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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Colossal oxygen vacancy formation at a fluorite-bixbyite interface

Oxygen vacancies in complex oxides are indispensable for information and energy technologies. There are several means to create oxygen vacancies in bulk materials. However, the use of ionic interfaces to create oxygen vacancies has not been fully explored. As such, we report an oxide nanobrush architecture designed to create high-density interfacial oxygen vacancies. An atomically well-defined (111) heterointerface between the fluorite CeO 2 and the bixbyite Y 2 O 3 is found to induce a charge modulation between Y 3+ and Ce 4+ ions enabled by the chemical valence mismatch between the two elements. Local structure and chemical analyses, along with theoretical calculations, suggest that more than 10% of oxygen atoms are spontaneously removed without deteriorating the lattice structure. Our fluorite–bixbyite nanobrush provides an excellent platform for the rational design of interfacial oxide architectures to precisely create, control, and transport oxygen vacancies critical for developing ionotronic and memristive devices for advanced energy and neuromorphic computing technologies.

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

Depth-dependent recovery of thermal conductivity after recrystallization of amorphous silicon

The depth-dependent recovery of silicon thermal conductivity was achieved after the recrystallization of silicon that had been partially amorphized due to ion implantation. Transmission electron microscopy revealed nanoscale amorphous pockets throughout a structurally distorted band of crystalline material. The minimum thermal conductivity of as-implanted composite material was 2.46 W m −1 K −1 and was found to be uniform through the partially amorphized region. X-ray diffraction measurements reveal 60% strain recovery of the crystalline regions after annealing at 450 °C for 30 min and almost full strain recovery and complete recrystallization after annealing at 700 °C for 30 min. In addition to strain recovery, the amorphous band thickness reduced from 240 to 180 nm after the 450 °C step with nanoscale recrystallization within the amorphous band. A novel depth-dependent thermal conductivity measurement technique correlated thermal conductivity with the structural changes, where, upon annealing, the low thermal conductivity region decreases with the distorted layer thickness reduction and the transformed material shows bulk-like thermal conductivity. Full recovery of bulk-like thermal conductivity in silicon was achieved after annealing at 700 °C for 30 min. After the 700 °C anneal, extended defects remain at the implant projected range, but not elsewhere in the layer. Previous results showed that high point-defect density led to reduced thermal conductivity, but here, we show that point defects can either reform into the lattice or evolve into extended defects, such as dislocation loops, and these very localized, low-density defects do not have a significant deleterious impact on thermal conductivity in silicon.

Huynh, Kenny↗
DOE OSTI2022

Dynamics and Transport in Strongly-Anisotropic Quantum Magnets (Final Report)

This DOE Award has evolved from a set of projects centered on the thermal transport phenomena in quantum magnets to the broader effort in the theory of dynamical properties of complex magnets, with the focus on their enigmatic ground states, disorder-induced phenomena, and novel spectroscopic and transport effects in them. Most recent emphasis of the research under the umbrella of this Award has been on the rare-earth- and transition-metal-based strongly-anisotropic magnets, the effort that has utilized a significant experience of our group in the studies of excitations, transport, and disorder in these new materials. The studies performed in our group have advanced basic understanding of fundamental physical properties of a diverse group of materials and yielded predictions of new phenomena in them. The research under this Award has targeted the problems that are at the forefront of the modern condensed matter physics and has also addressed the need for the theoretical understanding of experiments. Our work has influenced experiments conducted at the national and international facilities and provided an impact on the DOE basic energy science missions and areas of thrust in new electronic materials, energy transport, neutron- and X-ray scattering science, and in nanoscale science.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

