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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Characterization of the degradation of gamma-irradiated elastomers using Raman spectroscopy

This report presents key findings from Raman spectroscopic analysis of gamma-irradiated rubber samples extracted from a laminated lead-damped rubber (LDR) seismic isolation device. The samples were exposed to gamma radiation from a 60Co source in a Foss Therapy Services gamma irradiator, reaching absorbed doses up to 1600 kGy. A distinct threshold near 400 kGy was identified, beyond which significant spectral changes were observed. Two Raman peaks - at approximately 425 cm-1 and 2440 cm-1 - were tracked as a function of dose using Gaussian fitting. The 425 cm-1 peak, attributed to sulfur–sulfur (S–S) bond stretching (resulting from vulcanization of the rubber), exhibited a dose-dependent upshift, indicating radiation-induced crosslinking within the sulfur-based polymer network. Conversely, the 2440 cm-1 peak, likely associated with vibrational modes of additives or impurities, showed a downward shift with increasing dose, suggesting chain scission and degradation of non-rubber constituents. These results provide first-of-a-kind insights into the microstructural evolution of elastomers under high-dose gamma irradiation and establish a preliminary dose threshold for significant degradation. Future work will incorporate multi-modal characterization—including Fourier Transform Infrared (FTIR) spectroscopy, scanning electrom microscopy (SEM) of the rubber surface morphology, thermogravimetric analysis (TGA) to determine changes in thermal stability, and mechanical testing—to correlate molecular-level changes with macroscopic performance of these elastomers as damping media in seismic isolation devices. These findings are expected to provide regulatory guidance and design criteria for qualifying low-damping rubber seismic isolators in advanced nuclear reactor applications.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

Investigating the failure behavior of cast Al-11Ce-0.4Mg alloys using in-situ scanning electron microscopy tensile testing

Within the last decade, research on Al-Ce-Mg alloys has reported promising results for use in cast part applications. In this paper, the failure behavior of cast Al-11Ce-0.4Mg (wt%) was investigated experimentally with focus on the effect the matrix and intermetallic phases have on the fracture propagation behavior at failure. For the first time, in-situ SEM tensile testing was used to study the failure behavior of cast Al-Ce alloys, reporting results for uniaxial, DIC, and single edge notch tensile tests. The results of the in-situ SEM tensile testing were compared with the materials characterization experiments, which included serial sectioning, EBSD, EDS, and fractography. Analysis of EBSD and EDS mapping of cast Al-11Ce-0.4Mg showed that the cast microstructure was a hypereutectic two phase Al-Ce alloy with grains encompassing large complex colonies of laminar eutectic Al 11 Ce 3 intermetallic. The uniaxial tensile results reported the effect casting defects have on the strength and ductility of the alloy, and DIC in-situ testing showed that the eutectic colonies plastically deform less than the matrix phase. In-situ SEM single edge notch tensile testing displayed how the strength of an individual phase affected the crack propagation direction in the alloy. The results of both the materials characterization and in-situ tensile testing experiments on the failure of this alloy revealed further directions for future alloy development that can improve both the strength and fracture toughness of Al-Ce-Mg alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A meshing framework for digital twins for extrusion based additive manufacturing

Additive manufacturing (AM) allows for manufacturing of complex three-dimensional geometries not typically realizable with standard manufacturing practices. The internal microstructure of AM components has a significant impact on mechanical, vibrational, and shock properties and permits richer design space when this is controllable. Due to complex interactions of internal geometry of an extrusion-based AM component, it is common practice to assume homogeneous behavior or to perform characterization testing on specific toolpath configurations. To avoid testing or material waste, it is necessary to develop a consistently accurate numerical simulation framework with relevant boundary value problems that can handle the complicated geometry of internal material microstructure present in AM components. Herein, a framework is proposed to directly create computational meshes suitable for finite element analysis (FEA) of the fine-scale features generated from extrusion-based AM tool paths to maintain a strong process–structure–property-performance linkage. This mesh can be manually or automatically analyzed using standard FEA simulations such as quasi-static preloading or modal analysis. The framework allows an in-silico assessment of a target AM geometry where fine-scale features greatly impact quantities of design interest such as in soft elastomeric lattices where toolpath infill can greatly influence the self-contact of a structure in compression, which we use as a motivating exemplar. This approach greatly reduces both time and resource waste present in traditional build and test design cycles for non-intuitive design spaces, and acts as a tool for use in the production of a key component of a digital twin, a mesh suitable for finite element analysis. In conclusion, it also further allows for the exploration of toolpath infill to optimize component properties beyond simple linear properties such as density and stiffness.

