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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 145 records · Page 8

Effect of Data Reduction and Fiber-Bridging on Mode I Delamination Characterization of Unidirectional Composites

Reliable delamination characterization data for laminated composites are needed for input in analytical models of structures to predict delamination onset and growth. The double-cantilevered beam (DCB) specimen is used to measure fracture toughness, GIc, and strain energy release rate, GImax, for delamination onset and growth in laminated composites under mode I loading. The current study was conducted as part of an ASTM Round Robin activity to evaluate a proposed testing standard for Mode I fatigue delamination propagation. Static and fatigue tests were conducted on specimens of IM7/977-3 and G40-800/5276-1 graphite/epoxies, and S2/5216 glass/epoxy DCB specimens to evaluate the draft standard "Standard Test Method for Mode I Fatigue Delamination Propagation of Unidirectional Fiber-Reinforced Polymer Matrix Composites." Static results were used to generate a delamination resistance curve, GIR, for each material, which was used to determine the effects of fiber-bridging on the delamination growth data. All three materials were tested in fatigue at a cyclic GImax level equal to 90% of the fracture toughness, GIc, to determine the delamination growth rate. Two different data reduction methods, a 2-point and a 7-point fit, were used and the resulting Paris Law equations were compared. Growth rate results were normalized by the delamination resistance curve for each material and compared to the nonnormalized results. Paris Law exponents were found to decrease by 5.4% to 46.2% due to normalizing the growth data. Additional specimens of the IM7/977-3 material were tested at 3 lower cyclic GImax levels to compare the effect of loading level on delamination growth rates. The IM7/977-3 tests were also used to determine the delamination threshold curve for that material. The results show that tests at a range of loading levels are necessary to describe the complete delamination behavior of this material.

Murri, Gretchen B.↗

Mono-/Bimetallic Doped and Heterostructure Engineering for Electrochemical Energy Applications

Designing efficient materials is crucial to meeting specific requirements in various electrochemical energy applications. Mono-/bimetallic doped and heterostructure engineering have attracted considerable research interest due to their unique functionalities and potential for electrochemical energy conversion and storage. However, addressing material imperfections such as low conductivity and poor active sites requires a strategic approach to design. This review explores the latest advancements in materials modified by mono-/bimetallic doped and heterojunction strategies for electrochemical energy applications. It can be subdivided into three key points: (i) the regulatory mechanisms of metal doping and heterostructure engineering for materials; (ii) the preparation methods of materials with various engineering strategies; and (iii) the synergistic effects of two engineering approaches, further highlighting their applications in supercapacitors, alkaline ion batteries, and electrocatalysis. Finally, the review concludes with perspectives and recommendations for further research to advance these technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evolutionary inverse design of defects at graphene 2D lateral interfaces

Grain boundaries (GBs) in two-dimensional (2D) materials often have a profound impact on various material properties from mechanical to optical to electronic, yet predicting all possible GB formations is a challenge. Here, we introduce a workflow based on an evolutionary algorithm for exploring possible GBs formed at a lateral 2D interface. In a departure from conventional genetic algorithm based structure optimization methods, we perform genetic operations in the near interface region that allow us to be computationally efficient. We benchmark our method using graphene, which is a well-studied 2D material with a wide range of point defects. An empirical potential was used as the surrogate of the evolutionary search. More than 11.5 × 106 structures in total were evaluated for 128 GB orientations, and for each orientation, the ten best structures are recorded. A subset of low energy GBs predicted by empirical potential based search was relaxed by first-principles calculations and used to validate the energetic rank order. With the validated formation energy, we rank-ordered the best 128 GB structures and performed a detailed statistical analysis of primitive rings to find the correlation between the ring distribution and the formation energy. We found that for low energy GBs (below 0.5eV/Å), Stone–Wales defects will dominate, while structures with a higher energy (0.5–1.1eV/Å) show an increasing population of heptagons and nine-membered rings to form seven-nine defect pairs. For structures with energy higher than 1.1eV/Å, the percentage of octagons and nine-membered rings increases, which indicates that these two types of rings are not energetically favorable. Our proposed methodology is broadly applicable to explore defective low dimensional materials and represents a powerful tool that enables a systematic search of GBs of lateral interfaces for 2D materials.