NSUF Rad-AFM: Nanoscale Material Property Measurements of Radioactive Materials

Many advances in our understanding of radiation induced damage mechanisms are due to imaging techniques including transmission electron microscopy and scanning electron microscopy. However, the effect of these radiation induced defects characterized on the atomic to micrometer scale are often interpreted by changes in bulk material properties measured in the hundreds of microns to cm scale. In order to bridge this gap, additional tools need to be developed for use with radioactive materials. To this end a new Asylum Infinity multimodal atomic force microscope (AFM) has been added to the library of Nuclear Science User Facility (NSUF) instruments for use on radioactive materials. This instrument is housed in the Radiochemical Processing Laboratory (RPL) which is a Department of Energy Hazard Category II Non-Reactor Nuclear Facility operated by Battelle at Pacific Northwest National Laboratory. This allows for the handling, sample preparation, and characterization of highly radioactive materials providing a unique capability to understand fundamental properties of nuclear materials and the effects of radiation induced damage.

Riechers, Shawn L.↗
DOE OSTI2021

Adoption of image-driven machine learning for microstructure characterization and materials design: A Perspective

Microstructure characterization enables the development of structure-processing-property relationships critical to several research areas within the broad field of materials science, from alloy design to the assessment of corrosion resistance, and failure analysis. Conventional approaches to material characterization have relied on either qualitative inference by the human ex-pert or software applications that can extract high-level features from images, such as boundary segmentation, average grain diameter, etc. Such approaches rely heavily on subject matter expert user intervention and knowledge of what phases or more generally, what microstructural features, are of interest. The recent surge in the adoption of machine learning techniques to address problems in materials engineering has brought with it an increased interest and application of Image Driven Machine Learning (IDML) approaches. In this work, we review the applications of IDML to the field of materials characterization. A canonical hierarchy of stages is defined, which when put sequentially together completes an IDML study: problem definition, dataset building, model selection and training, model evaluation, and integration with existing instrumentation or simulation workflow. The studies reviewed in this work are analyzed from the perspective of each of these stages. Such a review permits agranular assessment of the field, for example the impact of IDML on materials characterization at the nanoscale, the size of a typical dataset required to train a semantic segmentation model on electron microscopy images, ubiquitousness of transfer learning in the domain, etc. Finally, we discuss the importance of interpretability and explainability in the field of IDML for materials characterization, and provide an overview of two emerging techniques in the field: semantic segmentation and generative adversarial networks.

Baskaran, Arun↗
DOE OSTI2025

A machine-learning approach to measure 3D sample properties from 2D Transmission Electron Microscopy images

Transmission Electron Microscopy (TEM) is a powerful tool for the characterization of materials at the nanoscale; however, its inherent two-dimensional (2D) nature poses significant challenges to accurately measure three-dimensional (3D) properties. We introduce a supervised machine-learning model that predicts 3D structural information, such as sample thickness and curvature, from a series of conventional 2D TEM images. The model, a U-Net convolutional neural network, is trained on a large synthetic dataset generated from dynamical diffraction simulations that model TEM’s complex, nonlinear image formation, accounting for sample thickness and curvature. This physically realistic framework enables exploration of a broad parameter space impractical to sample experimentally. We demonstrate that the trained model has accurate predictions for experimental single-crystal silicon samples, achieving performance comparable to established measurement techniques. This work highlights the critical role of robust, simulation-based training in overcoming the limitations of real-world imaging artifacts and inconsistent sample geometries. By integrating machine learning with numerical simulations, we offer an efficient and scalable framework for quantitative TEM analysis, paving the way for more sophisticated 3D characterization of complex materials.

