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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Systems and methods for detecting metal ion concentrations in subjects

A method of selective detection of a concentration of a metal ion species in a subject is provided in which a biofluid sample is obtained from the subject. The biofluid sample is exposed to a functionalized porous aromatic polymer. The polymer selectively captures and concentrates the metal ion species from the biofluid. Subsequently, the biofluid is washed from the polymer. The polymer is then exposed to a solution comprising a colorimetric indicator that extracts the metal ion species from the washed polymer thereby changing a color of the solution as a function of an amount of the metal ion species in the polymer. The concentration of the metal ion species in the subject is then spectroscopically determined from the color of the solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Applying Anodic Stripping Voltammetry to Complex Wastewater Streams for Rapid Metal Detection (Final Report)

The overall objective of this project is the development of a lab-on-a-chip (LOC) electrochemical sensor capable of accurately measuring heavy metal (lead (Pb), cadmium (Cd), and arsenic (As)) concentrations in complex aqueous streams such as wastewater. The specific goals include: i) identify how heavy metal speciate and transform during the different stages of the wastewater treatment train, and explore pre-treatment methods that will de-complex heavy metals, making them available to ASV, ii) develop appropriate electrodes for ASV using organic/inorganic nanomaterials, and iii) integrate pre-treatment steps and specialized electrodes into an LOC sensor device capable of autonomously determining heavy metal concentrations in complex wastewater streams.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1998

Detection of Metallic Compounds in Rocket Plumes Using Ion Probes

This grant experimentally verified that ion probes can consistently detect metallic compounds in a hybrid rocket plume. Two electrostatic detection methods were tested. The first method used an unbiased ion probe. It responded to collisions or near collisions with charged particulates. The amplitude of the response to metallic ions always exceeded that of the combustion products. The second device was a cylindrical Gaussian surface that surrounded, but did not touch, the plume. A charge imbalance in the plume induced a current in cylinder that was detected by a sensitive amplifier. The probe was more sensitive to metallic compounds than the cylinder. However, the Gaussian cylinder demonstrated sufficient sensitivity to warrant serious future consideration. Since the cylinder is nonintrusive, it is particularly attractive. Apparently, ions formed during combustion transfer to the metallic impurities. The formation of these metallic ions slows the ion recombination rate and helps preserve charges in the plume. The electrostatic detectors, in turn, respond to the charges carried by the metallic impurities.

Dunn, Robert W.↗
DOE OSTI2025

Unimodal Imaging of Monovalent Metal-Chelator Complexes and Lipids by MALDI Imaging Mass Spectrometry

Careful regulation of monovalent metal ions (M + ) is necessary to maintain a functional cellular system. Of these ions, appropriate sodium (Na + ) and potassium (K + ) concentrations are particularly integral for electrochemical signaling, as well as the secondary transport of nutrients and waste. Dysregulation of M + homeostasis can disrupt these mechanisms, potentially influencing the metabolism of downstream biomolecules such as lipids. Thus, the relationship between M + abundances and related biomolecular distributions must be elucidated to better understand the physiology of healthy and disordered tissues. Traditional techniques for imaging biological metal distributions include SIMS, LA-ICP-MS, and XRF; however, these capabilities are limited to elemental analysis or the analysis of molecular fragments and must be paired with other modalities to visualize distributions of more complex biomolecules within the same or similar samples. Conversely, matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful tool often used for mapping such biomolecular distributions, but current methods are unable to detect metals within tissue. This study illustrates a novel methodology that adds metal detection to the MALDI IMS repertoire through which the simultaneous detection of M + metals and lipids is achievable. Using a robotic sprayer for homogeneous application, on-tissue deposition of the chelator deferiprone (DEF) enables subsequent detection of the ionizable metal-chelator complex by MALDI without hindering lipid detection. Our work provides proof-of-concept data for the simultaneous detection of K + , Na + , and intact lipids using MALDI IMS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

You Only Look Once v5 and Multi-Template Matching for Small-Crack Defect Detection on Metal Surfaces

This paper compares the performance of Deep Learning (DL) and multi-template matching (MTM) models for detecting small defects. DL models extract distinguishing features of objects but require a large dataset of images. In contrast, alternative computer vision techniques like MTM need a relatively small dataset. The lack of large datasets for small metal-surface defects has inhibited the adoption of automation in small-defect detection in remanufacturing settings. This motivated this preliminary study to compare template-based approaches, like MTM, with feature-based approaches, such as DL models, for small-defect detection on an initial laboratory and remanufacturing industry dataset. This study used You Only Look Once v5 (YOLOv5) as the DL model and compared its performance against the MTM model for small-crack detection. The findings of our preliminary investigation are as follows: (i) YOLOv5 demonstrated higher performance than MTM in detecting small cracks; (ii) an extra-large variant of YOLOv5 outperformed a small-size variant; (iii) the size and object variety of the data are crucial in achieving robust pre-trained weights for use in transfer learning; and (iv) enhanced image resolution contributes to precise object detection.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