Zhang, Jianan↗

Total Measurement Uncertainty in Neutron Coincidence Multiplicity Analysis

Neutron multiplicity counting is the most commonly used nondestructive assay technique for determining the plutonium mass within containers of scrap PuO 2 or mixed oxide (MOX). In multiplicity analysis, the 240 Pu eff mass, leakage multiplication, and alpha ratio (the ratio of [α, n]-to-spontaneous fission neutron production) are the three primary unknown sample properties. They must be determined simultaneously. To solve for these three unknowns in a multiplicity assay, three measured values are needed: the singles, doubles, and triples neutron count rates. While the analysis is limited to solving for three unknowns, there are many additional factors that impact the observed count rates and contribute to the measurement uncertainty. In this study we investigate the various uncertainty contributors for the multiplicity analysis through a combination of traditional uncertainty propagation techniques supplemented by Monte Carlo simulations to address the dependences not explicitly expressed by the point source model. Uncertainties arising from counting statistics, calibration parameters, calibration method, nuclear data, and various material characteristics (isotopic abundances, chemical form, density, and impurities) are considered. A Total Measurement Uncertainty (TMU) estimate is then developed from these uncertainty contributors. This study is confined to multiplicity analysis of items commonly encountered in international safeguards applications. That is, the study focused on Pu oxides and MOX materials for the masses ranging up to 4000 grams total Pu. Multiplicity measurements were simulated using MCNP V6 based on the Plutonium Scrap Multiplicity Counter (PSMC), Epithermal Multiplicity Counter (ENMC), Pyrochemical Multiplicity Counter, and Large Epithermal Multiplicity Counter (LEMC) for this study; however, this report focuses on the parameterization of the uncertainties for the PSMC. The performance differences between the PSMC and the other multiplicity counting systems are relatively small, primarily manifesting in the impact on measurement precision so that the evaluation developed for the PSMC can be applied to the other multiplicity counting systems. Finally an analysis tool, the Multiplicity TMU Estimator, was developed from this study to serve as an aid for evaluation of the total measurement uncertainty of multiplicity assay results obtained from the commonly used INCC acquisition and analysis software.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

STEM Imaging of Materials: Final Report for DE-FG02-08ER46547

This project supported research advancing the state of the art in scanning transmission electron microscopy (STEM) imaging and characterization of materials, especially electronic materials. The project began with studies of point defects in materials using high-resolution Z-contrast STEM, then evolved to including methods in four-dimensional (4D) STEM and machine learning. Highlights include: (1) the discovery of stable, p-type ZnO via Sb doping, (2) demonstration that the high performance of InGaN LEDs is not due to In composition fluctuations as previously proposed, (3) the demonstration of the first sub-pm precision high-resolution STEM images using non-rigid registration of a series of STEM images, (4) the extension of high-precision STEM to low dose imaging and spectrum imaging, (5) discovery of a synthesis method for twisted spiral growth of transition-metal dichalcogenide materials via chemical vapor deposition, and (6) development of machine-learning methods for analysis and denoising of enormous 4D STEM data sets.

36 MATERIALS SCIENCE↗

High temperature materials characterization

A lab facility for measuring elastic moduli up to 1700 C was constructed and delivered. It was shown that the ultrasonic method can be used to determine elastic constants of materials from room temperature to their melting points. The ease in coupling high frequency acoustic energy is still a difficult task. Even now, new coupling materials and higher power ultrasonic pulsers are being suggested. The surface was only scratched in terms of showing the full capabilities of either technique used, especially since there is such a large learning curve in developing proper methodologies to take measurements into the high temperature region. The laser acoustic system does not seem to have sufficient precision at this time to replace the normal buffer rod methodology.

Workman, Gary L.↗

Method for determining the point of zero zeta potential of semiconductor

A method to determine the potential of zero charge of an unpowdered semiconductor material is presented. The semiconductor material is used as the working electrode of a standard three electrode photoelectrochemical cell. The onset potential of the semiconductor material is measured at several different cell temperatures. The slope of the graph of onset potential versus temperature is used to compute the potential of zero charge.

Reichman, B.↗

Abstract for CRADA between NETL and GlycoSurf, Inc.

