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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Using ERF Devices to Control Deployments of Space Structures

A report proposes devices containing electrorheological fluids (ERFs) damper for controlling deployments of lightweight, flexible structures in outer space. The structures would include spring members that could be wound or compressed for compact stowage during transport. The ERF based damper would keep the structures compacted and/or regulate the speeds with which the structures would spring out for deployment. After deployment, ERF based dampening mechanism could be used to rigidize the structures or damp their vibrations. An experimental ERF deployment controlled structure described in the report comprised two metal carpenter s measuring tapes sandwiched together, held slightly apart by rubber-band spacers, and placed in a bag filled with an ERF. The viscosity of the ERF varied with the voltage applied to the tapes, such that it was possible to hold the tapes in the wound condition or slow the speed with which they sprung from the wound to the straight condition. The report describes several potential variations on the basic concept of an ERF-controlled structural member, including compartmentalization of the interior volume to prevent total loss of the ERF in case of a leak and the use of multiple, individually addressable electrode pairs to enable more localized control.

Bar-Cohen, Yoseph↗
DOE OSTI2021

Off-stoichiometric semiconductors Cu 1.33+x Zn 1.33-x In 1.33 Se 4 (x = 0, 0.1, 0.2 and 0.3): Synthesis, structure, and thermal and electrical properties

The synthesis, structure, and temperature dependent thermal and electrical properties of off-stoichiometric polycrystalline modified zinc blende quaternary chalcogenides Cu 1.33+x Zn 1.33-x In 1.33 Se 4 , where x = 0, 0.1, 0.2 and 0.3, are investigated. Temperature-dependent electrical properties reveal these compositions to be semiconductors with alteration of the carrier concentration and electrical transport via stoichiometric variation. The thermal conductivity is low for all specimens and intrinsic to these materials. First principles calculations are also reported in establishing a fundamental investigation that illustrates the large variation in stoichiometry that is possible in these materials. This stoichiometric variation results in the observed variation of the transport properties. Overall, the results presented reveal fundamental structure-property relationships in these quaternary chalcogenides, and provides a basis for further research into the viability for large stoichiometric variation in other materials that are of interest for technological applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Developing Procedures to Implement Geometric Imperfections Beyond Right Circular Cylindrical Shells in Finite Element Method Models

Analysis of aerospace structures is frequently conducted using nominal dimensions and frequently assumes ideal conditions in loading, contact, constraints, et cetera. Off-nominal dimensions and nonideal conditions, however, are present in all structures. These are the result of widely ranging causes from coefficient of thermal expansion mismatches, manufacturing tooling anomalies, to assembly procedures that inadvertently alter the structure. Specifically, geometric imperfections can have potentially significant influence on the response of a structural test article observed in an experiment versus the response given by a numerical simulation. The Python Tool for Implementing Geometric Imperfections in Reduced Structures (Py_TIGIRS) was previously presented as a set of Python scripts to calculate and implement as-manufactured geometric midsurface and thickness imperfections into finite element method (FEM) shell models of nominally right circular cylinders. By taking advantage of the simple shape of a right circular cylinder, interpolations of the measured data points were able to be performed along directions that aligned to the cylindrical coordinate system axes of the entire structure. By taking advantage of the shell representation of the real structure as opposed to modeling using a continuum representation, the thickness variation was able to be implemented by shell section definitions instead of having to modify the position of multiple nodes in the thickness direction. Py_TIGIRS is a useful tool that established a procedural example on how to implement geometric imperfections in right circular cylindrical shell structures. Three new procedures, each expanded from concepts established in Py_TIGIRS, are proposed for various test-article designs and are intended to broaden the range of structures that can be modeled with measured geometric imperfections in the structural analysis community. Each test-article design introduces new challenges to successfully implement geometric imperfections into a FEM model. The first test-article design consists of a carbon fiber reinforced polymer square plate with a hat-shaped stiffener co-cured on one side. This test-article design was for a novel seven-point bend test that was also previously presented. Manufacturing and cure-cycle imperfections are observed using digital image correlation (DIC) techniques. As thermal expansion coefficient mismatches between the plate and stiffener materials were anticipated, a thermal analysis study with continuum shell and solid elements was conducted to capture the global shape observed prior to testing. The second test-article design is of a similar hat-stiffened plate configuration, but with a side length ratio near 3:1 with elongation in the stiffener direction. The test article was used to characterize the response to uniaxial compressive loading in the direction of the stiffener. Due to differing manufacturing steps, a thermal analysis like the one developed for the seven-point bend configuration was unable to mimic the observed geometric imperfections. Instead, a strategy based on applying deformations directly to the structure during analysis was developed for continuum shell and solid element representation of a stiffened panel.

