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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Single layer graphene protective layer on GaAs photocathodes for spin-polarized electron source

GaAs-based photocathodes are the primary choice for polarized electron sources, commonly used in polarized electron microscopes and polarized positron sources. GaAs photocathodes are typically activated with cesium and oxygen, which are highly reactive and require an ultra-high vacuum (⁠~ 10 -11 Torr or lower) to operate reliably, resulting in substantial operational difficulties. A short exposure to a mediocre vacuum results in an instantaneous loss of cathode quantum efficiency (QE) due to the chemical reaction of the active layer with residual gas molecules or back-bombardment ions during operation. Covering the GaAs cathode with a 2D material, such as monolayer graphene, could provide protection against such damage due to the inhibition of chemical reactions with residual gas molecules. In this paper, we have incorporated a method known as intercalation to pass the active material underneath the graphene and activate the superlattice GaAs/GaAsP (SL-GaAs) photocathode. X-ray photoelectron spectroscopy, low-energy electron microscopy, and Mott scattering measurements were performed to evaluate the formation of the photocathode under graphene, as well as its spectral response and electron spin polarization. Our results demonstrate that the successful activation of the SL-GaAs photocathode with a graphene protection layer is achieved with a moderate QE. Furthermore, we found that the electron spin polarization of the cathode with a surface protection layer is higher than the conventional cathode without a protection layer.

2D materials↗
DOE OSTI2026

Illuminating the Material World: Autonomous Microscopy to Understand Order, Disorder, and Everything In Between

Artificial intelligence (AI) holds immense promise for revolutionizing microscopy, yet its widespread adoption has been hindered by challenges ranging from user inexperience to limited model transferability and difficulties in operationalizing machine learning. This presentation showcases our approach to developing practical autonomy for materials discovery, aiming to accelerate the integration of AI into everyday microscopy workflows. As shown in Fig. 1, I will focus on three key areas: understanding order-disorder transitions, quantifying point defects, and achieving truly device-scale microscopy. First, I will demonstrate the power of multi-modal knowledge graphs for integrating diverse microscopy data. By combining imaging, spectroscopy, and diffraction data, these graphs provide a holistic view of material behavior, capturing the intricate relationships between different modalities [1,2]. I will present a case study on how these models illuminate the structural and chemical changes associated with irradiation in oxide thin films, revealing critical insights for designing materials for extreme environments like spaceflight and nuclear energy. Specifically, I will show how multi-modal analysis clarifies the evolution of order-disorder transitions under irradiation, a key factor influencing material performance in these applications. Next, I will address the challenge of quantifying point defects in 2D materials. We demonstrate the application of computer vision and transfer learning to accurately identify and classify various defect types, such as vacancies and substitutional atoms, and to quantify their concentrations. This information is crucial for understanding and tailoring the properties of 2D materials for applications in electronics, optoelectronics, and catalysis. For example, I will show how our models can characterize the topological distribution of point defects in MXene transition metal carbides, providing valuable insights for optimizing their performance in energy storage and separation science. Finally, I will discuss our progress toward autonomous device-scale microscopy [3,4]. We are fundamentally redesigning electron microscopes around the principles of machine reasoning, enabling automation beyond basic tasks like sample navigation and data acquisition to include sophisticated experimental design. This approach paves the way for truly reproducible and massively scaled analysis campaigns. I will emphasize the importance of autonomous microscopy platforms for high-throughput materials discovery and characterization, facilitating the rapid screening of materials for a broad range of applications and accelerating the development of next-generation technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Topotactic Reduction‐Driven Crystal Field Excitations in Brownmillerite Manganite Thin Films

