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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Exposed Phosphatidylserine as a Biomarker for Clear Identification of Breast Cancer Brain Metastases in Mouse Models

Brain metastasis is the most common intracranial malignancy in adults. The prognosis is extremely poor, partly because most patients have more than one brain lesion, and the currently available therapies are nonspecific or inaccessible to those occult metastases due to an impermeable blood–tumor barrier (BTB). Phosphatidylserine (PS) is externalized on the surface of viable endothelial cells (ECs) in tumor blood vessels. In this study, we have applied a PS-targeting antibody to assess brain metastases in mouse models. Fluorescence microscopic imaging revealed that extensive PS exposure was found exclusively on vascular ECs of brain metastases. The highly sensitive and specific binding of the PS antibody enables individual metastases, even micrometastases containing an intact BTB, to be clearly delineated. Furthermore, the conjugation of the PS antibody with a fluorescence dye, IRDye 800CW, or a radioisotope, 125I, allowed the clear visualization of individual brain metastases by optical imaging and autoradiography, respectively. In conclusion, we demonstrated a novel strategy for targeting brain metastases based on our finding that abundant PS exposure occurs on blood vessels of brain metastases but not on normal brain, which may be useful for the development of imaging and targeted therapeutics for brain metastases.

Oncology↗
DOE OSTI2026

Web-based Preprocessing and Visualization of 3D FIB Tomography Data for Nuclear Fuel Characterization

Three-dimensional (3D) focused ion beam (FIB) tomography enables reconstruction of internal nuclear fuel features that can't be fully evaluated through surface imaging alone. This capability supports characterization of fuel constituents and defects under thermal and irradiation conditions relevant to microreactor development. However, large tomography datasets can create data-handling, loading, and visualization challenges, especially when image-stack preparation and file conversion must be completed with separate tools. The Computational Ultraspatial Tomography Toolkit for High-Resolution Object Analysis Tools (CUTTRHOAT) is an open-source web application being developed to display FIB tomography datasets available through the Nuclear Research Data System (NRDS). The current alpha version requires prepared HDF5 datasets and has limited integrated data-preparation capabilities. This project improves CUTTHROAT by adding dataset-folder selection, automatic input detection, dataset scanning, missing-slice identification, blank-slice insertion, and image-stack-to-HDF5 conversion. Two applications will be compared: the baseline CUTTHROAT alpha workflow and the updated application containing the integrated data-handling and preprocessing functions. Evaluation will consider dataset detection accuracy, conversion success, loading time, rendering responsiveness, application stability, and user interaction. Preliminary results demonstrate successful loading of existing HDF5 files and converted image stacks, while testing also identified performance reductions caused by excessive blank-slice generation. The updated workflow reduces reliance on external preparation tools and supports more direct movement from image stacks to color-code 3D visualization. Future work includes refining missing-slice handling, integrating additional preprocessing functions, like a denoising feature, parsing TIFF metadata for automatic voxel scaling, and adding manual X, Y, and Z voxel-spacing inputs for PNG and JPEG.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Neutron-Friendly Li-Ion Battery Coin Cell for In Situ 3D Visualization of Li Plating

Advanced battery characterization using in situ/operando neutron imaging is critical for uncovering degradation modes such as lithium (Li) plating in Li-ion batteries (LIBs). However, conventional LIBs hinder operando neutron radiography (NR) and in situ neutron micro-computed tomography (N-μCT) for visualizing Li plating near the graphite-separator interface due to strong attenuation from hydrogen-rich components like PP–PE–PP separators, electrolyte, and Fe-based spacers. In this work, we designed and tested a neutron-friendly battery (NFB) optimized for in situ Li detection during extreme fast charging (XFC). Guided by neutron attenuation cross-sections and material transmission, the NFB enables clear visualization at the graphite–separator interface, which is typically opaque in standard LIBs. Electrochemical tests show the NFB exhibits voltage/current responses like standard cells for up to 50 XFC cycles. However, its lower reversibility and capacity are likely due to Cu-coated Al spacer degradation from delamination or corrosion. We propose titanium spacers as a more stable alternative, albeit requiring custom machining. Using this optimized cell, we achieved simultaneous neutron tomography of multiple cells, capturing in situ 3D images of dead Li accumulation, particularly near graphite edges. These heterogeneous deposits and disconnected Li clusters suggest localized current density hotspots during XFC.

