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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Field-resolved space–time characterization of few-cycle structured light pulses

Accompanied by the rapid development of ultrafast laser platforms in recent decades, the spatiotemporal manipulation of ultrashort laser pulses has attracted much attention due to the potential for cutting-edge applications of structured light, including optical tweezers, optical communications, super-resolution imaging, time-resolved spectroscopy in molecules and quantum materials, and strong-field physics. Today, techniques capable of characterizing the full spatial, temporal, and polarization state properties of structured light are strongly desired. Here, we demonstrate a technique, termed 3D TIPTOE, for characterizing structured mid-infrared waveforms, which uses only a two-dimensional silicon-based image sensor as both the detector and the nonlinear medium. By combining the advantages of the sub-cycle time resolution afforded by nonlinear excitation and the spatial resolution inherent to the two-dimensional sensor, the 3D TIPTOE technique allows full characterization of structured electric fields, significantly reducing the complexity of detection compared to other techniques. The validity of the technique is established by measuring both few-cycle Bessel–Gaussian pulses and radially polarized femtosecond vector beams.

Liu, Yangyang (ORCID:0000000335205332)↗
DOE OSTI2025

Generating multi-scale Li-ion battery cathode particles with radial grain architectures using stereological generative adversarial networks

Abstract Understanding structure-property relationships of Li-ion battery cathodes is crucial for optimizing rate-performance and cycle-life resilience. However, correlating the morphology of cathode particles, such as in LiNi0.8Mn0.1Co0.1O2 (NMC811), and their inner grain architecture with electrode performance is challenging, particularly, due to the significant length-scale difference between grain and particle sizes. Experimentally, it is not feasible to image such a high number of particles with full granular detail. A second challenge is that sufficiently high-resolution 3D imaging techniques remain expensive and are sparsely available at research institutions. Here, we present a stereological generative adversarial network-based model fitting approach to tackle this, that generates representative 3D information from 2D data, enabling characterization of materials in 3D using cost-effective 2D data. Once calibrated, this multi-scale model can rapidly generate virtual cathode particles that are statistically similar to experimental data, and thus is suitable for virtual characterization and materials testing through numerical simulations. A large dataset of simulated particles with inner grain architecture has been made publicly available.

25 ENERGY STORAGE↗
NASA NTRS2006

Automated objective characterization of visual field defects in 3D

A method and apparatus for electronically performing a visual field test for a patient. A visual field test pattern is displayed to the patient on an electronic display device and the patient's responses to the visual field test pattern are recorded. A visual field representation is generated from the patient's responses. The visual field representation is then used as an input into a variety of automated diagnostic processes. In one process, the visual field representation is used to generate a statistical description of the rapidity of change of a patient's visual field at the boundary of a visual field defect. In another process, the area of a visual field defect is calculated using the visual field representation. In another process, the visual field representation is used to generate a statistical description of the volume of a patient's visual field defect.

Fink, Wolfgang↗
NASA NTRS2019

A TID and SEE Characterization of Multi-Terabit COTS 3D NAND Flash

Single-event effects and total ionizing dose testing are described for a 32-layer NAND flash memory, in both SLC and MLC configurations, with special considerations for unique three-dimensional test results. Extraction of three-dimensional heavy-ion test data presents a unique visualization of angular effects in NAND flash. Pattern dependence differences between SLC and MLC mode are noted, along with slightly non-uniform angular cross-section results due to the complex volume. Finally, TID data under different operating and bias conditions shows that the failure point remains the higher-voltage erasure circuitry.

Flash Memory↗
DOE OSTI2025

Construction of 3D MHD pressure drop correlation and flow characterization in the contraction region of a fusion blanket manifold

Inlet and outlet manifolds are typical components of liquid metal (LM) blanket designs of a fusion power reactor to be used to distribute the LM flow into breeding channels and collect it at the exit of the blanket. High pressure loss in the magnetohydrodynamic (MHD) flows featuring abrupt geometrical changes is one of the main feasibility issues of such designs. Recently, optimization studies were conducted to construct 3D MHD pressure drop correlations for a LM flow in an electrically insulating manifold with gradual expansion. Here, the 3D computational approach developed in that study is applied to the outlet manifold featuring gradual contraction. A systematic analysis was performed with a total number of 135 flow cases computed with COMSOL Multiphysics for Hartmann numbers 1000 < Ha < 10,000, Reynolds numbers 100 < Re < 12,000, and contraction angles 45° < θ < 75° for a fixed contraction ratio of 4. The effects of Ha, Re and θ on the flow recirculation, development length and the total pressure drop were carefully examined. A linear regression analysis was used to determine the power rule of pressure drop coefficient k related to Ha and Re, demonstrating a good match with the Ludford layer theory. Eventually, a correlation for the 3D MHD pressure drop coefficient was constructed as a function of Ha, Re and θ. Further, the results were compared against the inlet manifold. It was found that the flow in the inlet manifold exhibits larger recirculation zones. In the investigated range of Ha, Re and θ, the pressure drop coefficient k of the LM MHD flow in the gradual contraction is only slightly lower (< 8 %) than that in the gradual expansion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A machine-learning approach to measure 3D sample properties from 2D Transmission Electron Microscopy images