Geometric imperfections↗
DOE OSTI2025

Influences of shock imprinting on mix in a 3D-printed porous media

Mixing of materials in porous media can cause a significant impact on fusion yield as previously demonstrated by the National Ignition Facility (NIF) MARBLE Campaign. Initially, the reactants are separated, with deuterium in the lattice struts and a tritium gas fill in the voids. Lattice parameters such as the strut thickness and relative pitch, provide a control for the mix parameters in the experiment. Los Alamos National Laboratory’s (LANL) BOSQUE project looks to better understand how the mix of the reactants and shell materials impact the fusion burn and resultant yield on various laser platforms. xRAGE’s Eulerian hydrodynamics and adaptive mesh refinement (AMR) provide the unique ability to study the impacts of multiscale features of complex lattice structures. This modeling provides the ability to measure shock front variations as the wave progress’ through a given media. Initial conditions of the lattice are essential to accurately model mix and burn measured by experiment. By varying the initial orientation and densities of these lattice regions the early time dynamics of how the shock is launched into the system is changed and advocates for the study of resulting effects. In this work, we will study the sensitivities of shock effects in varying 3D printed geometric systems and how these shocks alter the structure and mix in the lattice. We will discuss both preliminary experimental results and simulations to help plan and constrain future experiments where we will study the impact of different lattice geometries and lattice bulk densities. This work concludes with the relative impacts of lattice geometries on shock speeds at different bulk densities and the resultant mix widths due to those shock interactions. We see agreement with theory at the higher end of our bulk density study, however, as we approach lower bulk density systems the dynamics of these interactions begin to change.

2 Photon Polymerization↗
DOE OSTI2023

Nanoscale chemical imaging with structured X-ray illumination

High-resolution imaging with compositional and chemical sensitivity is crucial for a wide range of scientific and engineering disciplines. Although synchrotron X-ray imaging through spectromicroscopy has been tremendously successful and broadly applied, it encounters challenges in achieving enhanced detection sensitivity, satisfactory spatial resolution, and high experimental throughput simultaneously. In this work, based on structured illumination, we develop a single-pixel X-ray imaging approach coupled with a generative image reconstruction model for mapping the compositional heterogeneity with nanoscale resolvability. This method integrates a full-field transmission X-ray microscope with an X-ray fluorescence detector and eliminates the need for nanoscale X-ray focusing and raster scanning. We experimentally demonstrate the effectiveness of our approach by imaging a battery sample composed of mixed cathode materials and successfully retrieving the compositional variations of the imaged cathode particles. Bridging the gap between structural and chemical characterizations using X-rays, this technique opens up vast opportunities in the fields of biology, environmental, and materials science, especially for radiation-sensitive samples.

Li, Jizhou↗
DOE OSTI2020

A Nonlocal Feature-Driven Exemplar-Based Approach for Image Inpainting

Here, we present a nonlocal variational image completion technique which admits simultaneous inpainting of multiple structures and textures in a unified framework. The recovery of geometric structures is achieved by using general convolution operators as a measure of behavior within an image. These are combined with a nonlocal exemplar-based approach to exploit the self-similarity of an image in the selected feature domains and to ensure the inpainting of textures. We also introduce an anisotropic patch distance metric to allow for better control of the feature selection within an image and present a nonlocal energy functional based on this metric. Finally, we derive an optimization algorithm for the proposed variational model and examine its validity experimentally with various test images.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Abundance inhomogeneities and atmospheric structure in CN-bimodal globular cluster giants

It has been suggested by several authors that the sodium and aluminum abundance variations correlating with CN-band strength, frequently observed in CN-bimodal globular cluster giants, could be spurious manifestations of different temperature structures in the 'CN-strong' and 'CN-weak' stars, caused by different molecular line blanketing related to the C, N, and O trio. For stellar parameters generally appropriate to giants in the intermediate metallicity CN-bimodal cluster M4, we demonstrate through new model atmosphere calculations, employing opacity sampling and spherical geometry, that the observed abundance anomalies cannot be the result of atmospheric temperature structure. Our results using spherical geometry are compared to identical calculations performed with plane-parallel geometry: the effects of atmospheric extension on derived abundances for all lines considered amount to less than 0.1 dex.

