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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

LDEF polymeric materials: A summary of Langley characterization

The NASA Long Duration Exposure Facility (LDEF) enabled the exposure of a wide variety of materials to the low earth orbit (LEO) environment. This paper provides a summary of research conducted at the Langley Research Center into the response of selected LDEF polymers to this environment. Materials examined include graphite fiber reinforced epoxy, polysulfone, and additional polyimide matrix composites, films of FEP Teflon, Kapton, several experimental high performance polyimides, and films of more traditional polymers such as poly(vinyl toluene) and polystyrene. Exposure duration was either 10 months or 5.8 years. Flight and control specimens were characterized by a number of analytical techniques including ultraviolet-visible and infrared spectroscopy, thermal analysis, scanning electron and scanning tunneling microscopy, x-ray photoelectron spectroscopy, and, in some instances, selected solution property measurements. Characterized effects were found to be primarily surface phenomena. These effects included atomic oxygen-induced erosion of unprotected surfaces and ultraviolet-induced discoloration and changes in selected molecular level parameters. No gross changes in molecular structure or glass transition temperature were noted. The intent of this characterization is to increase our fundamental knowledge of space environmental effects as an aid in developing new and improved polymers for space application. A secondary objective is to develop benchmarks to enhance our methodology for the ground-based simulation of environmental effects so that polymer performance in space can be more reliably predicted.

Young, Philip R.↗
NASA NTRS1998

Impact and Penetration Simulations for Composite Wing-like Structures

The goal of this research project was to develop methodologies for the analysis of wing-like structures subjected to impact loadings. Low-speed impact causing either no damage or only minimal damage and high-speed impact causing severe laminate damage and possible penetration of the structure were to be considered during this research effort. To address this goal, an assessment of current analytical tools for impact analysis was performed. Assessment of the analytical tools for impact and penetration simulations with regard to accuracy, modeling, and damage modeling was considered as well as robustness, efficient, and usage in a wing design environment. Following a qualitative assessment, selected quantitative evaluations will be performed using the leading simulation tools. Based on this assessment, future research thrusts for impact and penetration simulation of composite wing-like structures were identified.

Knight, Norman F.↗
DOE OSTI2020

Functional metal–organic frameworks as effective sensors of gases and volatile compounds

Developing efficient sensor materials with superior performance for selective, fast and sensitive detection of gases and volatile organic compounds (VOCs) is essential for human health and environmental protection, through monitoring indoor and outdoor air pollutions, managing industrial processes, controlling food quality and assisting early diagnosis of diseases. Metal–organic frameworks (MOFs) are a unique type of crystalline and porous solid material constructed from metal nodes (metal ions or clusters) and functional organic ligands. They have been investigated extensively for possible use as high performance sensors for the detection of many different gases and VOCs in recent years, due to their large surface area, tunable pore size, functionalizable sites and intriguing properties, such as electrical conductivity, magnetism, ferroelectricity, luminescence and chromism. The high porosity of MOFs allows them to interact strongly with various analytes, including gases and VOCs, thus resulting in easily measurable responses to different physicochemical parameters. Although much of the recent work on MOF-based luminescent sensors have been summarized in several excellent reviews (up to 2018), a comprehensive overview of these materials for sensing gases and VOCs based on chemiresistive, magnetic, ferroelectric, and colorimertic mechanisms is missing. In this review, we highlight the most recent progress in developing MOF sensing and switching materials with an emphasis on sensing mechanisms based on electricity, magnetism, ferroelectricity and chromism. We provide a comprehensive analysis on the MOF–analyte interactions in these processes, which play a key role in the sensing performance of the MOF-based sensors and switches. We discuss in detail possible applications of MOF-based sensing and switching materials in detecting oxygen, water vapor, toxic industrial gases (such as hydrogen sulfide, ammonia, sulfur dioxide, nitrous oxide, carbon oxides and carbon disulfide) and VOCs (such as aromatic and aliphatic hydrocarbons, ketones, alcohols, aldehydes, chlorinated hydrocarbons and N,N'-dimethylformamide). Altogether, this review serves as a timely source of information and provides insight for the future development of advanced MOF materials as next-generation gas and VOC sensors.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Comparison of earth-based radio metric data strategies for deep space navigation