Additive manufacturing↗
DOE OSTI2020

Gradient microstructure induced shear band constraint, delocalization, and delayed failure in CuZr nanoglasses

The mechanical properties of metallic glasses (MGs) can be significantly tuned by introducing a nanoscale glass-glass interface microstructure. Here, we design three types of Cu 64 Zr 36 MG seamless gradient microstructures by combining glassy grain sizes from 3 to 15 nm. We perform tensile loading molecular dynamics simulations on the named gradient nanoglasses to characterize their mechanical behavior. In all cases, results indicate the generation of gradient plasticity following the gradient in grain size, i.e. local plasticity increases from large to small grain size regions. Loading parallel to the gradient direction results in initial broad necking followed by catastrophic failure. In contrast, loading perpendicular to the gradient direction results in diffused shear band propagation from large to small grain size regions, delaying the generation of a dominant shear band and further delocalizing plastic deformation. In conclusion, the results demonstrate the synergistic effects generated by heterogeneous gradient designs in the mechanical behavior of metallic glasses.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Atomic force microscopy and scanning electron microscopy characterization of the controlling of surface morphology of epoxy‐amine‐cured spin‐coated films

Abstract Atomic force microscopy (AFM) was successfully used to study spin‐coated, amine‐cured epoxy film microstructure and morphology. The air‐epoxy and epoxy‐substrate interfaces were examined using tapping‐mode height and phase imaging AFM. The impact of relative humidity on the morphology and microstructure of the surfaces was determined. AFM was able to elucidate the changes on the surface as relative humidity during processing increased. It was observed that large nodular formations formed on the epoxy surface expose to the air but not epoxy surface formed on the substrate in addition to varying regions of more or less compliant structures, which was attributed to carbamate formation caused by the amine curing agent reaction with atmospheric CO 2 . Scanning electron microscopy (SEM) was used to further elucidate interface and interphase morphology of spin‐coated epoxies. Experimentation also demonstrated that post‐curing above the glass transition did not change the morphology structure, suggesting surface structures are “locked‐in.” SEM was used to further elucidate how the interface and interphase change with changing environmental conditions at both the air‐epoxy and epoxy‐substrate interface/interphases, including the impact of atmospheric CO 2 on Marangoni cell formation.

Shenk, Timothy M.↗
DOE OSTI2020

Fullerene-like defects in high-temperature neutron-irradiated nuclear graphite

Irradiation-induced defect evolution in graphite is particularly important for its application in graphite-moderated nuclear reactors. The evolution of defects directly influences macroscopically observed property changes in irradiated nuclear graphite which, in turn, can govern the lifetime of graphite components. This article reports novel defect structures and the irradiation response of microstructural features occurring in high-temperature irradiated nuclear graphite IG-110. High resolution transmission electron microscopy (HRTEM) was used to characterize specimens neutron-irradiated at a high temperature (≥ 800°C) at doses of 1.73 and 3.56 atomic displacements per atom (dpa). Concentric shelled and fullerene-like defects were found to result in swelling along the c-axis and contraction along the a/b-axis of crystallites. Furthermore, such defects are shown to occur within, and partially fill, Mrozowski cracks prior to turnaround dose. In addition, in situ TEM under similar irradiation conditions was used to capture the real-time dynamic evolution of defects, providing unambiguous analysis of the evolution of the graphite structures during irradiation. Here, the results suggest the mainstream theory for radiation damage in nuclear graphite (which assumes additional basal plane formation as the sole reason) to be an incorrect interpretation of defect evolution contributing to irradiation-induced property changes at higher temperatures.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

An efficient instance segmentation approach for studying fission gas bubbles in irradiated metallic nuclear fuel

Abstract Gaseous fission products from nuclear fission reactions tend to form fission gas bubbles of various shapes and sizes inside nuclear fuel. The behavior of fission gas bubbles dictates nuclear fuel performances, such as fission gas release, grain growth, swelling, and fuel cladding mechanical interaction. Although mechanical understanding of the overall evolution behavior of fission gas bubbles is well known, lacking the quantitative data and high-level correlation between burnup/temperature and microstructure evolution blocks the development of predictive models and reduces the possibility of accelerating the qualification for new fuel forms. Historical characterization of fission gas bubbles in irradiated nuclear fuel relied on a simple threshold method working on low-resolution optical microscopy images. Advanced characterization of fission gas bubbles using scanning electron microscopic images reveals unprecedented details and extensive morphological data, which strains the effectiveness of conventional methods. This paper proposes a hybrid framework, based on digital image processing and deep learning models, to efficiently detect and classify fission gas bubbles from scanning electron microscopic images. The developed bubble annotation tool used a multitask deep learning network that integrates U-Net and ResNet to accomplish instance-level bubble segmentation. With limited annotated data, the model achieves a recall ratio of more than 90%, a leap forward compared to the threshold method. The model has the capability to identify fission gas bubbles with and without lanthanides to better understand the movement of lanthanide fission products and fuel cladding chemical interaction. Lastly, the deep learning model is versatile and applicable to the micro-structure segmentation of similar materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Combining synchrotron X-ray diffraction, mechanistic modeling and machine learning for in situ subsurface temperature quantification during laser melting

