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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 55 records · Page 3

Selective volatile organic compound gas sensor based on carbon nanotubes functionalized with ZnO nanoparticles

Here this paper describes the theory and results for a new class of low-cost chemoresistive gas sensors designed for selective hydrocarbon gas detection. The sensors utilize a multiwalled carbon nanotube (MWCNT) backbone functionalized with metal oxide nanocrystals. Specifically, nanoparticles were grown on the surface of the MWCNTs using atomic layer deposition. The crystallinity of the ZnO-MWCNTs' heterostructure was examined by using a high-resolution transmission electron microscope. The structure of the ZnO/MWCNTs was analyzed using a scanning electron microscope and energy dispersive x ray. The Hall effect measurement shows p-type characteristics of the MWCNTs, supporting the typical PN junction formation with n-type ZnO nanocrystals. The electron-donating ability of ZnO provided a strong response to the ppm levels of toluene at room temperature (25 °C) and showed strong selectivity with other volatile organic compound gases such as benzene, methane, and formaldehyde.

47 OTHER INSTRUMENTATION↗

Multiscale characterization and representation of variability in ceramic matrix composites

Low density, high strength, and high creep and oxidation resistance properties of ceramic matrix composites (CMCs) make them an ideal choice for use in extreme environments in space and military applications. This paper presents a detailed characterization study of structural and manufacturing flaws in Carbon fiber Silicon-Carbide-Nitride matrix (C/SiNC) CMCs at different length-scales. Energy-dispersive spectroscopy (EDS) is used for the chemical characterization of the material’s elemental constituents. High-resolution multiscale graphs obtained from scanning electron microscope (SEM) and confocal laser scanning microscope (LSM) are used to characterize the distribution and morphology of defects at different length scales. This is followed by the classification and quantification of the common manufacturing defects. An image processing algorithm based on the image segmentation process is developed to quantify the variability of various scale-dependent architectural parameters. Finally, a three-dimensional stochastic representative volume element (SRVE) generation algorithm is developed to provide precise representations of material textures at multiple length scales. The developed algorithm accurately accounts for material features and flaws based on a range of multiscale structural and defects characterization results.

36 MATERIALS SCIENCE↗

Material Compatibility of 3D Printed Polymer Composites with Low GWP Refrigerants

The recent development of 3D printing brings numerous opportunities to develop polymer heat exchangers with desired configurations and allows access to the new complex engineering design for better performance. To be used in the HVAC&R system, the compatibility of these materials to refrigerants needs to be thoroughly investigated and understood. This study tested the material compatibility of the printed polymer composites according to the ASHRAE Guideline 38 using metal pressure vessels. These printed parts were tested with R-134A, R-1234YF, R-1234ZE, R-1233ZD(E), and 32-3 MAF POE (10 wt.%) was used as the lubricants. The change in volume, mass, hardness, and mechanical properties was studied in detail. Different compatibility of the composites with refrigerants was observed when the composition of the composite changed. After exposure to refrigerants, the morphological and thermal properties were studied with the scanning electron microscope, thermogravimetric analysis, and differential scanning calorimetry to further reveal the influence of these refrigerants.

Li, Kai↗

Utah FORGE: Well 16A(78)-32 Core Analysis Results

This dataset features petrographic, X-Ray Diffraction (XRD), and Scanning Electron Microscopy Analyses of core samples from well 16A(78)-32, which serves as the injection well for the Utah FORGE Enhanced Geothermal System (EGS) project. In addition to an overview of the analysis, the following items have been included here: images of 21 entire thin sections in plane-polarized and cross-polarized light from 16 depths, scanning electron microscope back scatter electron photomosaic maps of 21 thin sections from 16 depths, bulk XRD data from 16 depths, clay-sized XRD patterns from 16 depths, an optical petrography report, and scanning electron microscopy and energy dispersive spectroscopy analyses of eight selected samples.