25 ENERGY STORAGE↗
DOE OSTI2023

Visualizing moiré ferroelectricity via plasmons and nano-photocurrent in graphene/twisted-WSe2 structures

Abstract Ferroelectricity, a spontaneous and reversible electric polarization, is found in certain classes of van der Waals (vdW) materials. The discovery of ferroelectricity in twisted vdW layers provides new opportunities to engineer spatially dependent electric and optical properties associated with the configuration of moiré superlattice domains and the network of domain walls. Here, we employ near-field infrared nano-imaging and nano-photocurrent measurements to study ferroelectricity in minimally twisted WSe 2 . The ferroelectric domains are visualized through the imaging of the plasmonic response in a graphene monolayer adjacent to the moiré WSe 2 bilayers. Specifically, we find that the ferroelectric polarization in moiré domains is imprinted on the plasmonic response of the graphene. Complementary nano-photocurrent measurements demonstrate that the optoelectronic properties of graphene are also modulated by the proximal ferroelectric domains. Our approach represents an alternative strategy for studying moiré ferroelectricity at native length scales and opens promising prospects for (opto)electronic devices.

42 ENGINEERING↗
DOE OSTI2020

Determination of the Maturation Status of Dendritic Cells by Applying Pattern Recognition to High-Resolution Images

The maturation or activation status of dendritic cells (DCs) directly correlates with their behavior and immunofunction. A common means to determine the maturity of dendritic cells is from high-resolution images acquired via scanning electron microscopy (SEM) or atomic force microscopy (AFM). While direct and visual, the determination has been made by directly looking at the images by researchers. Here we report a machine learning approach using pattern recognition in conjunction with cellular biophysical knowledge of dendritic cells to determine the maturation status of dendritic cells automatically. The determination from AFM images reaches 100% accuracy. The results from SEM images reaches 94.9%. The results demonstrate the accuracy of using machine learning for accelerating data analysis, extracting information, and drawing conclusions from high-resolution cellular images, paving the way for future applications requiring high-throughput and automation, such as cellular sorting and selection based on morphology, quantification of cellular structure, and DC-based immunotherapy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Star cluster classification using deep transfer learning with PHANGS- HST

Currently available star cluster catalogues from the Hubble Space Telescope (HST) imaging of nearby galaxies heavily rely on visual inspection and classification of candidate clusters. Here, the time-consuming nature of this process has limited the production of reliable catalogues and thus also post-observation analysis. To address this problem, deep transfer learning has recently been used to create neural network models that accurately classify star cluster morphologies at production scale for nearby spiral galaxies (D ≲ 20 Mpc). Here, we use HST ultraviolet (UV)–optical imaging of over 20 000 sources in 23 galaxies from the Physics at High Angular resolution in Nearby GalaxieS (PHANGS) survey to train and evaluate two new sets of models: (i) distance-dependent models, based on cluster candidates binned by galaxy distance (9–12, 14–18, and 18–24 Mpc), and (ii) distance-independent models, based on the combined sample of candidates from all galaxies. We find that the overall accuracy of both sets of models is comparable to previous automated star cluster classification studies (~60–80 per cent) and shows improvement by a factor of 2 in classifying asymmetric and multipeaked clusters from PHANGS-HST. Somewhat surprisingly, while we observe a weak negative correlation between model accuracy and galactic distance, we find that training separate models for the three distance bins does not significantly improve classification accuracy. We also evaluate model accuracy as a function of cluster properties such as brightness, colour, and spectral energy distribution (SED)-fit age. Based on the success of these experiments, our models will provide classifications for the full set of PHANGS-HST candidate clusters (N ~ 200 000) for public release.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Design and demonstration of a low‐field magnetic resonance imaging rhizotron for in‐field imaging of energy sorghum roots