Spacecraft angular coordinates can be determined with a variety of radio tracking measurements, such as Doppler, range, and Very Long Baseline Interferometry (VLBI)-derived data types. A relatively new interferometric tracking technique under development is Connected Element Interferometry (CEI), which uses a single frequency standard, distributed to two antennas spaced 10 to 100 km apart, to make highly accurate measurements of the phase-delay of incoming radio signals. The angular navigation accuracies attainable with Doppler, range, CEI, and VLBI data strategies are compared, using simple analytic models for these data types. The measurement accuracies assumed for Doppler, range, and VLBI data represent the performance expected from these systems in the Magellan and Galileo missions, while the assumed CEI data accuracy represents the anticipated performance of an experimental connected element system being constructed at the Deep Space Network's Goldstone, California complex. The results indicate that the Galileo VLBI system can deliver 20- to 25-nrad accuracy throughout the ecliptic plane. A hypothetical CEI dual-baseline sysem at Goldstone yielded accuracies in the 35- to 50-nrad range, while another hypothetical Goldstone-based system, consisting of a single CEI baseline and an X-band (8.4 GHz) Doppler system, produced accuracies of 25 to 100 nrad. Angular accuracies obtained from Doppler and range were found to be highly dependent upon the sensitivity of earth-spacecraft differential acceleration to small changes in geocentric spacecraft position.

Thurman, Sam W.↗
NASA NTRS1990

Multi-disciplinary optimization of aeroservoelastic systems

Efficient analytical and computational tools for simultaneous optimal design of the structural and control components of aeroservoelastic systems are presented. The optimization objective is to achieve aircraft performance requirements and sufficient flutter and control stability margins with a minimal weight penalty and without violating the design constraints. Analytical sensitivity derivatives facilitate an efficient optimization process which allows a relatively large number of design variables. Standard finite element and unsteady aerodynamic routines are used to construct a modal data base. Minimum State aerodynamic approximations and dynamic residualization methods are used to construct a high accuracy, low order aeroservoelastic model. Sensitivity derivatives of flutter dynamic pressure, control stability margins and control effectiveness with respect to structural and control design variables are presented. The performance requirements are utilized by equality constraints which affect the sensitivity derivatives. A gradient-based optimization algorithm is used to minimize an overall cost function. A realistic numerical example of a composite wing with four controls is used to demonstrate the modeling technique, the optimization process, and their accuracy and efficiency.

Karpel, Mordechay↗
NASA NTRS1992

Multidisciplinary optimization of aeroservoelastic systems using reduced-size models

Efficient analytical and computational tools for simultaneous optimal design of the structural and control components of aeroservoelastic systems are presented. The optimization objective is to achieve aircraft performance requirements and sufficient flutter and control stability margins with a minimal weight penalty and without violating the design constraints. Analytical sensitivity derivatives facilitate an efficient optimization process which allows a relatively large number of design variables. Standard finite element and unsteady aerodynamic routines are used to construct a modal data base. Minimum State aerodynamic approximations and dynamic residualization methods are used to construct a high accuracy, low order aeroservoelastic model. Sensitivity derivatives of flutter dynamic pressure, control stability margins and control effectiveness with respect to structural and control design variables are presented. The performance requirements are utilized by equality constraints which affect the sensitivity derivatives. A gradient-based optimization algorithm is used to minimize an overall cost function. A realistic numerical example of a composite wing with four controls is used to demonstrate the modeling technique, the optimization process, and their accuracy and efficiency.