15 GEOTHERMAL ENERGY↗

In Situ and Operando Morphology Study of Germanium-Selenium Alloy Anode for Li-ion Batteries

Selenium-doped germanium (GeSe) micrometersized particles have been reported with good cycling performance and rate capability due to a Li-Se-Ge network formed during the first lithiation that provides a Li-ion fast pathway. To understand the effect of the Li-Se-Ge network at a high cycling rate, we monitored the morphology change of both pure Ge and GeSe particles during cycling with an in situ/operando focused-ion beam-scanning electron microscope method. Our results showed that the proposed inactive Li-Se-Ge network can provide fast Li-ion transport and also buffer volume variation, resulting in homogeneous volume change and uniform microstructural evolution.

germanium↗

Hyperspectral X-ray Imaging: Progress Towards Chemical Analysis in the SEM

The Hyperspectral X-ray Imaging (HXI) project will enable non-destructive chemical-state determination of nano-scale samples in the electron microscope for nuclear safeguards applications. To efficiently measure chemical state through electron-excited X-ray emission requires a combination of wide spectral bandwidth, high resolution, and high count rate capability. We are building a next-generation X-ray detector based on an array of transition edge sensors (TESs) to make these measurements possible and routine in the scanning electron microscope (SEM). Leveraging the large pixel densities afforded by microwave multiplexing readout and continuous, uninterrupted operation of a cryogen-free dilution refrigerator, this instrument will have efficiency to allow chemical species identification of nano-scale samples in hours instead of days to weeks. We describe prototype pixel designs for this HXI instrument, comprising three pixel types that will make up the hybrid TES array. Engineering design of the integrated HXI cryostat and SEM system is in progress, with full detector commissioning expected in Spring 2021 followed closely by full-scale integration with the SEM. Furthermore, we also report on the commissioning of a complementary TES-based X-ray emission spectroscopy platform for bulk samples to build a spectral library for HXI sample identification.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Using Fission-Track Radiography Coupled with Scanning Electron Microscopy for Efficient Identification of Solid-Phase Uranium Mineralogy at a Former Uranium Pilot Mill (Grand Junction, Colorado)

At a former uranium pilot mill in Grand Junction, Colorado, mine tailings and some subpile sediments were excavated to various depths to meet surface radiological standards, but residual solid-phase uranium below these excavation depths still occurs at concentrations above background. The combination of fission-track radiography and scanning electron microscope energy-dispersive X-ray spectroscopy (SEM-EDS) provides a uniquely efficient and quantitative way of determining mineralogic associations of uranium that can influence uranium mobility. After the creation of sample thin sections, a mica sheet is placed on those thin sections and irradiated in a nuclear research reactor. Decay of the irradiated uranium creates fission tracks that can be viewed with a microscope. The fission-track radiography images indicate thin section sample areas with elevated uranium that are focus areas for SEM-EDS work. EDS spectra provide quantitative elemental data that indicate the mineralogy of individual grains or grain coatings associated with the fission-track identification of elevated uranium. For the site in this study, the results indicated that uranium occurred (1) with coatings of aluminum–silicon (Al/Si) gel and gypsum, (2) dispersed in the unsaturated zone associated with evaporite-type salts, and (3) sorbed onto organic carbon. The Al/Si gel likely formed when low-pH waters were precipitated during calcite buffering, which in turn retained or precipitated trace amounts of Fe, As, U, V, Ca, and S. Understanding these mechanisms can help guide future laboratory and field-scale efforts in determining long-term uranium release rates to groundwater.

58 GEOSCIENCES↗

A study on the creep behavior of alloy 709 using in-situ scanning electron microscopy

