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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Thickness threshold study of polyaniline-based lightning strike protection coating for carbon/glass fiber reinforced polymer composites

Different polyaniline (PANI) based lightning strike protection (LSP) coating thicknesses were tested against simulated lightning strike tests to evaluate the threshold thickness of the coating. A series of lightning strike tests were performed on carbon/glass fiber reinforced polymer (CFRP/GFRP) composites subjected to simulated lightning currents ranging from 40 to 100 kA. Five LSP-coated specimens were considered herein: two CFRP and three GFRP composites. A minimum of ~ 345 μm thick PANI-based LSP coating on CFRP and GFRP composites under a 40 kA peak current retained 83 % and 100 % residual strength, respectively. Additionally, GFRP specimens tested against 60 and 100 kA peak currents exhibited 100 % residual strength. Finally, this study proposes that a PANI-based LSP coating is suitable for protecting GFRP composites, while the careful design is necessary for CFRP composites to avoid any catastrophic failure.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Stochastic nonlinear analysis of unidirectional fiber composites using image-based microstructural uncertainty quantification

Here, we present a data-driven nonlinear uncertainty quantification and propagation framework to study the microstructure-induced stochastic performance of unidirectional (UD) carbon fiber reinforced polymer (CFRP) composites. The proposed approach integrates (1) microscopic image characterization, (2) stochastic microstructure reconstruction, and (3) efficient multiscale finite element simulations enabled by self-consistent clustering (SCA) analysis. To model the complex microstructural variability, the proposed UQ methods take the non-Gaussian uncertainty sources into account through a distribution-free sampling approach leveraging nonparametric and asymptotic statistical tools. A hierarchical conditional sampling strategy enables the simultaneous sampling of multiple sources of uncertainties. Our approach provides insights into the impact of microstructural variabilities, which are shown to have an increasing impact on the nonlinear responses of UD CFRP parts under progressive compression loading and ultimately on the failure rate over time. We discover that before CFRP parts start to fail, a characteristic time period emerges with distinctive uncertainty distributions specific to the microstructure variability and the probability of failure. Identifying the failure time period is crucial to the reliability prediction, which is an essential component of CFRP design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Accurate Prediction of Voltage of Battery Electrode Materials Using Attention-Based Graph Neural Networks

Performing first-principles calculations to discover electrodes’ properties in the large chemical space is a challenging task. While machine learning (ML) has been applied to effectively accelerate those discoveries, most of the applied methods ignore the materials’ spatial information and only use predefined features: based only on chemical compositions. Here, we propose two attention-based graph convolutional neural network techniques to learn the average voltage of electrodes. Our proposed methods, which combine both atomic composition and atomic coordinates in 3D-space, improve the accuracy in voltage prediction significantly when compared to composition-based ML models. The first model directly learns the chemical reaction of electrodes and metal ions to predict their average voltage, whereas the second model combines electrodes’ ML predicted formation energy (E form ) to compute their average voltage. Our E form -based model demonstrates improved accuracy in transferability from our subset of learned Li ions to Na ions. Moreover, we predicted the theoretical voltage of 10 Na x MPO 4 F (M = Ti, Cr, Fe, Cu, Mn, Co, and Ni) fluorophosphate battery frameworks, which are unavailable in the Material Project database. It could be shown that we can expect average voltages higher than 3.1 V from those Na battery frameworks except from the NaTiPO 4 F and TiPO 4 F pair of electrodes, which offer an average voltage of 1.32 V.

25 ENERGY STORAGE↗
DOE OSTI2020

Recent advancements of plant-based natural fiber–reinforced composites and their applications

Demands for reducing energy consumption and environmental impacts are the major driving factors for the development of natural fiber–reinforced composites (NFRCs) in many sectors. Compared with synthesized fiber, natural fiber provides several advantages in terms of biodegradability, light weight, low price, life-cycle superiority, and satisfactory mechanical properties. However, the inherent features of plant-based natural fibers have presented challenges to the development and application of NFRCs, such as variable fiber quality, limited mechanical properties, water absorption, low thermal stability, incompatibility with hydrophobic matrices, and propensity to agglomeration. Substantial research has recently been conducted to address these challenges for improved performance of NFRCs and their applications. This article reviews the recent advancements of plant-based NFRCs, focusing on strategies and breakthroughs in enhancing the NFRCs’ performance, including fiber modification, fiber hybridization, lignocellulosic fillers incorporation, conventional processing techniques, additive manufacturing (3D printing), and new fiber source exploration. In conclusion, the sustainability of plant-based NFRCs using life-cycle assessment and the burgeoning applications of NFRCs with emphasis on the automotive industry are also discussed.