Karpel, Mordechay↗
NASA NTRS2016

Magnesium and Titanium Isotopic Compositions of an Unusual Hibonite-Perovskite Refractory Inclusion from Allende: It Is Fun

Introduction: Hibonite-rich refractory inclusions are among the first solids that formed in the solar nebula, and thus provide constraints on the earliest environment in the Solar System. An unusual hibonite-perovskite inclusion from Allende, SHAL, consists of a large (approximately 500 by 200 microns) single hibonite crystal and coexisting blocky perovskite (approximately 200 microns in size). The hibonite is characterized by chemical and oxygen isotopic compositions similar to those in the FUN (Fractionated and Unknown Nuclear anomalies) inclusion HAL. However, the rare earth element (REE) patterns measured at different spots of SHAL hibonite are highly variable, ranging from Group II-like (light REEs enriched relative to heavy REEs) to Group III-like (relatively flat with slight Eu depletions), but overall contrast largely with that of HAL, especially in the Ce and Yb abundances. This implies that SHAL hibonite formed and underwent distillation processes under more reducing conditions. Interestingly, the accompanying perovskite has uniform, unfractionated oxygen isotopic compositions (averaging delta (sup 17) O equals delta (sup 18) O equals −7 per mille) and REE abundances that are completely different from those of SHAL hibonite. This has been interpreted that perovskite and hibonite may not be co-genetic. Here we performed Al-Mg and Ti isotopic measurements of SHAL hibonite and perovskite to determine if the FUN characteristics are observed in these two isotope systems, and to further constrain the origin and evolution of SHAL. Results: Isotopic measurements of Al-Mg and Ti in SHAL were performed on the UCLA CAMECA ims-1290 ion microprobe by following the analytical protocols described in [1]. The Al-Mg and Ti data obtained in both terrestrial standards and SHAL hibonite and perovskite are shown below. Both SHAL hibonite and perovskite, despite very high (sup 27) Al to (sup 24) Mg ratios, are devoid of (sup 26) Mg excesses that can be attributed to the decay of (sup 26) Al. Delta (sup 25) Mg (mass-dependent fractionation) in hibonite is approximately −5 per mille per atomic mass unit relative to Madagascar hibonite, but is not well constrained for perovskite due to very large uncertainties owing to extremely low Mg contents. Similar to Mg isotopes, SHAL hibonite and perovskite show essentially the same Ti isotopic compositions, with anomalies in (sup 50) Ti of approximately 14 per mille, but the former shows greater Ti isotope fractionation than the latter (2.5 per mille per atomic mass unit versus 0 per mille). Discussion and Conclusions: The Al-Mg and Ti isotopic compositions of SHAL hibonite are consistent with those of HAL, suggesting that SHAL hibonite is a FUN inclusion and likely formed prior to homogenization of (sup 26) Al and Ti isotope variations in the solar nebula. However, the formation mechanisms for SHAL and HAL differ, given the differences in the REE patterns and degrees of oxygen mass-dependent fractionation. The Group-II to Group-III like REE patterns, the Yb depletions, and negative delta (sup 25) Mg observed in SHAL hibonite are all consistent with condensation of the hibonite precursor in a reducing environment.. The lack of large Ce depletions in SHAL hibonite implies that distillation processes that fractionated hibonite's oxygen isotopes must have taken place under a reducing condition, but the extent to which SHAL hibonite was distilled appears to be less than HAL because of the smaller degree of oxygen mass-dependent fractionation. The perovskite shares essentially the same Ti and Mg isotopic compositions as hibonite and probably formed in the same reservoir.. The ultrarefractory REE pattern seen in perovskite likely resulted from gas-solid fractionation which depleted HREEs in this reservoir. This process also explains why SHAL hibonite is generally depleted in HREEs relative to LREEs.

