

42 - ENGINEERING↗

Application of superalloy powder metallurgy for aircraft engines

The results of the Materials for Advanced Turbine Engines (MATE) program initiated by NASA are presented. Mechanical properties comparisons are made for superalloy parts produced by as-HIP powder consolidation and by forging of HIP consolidated billets. The effect of various defects on the mechanical properties of powder parts are shown.

Dreshfield, R. L.↗