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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Super resolution for magneto-optical microscopy

Sub-diffraction limited magneto-optical microscopy, such as Kerr or Faraday effect microscopy, provide many advantages to fields of science and technology for measuring, or imaging, the magnetization structures and magnetization domains of materials. Disclosed is a method and system for performing sub-diffraction limited magneto-optic microscopy. The method includes positioning a microlens or microlens layer relative to a surface of a sample to image the surface of the sample, forming a photonic nanojet to probe the surface of the sample, and receiving light reflected by the surface of the sample or transmitted through the sample at an imaging sensor. The methods and associated systems and devices enable sub-diffraction limited imaging of magnetic domains at resolutions 2 to 8 times the classical diffraction limit.

te Velthuis, Suzanne Gabriëlle Everdine↗
NASA NTRS1971

Doping explosive materials for neutron radiographic enhancement.

Discussion of studies relating to the selection of doping materials of high neutron absorption usable for enhancing the neutron radiographic imaging of explosive mixtures, without interfering with the proper chemical reaction of the explosives. The results of the studies show that gadolinium oxide is an excellent material for doping explosive mixtures to enhance the neutron radiographic image.

Golliher, K. G.↗
NASA NTRS1997

Pulse-Echo Ultrasonic Imaging Method for Eliminating Sample Thickness Variation Effects

A pulse-echo, immersion method for ultrasonic evaluation of a material which accounts for and eliminates nonlevelness in the equipment set-up and sample thickness variation effects employs a single transducer and automatic scanning and digital imaging to obtain an image of a property of the material, such as pore fraction. The nonlevelness and thickness variation effects are accounted for by pre-scan adjustments of the time window to insure that the echoes received at each scan point are gated in the center of the window. This information is input into the scan file so that, during the automatic scanning for the material evaluation, each received echo is centered in its time window. A cross-correlation function calculates the velocity at each scan point, which is then proportionalized to a color or grey scale and displayed on a video screen.

Roth, Don J.↗
NASA NTRS1986

An imaging spectrometer for the investigation of Mars

Unmanned misions to Mars will employ imaging spectrometry to yield compositional data about the target body, through visual and IR measurements of the intensity and distribution of characteristic spectral signature features in the radiation that is emitted and reflected by surface materials. Attention is presently given to a modular imaging spectrometer design with applicability to a diverse range of planetary missions. This visual and IR mapping spectrometer has been tentatively selected for NASA's recently approved Mars Observer mission. Detailed optical characteristics and capabilities of the instrument are presented.

Duval, James E.↗
DOE OSTI2021

Mapping of inhomogeneous quasi-3D electrostatic field in electro-optic materials

Abstract This paper describes a new method for direct measurement and evaluation of the inhomogeneous electrostatic vector field with translational symmetry in electro-optic materials exhibiting the Pockels effect. It is based on the evaluation of maximum transmittance of low intensity light passing through a sample under a voltage bias. Here, the sample is located between rotating crossed polarizers, and camera images are obtained at each point to determine the electric field. The evaluation procedure is demonstrated using data acquired on a CdZnTeSe quasi-hemispheric semiconductor gamma-ray detector. In addition to CdTe-related compounds, the method can be used for various other materials showing $$\overline{4}3m$$ 4 ¯ 3 m symmetry such as GaAs, CdTe, GaP, 3C-SiC, and ZnS. Furthermore, it can be generalized to other crystalline materials showing the Pockels effect. The method can be used to probe the space charge and the electric field in several kinds of electronic components and devices, as well as provide useful data on the role of defects, contact configurations and other surface and bulk inhomogeneities in the material that can affect the distribution of the internal electric field.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Compression Analysis of Materials via in situ X-ray Computed Tomography