Laser melting, such as that encountered during additive manufacturing, produces extreme gradients of temperature in both space and time, which in turn influence microstructural development in the material. Qualification and model validation of the process itself and the resulting material necessitate the ability to characterize these temperature fields. However, well established means to directly probe the material temperature below the surface of an alloy while it is being processed are limited. To address this gap in characterization capabilities, a novel means is presented to extract subsurface temperature-distribution metrics, with uncertainty, from in situ synchrotron X-ray diffraction measurements to provide quantitative temperature evolution data during laser melting. Temperature-distribution metrics are determined using Gaussian process regression supervised machine-learning surrogate models trained with a combination of mechanistic modeling (heat transfer and fluid flow) and X-ray diffraction simulation. The trained surrogate model uncertainties are found to range from 5 to 15% depending on the metric and current temperature. The surrogate models are then applied to experimental data to extract temperature metrics from an Inconel 625 nickel superalloy wall specimen during laser melting. The maximum temperatures of the solid phase in the diffraction volume through melting and cooling are found to reach the solidus temperature as expected, with the mean and minimum temperatures found to be several hundred degrees less. The extracted temperature metrics near melting are determined to be more accurate because of the lower relative levels of mechanical elastic strains. However, uncertainties for temperature metrics during cooling are increased due to the effects of thermomechanical stress.

36 MATERIALS SCIENCE↗
NASA NTRS1977

Characteristics of first order shock induced magnetic transitions in iron and discrimination from TRM

Reflected light microscopy provides information on first-order shock transitions in iron and iron-nickel and permits discrimination of microstructures due to shock transitions from those imparted by thermal transitions. In addition, thin-foil electron microscopy is used to characterize magnetic transitions in fine-particle iron. First-order magnetic phase changes, such as that from the antiferromagnetic face centered cubic state to the ferromagnetic body centered cubic state, are studied with the aim of calibrating the shock and thermal mechanisms of magnetization in iron with a particle size range between 250 and 1200 A. The efficiency of remanence due to shock transition is also estimated.

Wasilewski, P.↗
NASA NTRS1986

Nondestructive evaluation of structural ceramics

Research on nondestructive evaluation (NDE) of structural ceramics for heat engine applications is reviewed. Microfocus radiography and scanning laser acoustic microscopy are the NDE techniques highlighted. The techniques were applied to research samples of sintered silicon nitride and silicon carbide in the form of modulus-of-rupture (MOR) bars. The strength and limitations of the aforementioned techniques are given in terms of probablility of detection for voids in green and sintered MOR bars. Voids for this purpose were introduced by seeding green ceramic bars and characterizing each void in terms of its size, shape, location, and nature before and after sintering. The effects of material density, microstructure, surface finish, thickness, void depth, and size characteristics on detectability are summarized.

Vary, Alex↗
NASA NTRS1993

Characterization and durability testing of plasma-sprayed zirconia-yttria and hafnia-yttria thermal barrier coatings. Part 1: Effect of spray parameters on the performance of several lots of partially stabilized zirconia-yttria powder

Initial experiments conducted on thermal barrier coatings prepared in the newly upgraded research plasma spray facility and the burner rig test facilities are discussed. Part 1 discusses experiments which establish the spray parameters for three baseline zirconia-yttria coatings. The quality of five similar coating lots was judged primarily by their response to burner rig exposure supplemented by data from other sources such as specimen characterizations and thermal diffusivity measurements. After allowing for burner rig variability, although there appears to be an optimum density (i.e., optimum microstructure) for maximum burner rig life, the distribution tends to be rather broad about the maximum. In Part 2, new hafnia-yttria-based coatings were evaluated against both baseline and alternate zirconia-yttria coatings. The hafnia-yttria coatings and the zirconia-yttria coatings that were prepared by an alternate powder vendor were very sensitive to plasma spray parameters, in that high-quality coatings were only obtained when certain parameters were employed. The reasons for this important observation are not understood. Also not understood is that the first of two replicate specimens sprayed for Part 1 consistently performed better than the second specimen. Subsequent experiments did not display this spray order affect, possibly because a chiller was installed in the torch cooling water circuit. Also, large changes in coating density were observed after switching to a new lot of electrodes. Analyses of these findings were made possible, in part, because of the development of a sensitive density measurement technique described herein in detail. The measured thermal diffusivities did not display the expected strong relationship with porosity. This surprising result was believed to have been caused by increased microcracking of the denser coatings on the stainless steel substrates.