Liu, M.-C.↗
DOE OSTI2023

Operando studies reveal active Cu nanograins for CO 2 electroreduction

Carbon dioxide electroreduction facilitates the sustainable synthesis of fuels and chemicals. Although Cu enables CO 2 -to-multicarbon product (C 2+ ) conversion, the nature of the active sites under operating conditions remains elusive. Importantly, identifying active sites of high-performance Cu nanocatalysts necessitates nanoscale, time-resolved operando techniques. Here, we present a comprehensive investigation of the structural dynamics during the life cycle of Cu nanocatalysts. A 7 nm Cu nanoparticle ensemble evolves into metallic Cu nanograins during electrolysis before complete oxidation to single-crystal Cu 2 O nanocubes following post-electrolysis air exposure. Operando analytical and four-dimensional electrochemical liquid-cell scanning transmission electron microscopy shows the presence of metallic Cu nanograins under CO 2 reduction conditions. Correlated high-energy-resolution time-resolved X-ray spectroscopy suggests that metallic Cu, rich in nanograin boundaries, supports undercoordinated active sites for C–C coupling. Quantitative structure–activity correlation shows that a higher fraction of metallic Cu nanograins leads to higher C 2+ selectivity. A 7 nm Cu nanoparticle ensemble, with a unity fraction of active Cu nanograins, exhibits sixfold higher C 2+ selectivity than the 18 nm counterpart with one-third of active Cu nanograins. Importantly, the correlation of multimodal operando techniques serves as a powerful platform to advance our fundamental understanding of the complex structural evolution of nanocatalysts under electrochemical conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Lessons Learned in Employing Data Analytics to Predict Oxidation Kinetics and Spallation Behavior of High-Temperature NiCr-Based Alloys

Machine learning (ML) can offer many advantages in predicting material properties over traditional materials development methods based solely on limited experimental investigations or physical-based simulations with the capability to reduce development cost, risk, and time. However, so far, limited efforts have been made to predict alloy oxidation kinetics and spallation behavior via ML due to the lack of consistently measured and sufficient experimental data and the inherent complexity in oxidation behavior of multicomponent high-temperature alloys. A previous study reported the ability of ML to predict oxidation kinetics of NiCr-based alloys as a function of alloy composition and operating conditions. Here, the performance of a ML model in predicting rate constants and spallation probability was evaluated in light of the roles of the data distribution of the experimental dataset (data analytics), the alloy composition, the exposure environment and the chosen oxidation approach to extracting kinetic values from the measured mass changes (but using either a simple parabolic law or a statistical cyclic oxidation model). Potential strategies to improve the predictions and enhance the extrapolative capability of the previously trained model will be discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Perovskite Oxide–Halide Solid Solutions: A Platform for Electrocatalysts

The successful integration or hybridization of perovskite oxides with their halide cousins would enable the formation of both multi-anionic and multi-cationic solid solutions with unique metal-ion sites and synergistic properties that could potentially surpass the performance of classic perovskites. However, such solid solutions had not been produced previously owing to their distinct formation energies and different synthesis conditions. Solid solutions combining perovskite oxides with fluorides were produced in this study by mechanochemical synthesis. The obtained perovskite oxide–halide solid solutions had highly mixed elements and valences, uniform element distributions, and single-phase crystalline structures. In this work, the solid solution with an optimized combination of oxides and fluorides exhibited enhanced catalytic performance in the oxygen evolution reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Bio-inspired gas sensing: boosting performance with sensor optimization guided by “machine learning”

The performance of existing gas sensors often degrades in field conditions because of the loss of measurement accuracy in the presence of interferences. Thus, new sensing approaches are required with improved sensor selectivity. We are developing a new generation of gas sensors, known as multivariable sensors, that have several independent responses for multi-gas detection with a single sensor. In this study, we analyze the capabilities of natural and fabricated photonic three-dimensional (3-D) nanostructures as sensors for the detection of different gaseous species, such as vapors and non-condensable gases. We employed bare Morpho butterfly wing scales to control their gas selectivity with different illumination angles. Next, we chemically functionalized Morpho butterfly wing scales with a fluorinated silane to boost the response of these nanostructures to the vapors of interest and to suppress the response to ambient humidity. Further, we followed our previously developed design rules for sensing nanostructures and fabricated bioinspired inorganic 3-D nanostructures to achieve functionality beyond natural Morpho scales. These fabricated nanostructures have embedded catalytically active gold nanoparticles to operate at high temperatures of ≈300 °C for the detection of gases for solid oxide fuel cell (SOFC) applications. Our performance advances in the detection of multiple gaseous species with specific nanostructure designs were achieved by coupling the spectral responses of these nanostructures with machine learning (a.k.a. multivariate analysis, chemometrics) tools. Our newly acquired knowledge from studies of these natural and fabricated inorganic nanostructures coupled with machine learning data analytics allowed us to advance our design rules for sensing nanostructures toward the required gas selectivity for numerous gas monitoring scenarios at room and high temperatures for industrial, environmental, and other applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1996