Topotactic reduction of perovskite oxides offers a powerful approach for discovering novel phenomena, such as superconducting infinite-layer nickelates and polar metallicity, and is commonly accompanied by the emergence of multiple valence states and/or complex crystal fields of transition metals. However, understanding the complex interplay between crystal chemistry, electronic structure, and physical properties at the spin- and orbital-resolved levels in these reduced systems remains elusive. Here, in this study, x-ray absorption spectroscopy, resonant inelastic x-ray scattering (RIXS), and density functional theory calculations are used to uncover topotactic metal-insulator transition and orbital-specific crystal field excitations in brownmillerite La 0.67 Ca 0.33 MnO 2.5 thin films. The Mn valence states are found to be Mn 2+ /Mn 3+ , along with their corresponding populations at octahedral and tetrahedral sites, which effectively weaken the Mn-O hybridization compared to the parent perovskite phase. As a result, La 0.67 Ca 0.33 MnO 2.5 films exhibit an antiferromagnetic insulating ground state. Moreover, by combining the RIXS measurements on selected single-valence manganites, specifically MnO, LaMnO 3 , and CaMnO 3 , with orbital- and spin-resolved density-of-states calculations, the study identifies the dd excitations of octahedrally and tetrahedrally coordinated Mn 2+ /Mn 3+ ions, directly linking the microscopic electronic structure to the macroscopic magnetic/electrical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Characterization of Incremental Markings in the Sagittal Otolith of the Pacific Sardine ( Sardinops sagax ) Using Different Imaging Modalities

Teleost fish possess calcium carbonate otoliths located in separate chambers (utriculus, sacculus, and lagena) of their membranous labyrinth. This study analyzed the surface topography of the sagittal otolith of the Pacific sardine (Sardinops sagax) and the daily and annual increments in these otoliths. The otolith surface, characterized by laser scanning confocal microscopy for the first time, consisted of a system of prominent ridges and valleys (grooves), but it is unclear whether these structures are functional or represent time-resolving markings reflecting growth periodicity. Within the first-year volume, daily increments, each consisting of an incremental (more mineralized) and a discontinuous (less mineralized) zone, were resolved by optical microscopy and backscattered electron (BSE) imaging in the scanning electron microscope (SEM). Daily growth increments could, however, not be resolved in volumes formed after the first year, presumably because otolith growth markedly slows down and spacing of incremental markings narrows in older fish. Throughout otolith growth, the crystalline network continues across the discontinuous zones. Fluorochrome labeling provides additional information on growth after the first year. Compared with optical and BSE imaging, synchrotron microComputed Tomography of intact otoliths (with 0.69 µm volume elements) was less able to resolve daily increments; X-ray phase contrast reconstructions provided more detail than reconstructions with absorption contrast. Future research directions are proposed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Revealing Progressive Degradation of Cobalt Oxide Nanoparticles During Thermochemical Redox Cycling via Operando STEM-EELS

Metal oxides are promising materials for long-duration thermochemical energy storage. Efforts to characterize their reaction kinetics, conversion rate, and morphological evolution during thermochemical cycling have largely focused on bulk and microscale measurements. However, the design of nanostructured metal oxides could improve the reaction reversibility and kinetics, warranting the development of platforms to investigate how these materials behave at the nanoscale. Here, we demonstrate the use of correlative, time-resolved electron energy loss spectroscopy and imaging in an environmental transmission electron microscope for studying the thermochemical cyclability of cobalt oxide nanoparticles with high spatial and temporal resolution. The spectroscopic data reveal a striking decrease in reaction kinetics after the first cycle, resulting from sintering-driven nanostructural densification. Comparison between cycling in humid and dry air shows that atmospheric conditions can modulate reaction transition temperatures but have limited effects on sintering over multiple cycles, suggesting long-term durability will instead rely on synthetic and/or nanostructural modifications.

25 ENERGY STORAGE↗
DOE OSTI2025

Learning and Controlling Silicon Dopant Transitions in Graphene Using Scanning Transmission Electron Microscopy

A machine learning approach is introduced to determine the transition dynamics of silicon atoms on a single layer of carbon atoms, when stimulated by the electron beam of a scanning transmission electron microscope (STEM). This method is data-centric, leveraging data collected on a STEM. The data samples are processed and filtered to produce symbolic representations, which is used to train a neural network to predict transition probabilities. These learned transition dynamics are then leveraged to guide a single silicon atom throughout the lattice to pre-determined target destinations. Empirical analyses are presented that demonstrate the efficacy and generality of the approach.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tip-Induced 3D Printing on the Nanoscale with Field Emission Scanning Probes

3D printing down to the nanoscale remains a significant challenge. In this paper, the study explores the use of scanning probes that emit low-energy electrons (<100 eV) coupled with the localized injection and electron-induced decomposition of precursor molecules, for the precise localized deposition of 3D nanostructures. The experiments are performed inside the chamber of a scanning electron microscope (SEM), enabling the use of the in-built gas injector system (GIS) with gaseous naphthalene precursor for carbon deposition, as well as immediate inspection of the deposits by SEM. Substrate materials are planar fused silica with thin conductive coatings and non-planar copper wedges. After investigation of the deposition process parameters, various 2D and 3D carbon deposits are grown. Vertical nanowires several microns in length with a diameter <100 nm are achieved and 3D deposits with a high degree of nanoscale branching are also obtained, presumably due to a charging effect. High aspect ratio carbon nanostructures such as those demonstrated here can be employed as miniaturized electrodes or field emitters. The tip-based approach presented thus paves the way toward 3D nanoscale printing of various materials and functional nanostructures.