Drake, Jeremy J.↗
DOE OSTI2021

Disentangling ferroelectric domain wall geometries and pathways in dynamic piezoresponse force microscopy via unsupervised machine learning

In this work, domain switching pathways in ferroelectric materials visualized by dynamic piezoresponse force microscopy (PFM) are explored via variational autoencoder, which simplifies the elements of the observed domain structure, crucially allowing for rotational invariance, thereby reducing the variability of local polarization distributions to a small number of latent variables. For small sampling window sizes the latent space is degenerate, and variability is observed only in the direction of a single latent variable that can be identified with the presence of domain wall. For larger window sizes, the latent space is 2D, and the disentangled latent variables can be generally interpreted as the degree of switching and complexity of domain structure. Applied to multiple consecutive PFM images acquired while monitoring domain switching, the polarization switching mechanism can thus be visualized in the latent space, providing insight into domain evolution mechanisms and their correlation with the microstructure.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS2001

Detection and Characterization of Imperfections in Composite Pressure Vessels

The thermographic evaluation of composite structures for delaminations, disbonds, inclusions, porosity and microcracking has proven to be a valuable asset in the field of nondestructive testing. Coupling large area coverage, variable sensitivity and minimal surface contact with a photographic type image representation of structural anomalies; thermography has become a primary inspection method for composite structures. Thermography works well for locating both surface and subsurface defects in most composite systems ranging in thickness of up to 0.25 inch (0.64 cm) or more. The thermographic method for inspection of composite structures typically involves applying an external source of heat to the structure and then recording the changes in the surface heat profile manifested by embedded defects or by material property variations. If these temperature variations are large enough and an infrared camera with sufficient sensitivity is used, then the material or structural abnormality can be detected and referred back to its source. Interpreting the information given in a thermogram, can be a difficult task under ideal circumstances and extremely challenging in a real world setting. Variables including depth, thermal conductivity, orientation and size of the abnormality can all have a great influence on how its heat pattern will be seen by the imager. The work discussed in this paper illustrates how the microstructure of several commonly found defects in composite structures relate to their thermographic image counterpart. Two test cases are studied herein, including a large graphite/epoxy RP-1 fuel tank and a graphite composite cryogenic fuel feedline. The structures used in this study were designed to serve as manufacturing proof of concept specimens and to undergo hydroburst testing to verify manufacturing practices and structural design. Prior to hydrostatic testing the structures underwent 100% thermographic evaluation to ensure that no manufacturing or handling damage was present. Due to a large inclusion found in the feedline, it was pulled from service and dissected without performing the hydroproof The thermographic indications found in the RP-1 tank were below critical limits so it underwent a complete hydroproof loading series and finally a hydroburst. Following the hydroburst samples were cut from the tank in regions where thermography had located damage before the test. These regions were thermographically and then were cross-sectioned and photomicrographed.

Walker, James L.↗
NASA NTRS1992

Photoluminescence structure, and composition of laterally anodized porous Si

We have studied the photoluminescence (PL), structure, and composition of laterally anodized porous Si. Broad PL peaks were observed centered between about 620-720 nm with strong intensities measured from 500 to 860 nm. Macroscopic variations in PL intensities and peak positions are explained in terms of the structure and anodization process. Structural studies suggest that the PL appears to originate from a multilayered porous Si structure in which the top two layers are amorphous. X-ray diffraction spectra also suggest the presence of a significant amorphous phase. In addition to high concentrations of B and N, we have measured extremely high concentrations much greater than 10 exp 20 cu cm of H, C, O, and F. Our results indicate that laterally anodized porous Si does not fit the crystalline Si quantum wire model prevalent in the literature suggesting that some other structure is responsible for the observed luminescence.

Jung, K. H.↗
DOE OSTI2025

Synthetic Scientific Image Generation with VAE, GAN, and Diffusion Model Architectures

Generative AI (genAI) has emerged as a powerful tool for synthesizing diverse and complex image data, offering new possibilities for scientific imaging applications. This review presents a comprehensive comparative analysis of leading generative architectures, ranging from Variational Autoencoders (VAEs) to Generative Adversarial Networks (GANs) on through to Diffusion Models, in the context of scientific image synthesis. We examine each model's foundational principles, recent architectural advancements, and practical trade-offs. Our evaluation, conducted on domain-specific datasets including microCT scans of rocks and composite fibers, as well as high-resolution images of plant roots, integrates both quantitative metrics (SSIM, LPIPS, FID, CLIPScore) and expert-driven qualitative assessments. Results show that GANs, particularly StyleGAN, produce images with high perceptual quality and structural coherence. Diffusion-based models for inpainting and image variation, such as DALL-E 2, delivered high realism and semantic alignment but generally struggled in balancing visual fidelity with scientific accuracy. Importantly, our findings reveal limitations of standard quantitative metrics in capturing scientific relevance, underscoring the need for domain-expert validation. We conclude by discussing key challenges such as model interpretability, computational cost, and verification protocols, and discuss future directions where generative AI can drive innovation in data augmentation, simulation, and hypothesis generation in scientific research.

