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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

In Situ Transmission Electron Microscopy Study of Conductive Filament Formation in Copper Oxides

The structural and electrical property changes of two types of copper oxides (CuO and Cu 2 O) under voltage bias are studied with in situ transmission electron microscopy (TEM). The phases of different materials are confirmed with electron diffraction. In both types of oxides, dynamic conductive path formation and dissolution are observed. The decrease in resistance of CuO film is found to be accompanied with the formation of Cu 4 O 3 phase where the electric field strength is highest. We also find that the decrease in resistivity of Cu 2 O film is more extensive and occurs in an area depending on the level of current compliance. In conclusion, the physical mechanisms responsible for the observations and their implications for the formation of conducting regions in copper oxide-based memristors are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Iterative Learning Control for Video-rate Atomic Force Microscopy

We present a control scheme for video-rate atomic force microscopy with rosette pattern. The controller structure involves a feedback internal-model-based controller and a feedforward iterative learning controller. The iterative learning controller is designed to improve tracking performance of the feedback-controlled scanner by rejecting the repetitive disturbances arising from the system nonlinearities. We investigate the performance of two inversion techniques for constructing the learning filter. We conduct tracking experiments using a two-degree-of-freedom microelectromechanical system (MEMS) nanopositioner at frame rates ranging from 5 to 20 frames per second. Furthermore, the results reveal that the algorithm converges rapidly and the iterative learning controller significantly reduces both the transient and steady-state tracking errors. We acquire and report a series of high-resolution time-lapsed video-rate AFM images with the rosette pattern.

42 ENGINEERING↗
DOE OSTI2021

Applications of analytical electron microscopy to guide the design of boron carbide

Compositional analysis of boron carbide on nanometer length scales to examine or interpret atomic mechanisms, for example, solid-state amorphization or grain-boundary segregation, is challenging. This work reviews advancements in high-resolution microanalysis to characterize multiple generations of boron carbide. First, ζ-factor microanalysis will be introduced as a powerful (scanning) transmission electron microscopy ((S)TEM) analytical framework to accurately characterize boron carbide. Three case studies involving the application of ζ-factor microanalysis will then be presented: (1) accurate stoichiometry determination of B-doped boron carbide using ζ-factor microanalysis and electron energy loss spectroscopy, (2) normalized quantification of silicon grain-boundary segregation in Si-doped boron carbide, and (3) calibration of a scanning electron microscope X-ray energy-dispersive spectroscopy (XEDS) system to measure compositional homogeneity differences of B/Si-doped arc-melted boron carbides in the as-melted and annealed conditions. Overall, the improvement and application of advanced analytical tools have helped better understand processing–microstructure–property relationships and successfully manufacture high-performance ceramics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

In situ plasmonic tip preparation and validation techniques for scanning tunneling microscopy

Among the many parts constituting a scanning tunneling microscope, the metallic tip is the component that directly interacts with the specimen and plays a critical role in visualizing the physical quantity of interest. While tip materials such as W and Pt–Ir are commonly used for topographic imaging and their preparation is well-documented, the preparation of plasmonic materials such as Ag for tip-enhanced Raman spectroscopy is relatively less standardized. Furthermore, we present several in situ Ag tip preparation and validation techniques for the microscopist to use depending on their intended application, including atomic resolution imaging, scanning tunneling spectroscopy (STM), and tip-enhanced Raman spectro-microscopy in ultrahigh vacuum. Besides optical applications, these methods are not limited to Ag but also applicable to other STM tip materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Combining molecular beam epitaxy and low-energy electron microscopy with in situ magnetic susceptibility measurements within an integrated ultrahigh vacuum system

Quantum two-dimensional materials, including ultrathin superconducting films, are of great current research interest. These films are typically fabricated under ultra-high vacuum (UHV) conditions and are sensitive to the environment—prone to oxidation and contamination when exposed to the atmosphere. This hampers the study of their intrinsic properties by standard ex situ techniques. Here, we present a variable-temperature mutual inductance probe system integrated under UHV with molecular beam epitaxy (MBE) synthesis and low-energy electron microscopy, enabling nondestructive in situ characterization of superconducting thin films. The system employs a reflection-type configuration and reaches a low temperature (∼4 K) using a high-cooling-power, vibration-isolated cryocooler. In conclusion, we demonstrate the system performance by measuring the superconducting critical temperature in a copper-oxide thin film.