Dynamical diffraction↗
DOE OSTI2024

3D imaging of magnetic domains in Nd 2 Fe 14 B using scanning hard X-ray nanotomography

Nanoscale structural and electronic heterogeneities are prevalent in condensed matter physics. Investigating these heterogeneities in 3D has become an important task for understanding material properties. To provide a tool to unravel the connection between nanoscale heterogeneity and macroscopic emergent properties in magnetic materials, scanning transmission X-ray microscopy (STXM) is combined with X-ray magnetic circular dichroism. A vector tomography algorithm has been developed to reconstruct the full 3D magnetic vector field without any prior noise assumptions or knowledge about the sample. Two tomographic scans around the vertical axis are acquired on single-crystalline Nd 2 Fe 14 B pillars tilted at two different angles, with 2D STXM projections recorded using a focused 120 nm X-ray beam with left and right circular polarization. Image alignment and iterative registration have been implemented based on the 2D STXM projections for the two tilts. Dichroic projections obtained from difference images are used for the tomographic reconstruction to obtain the 3D magnetization distribution at the nanoscale.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Nanoscale Three-Dimensional Imaging of Integrated Circuits Using a Scanning Electron Microscope and Transition-Edge Sensor Spectrometer

X-ray nanotomography is a powerful tool for the characterization of nanoscale materials and structures, but it is difficult to implement due to the competing requirements of X-ray flux and spot size. Due to this constraint, state-of-the-art nanotomography is predominantly performed at large synchrotron facilities. We present a laboratory-scale nanotomography instrument that achieves nanoscale spatial resolution while addressing the limitations of conventional tomography tools. The instrument combines the electron beam of a scanning electron microscope (SEM) with the precise, broadband X-ray detection of a superconducting transition-edge sensor (TES) microcalorimeter. The electron beam generates a highly focused X-ray spot on a metal target held micrometers away from the sample of interest, while the TES spectrometer isolates target photons with a high signal-to-noise ratio. This combination of a focused X-ray spot, energy-resolved X-ray detection, and unique system geometry enables nanoscale, element-specific X-ray imaging in a compact footprint. The proof of concept for this approach to X-ray nanotomography is demonstrated by imaging 160 nm features in three dimensions in six layers of a Cu-SiO 2 integrated circuit, and a path toward finer resolution and enhanced imaging capabilities is discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Nanoscale Structure and Interfacial Electrochemical Reactivity of Moiré-Engineered Atomic Layers

Here, the electronic properties of atomically thin van der Waals (vdW) materials can be precisely manipulated by vertically stacking them with a controlled offset (for example, a rotational offset─i.e., twist─between the layers, or a small difference in lattice constant) to generate moiré superlattices. In recent years, the application of this “twistronics” concept to interfacial electrochemistry has unveiled unique pathways for tailoring the electrochemical reactivity. Furthermore, this Account provides an overview of our work that leveraged a suite of structural characterization methods, such as interferometric four-dimensional scanning transmission electron microscopy, dark-field transmission electron microscopy, and scanning tunneling microscopy, along with nanoscale electrochemical measurement techniques, namely, scanning electrochemical cell microscopy (SECCM), to uncover and dissect the profound impact of electrode electronic structure, controlled by interlayer twist, on interfacial electron transfer kinetics.

Charge transfer↗
DOE OSTI2026

Structural and Mechanical Analysis of Individual Mineralized Collagen Fibrils Using In Situ Transmission Electron Microscopy

Bone serves as an example of nature’s architectured material with its characteristic blend of strength and toughness, all at a lightweight design. Given the hierarchical nature of these materials, it is essential to understand the governing mechanisms and organization of their constituents across length scales for bioinspired structural design. Despite recent advances in transmission electron microscopy (TEM) that have allowed us to witness the hierarchical arrangement of bone at micro-down to the nanoscale, we are still missing the details about the structural organization and mechanical properties of the main building blocks of bone─mineralized collagen fibrils (MCFs). Here, we present a method to extract individual MCFs from nature’s model material, mineralized turkey leg tendon, using a dropcasting procedure. By isolating the MCFs onto TEM supporting grids, we visualized the arrangement of organic and mineral phases within individual MCFs at the nanoscale. Using a four-dimensional scanning transmission electron microscopy (4D-STEM) approach, the orientation of individual mineral crystals within the MCFs was examined. Furthermore, we conducted in situ tensile experiments, revealing exceptional tensile strains of at least 8%, demonstrating the intricate relationship between structural organization and the mechanical behavior of MCFs. These insights into the ultrastructure of mineralized tissue building blocks, as well as the proposed sample-extraction method compatible with in situ mechanical testing, provide a strong basis for research into nature-inspired material design.