3D reinforcement↗
DOE OSTI2024

Mechanical and Thermal Forcing for Upslope Flows and Cumulus Convection over the Sierras de Córdoba

Abstract The upslope flow processes affecting the vertical extent of orographic cumulus convection are examined using observations from the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. Specifically, clear air returns from the U.S. Department of Energy (DOE) second-generation C-band scanning Atmospheric Radiation Measurement (ARM) precipitation radar (CSAPR2) are used to characterize the structure and variability of the ridge-normal (i.e., up/downslope) flow components, which transport mass to the crest of Argentina’s Sierras de Córdoba and contribute to convective initiation. Data are compiled for the entire CACTI period (October–April), including days with clear skies, shallow cumuli, cumulus congestus, and deep convection. To examine shared variability among >70 000 radar scans, we use (i) a principal component analysis (PCA) to isolate modes of variability in the upslope flow and (ii) composite analysis based on convective outcomes, determined from GOES-16 satellite observations. These data are contextualized with observed surface sensible heat fluxes, thermodynamic profiles, and synoptic-scale analysis. Results indicate distinct thermally and mechanically forced upslope flow modes, modulated by diurnal heating and synoptic-scale variations, respectively. In some instances, there is a superposition of thermal and mechanical forcing, yielding either deeper or shallower upslope flow. The composite analyses based on satellite data show that successively deeper convective outcomes are associated with successively deeper upslope flow layers that more readily transport mass to the ridge crest in conjunction with lower lifting condensation levels, facilitating convective initiation. These results help to isolate the forcing mechanisms for orographic convection and thus provide a foundation for parameterizing orographic convective processes in coarse resolution models.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Environmental remediation with functional aerogels and xerogels

Several different types of aerogel and/or xerogel scaffolds have been demonstrated as effective sorbents for the capture and immobilization of radionuclides in gaseous form [e.g., iodine gas or I2(g), Xe] as well as ionic form (e.g., Ce4+, Cs+, I–, IO3-, Rb+, Sr2+, 99Tc7+, and U6+). These scaffolds have unique properties, which include high specific surface areas, high pore volumes, varieties of pore sizes, and functionalities that provide methods for binding radionuclides through physisorption, chemisorption, or a combination thereof. This combination of properties and functionalities make these types of materials ideal scaffolds for use as sorbents for capturing radionuclides. The primary base materials that will be discussed in this chapter include Ag0-functionalized silica aerogels, Ag+-impregnated aluminosilicate aerogels, Ag0-functionalized aluminosilicate aerogels, metal-impregnated (non-Ag) aluminosilicate aerogels and xerogels, sulfide-based aerogels, and carbon-based aerogel composites. For the capture of I2(g), the materials reported herein show some of the highest iodine loadings ever reported for inorganic sorbents. For the capture of ionic species, these materials also show promise to be some of the next generations of materials for active radionuclide remediation. This progress report will describe how these materials are fabricated, the general properties of these materials, as well as an overview of how they have been used for different applications in environmental remediation of radionuclides.

aerogel, xerogel, iodine, radionuclide remediation↗
DOE OSTI2022

An extrapolation method to remove spurious stress concentration in micromechanical analyses of composites using pixel-based meshes

It is easier to generate a finite element mesh of complicated geometries with voxel-based meshes compared to conformal meshes. However, the local stresses in voxel-based meshes are higher owing to artificial stress concentration caused due to jagged lines that approximate a curve. Here, we propose a method that accounts for this anomaly which would lead to accurate prediction of maximum von Mises stress in voxel-based meshes. The method is based on the variation of reciprocal of stresses and associated numerical gradient. The prediction of the proposed method is compared against the results of a conformal mesh by considering four two-dimensional example problems. The accuracy of the proposed method is verified using different mesh densities, material properties, and integration schemes. The proposed method was also implemented on a conformal mesh to verify that it filters out just the spurious stress concentration and not the realistic stress concentration.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Intermediate-Temperature Proton Exchange Membranes Based on Cerium Ultraphosphate Composited with Polybenzimidazole

This paper reports the rational fabrication and structural, thermal, mechanical and electrochemical characterization of a new type of intermediate-temperature (IT) polymer-inorganic composite (PIC) proton exchange membranes (PEMs) that are made of cerium ultraphosphate (CeP 5 O 14 —CUP) as the solid-state proton conductor composited with a high-temperature (HT) polybenzimidazole (PBI) as the polymeric binder. Here, flexible PBI-CUP PIC membranes with the thickness of ~135 μ m and CUP mass fraction of up to 75% were prepared by solution-casting without additional acid-doping (e.g., phosphoric acid). The proton conductivity of the fabricated IT-PIC-PEMs was up to 5.80 × 10 –2 S cm –1 as measured from a prototype IT PEM fuel cell (PEMFC) operated at 200 °C in the humidified hydrogen and air environment. This type of IT-PIC-PEMs also demonstrated sufficient mechanical strength and flexibility, excellent thermal stability (up to 350 °C), and very good durability of the proton conductivity (within the test duration of 500 h). The present experimental study shows the promising future of the IT-PIC-PEMs for applications in various IT electrochemical processes including IT-PEMFCs, IT-electrolyzers, etc.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Estimating Switchgrass Biomass Yield and Lignocellulose Composition from UAV-Based Indices

