SEARCH · Search NASA

Results for “Base Composition”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Interfacial Effects on the Dielectric Properties of Elastomer Composites and Nanocomposites

Elastomer-based composites and nanocomposites are discussed, with the emphasis on the filler and interfacial effects on their dynamics, and the resulting manifestation in their macroscopic dielectric or mechanical response. Specifically, selected polydimethylsiloxane (PDMS)/barium-titanate and styrene-butadiene rubber (SBR)/graphene oxide nanocomposites are discussed, as examples where controlled spatial distribution of filler (structured composites) gives rise to significantly different dielectric and thermomechanical behaviors. Also, ethylene–propylene–diene (EPDM)/carbon black (CB) composites are presented, as examples of systems that exhibit an abnormal temperature dependence of dielectric relaxation; and this response is discussed in the context of CB cluster polarization and quantified through a simple scaling model of the same. Finally, multi-filler EPDM/CB/ceramic elastomer nanocomposites are discussed, as examples of systems with antagonistic interfacial effects between conductive and dielectric fillers, as well as with strong interphase responses that can overwhelm the dielectric contributions from the fillers; in these systems, interphasial responses result in counter-intuitive dielectric behaviors and in strong deviations from standard design principles typically employed in the design of dielectric composite systems.

Li, Bo↗

DOE OSTI2024

A recyclable self-healing composite with advanced sensing property

Polymer-based composites frequently encounter damage, often lurking beneath the surface and proving challenges to their early detection and repair. While material-based sensors show promise for encoding self-sensing properties within these composites, their in situ healing and reprocessability remain significant challenges. Therefore, the overarching goal of this study is the creation of a reprocessable polymeric composite encoded with self-healing attributes and the ability to autonomously sense damage. At the core of this innovation are vitrimers, a polymeric material characterized by a covalently adaptive dynamic network responsive to external factors such as heat. They combine thermoset-like resilience with thermoplastic-like flowability on demand under external stimuli. We nanoengineer a polyester-based vitrimeric polymer by incorporating piezoresistive carbon nanotubes (CNTs) as reinforcing elements that not only enhance its mechanical strength but also create a percolation network within the composite, thereby enabling piezoresistive self-sensing properties, all the while preserving the intrinsic self-healing capabilities offered by the vitrimeric matrix. The fabrication process of the composite involves a solvent-free in situ polymerization method that combines epoxy and anhydride-containing monomers with ~ 0.1 wt.% of CNTs. Once it was established that the introduction of CNTs into the polymeric matrix did not compromise the mechanical properties of the composite, their strain-sensing properties were characterized by applying cyclic loading while measuring their electrical resistance. Strikingly, CNT-enhanced vitrimer composite consistently retains its mechanical and sensing properties through repeated cycles of reshaping and reprocessing, underscoring its potential as a robust distributed strain sensor. This polyester-based vitrimeric composite is also easily recyclable without harsh chemical treatments. Preliminary findings from this study conclusively demonstrate that the bulk composite boasts both self-sensing capabilities and in situ detect healing properties, charting a promising course towards the development of a mechanically resilient multifunctional composite that seamlessly integrates selfsensing and healing capabilities.

Rohewal, Sargun Singh↗

DOE OSTI2020

Application of a Null-Space Monte Carlo Flow Model Set to the Composite Analysis Base Case Fate and Transport Modeling