X-ray computed tomography (X-ray CT) is an analytical technique used in materials science to non– destructively characterize features in a variety of materials like polymers, metals, composites, and explosives. The non-destructive imaging allows for the analysis of features (voids and cracks), which give a fundamental understanding of material characteristics.This is more effective when combinedwith a load cell to expose the material to realworld stimuli to understand material characteristics and morphological behavior in situ. This study focused on using in situ X-ray CT to understand the material characteristics and morphological changes of sugar prills and a lattice under a compressive load. Sugar prills are used as a surrogate to analyze explosives in a safer and less expensiveway. The sugar prills were found to be brittle and shattered when compressed via the CT renderings and the stress/strain information. The lattices are used as both the basis and ground truth comparison for the development of models to predict the morphological and material characteristic changes that occur as a result of loading. The lattice was found to have weak regions due to low polymer interlayer fusion in these regions during the printing process. It was also found that under the initial compression the lattice demonstrated elastic behavior as its cellular structure was intact until the cellular structure started to collapse causing yielding in the lattice. Additionally, the analysis of the sugar prills and lattice demonstrate the information that can be gleaned from in situ X-ray CT experiments that would be lost in traditional pre- and post-mortem X-rayCT analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science

This presentation explores the transformative potential of autonomous electron microscopy and artificial intelligence (AI) in accelerating materials science discovery, particularly for energy applications and materials operating in extreme environments. We discuss pioneering self-driving laboratories at NREL designed to intelligently probe material synthesis and degradation across multiple scales, aiming to rapidly bridge the gap between atomic-level understanding and the development of high-performance, reliable materials. Utilizing advanced machine learning techniques, such as few-shot learning and multimodal analysis integrating imaging and spectroscopy, we demonstrate methods to extract actionable descriptors for material behavior, quantify complex microstructural evolution, and statistically link synthesis parameters to defect populations. This AI-driven approach promises to accelerate the creation of predictive materials tailored for specific missions, enabling faster development cycles and enhanced material assurance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science

This presentation explores the transformative potential of autonomous electron microscopy and artificial intelligence (AI) in accelerating materials science discovery, particularly for energy applications and materials operating in extreme environments. We discuss pioneering self-driving laboratories at NREL designed to intelligently probe material synthesis and degradation across multiple scales, aiming to rapidly bridge the gap between atomic-level understanding and the development of high-performance, reliable materials. Utilizing advanced machine learning techniques, such as few-shot learning and multimodal analysis integrating imaging and spectroscopy, we demonstrate methods to extract actionable descriptors for material behavior, quantify complex microstructural evolution, and statistically link synthesis parameters to defect populations. This AI-driven approach promises to accelerate the creation of predictive materials tailored for specific missions, enabling faster development cycles and enhanced material assurance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

System and method for sub micron additive manufacturing

An apparatus is disclosed for performing an additive manufacturing operation to form a structure by processing a photopolymer resist material. The apparatus may incorporate a laser for generating a laser beam, and a tunable mask for receiving the laser beam which has an optically dispersive element. The mask splits the laser beam into a plurality of emergent beams each having a subplurality of beamlets of varying or identical intensity, with each beamlet emerging from a unique subsection of illuminated regions of the mask. A collimator collimates at least one of the emergent beams to form a collimated beam. One or more focusing elements focuses the collimated beam into a focused beam which is projected as a focused image plane on or within the resist material. The focused beam simultaneously illuminates a layer of the resist material to process an entire layer in a parallel fashion.

Saha, Sourabh Kumar↗
DOE OSTI2024

Deep-Learning-Based Segmentation of Keyhole in In-Situ X-ray Imaging of Laser Powder Bed Fusion

