Correlative SIP-FISH-Raman-SEM-NanoSIMS links identity, morphology, biochemistry, and physiology of environmental microbes
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George A Schaible↗
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2D microstructure reconstruction for SEM via non-local patch-based image inpainting.
Abstract not provided.
Tran, Anh↗
NEUP IMEBM Project: Solubility Experiments on Carbon Fibers, Results from SEM-EDS & XRD.
Abstract not provided.
Jove-Colon, Carlos↗
Slides on AFC-4C-R5 MNT20E destructive PIE :SEM, Micro-tensile testing, Post-test TEM Characterization
Slides containing updated PIE results for AFC-4C-R5 (MNT20E)
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Chemo-Mechanical Instabilities in Lithium Cobalt Oxide at Higher State-Of-Charge in Li-Ion Batteries
Transition metal oxide cathodes are widely used in commercial Li-ion batteries. However, their practical charge capacity is limited due to severe chemo-mechanical instabilities at higher charge voltage, and state-of-charge condition. Here, in situ stress and strain measurements were synchronized to probe mechanical deformations in the lithium cobalt oxide (LCO) cathode via a multi-beam stress sensor and digital image correlation, respectively. In situ mechanical measurements revealed how Li removal from the electrode structure induces deformations on the LCO composite cathodes during cycling. The structure and morphology of the LCO cathodes were further investigated by X-ray diffraction (XRD) and scanning electron microscopy (SEM) studies. Two distinct electrochemical and mechanical behaviors were identified when the LCO was charged up to 4.65 V. The LCO undergoes a compressive stress generation when charged up to 4.2 V and surface fractures on the LCO particles were detected by SEM. LCO cathode experienced significantly large contractions (negative strains) when charged up to 4.65 V, where intergranular crack formation and phase transformation were detected on the LCO particles via SEM and XRD, respectively. Overall, the study bridges complicated structural deformations with in situ analysis of mechanical degradations in LCO cathodes charged at higher voltages. The correlation is vital to understanding instability mechanisms in transition metal oxides at high voltages for alkali metal ion batteries.
higher state-of-charge↗
Resolving the Electron Plume within a Scanning Electron Microscope
Scanning electron microscopy (SEM), a century-old technique, is today a ubiquitous method of imaging the surface of nanostructures. However, most SEM detectors simply count the number of secondary electrons from a material of interest, and thereby overlook the rich material information contained within them. Here, by simple modifications to a standard SEM tool, we resolve the momentum and energy information on secondary electrons by directly imaging the electron plume generated by the electron beam of the SEM. Leveraging these spectroscopic imaging capabilities, our technique is able to image lateral electric fields across a prototypical silicon p–n junctions and to distinguish differently doped regions, even when buried beyond depths typically accessible by SEM. Intriguingly, the subsurface sensitivity of this technique reveals unexpectedly strong surface band bending within nominally passivated semiconductor structures, providing useful insights for complex layered component designs, in which interfacial dynamics dictate device operation. Further, these capabilities for noninvasive, multimodal probing of complicated electronic components are crucial in today’s electronic manufacturing but is largely inaccessible even with sophisticated techniques. These results show that seemingly simple SEM can be extended to probe complex and useful material properties.
36 MATERIALS SCIENCE↗
Paw-Net: Stacking ensemble deep learning for segmenting scanning electron microscopy images of fine-grained shale samples
Segmentation of scanning electron microscopy (SEM) images is critical yet time-consuming for geological analyses, as it needs to differentiate the boundaries for different mineral objects to facilitate subsequent analyses, such as porosity calculation. Recently, various machine learning methods, especially convolutional neural networks (CNNs), have been explored to segment SEM images of fine-grained shale samples. However, we found that general CNNs do not yield optimal performance due to insufficient training data and imbalanced objects in SEM images. This work has revised the U-Net architecture, a popular approach for biomedical image analyses, by incorporating a loss function that addresses the imbalance issue. Furthermore, we used the ensemble learning method to train multiple models and combined the results to improve the overall performance of segmentation. We prepared 2162 sub-images from raw SEM images in our experiments and divided them into training, validation, and testing datasets. The overall results show that our method improves the average Intersection over Union (IOU) of mineral objects from 0.49 to 0.58, compared to the original U-Net model. Our method can clearly distinguish each object from others with boundaries, even in highly imbalanced images. Training our models takes less than three minutes using a single GPU, while manual labeling can take up to three hours for each image. Furthermore, the method helps geoscientists gain insights quickly and effectively by building neural network models from a small dataset of SEM images.