2D materials↗
DOE OSTI2023

Quantitative Scanning Transmission Electron Microscopy for Materials Science: Imaging, Diffraction, Spectroscopy, and Tomography

Scanning transmission electron microscopy (STEM) is one of the most powerful characterization tools in materials science research. Due to instrumentation developments such as highly coherent electron sources, aberration correctors, and direct electron detectors, STEM experiments can examine the structure and properties of materials at length scales of functional devices and materials down to single atoms. STEM encompasses a wide array of flexible operating modes, including imaging, diffraction, spectroscopy, and 3D tomography experiments. This review outlines many common STEM experimental methods with a focus on quantitative data analysis and simulation methods, especially those enabled by open source software. The hope is to introduce both classic and new experimental methods to materials scientists and summarize recent progress in STEM characterization. The review also discusses the strengths and weaknesses of the various STEM methodologies and briefly considers promising future directions for quantitative STEM research.

36 MATERIALS SCIENCE↗
DOE OSTI2020

In situ electrochemical scanning/transmission electron microscopy of electrode–electrolyte interfaces

Insights into the dynamics of electrochemical processes are critically needed to improve our fundamental understanding of electron, charge, and mass transfer mechanisms and reaction kinetics that influence a broad range of applications, from the functionality of electrical energy-storage and conversion devices (e.g., batteries, fuel cells, and supercapacitors), to materials degradation issues (e.g., corrosion and oxidation), and materials synthesis (e.g., electrodeposition). To unravel these processes, in situ electrochemical scanning/transmission electron microscopy (ec-S/TEM) was developed to permit detailed site-specific characterization of evolving electrochemical processes that occur at electrode–electrolyte interfaces in their native electrolyte environment, in real time and at high-spatial resolution. This approach utilizes “closed-form” microfabricated electrochemical cells that couple the capability for quantitative electrochemical measurements with high spatial and temporal resolution imaging, spectroscopy, and diffraction. Here, we review the state-of-the-art instrumentation for in situ ec-S/TEM and how this approach has resulted in new observations of electrochemical processes.

25 ENERGY STORAGE↗
DOE OSTI2023

Resolving intragranular stress fields in plastically deformed titanium using point-focused high-energy diffraction microscopy

Abstract The response of a polycrystalline material to a mechanical load depends not only on the response of each individual grain, but also on the interaction with its neighbors. These interactions lead to local, intragranular stress concentrations that often dictate the initiation of plastic deformation and consequently the macroscopic stress–strain behavior. However, very few experimental studies have quantified intragranular stresses across bulk, three-dimensional volumes. In this work, a synchrotron X-ray diffraction technique called point-focused high-energy diffraction microscopy (pf-HEDM) is used to characterize intragranular deformation across a bulk, plastically deformed, polycrystalline titanium specimen. The results reveal the heterogenous stress distributions within individual grains and across grain boundaries, a stress concentration between a low and high Schmid factor grain pair, and a stress gradient near an extension twinning boundary. This work demonstrates the potential for the future use of pf-HEDM for understanding the local deformation associated with networks of grains and informing mesoscale models. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2020

Data Report: High-Resolution Microscopy Images of Sediments from Green Canyon Block 955, Gulf of Mexico

We took Leica microscopy images of sediment samples acquired at Holes H002 (4 samples) and H005 (1 sample) during the UT-GOM2-1 Expedition in Green Canyon Block 955, in the northern Gulf of Mexico. A total of 37 images were acquired. The images document a prevalence of spherical conchoidal minerals, cleavage planes typical of feldspar or mica, and black fragmented minerals which stand out from the surrounding matrix. Drilling mud intrusion is thought to contribute to a grey metallic matrix observed across multiple samples.

03 NATURAL GAS↗
DOE OSTI2025

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science

This presentation explores the transformative potential of autonomous electron microscopy and artificial intelligence (AI) in accelerating materials science discovery, particularly for energy applications and materials operating in extreme environments. We discuss pioneering self-driving laboratories at NREL designed to intelligently probe material synthesis and degradation across multiple scales, aiming to rapidly bridge the gap between atomic-level understanding and the development of high-performance, reliable materials. Utilizing advanced machine learning techniques, such as few-shot learning and multimodal analysis integrating imaging and spectroscopy, we demonstrate methods to extract actionable descriptors for material behavior, quantify complex microstructural evolution, and statistically link synthesis parameters to defect populations. This AI-driven approach promises to accelerate the creation of predictive materials tailored for specific missions, enabling faster development cycles and enhanced material assurance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science