From Quantum to Classical: Sensing Materials, Methods, and Platforms for Energy

This presentation covers several ongoing sensors projects at NETL, including the use of quantum sensors for energy sector applications (e.g. infrastructure monitoring, critical metal detection, grid modernization) as well as NETL-developed materials and platforms for detecting economically critical metals including rare earth elements, cobalt, and aluminum. Taken together, these projects demonstrate NETL's leadership in unleashing American energy through the development of high performance sensors for reliable energy production and consumption.

critical minerals↗
NASA NTRS2006

Optical Microscopy Techniques to Inspect for Metallic Whiskers

Metal surface finishes of tin, zinc and cadmium are often applied to electronic components, mechanical hardware and other structures. These finishes sometimes unpredictably may form metal whiskers over periods that can take from hours to months or even many years. The metal whiskers are crystalline structures commonly having uniform cross sectional area along their entire length. Typical whisker dimensions are nominally on the order of only a few microns (um) across while their lengths can extend from a few microns to several millimeters. Metal whiskers pose a reliability hazard to electronic systems primarily as an electrical shorting hazard. The extremely narrow dimensions of metal whiskers can make observation with optical techniques very challenging. The videos herein were compiled to demonstrate the complexities associated with optical microscope inspection of electronic and mechanical components and assemblies for the presence or absence of metal whiskers. The importance of magnification, light source and angle of illumination play critical roles in being able to detect metal whiskers when present. Furthermore, it is demonstrated how improper techniques can easily obscure detection. It is hoped that these videos will improve the probability of detecting metal whiskers with optical inspection techniques.

Brusse, Jay A.↗
NASA NTRS1991

Detection of metal stress in boreal forest species using the 0.67-micron chlorophyll absorption band

Several recent studies have shown that a shift of the red-edge inflection near 0.70 micron in vegetation reflectance spectra is an indicator of metal stress, partially attributable to changes in chlorophyll concentration. This 'red-edge shift', however, is difficult to detect and has been reported both toward longer (red) and shorter (blue) wavelengths. Our work demonstrates that direct measurement of the depth and width of the chlorophyll absorption band at 0.67 micron using digital feature extraction and absorption band characterization procedures developed for the analysis of mineral spectra is a more consistent indicator of metal stress. Additionally, the magnitude of these parameters is generally greater than that of the red edge shift and thus should be more amenable to detection and mapping using field and aircraft spectrometers.

Singhroy, Vernon H.↗
DOE OSTI2025

Utilization of Data Augmentation Techniques in Automated Inspection Systems for Defect Detection in Metals With Limited Data

Accurate identification of defects on metal surfaces is of great interest to many industry sectors, such as the automotive and aerospace industries. In contrast to conventional manual inspection techniques, recent automated inspection systems employ deep learning models trained to detect defects rapidly and precisely. The development of these models often requires a substantial image dataset to acquire adequate knowledge of defect features and enhance their predictive accuracy. When data is limited, augmentation techniques are often used to improve the precision and accuracy of defect detection systems. This study examined the prediction performance of two object detection models, namely Faster Region‐based Convolutional Neural Network (Faster R‐CNN) and You Only Look Once version 8 (YOLOv8), to identify dent defects in limited images of cast iron cylinder head surfaces. The original image set contains 46 images with 563 dents. To overcome limited data availability, common image augmentation techniques along with a copy‐paste method were applied. Results show that standard augmentation improved YOLOv8 accuracy by 8.00% and average precision (AP) by 3.00%. On the other hand, the copy‐paste technique achieved a 20.00% increase in accuracy and a 1% increase in AP with just 200 synthetic dents. Furthermore, these results provide support for using the copy‐paste augmentation strategy to enhance defect detection performance, with a limited dataset, contributing to more accurate defect identification in remanufacturing processes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Using 2.5D super-resolution to improve flaw detection in metal additive manufacturing parts

Industrial X-ray computed tomography (XCT) enables non-destructive inspection of additively manufactured (AM) parts, but high-resolution scanning requires long acquisition times and significant computational resources, limiting throughput in production environments. Super-resolution techniques can recover high-resolution information from low-resolution scans, but existing methods face a trade-off between 2D approaches that ignore inter-slice information and 3D methods that are computationally prohibitive for practical deployment. To address this trade-off, we propose a 2.5D deep learning-based super-resolution approach that uses seven neighbouring low-resolution slices to super-resolve the centre slice. This work evaluates the method on real XCT scans of steel AM parts, comparing reconstruction quality and flaw detection performance of 2D, 2.5D, and 3D ESRGAN-based super-resolution methods. Results demonstrate that 2.5D super-resolution significantly improves detection of small, process-induced flaws (e.g. porosity) compared to 2D methods, while avoiding the prohibitive computational burden of full 3D approaches. These findings provide initial evidence of 2.5D super-resolution as a practical, deployable solution for improving flaw detection in high-throughput industrial XCT inspection.