The National Energy Technology Laboratory (NETL) and GlycoSurf, Inc. (Participant) will collaborate in the development of novel luminescent sensing materials for rare earth elements using chemically modified surfactants. Rare earth elements are economically critical metals that are used in many technologies relevant to both energy and national defense. Slow and expensive characterization methods for rare earth element analysis are a major pain point for domestic production of these metals; the development of low-cost optical sensing materials and platforms can significantly reduce the time and financial costs associated with rare earth element prospecting and process monitoring. NETL has extensive experience developing inexpensive and compact optical sensors for critical metals such as rare earths. GlycoSurf, Inc. has commercialized high performance surfactants for the selective extraction of rare earth elements in complex environments such as acid mine drainage. By modifying these surfactants with fluorescent functional groups, trace concentrations of rare earths may be detected through a process called “photosensitization,” where the sensing material induces element-specific emission bands that enable different rare earth elements to be detected and distinguished. This project will enable the development of sensing materials capable of selectively detecting trace quantities of valuable rare earths in challenging conditions, including high ionic strength, highly acidic matrices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A minimally invasive, efficient method for propagation of full-field uncertainty in solid dynamics

In this work, we present a minimally invasive method for forward propagation of material property uncertainty to full-field quantities of interest in solid dynamics. Full-field uncertainty quantification enables the design of complex systems where quantities of interest, such as failure points, are not known a priori. The method, motivated by the well-known probability density function (PDF) propagation method of turbulence modeling, uses an ensemble of solutions to provide the joint PDF of desired quantities at every point in the domain. A small subset of the ensemble is computed exactly, and the remainder of the samples are computed with approximation of the evolution equations based on those exact solutions. Although the proposed method has commonalities with traditional interpolatory stochastic collocation methods applied directly to quantities of interest, it is distinct and exploits the parameter dependence and smoothness of the driving term of the evolution equations. The implementation is model independent, storage and communication efficient, and straightforward. We demonstrate its efficiency, accuracy, scaling with dimension of the parameter space, and convergence in distribution with two problems: a quasi-one-dimensional bar impact, and a two material notched plate impact. For the bar impact problem, we provide an analytical solution to PDF of the solution fields for method validation. With the notched plate problem, we also demonstrate good parallel efficiency and scaling of the method.

42 ENGINEERING↗

Space Systems - Safety and Compatibility of Materials - Method to Determine the Flammability Thresholds of Materials

Spacecraft fire safety emphasizes fire prevention, which is achieved primarily through the use of fire-resistant materials. Materials selection for spacecraft is based on conventional flammability acceptance tests, along with prescribed quantity limitations and configuration control for items that are non-pass or questionable. ISO 14624-1 and -2 are the major methods used to evaluate flammability of polymeric materials intended for use in the habitable environments of spacecraft. The methods are upward flame-propagation tests initiated in static environments and using a well-defined igniter flame at the bottom of the sample. The tests are conducted in the most severe flaming combustion environment expected in the spacecraft. The pass/fail test logic of ISO 14624-1 and -2 does not allow a quantitative comparison with reduced gravity or microgravity test results; therefore their use is limited, and possibilities for in-depth theoretical analyses and realistic estimates of spacecraft fire extinguishment requirements are practically eliminated. To better understand the applicability of laboratory test data to actual spacecraft environments, a modified ISO 14624 protocol has been proposed that, as an alternative to qualifying materials as pass/fail in the worst-expected environments, measures the actual upward flammability limit for the material. A working group established by NASA to provide recommendations for exploration spacecraft internal atmospheres realized the importance of correlating laboratory data with real-life environments and recommended NASA to develop a flammability threshold test method. The working group indicated that for the Constellation Program, the flammability threshold information will allow NASA to identify materials with increased flammability risk from oxygen concentration and total pressure changes, minimize potential impacts, and allow for development of sound requirements for new spacecraft and extravehicular landers and habitats. Furthermore, recent research has shown that current normal gravity materials flammability tests do not correlate with flammability in ventilated, micro- or reduced-gravity conditions. Currently, the materials selection for spacecraft is based on the assumption of commonality between ground flammability test results and spacecraft environments, which does not appear to be valid. Materials flammability threshold data acquired in normal gravity can be correlated with data obtained in microgravity or reduced-gravity experiments, and consequently a more accurate assessment of the margin of safety of the material in the real environment can be made. In addition, the method allows the option of selecting better or best space system materials, as opposed to what would be considered just acceptable from a flammability point of view and realistic assessment of spacecraft fire extinguishment needs, which could result in significant weight savings. The knowledge afforded by this technique allows for limited extrapolations of flammability behavior to conditions not specifically tested and that could potentially result in significant cost and time savings. The intent of this Technical Specification is to bring to the attention of International Aerospace Community the importance of correlating laboratory test data with real-life space systems applications. The method presented is just one of the possibilities that are believed will lead to better understanding the applicability of laboratory aerospace materials flammability test data. International feedback on improving the proposed method, as well as suggestions for correlating other laboratory aerospace test data with real-life applications relevant to space systems are being sought.