This presentation explores the transformative potential of autonomous electron microscopy and artificial intelligence (AI) in accelerating materials science discovery, particularly for energy applications and materials operating in extreme environments. We discuss pioneering self-driving laboratories at NREL designed to intelligently probe material synthesis and degradation across multiple scales, aiming to rapidly bridge the gap between atomic-level understanding and the development of high-performance, reliable materials. Utilizing advanced machine learning techniques, such as few-shot learning and multimodal analysis integrating imaging and spectroscopy, we demonstrate methods to extract actionable descriptors for material behavior, quantify complex microstructural evolution, and statistically link synthesis parameters to defect populations. This AI-driven approach promises to accelerate the creation of predictive materials tailored for specific missions, enabling faster development cycles and enhanced material assurance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

The Art of Automation: Translating Electron Microscopy Workflows Into Automated Processes

Acquiring data using a scanning transmission electron microscope (STEM) is a complex, multi-step process. The intricacy of the process depends on the type of sample, composition of the material, desired results of the experiment, resolution requirement and other experimental factors. Each experiment presents unique complications, such as sample drift and contamination, that the microscopist must consider when acquiring data. All these challenges are handled fluidly and expertly by experienced microscopists, but to reach new levels of innovation in material development, including greater reproducibility, throughput, and precision, the automation of these workflows is essential. The initial phase of this work involved translating intuition-based workflows into discrete, programmable steps. Some common key stages in STEM workflows are the initial tuning, scanning the sample for areas of interest, and then acquiring the data. Each stage can be broken further into specific parameter adjustments, such as aberration correction and dwell time optimization, depending on the experiment. When deconstructing various experiments each step was assessed for automation feasibility based on the amount of real time operator decisions. There are steps that lend themselves to automation more readily than others, such as course focusing and sample screening, but there is potential for full automation of all stages with time. As an initial step, an automated montage routine was developed, allowing for the efficient acquisition of large portions of the sample without requiring continuous intervention from the operator. The automation of this small process of the procedure demonstrates the value of this capability. A major challenge in automation arises from discrepancies between commanded, reported and actual stage movements. Using systematic tests, stage movement was quantified. This error can be corrected algorithmically for more accurate workflows in the future. Expanding automation capabilities would result in larger, more efficient data acquisition which allows for more robust statistical analysis. Additionally, this work lays the groundwork for a closed loop system where machine learning algorithms would intake automatically acquired data and make real time decisions. By progressively automating this instrument, this work establishes the foundation for fully automated experimentation in transmission electron microscopy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Probing Dynamic Phase Changes in Electrochemical Systems with Cryogenic and in Situ Analytical Electron Microscopy (Final Technical Report)

In this project, we focus on the advancement of our newly developed, unique in situ and cryogenic analytical electron microscopy (AEM) techniques and the development of additional high-end capabilities to quantitatively elucidate the mechanisms of resistive state changes in solid-state electrochemical materials for non-volatile, neuromorphic memory. The objectives of the proposed research are (1) to characterize and elucidate the mechanisms by which electronic state changes occur in various solid-state devices to build guiding principles for electrochemically activated smart materials; (2) to advance our understanding of such mechanisms by coupling cryogenic and in situ techniques to control kinetics of the observed mechanisms while mitigating probe-induced damage; and (3) to utilize additional advanced techniques including electron-beam induced current and quantum mechanical simulations in order to identify the underlying fundamental science of such processes, including roles of defect formation and its effect on phase nucleation, as well as dynamics of these processes in the electrochemical systems at the nanometer scale.

25 ENERGY STORAGE↗
DOE OSTI2026

Development of high throughput light-sheet fluorescence lifetime imaging microscopy for 3D functional imaging of metabolic pathways in plant and microorganisms (Final Technical Report)