Miller, Robert A.↗
NASA NTRS1995

Study Of Nondestructive Techniques For Testing Composites

Study evaluates some nondestructive methods for characterizing ceramic-, metal-, and polymer-matrix composite materials. Results demonstrated utility of two ultrasonic methods for obtaining quantitative data on microstructural anomalies in composite materials.

Roth, D.↗
DOE OSTI2024

Advanced Characterization Capabilities for Nuclear Materials via Nuclear Science User Facilities (NSUF)

Advanced post-irradiation examination (PIE) techniques are required to design new or improved nuclear materials, characterize, and understand in-core behavior of fuel and materials, and support the qualification of new reactor materials. The Nuclear Science User Facilities (NSUF) is the U.S. Department of Energy Office of Nuclear Energy's only designated nuclear science user facility. NSUF provides researchers access to PIE capabilities at Idaho National Laboratory and at a diverse mix of university, national laboratory and industrial partner institutions. The PIE capabilities include novel destructive and non-destructive techniques for radiation damage characterization, such as advanced diffraction techniques (X-ray, electron, or neutron) coupled to extreme environments; in-situ observation of microstructural evolution under irradiation; in-situ irradiation to monitor corrosive attack in coolant environments; in-situ irradiation and mechanical testing; and test methods for synergistic effects of superimposed extreme environments (temperature, irradiation, stress, corrosion) on materials behaviors. This talk will provide an overview of NSUF PIE capabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Model-based quantification of margins and uncertainties in metal additive manufacturing for process design and qualification

Laser powder bed fusion (LPBF) Additive Manufacturing (AM) has the potential to enable the production of components with novel designs and material properties unachievable otherwise. However, process repeatability is a challenge, making qualification ill-defined and greatly reducing the utility of what could be an important manufacturing technology. In this work, a combination of modeling, uncertainty quantification (UQ), and experimentation are used in an effort to predict and bound the range of possible outcomes of the LPBF process. Quantities of interest predicted are melt pool dimensions, microstructure features, and mechanical distortions. A combination of high fidelity thermal-fluid models, microstructure growth models, and reduced fidelity, rapid thermal and mechanical models are used. Uncertainty propagation techniques are used to predict probability distributions of quantities of interest from estimates of process uncertainties. Repeated experiments are done to quantify observed probability distributions and compared to predicted distributions to determine if predictions are precise and accurate. Novel modeling methods are microstrucutre characterization techniques are also discussed. It is found that high fidelity models do a generally good job bounding experimentally observed melt pool morphologies for both bead-on-plate and powder bed cases. Microstructure models are able to bound a number of experimentally observed microstructure statistics, but with low precision due to challenges with calibrating the microstructure growth model parameters. A developed modified inherent strain distortion model does not accurately predict observed distortions. A lumped laser distortion model shows promise in being both accurately and precisely bounding observed outcomes from the deflection comb build, but requires further evaluation on more builds and geometries.

36 MATERIALS SCIENCE↗
NASA NTRS2007

Characterization of Nonlinear Rate Dependent Response of Shape Memory Polymers

Shape Memory Polymers (SMPs) are a class of polymers, which can undergo deformation in a flexible state at elevated temperatures, and when cooled below the glass transition temperature, while retaining their deformed shape, will enter and remain in a rigid state. Upon heating above the glass transition temperature, the shape memory polymer will return to its original, unaltered shape. SMPs have been reported to recover strains of over 400%. It is important to understand the stress and strain recovery behavior of SMPs to better develop constitutive models which predict material behavior. Initial modeling efforts did not account for large deformations beyond 25% strain. However, a model under current development is capable of describing large deformations of the material. This model considers the coexisting active (rubber) and frozen (glass) phases of the polymer, as well as the transitions between the material phases. The constitutive equations at the continuum level are established with internal state variables to describe the microstructural changes associated with the phase transitions. For small deformations, the model reduces to a linear model that agrees with those reported in the literature. Thermomechanical characterization is necessary for the development, calibration, and validation of a constitutive model. The experimental data reported in this paper will assist in model development by providing a better understanding of the stress and strain recovery behavior of the material. This paper presents the testing techniques used to characterize the thermomechanical material properties of a shape memory polymer (SMP) and also presents the resulting data. An innovative visual-photographic apparatus, known as a Vision Image Correlation (VIC) system was used to measure the strain. The details of this technique will also be presented in this paper. A series of tensile tests were performed on specimens such that strain levels of 10, 25, 50, and 100% were applied to the material while it was above its glass transition temperature. After deforming the material to a specified applied strain, the material was then cooled to below the glass transition temperature (Tg) while retaining the deformed shape. Finally, the specimen was heated again to above the transition temperature, and the resulting shape recovery profile was measured. Results show that strain recovery occurs at a nonlinear rate with respect to time. Results also indicate that the ratio of recoverable strain/applied strain increases as the applied strain increases.

