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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 91 records · Page 5

Calibrating cryogenic temperature of TEM specimens using EELS

Cryogenic Scanning/Transmission Electron Microscopy has been established as a leading method to image sensitive biological samples and is now becoming a powerful tool to understand materials' behavior at low temperatures. However, achieving precise local temperature calibration at low temperatures remains a challenge, which is especially crucial for studying phase transitions and emergent physical properties in quantum materials. In this study, we employ electron energy loss spectroscopy (EELS) to measure local cryogenic specimen temperatures. Here we use the temperature-dependent characteristics of aluminum's bulk plasmon peak in EEL spectra, which shifts due to changes in electron density caused by thermal expansion and contraction. We successfully demonstrate the versatility of this method by calibrating different liquid nitrogen cooling holders in various microscopes, regardless of whether a monochromated or non-monochromated electron beam is used. Temperature discrepancies between the actual temperature and the setpoint temperatures are identified across a range from room temperature to 100 K. This work demonstrates the importance of temperature calibrations at intermediate temperatures and presents a straightforward, robust method for calibrating local temperatures of cryogenically-cooled specimens in electron microscopes.

36 MATERIALS SCIENCE↗

Prolonging All-Optical Molecular Electron Spin Coherence in the Tissue Transparency Window

Coherent electron spin states within paramagnetic molecules hold significant potential for microscopic quantum sensing. However, all-optical coherence measurements amenable to high spatial and temporal resolution under ambient conditions remain a significant challenge. Here we conduct room-temperature, picosecond time-resolved Faraday ellipticity/rotation (TRFE/R) measurements of the electron spin decoherence time T 2 * in [IrBr 6 ] 2- . Decoherence is strongly sensitive to solution phase viscosity, pointing to molecular tumbling as an important decoherence mechanism. Accordingly, immobilization of [IrBr 6 ] 2- molecules in thin polymer films results in an order-of-magnitude increase in coherence lifetime and significantly greater magnetic field sensitivity. Here, by tuning energies of ligand-to-metal charge transfer (LMCT) states, TRFE/R enables spin initialization and readout in the tissue transparency window, paving the way toward all-optical, ultrafast molecular electron spin coherence imaging in biological systems.

Electron paramagnetic resonance spectroscopy↗

Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project

An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate clinical, biological and imaging data from patients with kidney disease. Ontologies are powerful tools that facilitate these efforts by enabling researchers to organize and make sense of different data elements and the relationships between them. Ontologies are critical to support the types of big data analysis necessary for kidney precision medicine, where heterogeneous clinical, imaging and biopsy data from diverse sources must be combined to define a patient’s phenotype. Here, the development of two new ontologies — the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation — will support the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney. These ontologies will improve the annotation of kidney-relevant data, and eventually lead to new definitions of kidney disease in support of precision medicine.

60 APPLIED LIFE SCIENCES↗

Shear wave generation by mode conversion in picosecond ultrasonics: Impact of grain orientation and material properties

Abstract Picosecond ultrasonics has seen wide application in the investigation of interfaces in semiconductors and 3D imaging in biological systems. Shear ultrasonic waves are important for elastic constant and grain orientation measurement in ceramic materials. In this study, we investigate the impact of grain orientation and material's elastic properties on the generation efficiency of shear waves by mode conversion at a transducer thin film/substrate interface. The solution of acoustic wave equations suggests that crystal grain orientation has a strong impact on the generated shear wave amplitude. This dependence is found to be closely related to the magnitude of longitudinal component of wave displacements. The applicability of analytical model is validated by the experimental results from time‐domain Brillouin scattering. Moreover, material properties determine acoustic wave amplitudes based on the acoustic mismatch model and, particularly, large elastic anisotropy defined by Zener ratio favors strong shear waves. In the light of this analysis, several recommendations on suitable grain orientations and film materials are made to facilitate shear wave detection.

Wang, Yuzhou↗

Enabling robust, stable, and accurate nonlinear optical measurements from squeezed light generated in hot rubidium vapor

The feasibility of nonlinear optical (NLO) imaging and spectroscopy using low intensity quantum states of light including entangled photon and squeezed light sources, such as those driven by two-photon absorption (TPA), has been a topic of ongoing debate. An unambiguous identification of the appreciable quantum advantage in such quantum light applications could enable NLO imaging of biological samples without photodegradation and phototoxicity. Recently, we have constructed a two-mode squeezed light source based on four-wave mixing in 85Rb vapor, which is capable of 7.9 dB of intensity-difference squeezing (IDS), corresponding to 8.7 dB upon electronic noise correction. In this talk, we discuss the stability of our system, including implementation details on achieving and maintaining 8.7 dB of IDS for several hours, and ensuring the two spatially multimode beams are properly overlapped in a sample with minimal optical loss.