Innovative methods for estimating commercial-scale switchgrass yields and feedstock quality are essential to optimize harvest logistics and biorefinery efficiency for sustainable aviation fuel production. This study utilized vegetation indices (VIs) derived from multispectral images to predict biomass yield and lignocellulose concentrations of advanced bioenergy-type switchgrass cultivars (“Liberty” and “Independence”) under two N rates (28 and 56 kg N ha –1 ). Field-scale plots were arranged in a randomized complete block design (RCBD) and replicated three times at Urbana, IL. Multispectral images captured during the 2021–2023 growing seasons were used to extract VIs. The results show that linear and exponential models outperformed partial least square and random forest models, with mid-August imagery providing the best predictions for biomass, cellulose, and hemicellulose. The green normalized difference vegetation index (GNDVI) was the best univariate predictor for biomass yield (R 2 = 0.86), while a multivariate combination of the GNDVI and normalized difference red-edge index (NDRE) enhanced prediction accuracy (R 2 = 0.88). Cellulose was best predicted using the NDRE (R 2 = 0.53), whereas hemicellulose prediction was most effective with a multivariate model combining the GNDVI, NDRE, NDVI, and green ratio vegetation index (GRVI) (R 2 = 0.44). These findings demonstrate the potential of UAV-based VIs for the in-season estimation of biomass yield and cellulose concentration.

09 BIOMASS FUELS↗
DOE OSTI2025

Synthesis and Characterization of Soy Hull Biochar-Based Flexible Polyurethane Foam Composites

Flexible polyurethane foams are a diverse class of materials encompassing furniture, packaging, automotive, and many other industrial and domestic applications. Polyurethane foams are synthesized by the addition of polyols and isocyanates; however, the petroleum origin and toxic nature of isocyanates have driven many to look for more sustainable routes to production. Renewable fillers have emerged as a biobased resource to decrease the carbon footprint of this widely used polymeric material. In this study, soy hulls, as mass-produced, industrial by-products of soybean production, were used to create a biochar beneficial in the synthesis of flexible polyurethane foam composites. The addition of soy hull biochar was found to maintain the compression properties of foams at a decreasing isocyanate index, reducing the amount of isocyanates needed for production. In addition, the addition of biochar decreased the flammability of foams, important for many applications where consumer safety is important. The results point to the ability to create safer, more sustainable, and even more cost-effective polyurethane foams through the reduction in isocyanate use while maintaining the properties of this important class of polymers.

Chemistry↗
DOE OSTI2020

Durable polymer-aerogel based superhydrophobic coatings: a composite material

Provided are polymer-aerogel composite coatings, devices and articles including polymer-aerogel composite coatings, and methods for preparing the polymer-aerogel composite. The exemplary article can include a surface, wherein the surface includes at least one region and a polymer-aerogel composite coating disposed over the at least one region, wherein the polymer-aerogel composite coating has a water contact angle of at least about 140° and a contact angle hysteresis of less than about 1°. The polymer-aerogel composite coating can include a polymer and an ultra high water content catalyzed polysilicate aerogel, the polysilicate aerogel including a three dimensional network of silica particles having surface functional groups derivatized with a silylating agent and a plurality of pores.

Kissel, David J.↗
DOE OSTI2023

CO2 Sorption in Aminopolymer-Based Direct Air Capture Composites Through Fluorescent Detection

Aminopolymer-mesoporous oxide composites are becoming widely recognized for their ability to adsorb CO2 directly from the air. However, a better fundamental understanding of the nature of these materials under different environmental operating conditions will be necessary before they become ubiquitous in industrial direct air capture (DAC) systems. For example, gas diffusion in general is coupled with polymer segmental mobility in these composites; diffusion is therefore affected by interactions of the polymer with the pore wall of the mesoporous oxide, by the relative humidity of the air, and by electrostatic crosslinks that develop as a function of CO2 sorption. Disentangling these and additional complicated effects in order to better optimize operating conditions is a major challenge for the field. Here, we present a method for quantifying the adsorption of CO2 and moisture in a polyethylenimine (PEI) - Al2O3 composite using infrared sensing while we simultaneously monitor polymer mobility with a fluorescent probe molecule doped into the composite. Both the fluorescence intensity and shape of the emission spectra are strongly dependent on the mobility of the supporting medium. We monitor the polymer mobility and CO2 adsorption kinetics across a series of different relative humidities (RH) with this technique, and we observed that the relative difference between polymer mobility and sorption kinetics from one RH to the next are quite dramatic. We interpret these results and discuss how they can be used to inform the design of more efficient DAC systems for real-world operating conditions.

carbon capture↗