Transmission Electron Microscopy (TEM) is a powerful tool for the characterization of materials at the nanoscale; however, its inherent two-dimensional (2D) nature poses significant challenges to accurately measure three-dimensional (3D) properties. We introduce a supervised machine-learning model that predicts 3D structural information, such as sample thickness and curvature, from a series of conventional 2D TEM images. The model, a U-Net convolutional neural network, is trained on a large synthetic dataset generated from dynamical diffraction simulations that model TEM’s complex, nonlinear image formation, accounting for sample thickness and curvature. This physically realistic framework enables exploration of a broad parameter space impractical to sample experimentally. We demonstrate that the trained model has accurate predictions for experimental single-crystal silicon samples, achieving performance comparable to established measurement techniques. This work highlights the critical role of robust, simulation-based training in overcoming the limitations of real-world imaging artifacts and inconsistent sample geometries. By integrating machine learning with numerical simulations, we offer an efficient and scalable framework for quantitative TEM analysis, paving the way for more sophisticated 3D characterization of complex materials.

Dynamical diffraction↗
NASA NTRSDate not supplied

MAB Phase Ceramics for Lunar Applications

During the ten-week internship my work focused on designing characterization protocol for 3D printed MAB phase ceramics on steel and Tiplates. I was mentored by Dr. Samuel Hocker of NASA and advised by Dr. Gupta from University of North Dakota. I also collaborated with Mackenzie Short from the University of North Dakota. The characterization protocol was divided into following steps; initially, we performed visual inspection of the plates. During this process, the coatings which spalled or delaminated were discarded for further evaluation. During the next step, we performed optical microscopy to discern and document surface features and porosities of the samples. We also noted some decomposition under the optical microscope as well. Thereafter, profilometry analysis was performed to understand the effect of power density on the surface roughness. Due to the deposited powder over the samples, the profilometry was inconclusive. We then cleaned the samples on the steel plate using ethanol and cotton swabs to wipe up the loose powder covering the samples. Detailed SEM analysis was then performed on the cleaned specimens. In parallel, the 3D printed samples on the Tiplate were cleaned by using an ultrasonic bath for 1h. Optical imaging showed that this cleaning process was more effective for cleaning except that small cracks propagated through the layered ceramics. The profilometry data gathered on the titanium plate after cleaning was more conclusive. The SEM data on the steel plate showed that there is decomposition at all wattages although at 100 W the extent of decomposition was lower. We are planning to characterize the steel samples after cleaning in ultrasonic bath for 5-10 min to minimize cracking during the cleaning process. In addition, we are also planning to study the fractured surface by SEM analysis.

Additive Manufacturing, Laser Powder Bed Fusion, S↗
NASA NTRS1995

Modeling and characterization of through-the-thickness properties of 3D woven composites

The through-the-thickness properties of three-dimensionally (3D) woven carbon/epoxy composites have been studied. The investigation aimed at the evaluation and development of test methodologies for the property characterization in the thickness direction, and the establishment of fiber architectures were studied: layer-to-layer Angle Interlock, through-the-thickness Orthogonal woven preform with surface pile was also designed and manufactured for the fabrication of tensile test coupons with integrated grips. All the preforms were infiltrated by the resin transfer molding technique. The microstructures of the composites were characterized along the warp and fill (weft) directions to determine the degree of yarn undulations, yarn cross-sectional shapes, and microstructural dimensions. These parameters were correlated to the fiber architecture. Specimens were designed and tested for the direct measurement of the through-the-thickness tensile, compressive and shear properties of the composites. Design optimization was conducted through the analysis of the stress fields within the specimen coupled with experimental verification. The experimentally-derived elastic properties in the thickness direction compared well with analytical predictions obtained from a volume averaging model.