58 GEOSCIENCES↗
A fine pore-preserved deep neural network for porosity analytics of a high burnup U-10Zr metallic fuel
Abstract U-10 wt.% Zr (U-10Zr) metallic fuel is the leading candidate for next-generation sodium-cooled fast reactors. Porosity is one of the most important factors that impacts the performance of U-10Zr metallic fuel. The pores generated by the fission gas accumulation can lead to changes in thermal conductivity, fuel swelling, Fuel-Cladding Chemical Interaction (FCCI) and Fuel-Cladding Mechanical Interaction (FCMI). Therefore, it is crucial to accurately segment and analyze porosity to understand the U-10Zr fuel system to design future fast reactors. To address the above issues, we introduce a workflow to process and analyze multi-source Scanning Electron Microscope (SEM) image data. Moreover, an encoder-decoder-based, deep fully convolutional network is proposed to segment pores accurately by integrating the residual unit and the densely-connected units. Two SEM 250 × field of view image datasets with different formats are utilized to evaluate the new proposed model’s performance. Sufficient comparison results demonstrate that our method quantitatively outperforms two popular deep fully convolutional networks. Furthermore, we conducted experiments on the third SEM 2500 × field of view image dataset, and the transfer learning results show the potential capability to transfer the knowledge from low-magnification images to high-magnification images. Finally, we use a pre-trained network to predict the pores of SEM images in the whole cross-sectional image and obtain quantitative porosity analysis. Our findings will guide the SEM microscopy data collection efficiently, provide a mechanistic understanding of the U-10Zr fuel system and bridge the gap between advanced characterization to fuel system design.
36 MATERIALS SCIENCE↗
The Combined Detection of Morphological and Molecular Biomarkers: Implications for Astrobiology
Experience gathered by previous researchers during their hunt for evidence of early Earth life has shown the complexity in interpreting observations of possible microfossils and to establish the evidence to be positive. Similarly, the stillsimmering controversy on the nature of the nano-structures in Martian meteorite ALH84001 described by McKay et al. (1996) emphasizes the difficulties of conclusively identifying those structures as (a) fossilized bacterial cells and (b) establish their indigeneity. A better understanding of biological signatures in rocks is needed in order to identify traces of microbial life, which include morphological, mineralogical and chemical traces. It is thus considered crucial to tackle the problems emerging in the search for evidence of early life on Earth and in exopaleontological research with a multidisciplinary approach. With this is mind we applied surface sensitive Time of Flight-Secondary Ion Mass Spectroscopy (ToF-SIMS) to a previously described 25 m.y. old fossil bacterial biofilm. This technique allows in situ analysis with high mass resolution as well as molecular imaging of micron sized structures. As no extraction or derivatisation of the sample is required for ToF-SIMS analysis, electron microscopical investigation of the same samples subsequent to analysis is possible, thus allowing the combination of molecular and morphological biomarkers. The analysed fossil bacterial biofilms were associated with macrofossils from volcanoclastic lacustrine sediments from the Upper Oligocene Enspel formation (Germany). Preliminary scanning electron microscopy (SEM) studies have shown that a fossil structure interpreted as a coprolite purely consisted of fossilized bacterial biofilm. For ToF-SIMS investigation small particles were taken from the fossil biofilm and mounted onto Au-coated In-foil and analysed in a Phi Evans T-2000 TRIFT system. The ToF-SIMS analysed samples were Au/Pd-sputter coated and imaged using a Philips XL40 Field Emission Gun SEM (FEG-SEM). ToF-SIMS analysis of the organic rich fossil biofilm (TOC 29%) in the 0-100 Dalton (Da) range showed significant amounts of inorganic