Hirsch, David↗

High frequency scattering from trihedral corner reflectors and other benchmark targets - SBR versus experiment

A general method for calculating the radar cross section (RCS) from a three-dimensional target is described. The target is first constructed by using a solid-geometry-modeling computer-aided design (CAD) package. Following the shooting and bouncing ray (SBR) method, a very dense grid of rays is launched from the incident direction toward the target. Each ray is traced according to the geometrical optics theory including the effect of ray tube divergence, polarization, and material reflection coefficient. At the point where the ray exits the target, a physical optics-type integration is performed to obtain the scattered far fields. This method is tested using several simple examples involving interaction among plates, cylinders, and spheres. The theoretical results are generally in good agreement with measured data.

Baldauf, John↗

An overview of engineering concepts and current design algorithms for probabilistic structural analysis

The article begins by examining the fundamentals of traditional deterministic design philosophy. The initial section outlines the concepts of failure criteria and limit state functions two traditional notions that are embedded in deterministic design philosophy. This is followed by a discussion regarding safety factors (a possible limit state function) and the common utilization of statistical concepts in deterministic engineering design approaches. Next the fundamental aspects of a probabilistic failure analysis are explored and it is shown that deterministic design concepts mentioned in the initial portion of the article are embedded in probabilistic design methods. For components fabricated from ceramic materials (and other similarly brittle materials) the probabilistic design approach yields the widely used Weibull analysis after suitable assumptions are incorporated. The authors point out that Weibull analysis provides the rare instance where closed form solutions are available for a probabilistic failure analysis. Since numerical methods are usually required to evaluate component reliabilities, a section on Monte Carlo methods is included to introduce the concept. The article concludes with a presentation of the technical aspects that support the numerical method known as fast probability integration (FPI). This includes a discussion of the Hasofer-Lind and Rackwitz-Fiessler approximations.

Duffy, S. F.↗

An investigation of the Iosipescu and Asymmetrical Four-Point Bend tests for composite materials

The results of an extensive analytical and experimental investigation of the Iosipescu and Asymmetrical Four-Point Bend (AFPB) test methods are summarized. Finite element analyses were used to assess the influence of notch parameters and load locations on the stress state in the specimens. The shear moduli and shear strengths were experimentally measured for quasi-isotropic graphite-epoxy laminates using both the Iosipescu and the AFPB test methods with various combinations of notch parameters and load locations. The test results indicate that changes in the notch geometry and load locations aimed at improving the stress distribution in the test section result in unexpected changes in the failure mode.

Spigel, B. S.↗

NASA GRC Fatigue Crack Initiation Life Prediction Models

Metal fatigue has plagued structural components for centuries, and it remains a critical durability issue in today's aerospace hardware. This is true despite vastly improved and advanced materials, increased mechanistic understanding, and development of accurate structural analysis and advanced fatigue life prediction tools. Each advance is quickly taken advantage of to produce safer, more reliable, more cost effective, and better performing products. In other words, as the envelope is expanded, components are then designed to operate just as close to the newly expanded envelope as they were to the initial one. The problem is perennial. The economic importance of addressing structural durability issues early in the design process is emphasized. Tradeoffs with performance, cost, and legislated restrictions are pointed out. Several aspects of structural durability of advanced systems, advanced materials and advanced fatigue life prediction methods are presented. Specific items include the basic elements of durability analysis, conventional designs, barriers to be overcome for advanced systems, high-temperature life prediction for both creep-fatigue and thermomechanical fatigue, mean stress effects, multiaxial stress-strain states, and cumulative fatigue damage accumulation assessment.