The Plateau to River Groundwater Model (P2R Model) is a groundwater flow and contaminant fate and transport (F&T) simulation model used to support remedial activities conducted by CH2M HILL Plateau Remediation Company at the Hanford Site in Washington State. Figure 1-1 illustrates the P2R Model extents, discretization, and boundary conditions. The P2R Model is utilized in the Composite Analysis (CA) for the Hanford Site as the computational engine for computing F&T predictions as described in CP-60406, Hanford Site Composite Analysis Technical Approach Description: Groundwater. The model simulates contaminants of concern within the saturated zone of the uppermost aquifer beneath the Central Plateau and downgradient to the Columbia River. CP-57037, Model Package Report for the Plateau to River Model Version 8.3, documents the current version of the P2R Model including a description of the conceptual site model, model development and calibration, and limitations to the model application. The overall objective of the saturated zone modeling effort is to provide a basis for making informed remedial action decisions based on descriptions of current and expected future contaminant concentrations in groundwater at decision points within and downgradient of the Central Plateau of the Hanford Site. Specifically, the purpose of this environmental calculation is to describe the application of the hydraulic property fields and recharge parameters documented in ECF-HANFORD-20-0027, Null Space Monte Carlo Evaluation of the Plateau to River Model, to the CA flow and fate and transport simulation results to quantify the uncertainty in the simulated results due to input parameter selection. Use of numerical groundwater models is always accompanied with uncertainty in the results produced by a model because models are approximations of reality. Thus, by definition, models lack the detail to fully represent observed behavior. Use of numerical techniques, such as a NSMC analysis, can help in identifying and quantifying the potential uncertainties associated with a numerical model such as the P2R Model. The result of NSCM analysis is a set of F&T simulations that provide an estimate of the range of possible outcomes that are used to quantify the uncertainty in simulated concentrations produced using the base case simulations. The simulated concentrations from all simulations will support calculation of the uncertainty of the total dose calculated in a separate calculation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Application of a Null-Space Monte Carlo Flow Model Set to the Composite Analysis Base Case Fate and Transport Modeling

The Plateau-to-River (P2R) Model is a groundwater flow and contaminant fate and transport (F&T) simulation model used to support remedial activities conducted by Central Plateau Cleanup Company (CPCCo) at the Hanford Site in Washington State. Figure 1 illustrates the P2R Model extents, discretization, and boundary conditions. The P2R Model is utilized in the composite analysis (CA) for the Hanford Site as the computational engine for computing F&T predictions as described in CP-60406, Hanford Site Composite Analysis Technical Approach Description: Groundwater. The model simulates contaminants of concern within the saturated zone of the uppermost aquifer beneath the Central Plateau and downgradient to the Columbia River. CP-57037, Model Package Report for the Plateau to River Model Version 8.3 documents the current version of the P2R Model including a description of the conceptual site model, model development and calibration, and limitations to the model application.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Carbon Nanotube and Graphene Oxide Reinforced Composites for Lightning Strike Protection of Composite Structures

Carbon fiber reinforced plastics (CFRP) composites have become the primary materials in the aerospace industry. Future transportation means, such as urban air mobility (UAM), will be employing CFRP structures. However, lightning strike damage on composite structures is a serious concern. CFRP composites possess low through-thickness electrical conductivity (≈ 1 S/m), which can cause extreme resistive heat in the event of lightning strikes. Research on polymeric lightning strike protection has gained momentum in the past few years. Researchers have studied various conductive fillers to improve the CFRP performance against lightning strikes. Carbon nanotubes (CNTs) and graphene oxide (GO) have been studied as future lightning Strike Protection (LSP) materials the most. The use of CNT and GO-based composites has shown improved mechanical properties and improved electrical conductivity of the composites. Researchers investigated CNTs and GO as the fillers to the matrix system, sizing the carbon fibers and the surface coating on top of the CFRP surface. This chapter highlights the remarkable improvement in the lightning damage suppression of CNT and GO-based composites and their structural applications. Special attention is given to their potential use as LSP material in future aircraft.