species, confirming the results obtained previously by EDX analysis, clearly showing the bacterial fossils to be mineralised. ToF-SIMS furthermore revealed the presence of a variety of low- and high-mass organic molecules and fragments thereof. These include peaks indicative of alkenes and alkanes, aromatic organic species and the polycyclic aromatic hydrocarbon naphthalene. More tentatively, peaks indicative of alkyl pyrroles and pyridyl-CH2 were identified. Other peaks of interest include peaks indicative of C(n)H(2n)O2 and C(n)H(2n-2)O2, which according to their general formula would suggest the presence of both saturated and unsaturated fatty acids although further in situ derivatisation experiments and GC-MS (Gas Chromatography MS) need to be applied to verify this beyond doubt. Furthermore, peaks at m/z 370, 384, 398, 412, 426, 440, 454 and 468 were identified, which indicate the potential presence of bacterial hopanes, a class of biomarkers indicative of bacteria. The main diagnostic peak for this group of chemicals is the fragment at m/z 191.18. Our studies conducted on purified hopane standards have shown that in the high-mass resolution mode differentiation of this diagnostic hopane peak and polyethylene at m/z 191.05 is possible. However, the spectra discussed here were collected in the lower resolution mapping mode, therefore this differentiation was not possible. The centroids of the possible hopane peaks obtained on the fossil biofilms are well within the range associated with bacterial hopanes. There is a strong possibility therefore that hopanoids may be associated with the fossil bacterial cells. Due to the non-destructive nature of ToF-SIMS, analysed samples can be studied using SEM, thus allowing the combination of morphological and molecular biomarkers. Subsequent SEM analysis of the ToF-SIMS analysed samples confirmed that the analysed material purely consists of fossil bacterial cells. This is thus the first successful effort to demonstrate the combination of spectral and morphological biomarkers. The advantages of highly sensitive non-destructive in situ analysis techniques for biomarker detection are invaluable, particularly with respect to envisaged Mars sample return missions, as it may allow us to identify remains and traces of former microbial life in both ancient terrestrial and extraterrestrial materials. This technique may prove particularly useful in the quest for extraterrestrial life with respect to precious extraterrestrial materials, as minute quantities are sufficient to conduct analysis.
Toporski, J.↗
Plug-and-Play Environmental Monitoring Spacecraft Subsystem
A Space Environment Monitor (SEM) subsystem architecture has been developed and demonstrated that can benefit future spacecraft by providing (1) real-time knowledge of the spacecraft state in terms of exposure to the environment; (2) critical, instantaneous information for anomaly resolution; and (3) invaluable environmental data for designing future missions. The SEM architecture consists of a network of plug-and- play (PnP) Sensor Interface Units (SIUs), each servicing one or more environmental sensors. The SEM architecture is influenced by the IEEE Smart Transducer Interface Bus standard (IEEE Std 1451) for its PnP functionality. A network of PnP Spacecraft SIUs is enabling technology for gathering continuous real-time information critical to validating spacecraft health in harsh space environments. The demonstrated system that provided a proof-of-concept of the SEM architecture consisted of three SIUs for measurement of total ionizing dose (TID) and single event upset (SEU) radiation effects, electromagnetic interference (EMI), and deep dielectric charging through use of a prototype Internal Electro-Static Discharge Monitor (IESDM). Each SIU consists of two stacked 2X2 in. (approximately 5X5 cm) circuit boards: a Bus Interface Unit (BIU) board that provides data conversion, processing and connection to the SEM power-and-data bus, and a Sensor Interface Electronics (SIE) board that provides sensor interface needs and data path connection to the BIU.