4D-STEM↗
DOE OSTI2022

Low‐Loss Tunable Infrared Plasmons in the High‐Mobility Perovskite (Ba,La)SnO 3

Abstract BaSnO 3 exhibits the highest carrier mobility among perovskite oxides, making it ideal for oxide electronics. Collective charge carrier oscillations known as plasmons are expected to arise in this material, thus providing a tool to control the nanoscale optical field for optoelectronics applications. Here, the existence of relatively long‐lived plasmons supported by high‐mobility charge carriers in La‐doped BaSnO 3 (BLSO) is demonstrated. By exploiting the high spatial and energy resolution of electron energy‐loss spectroscopy with a focused beam in a scanning transmission electron microscope, the dispersion, confinement ratio, and damping of infrared localized surface plasmons (LSPs) in BLSO nanoparticles are systematically investigated. It is found that LSPs in BLSO exhibit a high degree of spatial confinement compared to those sustained by noble metals and have relatively low losses and high quality factors with respect to other doped oxides. Further analysis clarifies the relation between plasmon damping and carrier mobility in BLSO. The results support the use of nanostructured degenerate semiconductors for plasmonic applications in the infrared region and establish a solid alternative to more traditional plasmonic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Redox Mediated Control of Electrochemical Potential in Liquid Cell Electron Microscopy

Liquid cell electron microscopy enables the study of nanoscale transformations in solvents with high spatial and temporal resolution, but for the technique to achieve its potential requires a new level of control over the reactivity caused by radical generation under electron beam irradiation. An understanding of how to control electron-solvent interactions is needed to further advance the study of structural dynamics for complex materials at the nanoscale. Additionally, we developed an approach that scavenges radicals with redox species that form well-defined redox couples and control the electrochemical potential in situ . This approach enables the observation of electrochemical structural dynamics at near-atomic resolution with precise control of the liquid environment. Analysis of nanocrystal etching trajectories indicates that this approach can be generalized to several chemical systems. The ability to simultaneously observe heterogeneous reactions at near-atomic resolution and precisely control the electrochemical potential enables the fundamental study of complex nanoscale dynamics with unprecedented detail.

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

Computational Theory Applied to Nanostructures (Final Report)

Within the nanoscale, phenomena occur that are characteristic of neither the atomic limit, nor the macroscopic limit. In particular, properties that are intensive at the macroscopic scale become size dependent at the nanoscale. These phenomena can have direct consequence for understanding and characterizing materials used in electronic, optical, and micro-mechanical applications related to energy science and technologies. To capitalize properly on predicting and understanding such phenomena in this nano regime, a deeper understanding of the quantum properties of materials will be required. The objective of our research program was to advance the field in computational modeling, analysis and understanding of materials at the nano scale, both in terms of dimensionality and quantum confinement. We employed a multidisciplinary approach, drawing from physics, materials science, chemical engineering and computer science. This research will provide new knowledge, computational techniques, and provide high-potential links across all these disciplines. Over sixty papers were published during the period in question. Ten of the papers were published in high impact journals such as Nano Letters, Nature Communications and Physical Review Letters.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ex-situ Heat Treatment of TEM Foils in a Custom Titanium Fixture: A Case Study on Ni-based Superalloy