In laser powder bed fusion processes, keyholes are the gaseous cavities formed where laser interacts with metal, and their morphologies play an important role in defect formation and the final product quality. The in-situ X-ray imaging technique can monitor the keyhole dynamics from the side and capture keyhole shapes in the X-ray image stream. Keyhole shapes in X-ray images are then often labeled by humans for analysis, which increasingly involves attempting to correlate keyhole shapes with defects using machine learning. However, such labeling is tedious, time-consuming, error-prone, and cannot be scaled to large data sets. To use keyhole shapes more readily as the input to machine learning methods, an automatic tool to identify keyhole regions is desirable. In this paper, a deep-learning-based computer vision tool that can automatically segment keyhole shapes out of X-ray images is presented. The pipeline contains a filtering method and an implementation of the BASNet deep learning model to semantically segment the keyhole morphologies out of X-ray images. The presented tool shows promising average accuracy of 91.24% for keyhole area, and 92.81% for boundary shape, for a range of test dataset conditions in Al6061 (and one AliSi10Mg) alloys, with 300 training images/labels and 100 testing images for each trial. Prospective users may apply the presently trained tool or a retrained version following the approach used here to automatically label keyhole shapes in large image sets.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Semi-automatic image annotation using 3D LiDAR projections and depth camera data

Efficient image annotation is necessary to utilize deep learning object recognition neural networks in nuclear safeguards, such as for the detection and localization of target objects like nuclear material containers (NMCs). This capability can help automate the inventory accounting of different types of NMCs within nuclear storage facilities. The conventional manual annotation process is labor-intensive and time-consuming, hindering the rapid deployment of deep learning models for NMC identifications. This paper introduces a novel semi-automatic method for annotating 2D images of nuclear material containers (NMCs) by combining 3D light detection and ranging (LiDAR) data with color and depth camera images collected from a handheld scan system. The annotation pipeline involves an operator manually marking new target objects on a LiDAR-generated map, and projecting these 3D locations to images, thereby automatically creating annotations from the projections. The semi-automatic approach significantly reduces manual efforts and the expertise in image annotation that is required to perform the task, allowing deep learning models to be trained on-site within a few hours. The paper compares the performance of models trained on datasets annotated through various methods, including semi-automatic, manual, and commercial annotation services. The evaluation demonstrates that the semi-automatic annotation method achieves comparable or superior results, with a mean average precision (mAP) above 0.9, showcasing its efficiency in training object recognition models. Additionally, the paper explores the application of the proposed method to instance segmentation, achieving promising results in detecting multiple types of NMCs in various formations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS1998

Sand Shear Band Thickness Measurements by Digital Imaging Techniques

Digital imaging analysis was used to study localized deformations in granular materials tested under plane strain condition. Two independent techniques were applied and compared. In the first, the digitized optical images of a grid printed on the latex membrane were used to measure the shear band orientation angle and thickness, and were found to be 54.5' and 3.01 mm respectively. The second technique involved introducing an ultra-low viscosity resin into the specimen in preparation for thin- sectioning and microscopic study of the internal fabric. A total of 24 microscopic images obtained from four thin sections were analyzed and void ratio variation was measured. The shear band thickness measurements from images located along the shear band axis (at two locations) were equal to 3.19 mm and 3.29 mm which are very close to the average value obtained from surface analysis. The study was then extended to investigate the effects of sand grain-size and properties, specimen density, and confining pressure on shear band thickness. It was found that the normalized shear band thickness decreases as grain-size and confining pressure increase and as density decreases. Finally, shear band thickness is highly influenced by the specimen dilatancy.

Alshibli, Khalid A.↗
NASA NTRS2011

Terahertz Computed Tomography of NASA Thermal Protection System Materials

A terahertz axial computed tomography system has been developed that uses time domain measurements in order to form cross-sectional image slices and three-dimensional volume renderings of terahertz-transparent materials. The system can inspect samples as large as 0.0283 cubic meters (1 cubic foot) with no safety concerns as for x-ray computed tomography. In this study, the system is evaluated for its ability to detect and characterize flat bottom holes, drilled holes, and embedded voids in foam materials utilized as thermal protection on the external fuel tanks for the Space Shuttle. X-ray micro-computed tomography was also performed on the samples to compare against the terahertz computed tomography results and better define embedded voids. Limits of detectability based on depth and size for the samples used in this study are loosely defined. Image sharpness and morphology characterization ability for terahertz computed tomography are qualitatively described.