3D printing↗
DOE OSTI2024

Uncertainty-aware particle segmentation for electron microscopy at varied length scales

Electron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron scale. To study the powder samples that are widely used in materials development, scanning electron microscopes (SEMs) are increasingly used at the laboratory scale to generate large datasets with hundreds of images. Parsing these images to identify distinct particles and determine their morphology requires careful analysis, and automating this process remains challenging. In this work, we enhance the Mask R-CNN architecture to develop a method for automated segmentation of particles in SEM images. We address several challenges inherent to measurements, such as image blur and particle agglomeration. Moreover, our method accounts for prediction uncertainty when such issues prevent accurate segmentation of a particle. Recognizing that disparate length scales are often present in large datasets, we use this framework to create two models that are separately trained to handle images obtained at low or high magnification. By testing these models on a variety of inorganic samples, our approach to particle segmentation surpasses an established automated segmentation method and yields comparable results to the predictions of three domain experts, revealing comparable accuracy while requiring a fraction of the time. These findings highlight the potential of deep learning in advancing autonomous workflows for materials characterization.

36 MATERIALS SCIENCE↗
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

Switching speed limits in electrically driven VO 2 structural Mott–Peierls transition

Mott materials are archetypal quantum systems actively explored as next-generation electronic and photonic platforms, with potential applications spanning non-Von Neumann computing, robotics, energy storage, and microwave technologies. Among these, vanadium dioxide (VO 2 ) has emerged as one of the most intensively studied compounds, owing to its sharp, near-room-temperature insulator-to-metal phase transition. VO 2 also serves as a benchmark system for testing cutting-edge theories and experimental techniques. Here, we directly visualize the electrically driven transition dynamics in VO 2 using a microwave-driven, frequency-tunable pulsed transmission electron microscope that combines nanometer spatial and picosecond temporal resolution. Under high-frequency (MHz–GHz) excitation, we capture the ultrafast nucleation, propagation, and dissolution of metallic domains within an operating device over millions of reversible cycles. We observe the ultrafast formation of consistent metallic nuclei beneath the electrodes, followed by the propagation of a structural phase front at 4.54 nm/ns. Our experiments show that phonon-mediated structural recovery ultimately limits reversible switching of VO 2 at GHz frequencies, and that a tunable regime for reversible operation spans from kHz to GHz through device engineering. Beyond VO 2 , our approach provides a powerful framework for probing non-equilibrium structural transformations in correlated and functional materials under realistic electrical stimuli.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Transmission electron microscopy with in-situ ion irradiation: Facilities and community

Whilst there is a clear scientific and technological need for the technical capabilities of transmission electron microscopes with in-situ ion irradiation, it also requires a collaborative community of international researchers to support such facilities in successfully meeting this demand. Instruments of this type serve to provide fundamental understanding of the mechanisms which drive changes in materials important to nuclear fission and fusion energy, the semiconductor industry, quantum information systems, space travel, astronomy, geology and many more applications. As these areas continue to evolve and the instrumentation possibilities expand, the capacity of in-situ ion irradiation facilities must also develop hand-in-hand with the user community to deliver an ever-greater diversity of high-fidelity extreme-environment experimentation. Future directions for the field, such as miniaturization from MEMS/microfluidic devices and advanced controls with ML-based analysis, continuously emerge to advance both the hardware and software which support the coupling of TEMs with ion beams. This review sets out to provide up-to-date insights into the community and advancement of current, and development of future, facilities which have the potential to further unlock access to the nanoscale exploration of coupled extreme environments crucial to many of the important science and engineering challenges we face today.