The advancement of microstructural characterization at the nanoscale is critical to understanding the microstructural evolution and performance of engineering materials. Transmission electron microscopy (TEM) plays a vital role in such investigations, particularly when coupled with controlled ex- and in-situ experiments. In this study, we introduce a novel method for ex-situ heat treatment (HT) of TEM foils using a custom-designed fixture, made from pure titanium, and vacuum furnace to inhibit oxidation. This approach ensures precise temperature control and minimal sample contamination during HT, critical for substructural characterization and analysis of metallic materials. The fixture consists of a titanium base with three slits, for three sample foils, and a titanium cap for closure. The entire assembly is placed in a vacuum heat treatment furnace with high vacuum capability to prevent oxidation. To validate the effectiveness of the setup, precipitation behavior and microstructural changes were studied in an IN725 variant heat-treated at 500°C for 1 hour and 282 variant heat-treated at 700°C for 1 hour, as case studies.

electron microscopy↗
DOE OSTI2024

Optical and electronic functionality arising from controlled defect formation in nanoscale complex oxide lateral epitaxy

Epitaxial crystallization of complex oxides provides the means to create materials with precisely selected composition, strain, and orientation, thereby controlling their functionalities. Extending this control to nanoscale three-dimensional geometries can be accomplished via a three-dimensional analog of oxide solid-phase epitaxy, lateral epitaxial crystallization. The orientation of crystals within laterally crystallized SrTiO 3 systematically changes from the orientation of the SrTiO 3 substrate. This evolution occurs as a function of lateral crystallization distance, with a rate of approximately 50° μm -1 . The mechanism of the rotation is consistent with a steady-state stress of tens of megapascal over a 100–nanometer scale region near the moving amorphous/crystalline interface arising from the amorphous-crystalline density difference. Second harmonic generation and piezoelectric force microscopy reveal that the laterally crystallized SrTiO 3 is noncentrosymmetric and develops a switchable piezoelectric response at room temperature, illustrating the potential to use lateral crystallization to control the functionality of complex oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Isotope-Resolved Electron Energy Loss Spectroscopy in a Monochromated Scanning Transmission Electron Microscope

The development and implementation of high-stability monochromators in state-of-the-art aberration-corrected scanning transmission electron microscopes has enabled materials characterization with an energy resolution as good as 3 meV. This allows the vibrational modes, which would otherwise be obscured by the energy spread of the electron beam, to be probed with very high precision in molecular materials. Since the vibrational energies depend on the weight of the atomic nuclei, vibrational spectroscopy can distinguish isotopes whose only difference lies in their neutron content. This opens up isotopic analysis and mapping in transmission electron microscopy as two important new research areas. In this paper, we review the monochromated electron energy loss spectroscopy (EELS) instrumentation, discuss optimal methods for probing beam-sensitive materials without destroying them, and review key nanoscale isotope-resolved results.

47 OTHER INSTRUMENTATION↗
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 OSTI2021

Machine learning for deep elastic strain engineering of semiconductor electronic band structure and effective mass

Abstract The controlled introduction of elastic strains is an appealing strategy for modulating the physical properties of semiconductor materials. With the recent discovery of large elastic deformation in nanoscale specimens as diverse as silicon and diamond, employing this strategy to improve device performance necessitates first-principles computations of the fundamental electronic band structure and target figures-of-merit, through the design of an optimal straining pathway. Such simulations, however, call for approaches that combine deep learning algorithms and physics of deformation with band structure calculations to custom-design electronic and optical properties. Motivated by this challenge, we present here details of a machine learning framework involving convolutional neural networks to represent the topology and curvature of band structures in k -space. These calculations enable us to identify ways in which the physical properties can be altered through “deep” elastic strain engineering up to a large fraction of the ideal strain. Algorithms capable of active learning and informed by the underlying physics were presented here for predicting the bandgap and the band structure. By training a surrogate model with ab initio computational data, our method can identify the most efficient strain energy pathway to realize physical property changes. The power of this method is further demonstrated with results from the prediction of strain states that influence the effective electron mass. We illustrate the applications of the method with specific results for diamonds, although the general deep learning technique presented here is potentially useful for optimizing the physical properties of a wide variety of semiconductor materials.

Tsymbalov, Evgenii↗