Volk, Brent↗
DOE OSTI2020

A Bezier Curve Informed Melt Pool Geometry to Model Additive Manufacturing Microstructures Using SPPARKS

Additive manufacturing is a transformative technology with the potential to manufacture designs which traditional subtractive machining methods cannot. Additive manufacturing offers fast builds at near final desired geometry; however, material properties and variability from part to part remain a challenge for certification and qualification of metallic components. AM induced metallic microstructures are spatially heterogeneous and highly process dependent. Engineering properties such as strength and toughness are significantly affected by microstructure morphologies resulting from the manufacturing process Linking process parameters to microstructures and ultimately to the dynamic response of AM materials is critical to certifying and qualifying AM built parts and components and improving the performance of AM materials. The AM fabrication process is characterized by building parts layer by layer using a selective laser melt process guided by a computer. A laser selectively scans and melts metal according to a designated geometry. As the laser scans, metal melts, fuses, and solidifies forming the final geometry in a layerwise fashion. As the laser heat source moves away, the metal cools and solidifies forming metallic microstructures. This work describes a microstructure modeling application implemented in the SPPARKS kinetic Monte Carlo computational framework for simulating the resulting microstructures. The application uses Bzier curves and surfaces to model the melt pool surface and spatial temperature profile induced by moving the laser heat source; it simulates the melting and fusing of metal at the laser hot spot and microstructure formation and evolution when the laser moves away. The geometry of the melt pool is quite flexible and we explore effects of variances in model parameters on simulated microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Characterization of the fatigue threshold behavior of UHMWPE

Ultra-high-molecular-weight-polyethylene (UHMWPE) has been the material of choice for bearings in total joint replacements (TJRs) for decades as a result of its excellent wear resistance, chemical inertness, energetic toughness, low friction, and biocompatibility. Utilization of this polymer in orthopedic devices requires oxidation, wear, and fatigue resistance. Balancing these important properties by tailoring processing techniques and modulating microstructural features has been an ongoing endeavor in the field. Research into the clinical applications of UHMWPE has primarily focused on the challenges of wear and oxidation while studies into the realm of fatigue have been more limited. Literature gaps exist in fully understanding the fatigue crack initiation near notches or propagation of small existing flaws in UHMWPE used in TJRs. In particular, the characterization of the fatigue thresholds and near-threshold fatigue behavior of orthopedic grade UHMWPE has yet to be thoroughly explored. In this work, we characterized the fatigue crack arrest threshold of clinically-relevant UHMWPE formulations. Correlations between the fatigue thresholds and bulk mechanical properties as well as microstructural properties were examined across these medical resins. The important role played by crosslinking in influencing the fatigue performance of UHMWPE is highlighted in this study. In addition, it is established that J-integral fracture toughness is the best predictor of fatigue thresholds and could possibly be used as a stand-in metric for fatigue performance if thresholds cannot be directly ascertained. Finally, this study corroborates that the true constitutive parameters best describe the mechanical behavior of UHMWPE.

Cross-linking↗
DOE OSTI2023

Three-dimensional morphology of an ultrafine Al-Si eutectic produced via laser rapid solidification

Al-Si alloys processed by laser rapid solidification yield eutectic microstructures with ultrafine and interconnected fibers. Such fibrous structures have long been thought to bear resemblance to those formed in impurity-doped alloys upon conventional casting. Here, we show that any similarity is purely superficial. By harnessing high-throughput characterization and computer vision techniques, we perform a three-dimensional analysis of the branching behavior of the ultrafine eutectic and compare it against an impurity-modified eutectic as well as a random fractal (as a benchmark). Differences in the branching statistics point to different microstructural origins of the impurity- and quench-modified eutectic. Finally, our quantitative approach is not limited to the data presented here but can be used to extract abstract information from other volumetric datasets, without customization.

36 MATERIALS SCIENCE↗