Patel, Jagdish↗
Miniature Variable Pressure Scanning Electron Microscope for In-Situ Imaging and Chemical Analysis
NASA Marshall Space Flight Center (MSFC) is leading an effort to develop a Miniaturized Variable Pressure Scanning Electron Microscope (MVP-SEM) for in-situ imaging and chemical analysis of uncoated samples. This instrument development will be geared towards operation on Mars and builds on a previous MSFC design of a mini-SEM for the moon (funded through the NASA Planetary Instrument Definition and Development Program). Because Mars has a dramatically different environment than the moon, modifications to the MSFC lunar mini-SEM are necessary. Mainly, the higher atmospheric pressure calls for the use of an electron gun that can operate at High Vacuum, rather than Ultra-High Vacuum. The presence of a CO2-rich atmosphere also allows for the incorporation of a variable pressure system that enables the in-situ analysis of nonconductive geological specimens. Preliminary testing of Mars meteorites in a commercial Environmental SEM(Tradmark) (FEI) confirms the usefulness of lowcurrent/low-accelerating voltage imaging and highlights the advantages of using the Mars atmosphere for environmental imaging. The unique capabilities of the MVP-SEM make it an ideal tool for pursuing key scientific goals of NASA's Flagship Mission Max-C; to perform in-situ science and collect and cache samples in preparation for sample return from Mars.
Gaskin, Jessica A.↗
Modeling a Miniaturized Scanning Electron Microscope Focusing Column - Lessons Learned in Electron Optics Simulation
This presentation discusses work done to assess the design of a focusing column in a miniaturized Scanning Electron Microscope (SEM) developed at the NASA Marshall Space Flight Center (MSFC) for use in-situ on the Moon-in particular for mineralogical analysis. The MSFC beam column design uses purely electrostatic fields for focusing, because of the severe constraints on mass and electrical power consumption imposed by the goals of lunar exploration and of spaceflight in general. The resolution of an SEM ultimately depends on the size of the focused spot of the scanning beam probe, for which the stated goal here is a diameter of 10 nanometers. Optical aberrations are the main challenge to this performance goal, because they blur the ideal geometrical optical image of the electron source, effectively widening the ideal spot size of the beam probe. In the present work the optical aberrations of the mini SEM focusing column were assessed using direct tracing of non-paraxial rays, as opposed to mathematical estimates of aberrations based on paraxial ray-traces. The geometrical ray-tracing employed here is completely analogous to ray-tracing as conventionally understood in the realm of photon optics, with the major difference being that in electron optics the lens is simply a smoothly varying electric field in vacuum, formed by precisely machined electrodes. Ray-tracing in this context, therefore, relies upon a model of the electrostatic field inside the focusing column to provide the mathematical description of the "lens" being traced. This work relied fundamentally on the boundary element method (BEM) for this electric field model. In carrying out this research the authors discovered that higher accuracy in the field model was essential if aberrations were to be reliably assessed using direct ray-tracing. This led to some work in testing alternative techniques for modeling the electrostatic field. Ultimately, the necessary accuracy was attained using a BEM/Fourier series hybrid approach. The presentation will give background remarks about the MSFC mini Lunar SEM concept and electron optics modeling, followed by a description of the alternate field modeling techniques that were tried, along with their incorporation into a ray-trace simulation. Next, the validation of this simulation against commercially available software will be discussed using an example lens as a test case. Then, the efficacy of aberration assessment using direct ray-tracing will be demonstrated, using this same validation case. The discussion will include practical error checks of the field solution. Finally, the ray-trace assessment of the MSFC mini Lunar SEM concept will be shown and discussed. The authors believe this presentation will be of general interest to practitioners of modeling and simulation, as well as those with a general optics background. Because electron optics and photon optics share many basic concepts (e.g., lenses, images, aberrations, etc.), the appeal of this presentation need not be restricted to just those interested in charged particle optics.