Abstract Root phenotyping provides critical information to plant breeders for developing varieties with improved drought tolerance, greater root biomass, and greater nutrient use efficiency. Phenotyping roots in the natural environment is important for understanding the effect of the soil environment on root genotypic expressions. The goal of this work was to design and test a field‐scale mobile low‐field magnetic resonance imaging (LF‐MRI) Rhizotron that produces actionable root phenotyping data. We demonstrated this novel technology for root visualization and quantification using a LF‐MRI Rhizotron operating at 47 mT with two soil types. The LF‐MRI Rhizotron weights 453 kg, with a height of 90 cm, a diameter of 28 cm and an imaging field of view of 28 cm × 28 cm. The unit was operated in a Belk clay (Entic Hapluderts) and Weswood silt loam (Udifluventic Halustepts) generating 2‐D and 3‐D image data sets. The 2‐D image data had a collection time of 16.5 min per image at an image resolution of 2.2 mm per pixel. The 3‐D data had a collection time of 13 h per image with a 2.2 × 2.2 × 2.2 mm voxel resolution. Low‐field magnetic resonance imaging worked well for visualizing roots in moderate to high clay soils, demonstrating the potential for this technology; however, the broad application of this platform is hampered due to the prohibitively long scanning time to obtain 3‐D images. By increasing the field strength, and therefore the signal‐to‐noise ratio, faster scan times can enable a more useful system for root phenotyping.

Bagnall, G. Cody↗
DOE OSTI2023

Tip-Enhanced Raman Chemical and Chemical Reaction Imaging in H 2 O with Sub-3-nm Spatial Resolution

Reproducible chemical and chemical reaction nano-imaging at solid-liquid interfaces remains challenging, particularly when resolutions on the order of a few nm are sought after. In this work, we demonstrate the latter through liquid tip-enhanced Raman (TER) measurements that target gold nanoplates functionalized with 4-mercaptobenzonitrile (MBN). In addition to chemical imaging and local optical field nano-visualization with high spatial resolution, we observe the signatures of 4-mercaptobenzoic acid, which forms as a result of plasmon-induced hydrolysis of MBN. Evidently, the solvent leads to distinct plasmon-induced/enhanced chemical reaction pathways that have not been documented. Here this work shows that such reactions that take place at solid-liquid interfaces can be tracked with a record sub-3 nm spatial resolution via TER spectral nano-imaging in liquids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Visualizing the Internal Nanocrystallinity of Calcite Due to Nonclassical Crystallization by 3D Coherent X–Ray Diffraction Imaging

The internal crystallinity of calcite is investigated for samples synthesized using two approaches: precipitation from solution and the ammonium carbonate diffusion method. Scanning electron microscopy (SEM) analyses reveal that the calcite products precipitated using both approaches have a well–defined rhombohedron shape, consistent with the euhedral crystal habit of the mineral. The internal structure of these calcite crystals is characterized using Bragg coherent diffraction imaging (BCDI) to determine the 3D electron density and the atomic displacement field. BCDI reconstructions for crystals synthesized using the ammonium carbonate diffusion approach have the expected euhedral shape, with internal strain fields and few internal defects. In contrast, the crystals synthesized by precipitation from solution have very complex external shapes and defective internal structures, presenting null electron density regions and pronounced displacement field distributions. These heterogeneities are interpreted as multiple crystalline domains, created by a nonclassical crystallization mechanism, where smaller nanoparticles coalescence into the final euhedral particles. The combined use of SEM, X–ray diffraction (XRD), and BCDI allows for structurally differentiating calcite crystals grown with different approaches, opening new opportunities to understand how grain boundaries and internal defects alter calcite reactivity.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Redox oscillations in 18650-type lithium-ion cell revealed by in operando Compton scattering imaging

Compton scattering imaging using high-energy synchrotron x rays allows the visualization of the spatiotemporal lithiation state in lithium-ion batteries probed in operando. Here, we apply this imaging technique to the commercial 18650-type cylindrical lithium-ion battery. Our analysis of the line shapes of the Compton scattering spectra taken from different electrode layers reveals the emergence of inhomogeneous lithiation patterns during the charge-discharge cycles. Moreover, these patterns exhibit oscillations in time where the dominant period corresponds to the timescale of the charging curve.