Kumar, Vipin↗

DOE OSTI2021

Thin-film composite membranes based on hyperbranched poly(ethylene oxide) for CO 2 /N 2 separation

Cross-linked amorphous poly(ethylene oxide) (XLPEO) is one of the leading membrane materials for post-combustion CO 2 capture. For example, XLPEO prepared from poly(ethylene glycol) methyl ether acrylate (PEGMEA) exhibited CO 2 permeability of 570 Barrer and CO 2 /N 2 selectivity of 41 at 35 °C. However, these XLPEOs cannot be dissolved in coating solutions, making it impossible to be fabricated into thin-film composite (TFC) membranes using state-of-the-art manufacturing processes. In this study, we synthesized high molecular weight yet soluble HPEO via atom transfer radical polymerization (ATRP). These polymers were thoroughly characterized and compared with XLPEO, including thermal transitions, free volumes, and pure-gas sorption and permeation properties. A polymer with the best combination of CO 2 permeability (540 Barrer) and CO 2 /N 2 selectivity (43) was fabricated into defect-free TFC membranes with a thickness as thin as 506 ± 44 nm. When challenged with simulated flue gas containing water vapor at 35 °C for over 100 h, the membrane shows stable CO 2 permeance of 850 GPU and CO 2 /N 2 selectivity of 37, comparable to the leading commercial membranes for carbon capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Structural stability of thin overhanging walls during material extrusion additive manufacturing of thermoset-based ink

Recent developments have enabled material extrusion additive manufacturing of thermoset-based composite inks on the large scale. In addition, printing out-of-plane components is of broad interest to the polymer material extrusion community. Here, we address some of the challenges associated with both large-scale and out-of-plane thermoset material extrusion additive manufacturing by studying the height at which thin overhanging walls collapse. Walls at a range of overhang angles were printed until they collapsed. An optical camera captured the profile of each wall throughout the print, allowing the collapse height to be identified and the geometric fidelity to the programmed angle to be evaluated. Using previously measured rheological properties, predictive models were generated to approximate the collapse height and profile of the deflected walls. First, an analytical model was created to predict the height at which the walls would yield. The analytical model assumes the walls exhibit a perfectly linear profile; however, experiments proved this assumption to be false. Therefore, a finite element simulation was developed to account for the elastic deflection that occurs during printing. The finite element simulation predicts both the yield height and the deflected profile after the deposition of each layer. For the properties of the thermoset ink used here, the yield height predicted by the analytical model and finite element simulation are virtually identical. These predictions match experimental data reasonably well, but minor errors are observed. Accounting for the fully plastic moment appears to explain the small mismatch between experimental data and predictions. Additionally, the finite element simulation provides an excellent prediction of the deflected profile before the wall begins to collapse. Finally, by demonstrating that the collapse height and deflected profile of thin overhanging walls can be predicted, this work illustrates how the soft viscoelastic properties of thermoset-based composite inks limit the scale of a key feature required to print some nonplanar components. It also provides a basis to tailor in-process curing systems to suppress deflection and collapse of thin overhanging walls.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Mechanical Properties of Polyisoprene-Based Elastomer Composites

Herein we have explored the origins of mechanical reinforcement in elastomers filled with polymer-grafted nanoparticles (NPs). The brush chains are constructed from the same monomers as the polymer melt, although they have different microstructures (i.e., different amounts of trans and cis isomers). The NPs display a variety of morphologies depending on variations in the graft density of the polymers, with these morphologies hardly changing when the matrix (and the grafts) is cross-linked using dicumyl peroxide (DCP). NMR measurements show that the cross-link densities depend only on the DCP content and are independent of NP morphologies. We find that the elastic moduli of these materials are strongly dependent on the NP morphology but that the maximum reinforcement occurs when the NPs percolate, in a manner where the cores are exposed enough to have strong enthalpic interactions; these interactions could either be due to direct core–core van der Waals attractions or due to bridging interactions driven by polymers adsorbed on adjacent NPs. The nonlinear mechanical response of these materials is less sensitive to changes in NP morphology and loading. These results emphasize the important role of the exposed NP surface in determining the moduli of cross-linked elastomers. This last aspect is apparently less relevant for the corresponding uncross-linked melts filled with NPs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Phase-Inversion Polymer Composite Separators Based on Hexagonal Boron Nitride Nanosheets for High-Temperature Lithium-Ion Batteries

Not provided.

energy storage (including batteries and capacitors↗

DOE OSTI2022

SERS-based ssDNA composition analysis with inhomogeneous peak broadening and reservoir computing