In this research, an experimental evaluation of creep properties of Alloy 709 in the temperature range of 750–850 °C was undertaken. Alloy 709 is a novel austenitic stainless steel with 20% Cr and 25% Ni by wt% that was developed for application in structural components of nuclear power plants. Creep rupture tests were conducted in an in-situ heating-loading and Scanning Electron Microscope (SEM) unit equipped with Electron Backscatter Diffraction (EBSD) detector and Energy Dispersive Spectroscopy (EDS). “Real-time” creep damage mechanisms of Alloy 709 at various stresses and temperatures using a flat, un-notched sample with continuously reducing cross-section is studied so that the failure and maximum creep damage occurred at the center of the sample where the in-situ SEM imaging could be focused. Accelerated creep tests at temperatures and stresses above service conditions were performed by employing multiple blocks of constant loads where the loads were increased once the sample attained constant creep rate, indicating a secondary creep regime. This technique ensures multiple data points can be obtained from the same test, saves the time required for an otherwise long-term creep test and usage of SEM. Further, Coincident Site Lattice (CSL) boundary maps were collected as control maps before testing, and the grain boundaries were observed during the creep test to understand the effect of grain boundary character on the creep damage mechanism. Void growth, grain boundary separation, and sliding were found to be the main creep mechanisms whose rate is dependent on stress and temperature. Failure mechanisms studied on the fracture surface using SEM fractography were correlated to the sample surface observations to create complementary information to better understand the underline creep mechanism of Alloy 709.

36 MATERIALS SCIENCE↗

Major to trace element imaging and analysis of iron age glasses using stage scanning in the analytical dual beam microscope (tandem)

Dark and clear silicate glasses formed during an iron age vitrification event ≈ 1500 years ago at the Broborg hillfort near Uppsala, Sweden have been analyzed using a scanning electron microscope equipped with a micro-X-ray fluorescence (μXRF) spectrometer. Correlated µXRF and electron beam-induced energy dispersive spectrometry (EDS) X-ray maps were collected via stage-scanning at constant velocity. This coupled procedure represents a new approach for the cultural heritage community to conduct analytical studies of archaeometric specimens composed of metal, ceramic, or mixed inorganic/organic materials, where major and trace element compositions are registered in space for areas up to the centimeter-length scale at micrometer-scale resolution. Overview images were used to select areas for EDS beam scan maps correlated with multispectral cathodoluminescence (CL) imaging and co-located quantitative EDS and μXRF point analysis. Fe, Ca, Mg, Ti, P, Mn, Zr, Zn, and Y are enriched in the dark glass, while Si, Al, K, Na, Ba, Sr, Rb, and Ga are enriched in the clear glass. Unmelted material is comprised predominately of quartz (SiO 2 ) along with trace apatite (Ca 5 (PO 4 ) 3 [Cl,OH]) and zircon (ZrSiO 4 ). Multivariate statistical analysis was used to measure the area fractions of high variance components while lower variance components represented phase mixtures. Differences between calculated melt viscosities for the glass compositions are consistent with field and laboratory observations. Coupled large area EDS and μXRF imaging shows significant promise for informed selection of higher spatial resolution and higher sensitivity follow-up studies, e.g., those performed using synchrotron analysis.

36 MATERIALS SCIENCE↗

Plasma Focused Ion Beam Nanothermometry

In this report we detail demonstration of temperature dependent effects on grayscale intensity imaged in Focused Ion Beam (FIB) microscope, as well as secondary electron (SE) dependence on temperature in the Auger Electron Spectroscopy (AES) and a Scanning Electron Microscope (SEM). In each instrument an intrinsic silicon sample is imaged at multiple temperatures over the course of each experiment. The grayscale intensity is shown to scale with sample temperature. Sample preparation procedures are discussed, along with hypothesized explanations for unsuccessful trials. Anticipated outcomes and future directions for these measurements are also detailed.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

FY23 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

Algorithms for Machine Learning (ML) and data analysis for the 3013 Surveillance Program have been developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). The objective of the algorithms is to automate the identification of corrosion and crack formation in the Inner Container Closure Weld Region (ICCWR) of the canister system used to store Pu-bearing material. Data for corrosion and cracking is collected from large binary files generated by a Laser Confocal Microscope (LCM), the Wide Area 3D Measurement System (WAMS), and in a recent proposal, by a Scanning Electron Microscope (SEM). The ML software uses the physical attributes in the data files (e.g., one or all of: height, color, and grayscale values as functions of position in a plane projection) to detect the presence of surface corrosion and cracking after being trained on similar data with the features to be detected labeled.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