Modeling Miniaturizing Scanning↗
New Insights on Subsurface Imaging of Carbon Nanotubes in Polymer Composites via Scanning Electron Microscopy
Despite many studies of subsurface imaging of carbon nanotube (CNT)-polymer composites via scanning electron microscopy (SEM), significant controversy exists concerning the imaging depth and contrast mechanisms. We studied CNT-polyimide composites and, by threedimensional reconstructions of captured stereo-pair images, determined that the maximum SEM imaging depth was typically hundreds of nanometers. The contrast mechanisms were investigated over a broad range of beam accelerating voltages from 0.3 to 30 kV, and ascribed to modulation by embedded CNTs of the effective secondary electron (SE) emission yield at the polymer surface. This modulation of the SE yield is due to non-uniform surface potential distribution resulting from current flows due to leakage and electron beam induced current. The importance of an external electric field on SEM subsurface imaging was also demonstrated. The insights gained from this study can be generally applied to SEM nondestructive subsurface imaging of conducting nanostructures embedded in dielectric matrices such as graphene-polymer composites, silicon-based single electron transistors, high resolution SEM overlay metrology or e-beam lithography, and have significant implications in nanotechnology.
Zhao, Minhua↗
Proposed Analytical Methods for Determining Filter Media Properties
High Efficiency Particulate Air (HEPA) filters, commonly used in nuclear filtration applications, are an integral part of the waste management processes in nuclear plants. HEPA filters are 99.97% efficient filtration devices characterized by their high resistance to air flow, or pressure drop. From theoretical models, the initial pressure drop across a clean filter is proven to be a function of the filter media fiber diameters and porosity of the media. These filter properties are relatively difficult to obtain with traditional manual methods; therefore, there is a need to develop analytical methods to find the fiber diameter and porosity to determine the pressure drop. Typically, these values can be found by substituting a calculated representative value based upon measured values, such as equivalent fiber diameter based upon a clean pressure drop. However, these values may also be directly recorded and measured by incorporating Scanning Electron Microscope (SEM) image analysis and other measurement methods to analyze the filter media and determine its physical properties without the need for media testing. DiameterJ, an open source Java plug-in, used with ImageJ, can process images of filter media taken by an SEM to find statistical data such as mean fiber diameter and porosity. To produce the raw data, SEM images of two filter media type samples are taken and segmented in DiameterJ using the traditional and statistical region merging segmentation algorithms. Manual segmentation is necessary after the initial segmentation by the algorithms as the images tend to be too complex for the algorithms to output with the necessary accuracy. However, complications exist in the manual segmentation process as these methods can be time intensive and prone to the individual bias of the user. This in turn can skew the final mean fiber diameter result, and lead to either an over or under prediction of the pressure drop. It was also discovered that the porosity data produced by DiameterJ is inaccurate, as the SEM analyzes the three-dimensional filter media by projecting its geometry onto a plane and analyzing it as a two-dimensional binary image. Thus, the porosity is artificially inflated through the segmentation process, rendering this result incorrect. Alternatively, density determination, gravimetric analysis, and thickness testing of the filter media is collectively used to determine the filter fiber porosity. Together, the SEM image analysis and analytical lab methods produce results through direct measurements which allow for the prediction of the initial pressure drop from clean filter media without the need for prior media testing to collect pressure data. By improving upon this proposed analytical method in the future, there is potential to streamline the process of finding these filter properties into a more direct methodology for determining the pressure drop across HEPA filters.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Exploring 3D leaf anatomical traits for C 4 photosynthesis: chloroplast and plasmodesmata pit field size in maize and sugarcane
Summary Volume and surface area of chloroplasts and surface area of plasmodesmata pit fields are presented for two C 4 species, maize and sugarcane, with respect to cell surface area and cell volume. Serial block face scanning electron microscopy (SBF‐SEM) and confocal laser scanning microscopy with the Airyscan system (LSM) were used. Chloroplast size estimates were much faster and easier using LSM than with SBF‐SEM; however, the results were more variable than SBF‐SEM. Mesophyll cells were lobed where chloroplasts were located, facilitating cell‐to‐cell connections while allowing for greater intercellular airspace exposure. Bundle sheath cells were cylindrical with chloroplasts arranged centrifugally. Chloroplasts occupied c. 30–50% of mesophyll cell volume, and 60–70% of bundle sheath cell volume. Roughly 2–3% of each cell surface area was covered by plasmodesmata pit fields for both bundle sheath and mesophyll cells. This work will aid future research to develop SBF‐SEM methodologies with the aim to better understand the effect of cell structure on C 4 photosynthesis.