X-ray CT↗
NASA NTRS1986

Lidar detection of metallic species at the mesopause level

The measurement alkali species present in the atomic form at the mesopause level has been performed by lidar for more than ten years. Atomic and ionic calcium density profiles are obtained for 3 years by the same technique in the visible range, at 423 nm for atomic calcium, and 393 nm for ionic calcium Ca(+). The experimental set-up and the preliminary results have been presented elsewhere. The 423 nm wavelength is directly obtained by the emission of a dye laser pumped by the third harmonic of a Nd-YAG laser. For the generation of the 393 nm wavelength, frequency mixing was used: the emission at 624 nm of a dye laser pumped by the 2nd harmonic of a Nd-Yag laser is mixed with the fundamental infrared emission (remaining after frequency doubling), in a non-linear KDP crystal, which gives the 393 nm emission. The behavior of the two atomic species, calcium and sodium, which are in the same altitude range are compared. For 45% of the observations, no ionic calcium was detected: the ionic calcium abundance was thus below the detection threshold. Contrasting with the density profiles of the atomic species, sodium and calcium, the ionic calcium profile present important variations on small time scales. The main characteristics of theatomic and ionic calcium behaviors that can be deduced from the measurements made are given.

Granier, C.↗
NASA NTRS1977

Sulfur in lunar mare basalts as a function of bulk composition

Sulfur abundances and metallic iron abundances in 18 Apollo 12 mare basalts were determined. No correlation between sulfur abundance and metallic iron content was detected; metallic iron abundances are not primarily caused by S loss. Sulfur abundances, directly related to the bulk composition of the rocks and especially to the TiO2 content, increase with increasing degrees of fractionation and appear to result from S concentration in the melts during fractionation. Unlike the Apollo 17 melts, the Apollo 12 melts were unsaturated with respect to sulfide. Composition appears to control S content for Apollo 17 basalts, and cumulus processes may cause Fe-FeS enrichment.

Gibson, E. K., Jr.↗
DOE OSTI2021

Identification of Metal Stresses in Arabidopsis thaliana Using Hyperspectral Reflectance Imaging

Industrial accidents, such as the Fukushima and Chernobyl disasters, release harmful chemicals into the environment, covering large geographical areas. Natural flora may serve as biological sensors for detecting metal contamination, such as cesium. Spectral detection of plant stresses typically employs a few select wavelengths and often cannot distinguish between different stress phenotypes. In this study, we apply hyperspectral reflectance imaging in the visible and near-infrared along with multivariate curve resolution (MCR) analysis to identify unique spectral signatures of three stresses in Arabidopsis thaliana : salt, copper, and cesium. While all stress conditions result in common stress physiology, hyperspectral reflectance imaging and MCR analysis produced unique spectral signatures that enabled classification of each stress. As the level of potassium was previously shown to affect cesium stress in plants, the response of A. thaliana to cesium stress under variable levels of potassium was also investigated. Increased levels of potassium reduced the spectral response of A. thaliana to cesium and prevented changes to chloroplast cellular organization. While metal stress mechanisms may vary under different environmental conditions, this study demonstrates that hyperspectral reflectance imaging with MCR analysis can distinguish metal stress phenotypes, providing the potential to detect metal contamination across large geographical areas.

multivariate curve resolution↗
DOE OSTI2020

Soil Sample Plan in Support of the Site 300 Explosives Waste Treatment Facility Ecological Risk Assessment Pursuant to the Hazardous Waste Facility Permit, Part V, Special Condition #14 a-f. August 2020

The Department of Toxic Substances Control issued the Final Hazardous Waste Facility Permit to Lawrence Livermore National Laboratory, Site 300 in 2017. As part of the continual process to ensure waste treatment emissions are not impacting ecological receptors, LLNL analyzed soil samples in the vicinity of the Explosive Waste Treatment Facility (EWTF) Burn Units (i.e., Burn Cage and Burn Pan) and the Detonation Pad. Soil samples were analyzed by EPA Solid Waste 846 Methods for furans, explosives, metals, and semivolatile compounds. In all samples, furans, explosives, and semi-volatile organic compounds were not detected. Metals were detected at concentrations below background levels. This soil sample plan will sample the same four downwind areas of the Burn Units and the same downwind areas of the Detonation, as well as including four new sample locations. The four new locations will be located to the northeast and southwest of the Burn Units and Detonation (as shown in Figure 3). The constituents to be analyzed are in Tables 2 and 3. Perchlorate was not identified as a constituent of concern in the 2007 Soil Sampling Plan. However, for this plan, all soil samples will be analyzed for perchlorate. After completion of the sampling event, a soil sample report will be submitted to DTSC in accordance with requirements specified in the Hazardous Waste Facility Permit, Part V, Special Conditions 16 a-f. This proposed soil sampling plan will be fully implemented no later than one year after receiving DTSC approval, in accordance with the Hazardous Waste Facility Permit, Part V, Special Condition 15.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Soil Sample Workplan in Support of the Site 300 Explosives Waste Treatment Facility Ecological Risk Assessment Pursuant to the Hazardous Waste Facility Permit (Part V, Special Condition #14 a-f)