Roth, D. J.↗
NASA NTRS1995

Pulse-echo ultrasonic imaging method for eliminating sample thickness variation effects

A pulse-echo, immersion method for ultrasonic evaluation of a material is discussed. It accounts for and eliminates nonlevelness in the equipment set-up and sample thickness variation effects employs a single transducer, automatic scanning and digital imaging to obtain an image of a property of the material, such as pore fraction. The nonlevelness and thickness variation effects are accounted for by pre-scan adjusments of the time window to insure that the echoes received at each scan point are gated in the center of the window. This information is input into the scan file so that, during the automatic scanning for the material evaluation, each received echo is centered in its time window. A cross-correlation function calculates the velocity at each scan point, which is then proportionalized to a color or grey scale and displayed on a video screen.

Roth, Don J.↗
DOE OSTI2020

Efficient Image Reconstruction Method for a Millimeter-wave Shoe Scanner

The Pacific Northwest National Laboratory (PNNL) has recently developed an active 3D microwave/millimeter-wave shoe scanner. This system is designed to detect threats concealed within the soles of common footwear. The system operates over the 10-40 GHz frequency range for excellent penetration of common materials. The system presents several challenges for efficient image reconstruction, including the thick dielectric window, multi-row linear arrays, and focusing close to the antenna elements. In this paper, an efficient back-projection reconstruction algorithm is presented that overcomes these challenges. Experimental imaging results are shown that demonstrate high-resolution imaging performance for this new scanner.

Sheen, David M.↗
DOE OSTI2025

Tunable Few-Layer van der Waals Crystals and Heterostructures as Emerging Energy and Quantum Materials (Final Technical Report)

2D and layered (van der Waals) semiconductors offer extraordinary opportunities for manipulating optically excited charge carriers, many-body excitations, and non-charge based quantum numbers. To date, research has focused on a limited group of materials, mostly transition metal dichalcogenides in the monolayer limit. Other van der Waals semiconductors, and especially few-layer to multilayer crystals and their heterostructures, carry large potential for the discovery of phenomena of interest for future energy and information technologies. But they remain largely unexplored, often due to a lack of access to high-quality materials and approaches for measuring their properties at the relevant scales. The goal of this project was to develop an EPSCoR-State/National Laboratory Partnership that addresses the challenges of preparing high-quality van der Waals semiconductors and of probing their structure, composition, and especially their optoelectronic and photonic properties, near the atomic scale using electron microscopy techniques. A central component of the project was the development of advanced methods for electron microscopy and electron-excited spectroscopy, taking advantage of unique samples as well as leading capabilities and expertise at the partner institutions. Efforts to advance leading-edge techniques was supported by ancillary developments, such as precision sample preparation for electron microscopy/spectroscopy, coordinated chemical imaging, and analytical electron microscopy. Experiments in materials synthesis and technique development were closely linked to theory and computation. The results obtained under this project yielded multifaceted benefits to the involved partners and their institutions, DOE-BES, the wider scientific community, and society at large, particularly in the State of Nebraska through dividends from knowledge and human capital generated under the project.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Thermal infrared satellite data for the study of tectonic features

Multispectral thermal infrared data from the NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) have been processed to evaluate their potential for mapping tectonic features. Day/night ratio data from 3 thermal bands between 3.7 and 12.0 microns were used to construct a thermal infrared color image that emphasizes heat retention differences in surface materials as a function of wavelength. The study area is an arid region of the Arabian Peninsula where lithologic units are widely exposed to satellite detectors. In spite of the coarse resolution of 1.1 km at nadir, the image of emitted radiation data contains prominent features that appear to relate to fault systems, unmapped extensions of fault systems, and drainage patterns that are lacking in AVHRR reflected radiation data.

Andre, C. G.↗