FY24 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

Algorithms for Machine Learning (ML) and data analysis for the 3013 Surveillance Program have been developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). The objective of the algorithms is to automate the identification of corrosion and crack formation in the Inner Container Closure Weld Region (ICCWR) of the canister system used to store Pu-bearing material. Data for corrosion and cracking is collected from large binary files generated by a Laser Confocal Microscope (LCM), the Wide Area 3D Measurement System (WAMS), or,in a recent proposal, by a Scanning Electron Microscope (SEM). The ML software uses the physical attributes in the data files (e.g., one or more of: height, color, and 16-bit grayscale values as functions of position in a plane projection) to detect signs of surface corrosion and cracking after being trained on similar data, with the features to be detected. Although the initial scope included screening for broader indicators of corrosion, e.g., pitting, identification of potential cracks was prioritized for the past several years at the request of program leadership. Labeled training data is essential to developing the ML algorithm, and enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the large volume of data required to train ML algorithms and the relative rarity of cracks in the ICCWR data set. The updated program will read binary data from either LCM, WAMS or SEM files, interrogate data attributes, facilitate user labeling of data for training ML algorithms, execute ML algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. In FY24, hourglass neural networks (HNNs) that were initiated in FY22 were further developed and tested using available LCM data, and their performance was tested against that of the alternative U-Net Neural Network algorithm structure. HNNs along with previously developed Convolutional Neural Networks (CNNs) and Deep Neural Networks (DNNs) comprise a suite of ML tools for identification of cracks in the ICCWR

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

FY25 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

Algorithms for Machine Learning (ML) and image analysis for the 3013 Surveillance Program have been developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). The objective of the algorithms is to automate the identification of corrosion and cracks in the Inner Container Closure Weld Region (ICCWR) of the canister system used to store Pu-bearing material. Data for corrosion and cracking is collected from large binary files generated by a Laser Confocal Microscope (LCM), the Wide Area 3D Measurement System (WAMS), or, in a recent proposal, by a Scanning Electron Microscope (SEM). The ML software uses the physical attributes in the data files (e.g., one or more of: height, color, and 16-bit grayscale values as functions of position in a plane projection) to detect signs of surface corrosion and cracking after being trained on similar data with the features to be detected. Although the initial scope included screening for broader indicators of corrosion, e.g., pitting, the identification of potential cracks was prioritized for the past several years at the request of program leadership.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Thermomechanical Degradation of Sintered Copper Under High-Temperature Thermal Shock

The need for reliable bonded interface materials is critical to realize the performance benefits of wide-bandgap devices in power electronics modules, especially in operating temperatures greater than 150 degrees C. In this paper, we investigate the thermomechanical performance of sintered copper (Cu) as a large-area attachment, bonded between Cu baseplates and active-metal-bonded substrates, under accelerated thermal shock (-40 degrees C to 200 degrees C) conditions. In the fabrication phase of the samples, we used different stencil patterns and found that the grid and stripe patterns resulted in a better outgassing of the residual organics during the sintering process, thereby ensuring a substantially improved bond quality compared to a full-area print. The paste consisted of Cu microflakes, and we performed sintering using a Budatec SP300 sintering press at 275 degrees C with 15 MPa of bonding pressure for 5 minutes in a nitrogen atmosphere. Under accelerated experiments, we monitored the degradation of the sintered Cu bond in the samples through C-mode scanning acoustic microscope (C-SAM) images. To quantify the defect percentage in C-SAM images, we investigated image denoising techniques to exclude the pattern prints. Finally, we cross-sectioned a sample and obtained scanning electron microscope images, which revealed adhesive fracture as the dominant failure mechanism.

ADVANCED PROPULSION SYSTEMS,INORGANIC, ORGANIC, PH↗

Machine Learning-Enabled Quantitative Analysis of Optically Obscure Scratches on Nickel-Plated Additively Manufactured (AM) Samples