Hartranft, Dru↗
NASA NTRS2019

A 3D-printed Broadband Millimeter Wave Absorber

We present the design, manufacturing technique, and characterization of a 3D-printed broadband graded index millimeter wave absorber. The absorber is additively manufactured using a fused filament fabrication (FFF) 3D printer out of a carbon-loaded high impact polystyrene (HIPS) filament and is designed using a space-filling curve to optimize manufacturability using said process. The absorber's reflectivity is measured from 63 GHz to 115 GHz and from 150 GHz to 215 GHz and is compared to electromagnetic simulations. The intended application is for terminating stray light in Cosmic Microwave Background (CMB) telescopes, and the absorber has been shown to survive cryogenic thermal cycling.

Matthew Petroff↗
NASA NTRSDate not supplied

3D Modeling of Solar-Type Stars to Characterize Stellar Jitter

Detection of Earth-mass planets requires measurements of radial velocity with extreme precision. To capture the tiny disturbances caused by a planet's motion, it is necessary to understand and characterize the host star’s turbulent dynamics in order to apply proper filtering to the observational data. We take advantage of current computational and technological capabilities to develop 3D realistic models of the stellar subsurface convection and atmospheres and thereby estimate the photospheric jitter. We have identified an initial set of target stars, obtained initial conditions using the MESA code, and obtained initial 3D radiative models of the stellar surfaces and atmospheres with a spatial resolution of 50km. We present initial 3D radiative hydrodynamic model results of the planet-hosting star HD209458.

SMD↗
NASA NTRS2015

Three-Dimensional Distribution of a Major Desert Dust Outbreak over East Asia in March 2008 Derived from IASI Satellite Observations

We describe the daily evolution of the three-dimensional (3D) structure of a major dust outbreak initiated by an extratropical cyclone over East Asia in early March 2008, using new aerosol retrievals derived from satellite observations of IASI (Infrared Atmospheric Sounding Interferometer). A novel auto-adaptive Tikhonov-Phillips-type approach called AEROIASI is used to retrieve vertical profiles of dust extinction coefficient at 10 microns for most cloud-free IASI pixels, both over land and ocean. The dust vertical distribution derived from AEROIASI is shown to agree remarkably well with along-track transects of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) spaceborne lidar vertical profiles (mean biases less than 110 meters, correlation of 0.95, and precision of 260 meters for mean altitudes of the dust layers). AEROIASI allows the daily characterization of the 3D transport pathways across East Asia of two dust plumes originating from the Gobi and North Chinese deserts. From AEROIASI retrievals, we provide evidence that (i) both dust plumes are transported over the Beijing region and the Yellow Sea as elevated layers above a shallow boundary layer, (ii) as they progress eastward, the dust layers are lifted up by the ascending motions near the core of the extratropical cyclone, and (iii) when being transported over the warm waters of the Japan Sea, turbulent mixing in the deep marine boundary layer leads to high dust concentrations down to the surface. AEROIASI observations and model simulations also show that the progression of the dust plumes across East Asia is tightly related to the advancing cold front of the extratropical cyclone.

Cuesta, Juan↗
NASA NTRS2017

A UAV-Based Fog Collector Design for Fine-Scale Aerobiological Sampling

Airborne microbes are found throughout the troposphere and into the stratosphere. Knowing how the activity of airborne microorganisms can alter water, carbon, and other geochemical cycles is vital to a full understanding of local and global ecosystems. Just as on the land or in the ocean, atmospheric regions vary in habitability; the underlying geochemical, climatic, and ecological dynamics must be characterized at different scales to be effectively modeled. Most aerobiological studies have focused on a high level: 'How high are airborne microbes found?' and 'How far can they travel?' Most fog and cloud water studies collect from stationary ground stations (point) or along flight transects (1D). To complement and provide context for this data, we have designed a UAV-based modified fog and cloud water collector to retrieve 4D-resolved samples for biological and chemical analysis.Our design uses a passive impacting collector hanging from a rigid rod suspended between two multi-rotor UAVs. The suspension design reduces the effect of turbulence and potential for contamination from the UAV downwash. The UAVs are currently modeled in a leader-follower configuration, taking advantage of recent advances in modular UAVs, UAV swarming, and flight planning.The collector itself is a hydrophobic mesh. Materials including Tyvek, PTFE, nylon, and polypropylene monofilament fabricated via laser cutting, CNC knife, or 3D printing were characterized for droplet collection efficiency using a benchtop atomizer and particle counter. Because the meshes can be easily and inexpensively fabricated, a set can be pre-sterilized and brought to the field for 'hot swapping' to decrease cross-contamination between flight sessions or use as negative controls.An onboard sensor and logging system records the time and location of each sample; when combined with flight tracking data, the samples can be resolved into a 4D volumetric map of the fog bank. Collected samples can be returned to the lab for a variety of analyses. Based on a review of existing flight studies, we have identified ion chromatography, metagenomic sequencing, cell staining and quantification, and ATP quantification as high-priority assays for implementation. Support for specific toxicology assays, such as methylmercury quantification, is also planned.