Allen, Harry [ORNL] (ORCID:0000000190253914)↗

Performance of novel VUV-sensitive Silicon Photo-Multipliers for nEXO

Liquid xenon time projection chambers are promising detectors to search for neutrinoless double beta decay (0νββ), due to their response uniformity, monolithic sensitive volume, scalability to large target masses, and suitability for extremely low background operations. The nEXO collaboration has designed a tonne-scale time projection chamber that aims to search for 0νββ of 136 Xe with projected half-life sensitivity of 1.35 x 10 28 yr. To reach this sensitivity, the design goal for nEXO is ≤1% energy resolution at the decay Q-value (2458.07 ± 0.31 keV). Reaching this resolution requires the efficient collection of both the ionization and scintillation produced in the detector. The nEXO design employs Silicon Photo-Multipliers (SiPMs) to detect the vacuum ultra-violet, 175 nm scintillation light of liquid xenon. This paper reports on the characterization of the newest vacuum ultra-violet sensitive Fondazione Bruno Kessler VUVHD3 SiPMs specifically designed for nEXO, as well as new measurements on new test samples of previously characterised Hamamatsu VUV4 Multi Pixel Photon Counters (MPPCs). Various SiPM and MPPC parameters, such as dark noise, gain, direct crosstalk, correlated avalanches and photon detection efficiency were measured as a function of the applied over voltage and wavelength at liquid xenon temperature (163 K). The results from this study are used to provide updated estimates of the achievable energy resolution at the decay Q-value for the nEXO design.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Adaptive optics for optical microscopy [Invited]

Optical microscopy is widely used to visualize fine structures. When applied to bioimaging, its performance is often degraded by sample-induced aberrations. In recent years, adaptive optics (AO), originally developed to correct for atmosphere-associated aberrations, has been applied to a wide range of microscopy modalities, enabling high- or super-resolution imaging of biological structure and function in complex tissues. Here, we review classic and recently developed AO techniques and their applications in optical microscopy.

59 BASIC BIOLOGICAL SCIENCES↗

Direct Visualization of Charge Migration in Bilayer Tantalum Oxide Films by Multimodal Imaging

Inspired by biological neuromorphic computing, artificial neural networks based on crossbar arrays of bilayer tantalum oxide memristors have shown to be promising alternatives to conventional complementary metal-oxide-semiconductor (CMOS) architectures. In order to understand the driving mechanism in these oxide systems, tantalum oxide films are resistively switched by conductive atomic force microscopy (C-AFM), and subsequently imaged by kelvin probe force microscopy (KPFM) and spatially resolved time-of-flight secondary ion mass spectrometry (ToF-SIMS). These workflows enable induction and analysis of the resistive switching mechanism as well as control over the resistively switched region of the film. In this work it is shown that the resistive switching mechanism is driven by both current and electric field effects. Reversible oxygen motion is enabled by applying low (<1 V) electric fields, while high electric fields generate irreversible breakdown of the material (>1 V). Fully understanding oxygen motion and electrical effects in bilayer oxide memristor systems is a fundamental step toward the adoption of memristors as a neuromorphic computing technology.

36 MATERIALS SCIENCE↗

Imaging Intact Filamentous Fungi from Spore to Hyphal Tip on the Nanoscale

Previously, the Pacific Northwest National Laboratory was limited by a 3-order of magnitude gap in resolution for direct 2-D and 3-D imaging of chemical, biological, energy and materials science systems. Our imaging instrumentation could directly visualize 3-D ultrastructure without labeling at resolutions less than 10-nanometers or greater than 10-micrometers. To address this gap, we procured and commissioned a Sigray NanoFast Bio-Lambda laboratory-based x-ray nanotomography system. This equipment provides the capability to image through tens of micrometers of organic materials at down to 35-nanometer resolution to bridge the nanoscale to the mesoscale for biological systems, organic polymers, environmental and particulate samples.