Generative Adversarial Networks↗
NASA NTRS1995

Corotating and transient structures of IMF at Venus and Earth orbits

Magnetometer data obtained from the Pioneer Venus orbiter (PVO) provide a unique data base for studying interplanetary magnetic field (IMF) structures at 0.7 AU. Comparison of the same structure observed at 0.7 and 1 AU provides information about the effects of stream interactions between these two distances. Besides, the PVO observations provide solar wind conditions at various longitude separations from the Sun-Earth line, because the orbital motion of Venus is about 0.6 deg/day faster than that of Earth. Thus, it is possible to examine the effects of time variations in the coronal conditions on the solar wind conditions by comparing corotating structures observed at Earth and those from the PVO at different longitude separations. Some results obtained so far are as follows. We have found several transient structures observed at both 0.7 and 1 AU, when the Sun, Venus, and Earth are closely aligned. Each event exhibits magnetic field variations very similar to each other between Venus and Earth, implying that the effects of stream interactions are small. The IMF sector boundaries were compared between the Venus and Earth orbits as typical examples of corotating structures. We have found both well-correlated and poorly-correlated structures depending on the longitude separation between the Earth and Venus, and on the persistence of the sector structures.

Marubashi, K.↗
DOE OSTI2026

Effect of 316 stainless steel powder processing conditions on microstructure

One parameter that has both economic and performance effects in the manufacturing of steel parts is the powder feedstock used. 316 L steel powder can be produced through water atomization or gas atomization, where both the powder size and the atomization process determine the cost of powder feedstock. Gas atomized powder is spherical and has a lower oxygen content than water atomized powder, making it the preferred choice for performance, but comes at a higher financial cost. Here, in this study, various 316 L powder batches are characterized to understand physical properties and microstructural variations. Density and flowability were determined using gas pycnometry and Hall flow tests. Powder morphology and porosity were qualitatively analyzed via optical microscopy and scanning electron microscopy, Finally, transmission electron microscopy was used to determine changes in phases present. Spherical gas atomized powder of 30–100 μm contained Mn$-$Si rich oxides both on the surface and within the matrix. Meanwhile, irregular water atomized powder 30 μm in diameter contained silicon oxides without manganese. All powder particles contained a nickel rich cellular structure which was shown to support the formation of additional phases. While literature has observed general microstructural features across 316 L powder particles, transmission electron microscopy (TEM) in this study has identified variations in precipitation and cell structures. Information regarding morphology, flowability, density, and phase distributions can be applied to understand variations in part consolidation, which will in turn show which powder aspects are significant for production.

Chemical segregation↗
DOE OSTI2022

Probing the Kinetic Origin of Varying Oxidative Stability of Ethyl- vs. Propyl-spaced Amines for Direct Air Capture

Amine-based adsorbents are promising for direct air capture of CO 2 , yet oxidative degradation remains a key unmitigated risk hindering wide-scale deployment. Borrowing wisdom from the basic auto-oxidation scheme, insights are gained into the underlying degradation mechanisms of polyamines by quantum chemical, advanced sampling simulations, adsorbent synthesis, and accelerated degradation experiments. The reaction kinetics of polyamines are contrasted with that of typical aliphatic polymers and they elucidate for the first time the critical role of aminoalkyl hydroperoxide decomposition in the oxidative degradation of amino-oligomers. The experimentally observed variation in oxidative stability of polyamines with different backbone structures is explained by the relationship between the local chemical structure and the free energy barrier of aminoalkyl hydroperoxide decomposition, suggesting that its energetics can be used as a descriptor to screen and design new polyamines with improved stability. In conclusion, the developed computational capability sheds light on radical-induced degradation chemistry of other organic functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Snow-corrected vegetation indices for improved gross primary productivity assessment in North American evergreen forests