In-situ irradiation↗
DOE OSTI2026

A large interlaboratory electron diffraction study of monolayer graphene

Standardisation of data collection and analysis is essential to enable commercialisation of 2D materials in a wide range of technologies. Selected area electron diffraction (SAED) in the transmission electron microscope (TEM) is one of the key methods for distinguishing monolayer from bilayer and few-layer graphene by comparing the 1st and 2nd order diffraction spot intensities. Yet there are many factors that can affect the reliability of data collection and interpretation, causing the measurement of monolayer samples to deviate from the literature boundary condition of $I_{\{\bar{2}110\}}$$/$$I_{\{1\bar{1}00\}}$ < 1 for monolayer graphene (1LG). Here we present the results of a large interlaboratory SAED comparison study, where 15 international laboratories measured and analysed nominally identical samples of chemical vapour deposited graphene. Large variations were observed in the measured ratios of diffraction spot intensities, with the largest variance associated with poor quality SAED data resulting from inadequate specimen handling and storage. To inform the reliable determination of monolayer thickness from SAED patterns we provide a description of best practice for specimen handling, TEM operation, data collection and analysis. This work was undertaken within VAMAS Technical Working Area 41: Graphene and related 2D materials—Project 9, the results of which have been directly incorporated into ISO/TS 21356–2 for the characterisation of graphene sheets. We find that when this methodology is followed, 1LG can be distinguished from bilayer or thicker material with high confidence where analysis of a single SAED pattern gives $I_{\{\bar{2}110\}}$$/$$I_{\{1\bar{1}00\}}$ < 1.2, even in the absence of precise specimen tilting.

2D materials↗
DOE OSTI2024

High‐Temperature Mechanical Behavior of Single‐Crystal FeCrAl Alloy Under In Situ Micropillar Compression

FeCrAl cladding is one of the candidate materials for the near‐term accident‐tolerant fuel technologies under development. Research on high‐temperature mechanical behaviors of single‐crystal FeCrAl alloy is rather limited. Previous studies have reported the mechanical property of low‐index orientation in single‐crystal FeCrAl alloy at room temperature. However, the critical resolved shear stress to activate slip systems can be orientation and temperature dependent. Here, single‐crystal grains in a coarse‐grained FeCrAl alloy with different crystallographic orientations are selected to preferentially activate {110}<111> slip systems or {112}<111> slip systems. Micropillars are fabricated in the selected single‐crystal grains and tested at elevated temperatures in situ in a scanning electron microscope. The critical resolved shear stresses of {110}<111> slip systems and {112}<111> slip systems are determined at various temperatures. The critical resolved shear stress shows a temperature dependence and orientation independence. This study provides important insight for understanding the deformation mechanisms of FeCrAl alloys at elevated temperatures.

Sun, Tianyi↗
DOE OSTI2024

Fluoro‐Ethylene‐Carbonate Plays a Double‐Edged Role on the Stability of Si Anode‐Based Rechargeable Batteries During Cycling and Calendar Aging

Abstract The energy storage density of Li‐ion batteries can be improved by replacing graphite anodes with high‐capacity Si‐based materials, though instabilities have limited their implementation. Performance degradation mechanisms that occur in Si anodes can be divided into cycling stability (capacity retention after repeated battery cycles) and calendar aging (shelf life). While cycling instabilities and improvement strategies have been researched intensively, there is little known about the underlying mechanisms that cause calendar aging. In this work, multiple electron microscope techniques are used to explore the mechanism that governs calendar aging from the sub‐nanometer‐to‐electrode scale. Plasma focused ion beam tomography is used to create 3D reconstructions of calendar aged electrodes and revealed the growth of a LiF‐rich layer at the interface between the copper current collector and the silicon material, which can lead to delamination and increased interfacial impendence. The LiF layer appeared to derive from the fluoro‐ethylene‐carbonate electrolyte additive, which is commonly used to improve cycling stability in Si‐based systems. The results reveal that additives necessary to improve cycling stability can cause performance degradation over the long‐term during calendar aging. The results show that high performing, stable systems require careful design to simultaneously mitigate both cycling and calendar aging instabilities.