Design↗
NASA NTRS2016

A UAV-Based Fog Collector Design for Fine-Scale Aerobiological Sampling

Airborne microbes are found throughout the troposphere and into the stratosphere. Knowing how the activity of airborne microorganisms can alter water, carbon, and other geochemical cycles is vital to a full understanding of local and global ecosystems. Just as on the land or in the ocean, atmospheric regions vary in habitability; the underlying geochemical, climatic, and ecological dynamics must be characterized at different scales to be effectively modeled. Most aerobiological studies have focused on a high level: 'How high are airborne microbes found?' and 'How far can they travel?' Most fog and cloud water studies collect from stationary ground stations (point) or along flight transects (1D). To complement and provide context for this data, we have designed a UAV-based modified fog and cloud water collector to retrieve 4D-resolved samples for biological and chemical analysis.Our design uses a passive impacting collector hanging from a rigid rod suspended between two multi-rotor UAVs (Unmanned Aerial Vehicles). The suspension design reduces the effect of turbulence and potential for contamination from the UAV downwash. The UAVs are currently modeled in a leader-follower configuration, taking advantage of recent advances in modular UAVs, UAV swarming, and flight planning.The collector itself is a hydrophobic mesh. Materials including Tyvek, PTFE, nylon, and polypropylene monofilament fabricated via laser cutting, CNC knife, or 3D printing were characterized for droplet collection efficiency using a benchtop atomizer and particle counter. Because the meshes can be easily and inexpensively fabricated, a set can be pre-sterilized and brought to the field for 'hot swapping' to decrease cross-contamination between flight sessions or use as negative controls.An onboard sensor and logging system records the time and location of each sample; when combined with flight tracking data, the samples can be resolved into a 4D volumetric map of the fog bank. Collected samples can be returned to the lab for a variety of analyses. Based on a review of existing flight studies, we have identified ion chromatography, metagenomic sequencing, cell staining and quantification, and ATP quantification as high-priority assays for implementation. Support for specific toxicology assays, such as methyl-mercury quantification, is also planned.

Design↗
DOE OSTI2025

Automated Image Segmentation and Processing Pipeline Applied to X–Ray Computed Tomography Studies of Pitting Corrosion in Aluminum Wires

Understanding pitting corrosion is critical, yet its kinetics and morphology remain challenging to study from X-ray computed tomography (XCT) due to manual segmentation barriers. To address this, an automated pipeline leveraging deep learning for efficient large-scale XCT analysis is developed, revealing new corrosion insights. The pipeline enables pit segmentation, 3D reconstruction, statistical characterization, and a topological transformation for visualization. Here, the pipeline is applied to 87 648 XCT images capturing commercial purity aluminum (1100 Al) wire exposed to sodium chloride (NaCl) salt particles over a period of 122 h. The pipeline achieves complete feature extraction and statistical quantification across the entire XCT dataset, leveraging distributed computing environment for high efficiency. Global growth kinetics such as high-level stepwise sigmoidal volume loss patterns and granular individual pit developments are both captured for 36 detected pits. By combining automation, computer vision, and extensive XCT datasets, this research accelerates precise corrosion assessment to enable materials science discoveries at scale.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗
NASA NTRS1981

Three-dimensional periodic disturbances acting upon airfoils in cascade

A theory is developed for three-dimensional periodic gusts interacting with loaded airfoils. The unsteady disturbances are linearized with respect to the mean potential flow of the airfoils. The vorticity transport equation is then integrated analytically in a Lagrangian form. The vorticity vector shows strong variations in its magnitude and wavelength as it interacts with the flowfield of a lifting airfoil. The streamwise component of the vorticity increases significantly with flow acceleration and flow turning. For simplicity the rectangular fan approximation is used and a single Helmholtz-like equation is derived to characterize the unsteady 3D flowfield. This is a new and significant result. The present theory is first applied to symmetric airfoils.

Atassi, H.↗