North American evergreen forests cover large areas and influence the global carbon cycle. Satellite remote sensing has been used to track the phenology of ecosystem photosynthesis of these forests by detecting variation in vegetation optical properties associated with physiological and structural features, and most of these methods have been closely tied to vegetation greenness. However, in evergreens, the application of satellite data to monitor photosynthetic phenology is often limited by the lack of sensitivity of greenness-based indices. In this study, we identified 47 evergreen forest flux sites in North America that had MODIS observation overlapping with the flux tower records. We then calculated four vegetation indices using MODIS MAIAC data (MCD19A1), including NDVI, CCI, NIRv, and kNDVI, for the 47 flux sites and evaluated relationships between gross primary productivity (GPP) and vegetation indices across the North American evergreen forests. Our results showed that snow had substantial effects on the performance of all vegetation indices in tracking GPP phenology, particularly in the early spring when rapid changes occurred to both GPP and snow cover. Furthermore, different vegetation indices were affected differently, indicating contradictory and confounding effects of snow on these indices. After correcting for the snow effects, both CCI and NIRv performed well in tracking GPP phenology, albeit for different reasons. CCI is sensitive to seasonal changes in the relative levels of chlorophyll and carotenoid pigments, which are closely tied to GPP phenology in evergreens. NIRv is sensitive to the absorbed photosynthetically active radiation and to the contribution of deciduous components to the overall optical properties. We also found that correlations between GPP and vegetation indices varied among ecoregions and climate classes. In general, regions with pronounced seasonal GPP patterns had stronger correlations between GPP and greenness-based indices than regions with weaker seasonal GPP patterns. These biome differences were less pronounced for CCI. The snow artifacts and complementary vegetation index effects reported here should be considered in any large-scale studies of GPP using reflectance-based indices from optical satellites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

cis-p -Coumarates acylate the lignin sidechain in grasses and other plants

In this study, we present evidence that the lignins of grasses and other plants undergo partial acylation by cis-p-coumarate. Unlike the more widely observed trans-p-coumarates, cis-p -coumarates represent a novel acylation pattern on the lignin sidechains. The finding was substantiated by detailed NMR analyses (HSQC, HSQC-TOCSY, HMBC) and alkaline hydrolysis of the lignin isolated from abacá, a plant that exhibits substantial amounts of cis-p -coumarate. The presence of cis-p -coumarates broadens the range of groups known to acylate lignin sidechains and suggests that subtle variations in the acylation pattern can modulate the final structure and properties of the lignin. A broad survey of lignins from diverse plant species revealed that all lignins incorporating trans-p-coumarates also incorporated cis-p-coumarates, albeit in varying proportions. The cis-p-coumarate content ranged from 2 % to 12 % of the total p-coumarate units, depending on the plant species. As cis-p -coumarate is formed through the isomerization of trans-p-coumarate triggered by UV light, this transformation may occur at various stages, including at the free p-coumaric acid level, at the monolignol p-coumarate level, or directly within the lignin polymer. The potential pathways through which cis-p -coumaric acid becomes incorporated into the lignin are discussed.

NMR↗
DOE OSTI2025

Finite element modeling of electropolishing of radio frequency dipole Nb crab cavity in hydrofluoric-sulfuric acid electrolyte

The superior performance of niobium superconducting radio frequency (SRF) cavities is achieved through meticulous surface treatment, notably via chemical electropolishing, ensuring exceptionally smooth surfaces. While this technique has been extensively employed for cylindrically symmetric structures, addressing more intricate geometries poses significant challenges in achieving uniform polishing and controlled material removal, especially when moving away from retractable cathodes. This presents a multifaceted electrochemical, thermal, and fluid dynamics conundrum. A prime example is the 197 MHz radio frequency dipole (RFD) crabbing cavity proposed for the Electron Ion Collider (EIC) project, exemplifying such complex structures. Our groundbreaking work integrates the localized oxide thickness variation, considering its impact on current distribution and Joule heating, within the framework of multi-physics modeling using the COMSOL® simulation suite. This approach was applied to a comprehensive model of the RFD cavity, allowing us to investigate optimal external cooling water flow conditions necessary for achieving desirable outcomes. In conclusion, this illustrates the increasing utility of such multi-physics codes to greatly aid in designing solutions to challenging processing requirements for increasingly complex accelerator cavities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Decoding the proton’s gluonic density with lattice QCD-informed machine learning

We present a first machine learning-based decoding of the gluonic structure of the proton from lattice QCD using a variational autoencoder inverse mapper (VAIM). Harnessing the power of generative AI, we predict the parton distribution function (PDF) of the gluon given information on the reduced pseudo-Ioffe-time distributions (RpITDs) as calculated from an ensemble with lattice spacing a ≈ 0.09 fm and a pion mass of M π ≈ 310 MeV. The resulting gluon PDF is consistent with phenomenological global fits within uncertainties, particularly in the intermediate-to-high-x region where lattice data are most constraining. A subsequent correlation analysis confirms that the VAIM learns a meaningful latent representation, highlighting the potential of generative AI to bridge lattice QCD and phenomenological extractions within a unified analysis framework.

Gluon parton distribution function↗