Surface-enhanced Raman spectroscopy employed in conjunction with post-processing machine learning methods is a promising technique for effective data analysis, allowing one to enhance the molecular and chemical composition analysis of information rich DNA molecules. In this work, we report on a room temperature inhomogeneous broadening as a function of the increased adenine concentration and employ this feature to develop one-dimensional and two dimensional chemical composition classification models of 200 long single stranded DNA sequences. Afterwards, we develop a reservoir computing chemical composition classification scheme of the same molecules and demonstrate enhanced performance that does not rely on manual feature identification.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Barium Chloride Based Pyrotechnic Compositions for Green Color Emissions

Here, we present research focusing on the green light emission using Barium chloride dihydrate (BaCl2.2H2O) as an emitter contrary to commonly used Ba(NO3)2, Ba(ClO3)2, BaCO3, etc. For this work, different compositions containing BaCl2.2H2O and other components acting as oxidant, fuel, etc. were made and analyzed using TGA and burning tests. The flame intensity was captured using a photocell attached with a green color filter. It was observed that the decomposition behavior and the flame intensity were strongly influenced by the ratio of barium chloride to the oxidizer and by the particle size of the pyrotechnic composition powder. Compositions having a higher amount of oxidizer were found to decompose faster and have a more intense flame color.

Kanitkar, Swarom↗

DOE OSTI2021

Localized superconcentrated electrolytes for silicon anodes

Localized superconcentrated electrolytes (LSEs) for use in systems with silicon-based or carbon/silicon composite-based anodes are disclosed. The LSEs include an active salt, a nonaqueous solvent in which the active salt is soluble, and a diluent in which the active salt has a solubility at least 10 times less than solubility of the active salt in the nonaqueous solvent. Systems including the LSEs also are disclosed.

Zhang, Ji-Guang↗

DOE OSTI2022

EFFECTS OF MECHANICAL RECYCLING ON CARBON FIBER-BASED HYBRID COMPOSITES

Explore the source record for details and available documents.

Rencheck, Mitch↗

DOE OSTI2022

Non-noble metal based electro-catalyst compositions for proton exchange membrane based water electrolysis and methods of making

The invention provides electro-catalyst compositions for an anode electrode of an acid mediated proton exchange membrane-based water electrolysis system. The compositions include a noble metal component selected from the group consisting of iridium oxide, ruthenium oxide, rhenium oxide and mixtures thereof, and a non-noble metal component selected from the group consisting of tantalum oxide, tin oxide, niobium oxide, titanium oxide, tungsten oxide, molybdenum oxide, yttrium oxide, scandium oxide, cooper oxide, zirconium oxide, nickel oxide and mixtures thereof. Further, the non-noble metal component can include a dopant. The dopant can be at least one element selected from Groups III, V, VI and VII of the Periodic Table. The compositions can be prepared using any solution based methods involving a surfactant approach or a sol gel approach. Further, the compositions are prepared using noble metal and non-noble metal precursors. Furthermore, a thin film containing the compositions can be deposited onto a substrate to form the anode electrode.

Kumta, Prashant N.↗

DOE OSTI2021

Hybrid of multi‐dimensional fillers for thermally enhanced polyamide 12 composites fabricated by selective laser sintering

Abstract Selective laser sintering (SLS) is an additive manufacturing technology that can provide a novel strategy to manufacture complex polymer‐based composites with tailored properties. In this study, polyamide 12 (PA12) composite powders based on Al 2 O 3 , boron nitride (BN), and carbon nanotubes (CNTs) were prepared via a two‐step mixing approach. Morphology characterization techniques indicated that the fillers were uniformly dispersed in the PA12 matrix as expected. Under the optimum 3D‐printing parameters, the fabrication of SLS parts with high filler loading could be obtained. With 40 wt% Al 2 O 3 , 8 wt% BN, and 2 wt% CNT hybrid fillers, the thermal conductivity of PA12 composites could reach 1.09 W/mK. It could be attributed to the synergistic effect of multi‐dimensional fillers to form dense and continuous thermal conduction paths. The factors influencing the performance of PA12 composites such as melting and crystallization behaviors, dielectric properties, and mechanical properties were also discussed. The results show that these composites have favorable dielectric and mechanical properties. Overall, the PA12 composites fabricated by SLS technology in this study exhibit excellent thermal management ability.