Arya, Vinod K.↗

Impact Ice Microstructure Segmentation Using Transfer Learned Model

A process of using machine learning to segment impact ice microstructure is presented and analyzed. The segmentation was conducted with the goal of obtaining average grain size estimations. The model was trained on a set of micrographs of impact ice grown at NASA Glenn’s Icing Research Tunnel. The model leveraged a model pre-trained on a large set of micrographs of various materials as a starting point. Post-processing of the segmented images was done to connect broken boundaries. An automatic method of determining grain size following an ASTM standard was implemented. Segmentation results using different training sets as well as different encoder and decoder pairs are presented. Calculated sizes are compared to manual grain size measurement methods. Results show promise in accuracy as well as a possible improvement in repeatability and consistency. Next steps for improving the model are suggested.

Machine learning↗

Lignin-based polymers with enhanced melt extrusion ability

A solid polymer blend material comprising: (i) lignin; and (ii) a polyamide having a melting point of no more than 240° C. and which is below the decomposition temperature of the lignin; wherein said lignin is homogeneously dispersed in said polyamide. Methods for producing the blend material are also described. Methods for producing objects made of the blend material by melt extrusion are also described, comprising: (a) melt blending components (i) and (ii) to form a polymer blend in which components (i) and (ii) are homogeneously blended, wherein the polymer blend exhibits a melt viscosity of no more than 2000 Pa·s at a shear rate of 100-1000 s −1 and when heated to a temperature of no more than 240° C.; and; (b) forming an object made of said polymer blend material.

Naskar, Amit K.↗

Adaptive sampling for accelerating neutron diffraction-based strain mapping *

Abstract Neutron diffraction is a useful technique for mapping residual strains in dense metal objects. The technique works by placing an object in the path of a neutron beam, measuring the diffracted signals and inferring the local lattice strain values from the measurement. In order to map the strains across the entire object, the object is stepped one position at a time in the path of the neutron beam, typically in raster order, and at each position a strain value is estimated. Typical dwell times at neutron diffraction instruments result in an overall measurement that can take several hours to map an object that is several tens of centimeters in each dimension at a resolution of a few millimeters, during which the end users do not have an estimate of the global strain features and are at risk of incomplete information in case of instruments outages. In this paper, we propose an object adaptive sampling strategy to measure the significant points first. We start with a small initial uniform set of measurement points across the object to be mapped, compute the strain in those positions and use a machine learning technique to predict the next position to measure in the object. Specifically, we use a Bayesian optimization based on a Gaussian process regression method to infer the underlying strain field from a sparse set of measurements and predict the next most informative positions to measure based on estimates of the mean and variance in the strain fields estimated from the previously measured points. We demonstrate our real-time measure-infer-predict workflow on additively manufactured steel parts—demonstrating that we can get an accurate strain estimate even with 30%–40% of the typical number of measurements—leading the path to faster strain mapping with useful real-time feedback. We emphasize that the proposed method is general and can be used for fast mapping of other material properties such as phase fractions from time-consuming point-wise neutron measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Optimization of Preparation Method, Nucleating Agent, and Stabilizers for Synthesizing Calcium Chloride Hexahydrate (CaCl2.6H2O) Phase Change Material

This study investigates improvements in low-cost latent heat storage material calcium chloride hexahydrate (CaCl2.6H2O). Its melting point is between 25 and 28 °C, with relatively high enthalpy (170–190 J/g); however, this phase change material (PCM) shows supercooling and phase separation. In CaCl2.6H2O incongruent melting causes lower hydrates of CaCl2 to form, which affects the overall energy storage capacity and long-term durability. In this work, PCM performance enhancement was achieved by adding SrCl2.6H2O as a nucleating agent and NaCl/KCl as a stabilizer to prevent supercooling and phase separation, respectively. We investigated the PCM preparation method and optimized the proportions of SrCl2.6H2O and NaCl/KCl. Thermal testing for 25 cycles combined with DSC and T-history testing was performed to observe changes in enthalpy, phase transitions and supercooling over the extended period of usage. X-ray diffraction was used to verify crystalline structure in the compounds. It was found that the addition of 2 wt.% of SrCl2.6H2O reduced supercooling from 12 °C to 0 °C compared to unmodified CaCl2.6H2O. The addition of 5 wt.% NaCl or KCl proved to effectively suppress separation and the melting enthalpy achieved was 169 J/g–178 J/g with congruent melting over 25 cycles, with no supercooling and almost no reduction in the latent heat.

42 ENGINEERING↗