On the Boundary Conditions at an Oscillating Contact Line: A Physical/Numerical Experimental Program

We will pursue an improved physical understanding and mathematical model for the boundary condition at an oscillating contact line at high Reynolds number. We expect that the body force is locally unimportant for earth-based systems, and that the local behavior may dominate the mechanics of partially-filled reservoirs in the microgravity environment. One important space-based application for this contact-line study is for Faraday-waves. Oscillations in the direction of gravity (or acceleration) can dominate the fluid motion during take-off and reentry with large steady-state accelerations and in orbit, where fluctuations on the order of 10(exp -4)g occur about a zero mean. Our experience with Faraday waves has shown them to be 'cleaner' than those produced by vertical or horizontal oscillation of walls. They are easier to model analytically or computationally, and they do not have strong vortex formation at the bottom of the plate. Hence many, if not most, of the experiments will be performed in this manner. The importance of contact lines in the microgravity environment is well established. We will compare high resolution measurements of the velocity field (lO micro-m resolution) using particle-tracking and particle-image velocimetry as the fluid/fluid interface is approached from the lower fluid. The spatial gradients in the deviation provide additional means to determine an improved boundary condition and a measure of the slip region. Dissipation, the size of the eddy near the contact line, and hysteresis will be measured and compare to linear and nonlinear models of viscous and irrotational but dissipative models.

Perlin, Marc↗
NASA NTRS2022

Modeling Broadband Phase Noise from Extended Targets in a 170 GHz Cloud-Imaging Radar

VIPR (Vapor Inside-cloud Profiling Radar) is a differential absorption radar operating over 155-175 GHz, covering a portion of the lower frequency flank of the 183 GHz water vapor absorption resonance. Transmitting at a ~1.9 mm wavelength, VIPR is highly sensitive to scattering from small particles comprising clouds and precipitation. Variation of VIPR’s cloud and precipitation echo power with frequency is often dominated by water vapor absorption, allowing humidity profiles to be retrieved along the radar’s beam path. One confounding effect in practical measurements is phase noise carried by the radar’s transmit signal, which can result in strong range sidelobes extending from bright targets and obscuring the echo signals of more weakly scattering clouds. Here we show that the magnitude and shape of phase-noise induced clutter from extended, bright cloud signals can be accurately modeled using a combination of empirical measurements of surface-echo phase noise and an analytic model based on the phase-noise sidelobe magnitude from a theoretical point target. This improved understanding of a potential clutter source in millimeter-wave imagine radar can lead to better performance modeling, and it provides motivation to improve the phase noise of very high frequency local oscillators.

Cooper, Ken B.↗
DOE OSTI2023

Halide Substitution Effects on Lithium-Ion Diffusion in Protonated Antiperovskites

