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DOE OSTI2021

Cepstral scanning transmission electron microscopy imaging of severe lattice distortions

The development of four-dimensional (4D) scanning transmission electron microscopy (STEM) using fast detectors has opened-up new avenues for addressing some of longstanding challenges in electron imaging. One of these challenges is how to image severely distorted crystal lattices, such as at a dislocation core. Here we develop a new 4D-STEM technique, called Cepstral STEM, for imaging disordered crystals using electron diffuse scattering. In contrast to analysis based on Bragg diffraction, which measures the average and periodic scattering potential, electron diffuse scattering can detect fluctuations caused by crystal disorder. Local fluctuations of diffuse scattering are captured by scanning electron nanodiffraction (SEND) using a coherent probe. The harmonic signals in electron diffuse scattering are detected through Cepstral analysis and used for imaging. By integrating Cepstral analysis with 4D-STEM, we demonstrate that information about the distortive part of electron scattering potential can be separated and imaged at nm spatial resolution. Here, we apply the technique to the analysis of a dislocation core in SiGe and lattice distortions in a high entropy alloy.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Tutorial on In Situ and Operando (Scanning) Transmission Electron Microscopy for Analysis of Nanoscale Structure–Property Relationships

In situ and operando (scanning) transmission electron microscopy [(S)TEM] is a powerful characterization technique that uses imaging, diffraction, and spectroscopy to gain nano-to-atomic scale insights into the structure–property relationships in materials. This technique is both customizable and complex because many factors impact the ability to collect structural, compositional, and bonding information from a sample during environmental exposure or under application of an external stimulus. In the past two decades, in situ and operando (S)TEM methods have diversified and grown to encompass additional capabilities, higher degrees of precision, dynamic tracking abilities, enhanced reproducibility, and improved analytical tools. Much of this growth has been shared through the community and within commercialized products that enable rapid adoption and training in this approach. This tutorial aims to serve as a guide for students, collaborators, and nonspecialists to learn the important factors that impact the success of in situ and operando (S)TEM experiments and assess the value of the results obtained. As this is not a step-by-step guide, readers are encouraged to seek out the many comprehensive resources available for gaining a deeper understanding of in situ and operando (S)TEM methods, property measurements, data acquisition, reproducibility, and data analytics.

(S)TEM↗

NASA NTRS1988

Growth of diamond by RF plasma-assisted chemical vapor deposition

A system has been designed and constructed to produce diamond particles by inductively coupled radio-frequency, plasma-assisted chemical vapor deposition. This is a low-pressure, low-temperature process used in an attempt to deposit diamond on substrates of glass, quartz, silicon, nickel, and boron nitride. Several deposition parameters have been varied including substrate temperature, gas concentration, gas pressure, total gas flow rate, RF input power, and deposition time. Analytical methods employed to determine composition and structure of the deposits include scanning electron microscopy, absorption spectroscopy, scanning Auger microprobe spectroscopy, and Raman spectroscopy. Analysis indicates that particles having a thin graphite surface, as well as diamond particles with no surface coatings, have been deposited. Deposits on quartz have exhibited optical bandgaps as high as 4.5 eV. Scanning electron microscopy analysis shows that particles are deposited on a pedestal which Auger spectroscopy indicates to be graphite. This is a phenomenon that has not been previously reported in the literature.

Meyer, Duane E.↗

DOE OSTI2019

Experimental and Theoretical Investigation of the Ion Conduction Mechanism of Tris(adiponitrile)perchloratosodium, a Self-Binding, Melt-Castable Crystalline Sodium Electrolyte

Sodium perchlorate (NaClO4) crystallizes with adiponitrile (ADN) as a 1:3 solvate to produce (ADN) 3 NaClO 4 , a solid electrolyte for sodium ion conduction. The solid possesses high thermal stability (up to 150 °C) and the ability to be melt-cast (T m = 81 °C). The pressed solid has a high ionic conductivity of 2.2 × 10 –4 S cm –1 at room temperature with a low activation barrier for ion conduction of 22 kJ mol –1 . The high conductivity is the result of low-affinity ion-conduction channels in the bulk based on the X-ray crystal structure, and by low grain-boundary resistance and possibly a grain-boundary percolating network due to a fluidlike nanoliquid layer between the grains, observable by scanning electron microscopy and differential scanning calorimetry. When the liquid nanolayer is rinsed away or removed by excessive drying, the bulk room temperature ionic conductivity is 4 × 10 –5 S cm –1 , activation energy for ionic conduction for an organic solid is 37 kJ mol –1 , and the sodium ion transference number is 0.71. Scanning electron microscopy and classical molecular dynamics simulations suggest that these cocrystals form a fluid layer of ADN at the surface, which facilitates the Na+ ion migration between the grains. Finally, density functional theory calculations are consistent with the possibility of ion conduction via a solvent–anion coordinated transition state through vacancy defects in the three symmetry-equivalent ion channels along separate directions, suggesting the possibility of ionic conductivity in three dimensions.