3D leaf imaging↗
Understanding Biases in Sample Preparation Techniques for Coupled Scanning Electron Microscopy and MAMA PuO 2 Morphological Analysis
In this project, the scanning electron microscopy (SEM) sampling method used during the statistical design study (SDS) was investigated to determine if any sampling biases were present in the analyzed data. Using standard particle size distribution powders from the National Institute of Standards and Technology (NIST 1984 standard reference material) with the origin wet dispersion method, it was determined that a bias to smaller particles was present. This was supported by theoretical calculations using Stokes’ law to determine the settling rate of spherical particles of roughly the same size and mass as those found in the SDS. Based on the theoretical calculations, it was determined that the settling rate for each of the 76 powder sets in the SDS could be unique based on specific particle shape and mass distributions, making a universal correction factor/formula not applicable. Therefore, priority shifted to developing an improved wet dispersion method that significantly reduced the particle settling rate for all particle size and shapes. This was achieved by replacing the original solvent (isopropyl alcohol) with a heavy liquid (lithium heteropolytungstates), which dramatically slowed the settling rate and allowed for the capture of a suitable homogeneous aliquot. SEM imaging and Morphological Analysis for Material Attribution (MAMA) software analysis were conducted on the NIST standard, and the SEM/MAMA data were compared to data captured by a dynamic image analysis particle size analyzer. The resulting data confirmed that the new wet dispersion method does indeed deliver an improved representative aliquot to the SEM stub. For instance, in the NIST certificate, the average particle size is ~17.1 µm ± 2.2 µm with a normal distribution. The initial wet dispersion method resulted in a drastically reduced average particle size of 6.1 µm in addition to a non-representative heavy bi-modal distribution whereas the improved LST wet dispersion method resulting in an average particle size that was much closer to the NIST certificate (12.7 µm) with a similar normal distribution. Although the improved method was still short of the NIST certificate average, atomic force microscopy analysis determined that the resulting ~20-25% reduction in size was due to particles sinking into the carbon sticky tape used for SEM imaging. It is believed that that this bias can be calibrated in a much more predicable manner than the original settling rate bias. In addition, the matching normal distribution curves between the NIST certificate and the heavy liquid method indicate a much-improved representative aliquot has been sampled and imaged. A surrogate CeO 2 powder was used to reflect PuO 2 more accurately and to aid in implementing radiological controls and shielding. The resulting data sets from the SEM/MAMA method and the particle size analyzer give almost identical average particle sizes and particle distribution statistics. Future work will re-analyze several select runs from the SDS to determine if morphological signatures can be found with the improved sampling method.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Development of Parameters for the Particle Size Distribution of TATB
Laser light scattering (LLS), manual counting of scanning electron microscopy (SEM) images, and reduction of SEM images using ImageJ (open source program) to determine Feret (caliper) diameters were applied to determine particle size distribution (PSD) of four preparations of 1,3,5‐triamino‐2,4,6‐trinitrobenzene (TATB) and yttria‐stabilized zirconia (YSZ), an SEM certified standard. Mie theory was used to reduce the LLS data. The spherical nature of the YSZ made it a good candidate for LLS. Variations in n , the refractive index, and iκ, the imaginary component, produced very little change in the PSD. However, changing the carrier liquid from H 2 O to a 40% aqueous sucrose solution, thereby changing the carrier refractive index, n 0 , substantially affected the PSD. The Mie complex refractive indices for the YSZ were n = 2.200, iκ = 0.100, with a 40% aqueous sucrose solution, n 0 = 1.400. The triclinic crystal structure of TATB made refractive index determinations more difficult, so a study was conducted varying Mie parameters and comparing them to the same data reduced using the Fraunhofer theory. Changing the n and κ parameters produced PSD with a small concentration of particles less than 1 µm in size or none in this range. SEM images, Feret data, manual counting, and Fraunhofer data reduction indicate particles less than 1 µm are probably < 5% in concentration. The final selection of Mie parameters for TATB was n = 2.283, iκ = 0.1, and suspension medium, n 0 = 1.330. Finally, computations, using density functional theory produced similar parameters.
Feret diameter↗