The Department of Toxic Substances Control issued the Final Hazardous Waste Facility Permit to Lawrence Livermore National Laboratory, Site 300 in 2017. As part of the continual process to ensure waste treatment emissions are not impacting ecological receptors, LLNL analyzed soil samples in the vicinity of the Explosive Waste Treatment Facility (EWTF) Burn Units (i.e., Burn Cage and Burn Pan) and the Detonation Pad. Soil samples were analyzed by EPA Solid Waste 846 Methods for furans, explosives, metals, and semi-volatile compounds. In all samples, furans, explosives, and semi-volatile organic compounds were not detected. Metals were detected at concentrations below background levels. This soil sample plan will sample the same four downwind areas of the Burn Units and the same downwind areas of the Detonation, as well as including four new sample locations. The four new locations will be located to the northeast and southwest of the Burn Units and Detonation (as shown in Figure 3). The constituents to be analyzed are in Tables 7 and 8. Perchlorate was not identified as a constituent of concern in the 2007 Soil Sampling Plan. However, for this plan, all soil samples will be analyzed for perchlorate. Nitrate and all CAM17 metals have been added to the sampling plan to comply with DTSC comments received in correspondence dated June 4, 2021. After completion of the sampling event, a soil sample report will be submitted to DTSC in accordance with requirements specified in the Hazardous Waste Facility Permit, Part V, Special Conditions 16 a-f. This proposed soil sampling plan will be fully implemented no later than one year after receiving DTSC approval, in accordance with the Hazardous Waste Facility Permit, Part V, Special Condition 15.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS2003

Detector Apparatus and Method

Transceiver and methods are included that are especially suitable for detecting metallic materials, such as metallic mines, within an environment. The transceiver includes a digital waveform generator used to transmit a signal into the environment and a receiver that produces a digital received signal. A tracking module preferably compares an in-phase and quadrature transmitted signal with an in-phase and quadrature received signal to produce a spectral transfer function of the magnetic transceiver over a selected range of frequencies. The transceiver initially preferably creates a reference transfer function which is then stored in a memory. Subsequently measured transfer functions will vary depending on the presence of metal in the environment which was not in the environment when the reference transfer function was determined. The system may be utilized in the presence of other antennas, metal, and electronics which may comprise a plastic mine detector for detecting plastic mines. Despite the additional antennas and other metallic materials that may be in the environment due to the plastic mine detector, the magnetic transceiver remains highly sensitive to metallic material which may be located in various portions of the environment and which may be detected by sweeping the detector over ground that may contain metals or mines.

Arndt, G. Dickey↗
NASA NTRS2004

Microwave-Spectral Signatures Would Reveal Concealed Objects

A proposed technique for locating concealed objects (especially small antipersonnel land mines) involves the acquisition and processing of spectral signatures over broad microwave frequency bands. This technique was conceived to overcome the weaknesses of older narrow- band electromagnetic techniques like ground-probing radar and low-frequency electromagnetic induction. Ground-probing radar is susceptible to false detections and/or interference caused by rocks, roots, air pockets, soil inhomogeneities, ice, liquid water, and miscellaneous buried objects other than those sought. Moreover, if the radar frequency happens to be one for which the permittivity of a sought object matches the permittivity of the surrounding soil or there is an unfavorable complex-amplitude addition of the radar reflection at the receiver, then the object is not detected. Low-frequency electromagnetic induction works well for detecting metallic objects, but the amounts of metal in plastic mines are often too small to be detectable. The potential advantage of the proposed technique arises from the fact that wideband spectral signatures generally contain more relevant information than do narrow-band signals. Consequently, spectral signatures could be used to make better decisions regarding whether concealed objects are present and whether they are the ones sought. In some cases, spectral signatures could provide information on the depths, sizes, shapes, and compositions of objects. An apparatus to implement the proposed technique (see Figure 1) could be assembled from equipment already in common use. Typically, such an apparatus would include a radio-frequency (RF) transmitter/receiver, a broad-band microwave antenna, and a fast personal computer loaded with appropriate software. In operation, the counter would be turned on, the antenna would be aimed at the ground or other mass suspected to contain a mine or other sought object, and the operating frequency would be swept over the band of interest.

Arndt, G.↗