Additively manufactured metal components often have rough and uneven surfaces, necessitating post-processing and surface polishing. Hardness is a critical characteristic that affects overall component properties, including wear. This study employed K-means unsupervised machine learning to explore the relationship between the relative surface hardness and scratch width of electroless nickel plating on additively manufactured composite components. The Taguchi design of experiment (TDOE) L9 orthogonal array facilitated experimentation with various factors and levels. Initially, a digital light microscope was used for 3D surface mapping and scratch width quantification. However, the microscope struggled with the reflections from the shiny Ni-plating and scatter from small scratches. To overcome this, a scanning electron microscope (SEM) generated grayscale images and 3D height maps of the scratched Ni-plating, thus enabling the precise characterization of scratch widths. Optical identification of the scratch regions and quantification were accomplished using Python code with a K-means machine-learning clustering algorithm. The TDOE yielded distinct Ni-plating hardness levels for the nine samples, while an increased scratch force showed a non-linear impact on scratch widths. The enhanced surface quality resulting from Ni coatings will have significant implications in various industrial applications, and it will play a pivotal role in future metal and alloy surface engineering.

36 MATERIALS SCIENCE↗

A digital holography ex situ measurement characterization of plasma-exposed surface erosion from an electrothermal arc source

Digital holography has been proposed to fulfill a need for an imaging diagnostic capable of in situ monitoring of surface erosion caused by plasma–material interaction in nuclear fusion devices. A digital holography diagnostic for 3D surface erosion measurement has been developed at Oak Ridge National Laboratory with the goal of deployment on a plasma device. A proof-of-concept in situ demonstration is planned which would involve measurement of plasma erosion on targets exposed to an electrothermal arc source. This work presents the results of an ex situ characterization of the capability and limitations of holographic imaging of targets exposed to the arc source. Targets were designed to provide a fiducial for comparison of deformed and unaffected areas. The results indicated that the average net erosion was ~150 nm/plasma exposure, which is expected to be within the diagnostic’s measurement capacity. Surface roughness averages determined by holographic image analysis showed good agreement with measurements taken with a profilometer. Finally, the limit of the holography diagnostic’s x–y spatial resolution was characterized by comparison with scanning electron microscope imaging.

47 OTHER INSTRUMENTATION↗

Quantitative Specifications to Avoid Degradation during E-Beam and Induced Current Microscopy of Halide Perovskite Devices

Degradation due to electron beam exposure has posed a challenge in the use of electron microscopy to probe halide perovskite materials and devices. Herein, the interaction between the electron beam and the perovskite across acceleration voltages and at low probe currents is investigated in a scanning electron microscope (SEM) by monitoring the electron-beaminduced current (EBIC) response in perovskite solar cells in a planview configuration. SEM probe conditions are identified where dozens of repeated scans over a single region of the perovskite solar cell induce minimal electronic degradation. Overall, the induced current response of the perovskite device is found to strongly depend upon the beam condition: rapid decay occurs at high beam powers, the current activates at the lowest beam powers, and a newfound quasi-steady response is revealed at intermediate beam conditions. A quantitative window for the successful conduction of e-beam studies with minimal electronic degradation is revealed by evaluating induced current response over a wide range of perovskite devices, which invites broader use of SEM-based characterization techniques, including EBIC, as powerful techniques for correlative microscopy investigations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sodium Dodecyl Sulfate–Mediated Graphene Sensor for Electrochemical Detection of the Antibiotic Drug: Ciprofloxacin

The present study involves detecting and determining CIP by a new electrochemical sensor based on graphene (Gr) in the presence of sodium dodecyl sulfate (SDS) employing voltammetric techniques. Surface morphology studies of the sensing material were analyzed using a scanning electron microscope (SEM) and atomic force microscope (AFM). In the electroanalysis of CIP at the developed electrode, an enhanced anodic peak response was recorded, suggesting the electro-oxidation of CIP at the electrode surface. Furthermore, we evaluated the impact of the electrolytic solution, scan rate, accumulation time, and concentration variation on the electrochemical behavior of CIP. The possible electrode mechanism was proposed based on the acquired experimental information. A concentration variation study was performed using differential pulse voltammetry (DPV) in the lower concentration range, and the fabricated electrode achieved a detection limit of 2.9 × 10 -8 M. The proposed sensor detected CIP in pharmaceutical and biological samples. The findings displayed good recovery, with 93.8% for tablet analysis and 93.3% to 98.7% for urine analysis. The stability of a developed electrode was tested by inter- and intraday analysis.

36 MATERIALS SCIENCE↗