Solid-state electrolytes (SSEs) for all-solid-state lithium-ion batteries are generating intense interest because these batteries can improve the safety and performance compared with devices fabricated with conventional, flammable liquid electrolytes. In these SSEs, it has been suggested that Li + ion diffusion in the grain boundaries is hindered and is a critical determinant of the overall ionic conductivity (σ). However, Li + ion diffusivities in the grain (D G ) and the grain boundary (D GB ) are difficult to determine experimentally, with few techniques capable of distinguishing the individual contributions. Here, we distinguished the D G and D GB for the protonated lithium antiperovskites (pLiAPs) SSEs: Li 2 OHCl, Li 2 OHBr, Li 2 OHF 0.1 Cl 0.9 , Li 2 OHF 0.1 Br 0.9 , and Li 2 OHCl 0.3 7Br 0.63 . The measurements were obtained directly from 7 Li pulsed-field gradient nuclear magnetic resonance (PFG-NMR) at 353 K. The 7 Li PFG-NMR echo profiles were composed of two primary components with additional secondary oscillatory components – the so-called NMR diffraction phenomenon. The length scale separating the two main components corresponds to a diffusion length of ~1.7 µm, which is thought to be the average grain size (by diameter). The short-range (≤ 1.7 µm) diffusion component associated with D G (≈10 -11 m 2 /s) varied minimally with halide substitution, while the long-range (≥ 1.7 µm) component D GB (≈10 -12 to 10 -15 m 2 /s) was highly sensitive to the substitution of halides and closely correlated with s. In addition, from the comparison of the ratio D GB /D G to D t (the Li + ion diffusion coefficient estimated from the rotational correlation time, t c ), it was determined that the contribution of D G to σ is negligible; 0.01 ~ 0.04 in the pLiAPs studied here. Finally, these insights provide fundamental understanding of the halide substitution effects on Li + ion grain versus grain boundary diffusion, and suggest that careful engineering of the grain boundaries at the microscopic level is necessary to achieve high-performance pLiAP SSEs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Turning Rubber into a Glass: Mechanical Reinforcement by Microphase Separation

Supramolecular associations provide a promising route to functional materials with properties such as self-healing, easy recyclability or extraordinary mechanical strength and toughness. The latter benefit especially from the transient character of the formed network, which enables dissipation of energy as well as regeneration of the internal structures. However, recent investigations revealed intrinsic limitations in the achievable mechanical enhancement. Here we present studies of a set of telechelic polymers with hydrogen-bonding chain ends exhibiting an extraordinarily high, almost glass-like, rubbery plateau. This is ascribed to the segregation of the associative ends into clusters and formation of an interfacial layer surrounding these clusters. An approach adopted from the field of polymer nanocomposites provides a quantitative description of the data and reveals the strongly altered mechanical properties of the polymer in the interfacial layer. These results demonstrate how employing phase separating dynamic bonds can lead to the creation of high-performance materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Chemically Cross-Linked Cellulose Nanocrystal Aerogels for Effective Removal of Cation Dye

In this study, porous aerogels were prepared by directional freeze-drying via cross-linking cellulose nanocrystals (CNCs) with poly(methyl vinyl ether-co-maleic acid) (PMVEMA) and poly(ethylene glycol) (PEG). The thermal properties and physical adsorption performance toward cation methylene blue dye of the obtained CNC aerogels were investigated. The maximum degradation temperature was increased from 324°C of CNCs to 355°C of cross-linked CNC aerogels. The dye adsorption isotherm results showed that the maximum methylene blue adsorption capacity of CNC aerogels was 116.2 mg g −1 , according to the Langmuir model, which was mainly due to the electrostatic attractions between negatively charged carboxyl groups or sulfonate groups on the CNC aerogles and cation MB molecules. The reusability test showed that the CNC aerogels contained the same dye adsorption performance in five adsorption/desorption cycles. Overall, this study described an ideal alternative for water purification with high dye adsorption capacity and enhanced physical performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A Probabilistic Model-Based Diagnostic Framework for Nuclear Engineering Systems

A fault diagnostic framework was investigated in this study for applications in thermal–hydraulic systems of nuclear power plants. The proposed framework consists of quantitative model-based diagnosis, statistical change detection and probabilistic reasoning. The use of physics-based diagnostic models provides high detection sensitivity and allows noise and measurement uncertainty to be incorporated robustly. Performance-related parametric models for each component are constructed based on first principles. Numerical model residuals are generated using the concept of analytical redundancy. Statistical change detection methods are employed to detect non-zero residuals in the presence of uncertainty. The diagnosis task is performed using Bayesian inference to detect and localize possible faults. Application to a single-phase heat exchanger for demonstration showed that the proposed probabilistic framework can provide improved results in comparison with traditional approaches while remaining less sensitive to false alarms in the presence of measurement and modeling uncertainty.

Bayesian network↗