This research program will enable new biochemical contrast in the nanosecond lifetime domain through use of the recently demonstrated electro-optic fluorescence lifetime imaging technique (EO-FLIM) for wide-field lifetime imaging. The Stanford/Stanford Linear Accelerator Center multidisciplinary collaboration -- physics, applied physics, and structural biology -- will develop a light-sheet fluorescence lifetime imaging microscope for functional studies of microbial and plant metabolic pathways and dynamic interactions between plants and microorganisms in the rhizosphere. The proposed approach overcomes the imaging time bottleneck associated with existing fluorescence lifetime imaging methods. Initial demonstrations have shown a factor of 100,000 improvement in photon throughput compared to existing methods. High photon efficiency allowed the first wide-field fluorescence lifetime imaging of single molecules. Recent work has improved the technique’s repetition rate to enable compatibility with mode-locked lasers and demonstrated the combination of wide-field fluorescence lifetime imaging with super-resolution localization microscopy, observations of single molecule dynamics, and observation of donor lifetime quenching in single-molecule imaging. These results were achieved on standard camera sensors and would not have been possible with other wide-field approaches. The throughput and photon economy of the EO-FLIM method enables new BER-relevant imaging opportunities. In particular, scanned single- and two-photon light-sheet excitation will be used to achieve volumetric imaging with time-domain contrast.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Bridging multimodal microscopy for advanced characterization on nuclear fuel using machine learning

Uranium dioxide (UO 2 ), widely used as driver fuel in light water reactors, experiences microstructure and property change by nuclear fission reactions. This paper bridges the characterization of fresh UO 2 fuel at different length scales, serving as a baseline for future post irradiation examination of irradiated UO 2 fuel. To characterize the microstructural change of nuclear fuel, modern approaches cover a wide range of length scales through different characterization techniques, such as mm scale for Synchrotron-based X-ray computed tomography (SXCT) and microscale for focused ion beam (FIB) and scanning electron microscopy (SEM). It is challenging to bridge the data and knowledge of the same sample in different length scales. This paper proposed a deep learning framework leveraging transfer learning to detect microstructural defects, trained from a sparse FIB, SEM, and SXCT images. The proposed model achieved superior performance in defect segmentation on multiscale microscopic data compared to four of the latest deep learning models.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Investigation of the thermal decomposition of Pu(IV) oxalate: a transmission electron microscopy study

The degradation of the internal structure of plutonium (IV) oxalate during calcination was investigated with Transmission Electron Microscopy (TEM), electron diffraction, Electron Energy-Loss Spectroscopy (EELS), and 4D Scanning TEM (STEM). TEM lift-outs were prepared from samples that had been calcined at 300°C, 450°C, 650°C and 950°C. The resulting phase at all calcination temperatures was identified as PuO 2 with electron diffraction. The grain size range was obtained with high-resolution TEM. In addition, 4D STEM images were analyzed to provide grain size distributions. In the 300°C calcined sample, the grains were <10 nm in diameter, at 650°C, the grains ranged from 10 to 20 nm, and by 950°C, the grains were 95–175 nm across. Using the Kolmogorov-Smirnov (K-S) two sample test, it was shown that morphological measurements obtained from 4D-STEM provided statistically significant distributions to distinguish samples at the different calcination conditions. Using STEM-EELS, carbon was shown to be present in the low temperature calcined samples associated with oxalate but had formed carbon (possibly graphite) deposits in the 950°C calcined sample. This work highlights the new methods of STEM-EELS and 4D-STEM for studying the internal structure of special nuclear materials (SNM).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Use of X-Ray Fluorescence Microscopy for Studies on Research Models of Hepatocellular Carcinoma

Introduction: TheraSphere ® microspheres containing yttrium 90 Y are among many radioembolization agents used clinically to reduce liver tumor burden, and their effects on cancer volume reduction are well-established. At the same time, concerns about off target tissue injury often limit their use. Deeper investigation into tissue distribution and long-term impact of these microspheres could inform us about additional ways to use them in practice. Methods: Healthy rat liver and rabbit liver tumor samples from animals treated with TheraSpheres were sectioned and their elemental maps were generated by X-ray fluorescence microscopy (XFM) at the Advanced Photon Source (APS) synchrotron at Argonne National Laboratory (ANL). Results: Elemental imaging allowed us to identify the presence and distribution of TheraSpheres in animal tissues without the need for additional sample manipulation or staining. Ionizing radiation produced by 90 Y radioactive contaminants present in these microspheres makes processing TheraSphere treated samples complex. Accumulation of microspheres in macrophages was observed. Conclusions: This is the first study that used XFM to evaluate the location of microspheres and radionuclides in animal liver and tumor samples introduced through radioembolization. XFM has shown promise in expanding our understanding of radioembolization and could be used for investigation of human patient samples in the future.

60 APPLIED LIFE SCIENCES↗