42 ENGINEERING↗
DOE OSTI2020

Computer-aided classification of suspicious pigmented lesions using wide-field images

Early identification of melanoma is conducted through whole-body visual examinations to detect suspicious pigmented lesions, a situation that fluctuates in accuracy depending on the experience and time of the examiner. Computer-aided diagnosis tools for skin lesions are typically trained using pre-selected single-lesion images, taken under controlled conditions, which limits their use in wide-field scenes. Here, we propose a computer-aided classifier system with such input conditions to aid in the rapid identification of suspicious pigmented lesions at the primary care level. 133 patients with a multitude of skin lesions were recruited for this study. All lesions were examined by a board-certified dermatologist and classified into “suspicious” and “non-suspicious”. A new clinical database was acquired and created by taking Wide-Field images of all major body parts with a consumer-grade camera under natural illumination condition and with a consistent source of image variability. 3–8 images were acquired per patient on different sites of the body, and a total of 1759 pigmented lesions were extracted. A machine learning classifier was optimized and build into a computer aided classification system to binary classify each lesion using a suspiciousness score. In a testing set, our computer-aided classification system achieved a sensitivity of 100% for suspicious pigmented lesions that were later confirmed by dermoscopy examination (“SPL_A”) and 83.2% for suspicious pigmented lesions that were not confirmed after examination (“SPL_B”). Sensitivity for non-suspicious lesions was 72.1%, and accuracy was 75.9%. With these results we defined a suspiciousness score that is aligned with common macro-screening (naked eye) practices. This work demonstrates that wide-field photography combined with computer-aided classification systems can distinguish suspicious from non-suspicious pigmented lesions, and might be effective to assess the severity of a suspicious pigmented lesions. We believe this approach could be useful to support skin screenings at a population-level.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

als microct recon (microct) v1

Jupyter notebooks to reconstruct and visualize microCT data from ALS beamline 8.3.2. Relies on standard tomography and image processing tools (astra, tomopy, itk, scikit-image) and ipywidgets (sliders, drop down menus, etc) to make parameter selection and data visualization easy for users.

Parkinson, Dilworth↗
DOE OSTI2020

Exploration of Water Jets in Supersonic Crossflow Using X-Ray Diagnostics

Here, near-field structures of pure- and aerated-liquid jets injected into Mach 2 crossflow environments were experimentally investigated at the 7-BM beamline of the Advanced Photon Source at Argonne National Laboratory using high-speed shadowgraph imaging, high-speed x-ray imaging, and pathlength-integrated x-ray fluorescence. Liquid was flush injected into a blowdown supersonic wind tunnel. Test section top and side windows were fitted with a polycarbonate plate for high x-ray transmittance. An axisymmetric aerated-liquid injector was fitted with an exchangeable nozzle adaptor to generate a liquid jet. Water and nitrogen, the gas used for aerated-liquid jets, were doped with specially selected dopants to facilitate x-ray measurements. Liquid column structures for a pure-liquid jet, typically masked by dense droplet clouds in a supersonic crossflow environment, were visualized with the present x-ray imaging setup. Surface-wave formation, movement, and transformation on the column windward surface of the pure-liquid jet, along with column deformation and breakup processes, were qualitatively characterized. We measured time-averaged line-of-sight (LOS) liquid mass distributions within the liquid jet near fields. Cross-sectional liquid column contours of pure-liquid jets at various deformation stages were reconstructed from LOS liquid mass distributions. The pure-liquid jet deformed liquid column reached a maximum width of 1.47 times the orifice diameter before exhibiting rapid mass removal. We also observed the plume-crossing phenomenon in the aerated-liquid jet.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Dense, continuous membrane labeling and expansion microscopy visualization of ultrastructure in tissues

Abstract Lipid membranes are key to the nanoscale compartmentalization of biological systems, but fluorescent visualization of them in intact tissues, with nanoscale precision, is challenging to do with high labeling density. Here, we report ultrastructural membrane expansion microscopy (umExM), which combines an innovative membrane label and optimized expansion microscopy protocol, to support dense labeling of membranes in tissues for nanoscale visualization. We validate the high signal-to-background ratio, and uniformity and continuity, of umExM membrane labeling in brain slices, which supports the imaging of membranes and proteins at a resolution of ~60 nm on a confocal microscope. We demonstrate the utility of umExM for the segmentation and tracing of neuronal processes, such as axons, in mouse brain tissue. Combining umExM with optical fluctuation imaging, or iterating the expansion process, yields ~35 nm resolution imaging, pointing towards the potential for electron microscopy resolution visualization of brain membranes on ordinary light microscopes.