Yuan, Yue↗

DOE OSTI2020

New Predictive Capabilities for Nuclear Weapons in Composite Fires

The prevalence of flammable carbon-based composite airframe materials and their use in high-temperature nuclear weapon re-entry systems requires analysts to address the abnormal thermal environment hazards associated with composite material fires. These fires tend to burn very differently than conventional fuel fires, usually burning less intensely, but much longer. This could lead to challenges in understanding margins in classic safety themes. The technical challenges in modeling the phenomena associated with these new types of fires are considerable, but new models have been developed. Their predictions have been compared with well-documented measurements of a vertical porous burner fire, known as a "wall fire" (a "wall-fire" validation simulation is reflected in the figures below). These measurements were conducted at FMGlobal, a mutual insurance company with a strong fire risk management program, as part of an ongoing collaboration between Sandia and FMGlobal. To date, the "wall-fire" scenario has been set up and initial model assessments with grid refinement studies have been conducted focusing on mesh resolutions suitable for full weapon system simulations. This work will continue with further verification and validation tasks assessing the predictions of the new model. Future work will address specific aspects of the wall models that are lacking in their predictive ability.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2025

A deep learning and finite element approach for exploration of inverse structure–property designs of lightweight hybrid composites

Hybrid composites have important applications, such as high-performance and lightweight materials in aerospace and automotive industries. Hybrid composites utilize the synergy of diverse fillers to achieve desired material properties, but usually have more complicated microstructures. While topology optimization can optimize a particular property, designing hybrid composites for customized mechanical performances, e.g. full-range stress–strain curve, remains challenging. Here, a computational framework that integrated finite element analysis (FEA) and artificial intelligence (AI) methods of Conditional Generative Adversarial Networks (cGAN) deep learning and transfer learning was developed to establish inverse structure–property relationships and design tailor-made hybrid composites. Based on FEA-generated datasets of hybrid fiber-particle–matrix microstructures and their corresponding full-range stress–strain curves, a cGAN architecture was trained to generate tailored microstructures and establish structure–property relationships. Similarity in microstructural features and well-matched stress–strain curves based on the AI-generated composites were achieved. In conclusion, transfer learning was used to expand the pre-trained model for designing different materials systems.

Hybrid composites↗

DOE OSTI2024

Comparing plant litter molecular diversity assessed from proximate analysis and 13 C NMR spectroscopy

Accurate representation of the chemical diversity of litter in ecosystem-scale models is critical for improving predictions of decomposition rates and stabilization of plant material into soil organic matter. In this contribution, we conducted a systematic review to evaluate how conventional characterization of plant litter quality using proximate analysis compares with molecular-scale characterization using 13 C NMR spectroscopy. Using a molecular mixing model, we converted chemical shift regions from NMR into fractions of carbon (C) in five organic compound classes that are major constituents of plant material: carbohydrates, proteins, lignins, lipids, and carbonylic compounds. We found positive correlations between the acid soluble fraction and carbohydrates, and between the acid insoluble fraction and lignins. However, the acid-soluble fraction underestimated carbohydrates, and the acid insoluble fraction overestimated lignins by 243%. We identified two sources of uncertainties: i) disparities between litter chemical composition based on hydrolysability and actual chemical composition obtained from NMR and ii) conversion factors to translate proximate fractions into organic constituents. Both uncertainties are critical, potentially leading to misinterpretations of decay rates in litter decomposition models. Consequently, we recommend including explicit substrate chemistry data in the next generation of litter decomposition models.

59 BASIC BIOLOGICAL SCIENCES↗