47 OTHER INSTRUMENTATION↗

Experimental study of energy-dependent angular broadening of MeV electron beams for high-resolution imaging in thick samples

In scanning transmission electron microscopy (STEM), spatial resolution is primarily influenced by the projected size of the electron probe within the specimen. In thin samples, a large semi-convergence angle enables a tightly focused beam and sub-nanometer resolution. However, in thick specimens, resolution is fundamentally limited by transverse beam broadening from multiple large-angle scattering events—for example, a probe with 10 mrad angular divergence can broaden by ∼100 nm over a 10 μm path. Since this broadening scales inversely with beam energy, MeV-STEM offers a promising route for high-resolution imaging in thick materials. To quantitatively assess this effect, we performed high-precision measurements at UCLA’s PEGASUS beamline, characterizing beam divergence and intensity profiles for 3–8 MeV electrons transmitted through a wedged-silicon sample of varying thickness. Our results reconcile discrepancies among analytical models and validate Monte Carlo simulations. Here, we find that increasing beam energy from 3.0 to 5.8 MeV reduces angular broadening by a factor of 2.6, with diminishing returns observed at 7.6 MeV. These findings provide a quantitative framework for optimizing MeV-STEM parameters in high-resolution imaging of thick biological and microelectronic specimens, and for guiding beam energy selection in other advanced imaging modes beyond STEM.

36 MATERIALS SCIENCE↗

A Step-by-Step Protocol from METASPACE to Biological Interpretation

Mass spectrometry imaging (MSI) represents an exceptional tool for exploring complex biological systems spatially at the molecular level. However, due to its multidimensional nature and large-scale data output, it presents considerable challenges when it comes to extracting meaningful biological insights. Recent advancements, such as the METASPACE platform, have enabled researchers to efficiently process, annotate, and interpret MSI datasets by leveraging machine learning and cloud-based infrastructure. In this tutorial, we present a detailed and user-friendly R-pipeline designed to help METASPACE users navigate untargeted metabolomic annotations and transform them into practical insights about their biological systems. By combining METASPACE annotations with rapid R-based screening, this workflow not only streamlined the analytical process but also enhanced the understanding of spatial molecular distribution, especially for complex systems. Here, this easy-to-follow approach has the potential for applications in diagnostics, drug discovery, environmental and ecological processes, and more. We envision this pipeline to be particularly useful for newcomers to the field of MSI and

Moreno Pedraza, Abigail↗

3D quantum ghost imaging microscope

Quantum ghost imaging uses quantum-entangled photons to generate a two-dimensional image with only a bucket detector at the sample. Here we expand on this approach to generate a three-dimensional image without scanning. A quantum-entangled light source directly links information between a pair of 2D sensors, one of which captures a standard image from one perspective and a second sensor which captures a ghost image from a perpendicular perspective. By correlating the spatial information from the two detectors for each photon pair, we obtain three dimensions of spatial information (x, y, and z) for each scattered photon. We demonstrate that this system can study microscopic environments by imaging scattering from metallic nanoparticle clusters. This approach has the potential to greatly reduce the flux of light required to obtain a 3D image of a biological sample and thereby extend the number of images that can be obtained before photodamaging the sample.

Eshun, Audrey [Lawrence Livermore National Laborat↗

NanoSIP: NanoSIMS Applications for Microbial Biology

High-resolution imaging with secondary ion mass spectrometry (nanoSIMS) has become a standard method in systems biology and environmental biogeochemistry and is broadly used to decipher ecophysiological traits of environmental microorganisms, metabolic processes in plant and animal tissues, and cross-kingdom symbioses. When combined with stable isotope-labeling—an approach we refer to as nanoSIP—nanoSIMS imaging offers a distinctive means to quantify net assimilation rates and stoichiometry of individual cell-sized particles in both low- and high-complexity environments. While the majority of nanoSIP studies in environmental and microbial biology have focused on nitrogen and carbon metabolism (using 15 N and 13 C tracers), multiple advances have pushed the capabilities of this approach in the past decade. The development of a high-brightness oxygen ion source has enabled high-resolution metal analyses that are easier to perform, allowing quantification of metal distribution in cells and environmental particles. New preparation methods, tools for automated data extraction from large data sets, and analytical approaches that push the limits of sensitivity and spatial resolution have allowed for more robust characterization of populations ranging from marine archaea to fungi and viruses. Further, NanoSIMS studies continue to be enhanced by correlation with orthogonal imaging and ‘omics approaches; when linked to molecular visualization methods, such as in situ hybridization and antibody labeling, these techniques enable in situ function to be linked to microbial identity and gene expression. Here we present an updated description of the primary materials, methods, and calculations used for nanoSIP, with an emphasis on recent advances in nanoSIMS applications, key methodological steps, and potential pitfalls.