Science & Technology - Other Topics↗
DOE OSTI2020

Non-destructive spatial analysis of phosphatase activity and total protein distribution in the rhizosphere using a root blotting method

Phosphorus (P) is an essential macronutrient for plant growth, but bioavailable P in soils is often limited due to immobilization resulting from pH and geochemical interactions. Understanding the dynamics of P in soils and elucidating the mechanisms by which plants access P from their environment are critical to evaluating productivity, particularly in nutrient poor environments. Phosphorus from organic matter can act as a major source of P for organisms in soil systems. Phosphatases, enzymes that liberate inorganic P from organic sources, are produced by both plants and microbes and are considered one of the most active classes of enzymes in soil. In this work we developed a root blotting method to spatially image phosphatase activity in the rhizosphere. Proteins from the rhizosphere are transferred to a nitrocellulose membrane while retaining their enzymatic activity and two-dimensional spatial distribution. Subsequent application of a fluorogenic phosphatase indicator, DDAO phosphate, enables visualization of the distribution of phosphatase activity in the sample. The proteins can then be fixed to the membrane and treated with a SYPRO® Ruby gel stain, a fluorescent total protein stain, allowing for visualization of total protein distribution. Taken together, the images of phosphatase activity and total protein localization can be mapped back to the root architecture and provide insight into factors affecting the spatial distribution of enzymatic activity and protein accumulation in the rhizosphere. Notably, this method can be applied to plants growing in rhizoboxes containing soil or soilless growth mixtures (e.g., sand or various potting mixes) and, because of the non-destructive nature of this approach, be performed over time to track changes. We anticipate that this fluorescent indicator imaging technique on root blots can be used in diverse plant-microbe-soil systems to better understand the role of phosphatases in P acquisition and soil P cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Characterizing Dislocation Defects in Dark Field X-ray Microscopy Images of Bulk Aluminum

Material defects play a large role in material response under shock loading, yet the process of how these defects initiate, propagate, and annihilate is not well understood. Using a newly developed diagnostic, dark field X-ray microscopy (DFXM), we can now visualize the behavior of dislocation defects in materials at the mesoscale under varying conditions. Using data from the European Synchrotron Radiation Facility, we apply a variety of image processing techniques to capture relevant features to locate and characterize size and orientation of dislocation defects in bulk aluminum DFXM images. Beyond simple visualization, this analysis drives statistical characterization of the defects and their dynamic response to further improve the relevant physics models.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Single-molecule live-cell RNA imaging with CRISPR–Csm

Abstract Understanding the diverse dynamic behaviors of individual RNA molecules in single cells requires visualizing them at high resolution in real time. However, single-molecule live-cell imaging of unmodified endogenous RNA has not yet been achieved in a generalizable manner. Here, we present single-molecule live-cell fluorescence in situ hybridization (smLiveFISH), a robust approach that combines the programmable RNA-guided, RNA-targeting CRISPR–Csm complex with multiplexed guide RNAs for direct and efficient visualization of single RNA molecules in a range of cell types, including primary cells. Using smLiveFISH, we track individual nativeNOTCH2andMAP1Btranscripts in living cells and identify two distinct localization mechanisms including the cotranslational translocation ofNOTCH2mRNA at the endoplasmic reticulum and directional transport ofMAP1BmRNA toward the cell periphery. This method has the potential to unlock principles governing the spatiotemporal organization of native transcripts in health and disease.

Biotechnology & Applied Microbiology↗
DOE OSTI2025

Non-linear enhancement of ultrafast X-ray diffraction through transient resonances

Diffraction-before-destruction imaging with ultrashort X-ray pulses can visualize non-equilibrium processes, such as chemical reactions, with sub-femtosecond precision in the native environment. Here, a nanospecimen diffracts a single X-ray flash before it disintegrates. The sample structure can be reconstructed from the coherent diffraction image (CDI). State-of-the-art X-ray snapshots lack high spatial resolution because of weak diffraction signal. Bleaching effects from photo-ionization significantly restrain image brightness scaling. We find that non-linear transient ion resonances can overcome this barrier if X-ray laser pulses are shorter than in most experiments. We compared snapshots from individual ≈ 100 nm Xe nanoparticles as a function of pulse duration and incoming X-ray fluence. Our experimental results and Monte Carlo simulations suggest that transient resonances can increase ionic scattering cross sections significantly beyond literature values. This provides a novel avenue towards substantial improvement of the spatial resolution in CDI in combination with sub-femtosecond temporal precision at the nanoscale.

47 OTHER INSTRUMENTATION↗