25 ENERGY STORAGE↗
DOE OSTI2025

Effect of Stoichiometry on the Structure and Polarization of BaTiO 3

Barium titanate (BaTiO 3 ) is a material of interest for photonic device applications due to its strong optical non-linearity. However, BaTiO 3 -based devices have not found widespread adoption, in part due to the challenges associated with synthesizing high quality thin-films. Here, high-resolution scanning transmission electron microscope (STEM) imaging is used to investigate the atomic structure of both on- and off-stoichiometric BaTiO 3 synthesized by molecular beam epitaxy (MBE). Here, this investigation reveals an asymmetry in the way the BaTiO 3 atomic lattice accommodates off-stoichiometry growth and unveils features beyond what is expected from diffraction or surface characterization techniques. Excess titanium incorporates into the BaTiO 3 lattice to form pervasive defects despite titanium-rich films having a low surface roughness and high-quality appearance in diffraction. Excess barium forms a rough, water-soluble surface layer but does not significantly impact the quality of the BaTiO 3 lattice. STEM is used to map titanium atom displacement in real-space. The average displacement distance is 30–60 pm in the strained thin-films, higher than the <20 pm displacement in bulk BaTiO 3 . Additionally, the titanium atom displacement direction deviates from the c-axis of the unit cell, which may have implications for the material's electro-optic tensor and thus for electro-optic device design.

Cavanagh, Ashley E. [Harvard Univ., Cambridge, MA ↗
DOE OSTI2024

Strain Field Around Individual Dislocations Controls Failure

Understanding material failure on a fundamental level is a key aspect in the design of robust structural materials, especially for metals and alloys capable to undergo plastic deformation. In the last decade, significant progress is made in quantifying the stresses associated with failure in both experiments and simulations. Nonetheless, the processes occurring on the most essential level of individual dislocations that govern semi-brittle and ductile fracture are still experimentally not accessible, limiting the failure prediction capabilities. Therefore, in the present work, a one-of-a-kind nanoscale fracture experiment is conducted on a single crystalline Cr bending beam in situ in the transmission electron microscope and for the first time quantify the transient strains around individual dislocations, as well as of the whole dislocation network during crack opening. The results reveal the importance of both pre-existing and newly emitted dislocations for crack-tip shielding via their intrinsic strain field and provide guidelines to design more damage tolerant materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nucleation rate controlled grain boundary and lattice creep

Nucleation versus diffusion rate-limited bicrystal and single crystal creep exhibit different scaling dependencies that enable the mechanisms to be isolated when measured as a function of sample size. It has recently been suggested that nucleation rate-limited kinetic models generally describe the non-Newtonian portion of the creep response well, but more direct evidence is required. This work analyzes the grain boundary creep response of UO 2 , a pyrochlore high entropy oxide, silver, and palladium, along with the lattice creep of silver using small-scale in situ loading in the transmission electron microscope. At small sizes, each system exhibits scale dependence associated with nucleation rate-limited kinetics. Fits of the data produce activation volumes on the order of a few Burgers vectors cubed with positive temperature coefficients as expected for nucleation kinetics. The activation enthalpies fall in the range of about 0.4 eV to 1.7 eV, being lower for the metals and higher for the oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi deep learning-based stochastic microstructure reconstruction and high-fidelity micromechanics simulation of time-dependent ceramic matrix composite response

A multi deep learning-based framework is developed for efficient, automated microstructure reconstruction and generation of stochastic representative volume elements (SRVEs) with periodic boundary conditions (PBCs) for accurate modeling of ceramic matrix composite (CMC) response. The methodology comprises a convolutional neural network coupled with regression layers to act as a vanilla regression network for semantic segmentation of the microstructure, allowing accurate characterization of the phases and their distributions at the microscale. Scanning electron microscope and confocal microscope are used to obtain C/SiNC and SiC/SiNC CMCs micrographs for vanilla regression testing. Microstructure variability in terms of fiber volume fraction and porosity are quantified through the output regression layer, ensuring accurate representation of material variability in SRVE construction. Generative adversarial network (GAN) and its variants are designed to produce high-fidelity SRVE, spanning CMCs microstructure variability space. A circular padding algorithm is developed to generate SRVEs with PBCs during training of GANs. The accuracy of the generated SRVEs is established through micromechanics simulations, where an efficient formulation of the high-fidelity generalized methods of cells (HFGMC) approach is used to compute the effective mechanical properties. Furthermore, an iterative algorithm is implemented in the HFGMC solver to simulate time-dependent deformation of SiC/SiNC subjected to creep loading conditions.

36 MATERIALS SCIENCE↗