07 ISOTOPE AND RADIATION SOURCES↗

Adaptive optical third-harmonic generation microscopy for in vivo imaging of tissues

Third-harmonic generation microscopy is a powerful label-free nonlinear imaging technique, providing essential information about structural characteristics of cells and tissues without requiring external labelling agents. In this work, we integrated a recently developed compact adaptive optics module into a third-harmonic generation microscope, to measure and correct for optical aberrations in complex tissues. Taking advantage of the high sensitivity of the third-harmonic generation process to material interfaces and thin membranes, along with the 1,300-nm excitation wavelength used here, our adaptive optical third-harmonic generation microscope enabled high-resolution in vivo imaging within highly scattering biological model systems. Examples include imaging of myelinated axons and vascular structures within the mouse spinal cord and deep cortical layers of the mouse brain, along with imaging of key anatomical features in the roots of the model plant Brachypodium distachyon. In all instances, aberration correction led to enhancements in image quality.

60 APPLIED LIFE SCIENCES↗

Quantum Imaging with X-rays

Quantum imaging encompasses a broad range of methods that exploit the quantum properties of light to capture information about an object. One such approach involves using a two-photon quantum state, where only one photon interacts with the object being imaged while its entangled partner carries spatial or temporal information. To implement this technique, it is necessary to generate specific quantum states of light and detect photons at the single-photon level. While this method has been successfully demonstrated in the visible electromagnetic spectrum, extending it to X-rays has faced significant challenges due to the difficulties in producing a sufficient rate of X-ray photon pairs and detecting them with adequate resolution. Here, we demonstrate record high rates of correlated X-ray photon pairs produced via a spontaneous parametric down-conversion process and we employ these photons to perform quantum correlation imaging of several objects, including a biological sample (E. cardamomum seedpod). Notably, we report an unprecedented detection rate of about 6,300 pairs per hour and the observation of energy anti-correlation for the X-ray photon pairs. We also present a detailed analysis of the properties of the down-converted X-ray photons, as well as a comprehensive study of the correlation imaging formation, including a study of distortions and corrections. These results mark a substantial advancement in X-ray quantum imaging, expanding the possibilities of X-ray quantum optical technologies, and illustrating the pathway towards enhancing biological imaging with reduced radiation doses.

Gofron, Kaz [ORNL] (ORCID:0000000314415736)↗

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

In materials science, plant biology, agriculture, and environmental research, the automated analysis of high-magnification, complex microscopy images, such as those generated by freeze-fracture electron microscopy (FF-TEM), remains a critical challenge that limits the scalability of data interpretation. We present a deep learning computer vision pipeline for high-throughput detection and morphological characterization analysis of cellulose synthase complexes (CSCs, or rosettes) in FF-TEM images. The pipeline integrates preprocessing, detection, human-in-the-loop verification, and semantic segmentation to quantify features such as rosette diameter and inter-lobe spacing. The approach was trained and tested on a curated dataset of high-resolution FF-TEM micrographs of Physcomitrium patens, expanded via strategic tiling and augmentation to over 650 images. We compare YOLOv8 and YOLOv9 architectures and demonstrate that YOLOv9 achieves superior performance in both localization accuracy (mAP50-95 = 0.854) and inference speed. The resulting distributions revealed biological variability consistent with prior manual studies, validating the approach for high-throughput applications. Our results show that the pipeline achieves human-expert level accuracy while dramatically reducing analysis time, enabling scalable, reproducible structural characterization of intramembrane protein complexes. The pipeline is broadly applicable to other domains requiring precise interpretation of complex microscopy data and establishes a foundation for future artificial intelligence (AI)-assisted workflows in biological imaging.

59 BASIC BIOLOGICAL SCIENCES↗

Optimize Electron Beam Energy toward In Situ Imaging of Thick Frozen Bio-Samples with Nanometer Resolution Using MeV-STEM

To optimize electron energy for in situ imaging of large biological samples up to 10 μm in thickness with nanoscale resolutions, we implemented an analytical model based on elastic and inelastic characteristic angles. This model has been benchmarked by Monte Carlo simulations and can be used to predict the transverse beam size broadening as a function of electron energy while the probe beam traverses through the sample. As a result, the optimal choice of the electron beam energy can be realized. In addition, the impact of the dose-limited resolution was analysed. While the sample thickness is less than 10 μm, there exists an optimal electron beam energy below 10 MeV regarding a specific sample thickness. However, for samples thicker than 10 μm, the optimal beam energy is 10 MeV or higher depending on the sample thickness, and the ultimate resolution could become worse with the increase in the sample thickness. Moreover, a MeV-STEM column based on a two-stage lens system can be applied to reduce the beam size from one micron at aperture to one nanometre at the sample with the energy tuning range from 3 to 10 MeV. In conjunction with the state-of-the-art ultralow emittance electron source that we recently implemented, the maximum size of an electron beam when it traverses through an up to 10 μm thick bio-sample can be kept less than 10 nm . This is a critical step toward the in situ imaging of large, thick biological samples with nanometer resolution.

36 MATERIALS SCIENCE↗