25 ENERGY STORAGE↗

DOE OSTI2023

Resolution of Virtual Depth Sectioning from Four-Dimensional Scanning Transmission Electron Microscopy

Abstract One approach to three-dimensional structure determination using the wealth of scattering data in four-dimensional (4D) scanning transmission electron microscopy (STEM) is the parallax method proposed by Ophus et al. (2019. Advanced phase reconstruction methods enabled by 4D scanning transmission electron microscopy, Microsc Microanal25, 10–11), which determines the scattering matrix and uses it to synthesize a virtual depth-sectioning reconstruction of the sample structure. Drawing on an equivalence with a hypothetical confocal imaging mode, we derive contrast transfer and point spread functions for this parallax method applied to weakly scattering objects, showing them identical to earlier depth-sectioning STEM modes when only bright field signal is used, but that improved depth resolution is possible if dark field signal can be used. Through a simulation-based study of doped Si, we show that this depth resolution is preserved for thicker samples, explore the impact of shot noise on the parallax reconstructions, discuss challenges to making use of dark field signal, and identify cases where the interpretation of the parallax reconstruction breaks down.

3D imaging↗

DOE OSTI2024

The 4D Camera: An 87 kHz Direct Electron Detector for Scanning/Transmission Electron Microscopy

We describe the development, operation, and application of the 4D Camera—a 576 by 576 pixel active pixel sensor for scanning/transmission electron microscopy which operates at 87,000 Hz. The detector generates data at ~480 Gbit/s which is captured by dedicated receiver computers with a parallelized software infrastructure that has been implemented to process the resulting 10–700 Gigabyte-sized raw datasets. The back illuminated detector provides the ability to detect single electron events at accelerating voltages from 30 to 300 kV. Through electron counting, the resulting sparse data sets are reduced in size by 10--300× compared to the raw data, and open-source sparsity-based processing algorithms offer rapid data analysis. The high frame rate allows for large and complex scanning diffraction experiments to be accomplished with typical scanning transmission electron microscopy scanning parameters.

47 OTHER INSTRUMENTATION↗

DOE OSTI2026

Chemical and morphological evolution of hybrid conversion coatings in low-Earth orbit space environment

Understanding how protective coatings respond to the harsh low-Earth orbit (LEO) environment is essential for ensuring the safety, longevity, and cost-effectiveness of spacecraft. In particular, identifying environmentally friendly, non-chromate alternatives that can maintain performance under such conditions has both technological and regulatory significance. This study investigates the environmental stability of zirconium-based hybrid conversion coatings with Cu additives (Cu10 and Cu20) applied to cold-rolled steel, tested in the Materials International Space Station Experiment (MISSE) outside the International Space Station (ISS). Chemical and morphological analyses were carried out using a combination of electron microscopy and X-ray spectroscopy techniques, including scanning electron microscopy (SEM), scanning transmission electron microscopy with energy-dispersive X-ray spectroscopy (STEM-EDS), X-ray photoelectron spectroscopy (XPS), and X-ray absorption near-edge structure (XANES) spectroscopy. After exposure outside the ISS, all coatings remained structurally intact, with all exhibiting a uniform Zr-rich matrix and embedded Cu-rich clusters, while a thin Si-rich surface layer developed from interaction with space environments. Depth-resolved XPS showed a layered structure with CuO on the surface, Cu 2 O, and partial Zr(IV) reduction near Cu-rich sites, evidence of Atomic Oxygen (AO)-driven surface oxidation. These results demonstrate that Cu–Zr coatings maintain their chemical integrity and microstructure in harsh space environments, offering a non-chromate alternative for long-term aerospace protection. These insights provide valuable guidance for developing next-generation protective coatings that combine environmental sustainability with the reliability required for future aerospace and orbital applications.

36 MATERIALS SCIENCE↗

NASA NTRS2015

Microstructure-Sensitive Investigation of Fracture Using Acoustic Emission Coupled With Electron Microscopy

A novel technique using Scanning Electron Microscopy (SEM) in conjunction with Acoustic Emission (AE) monitoring is proposed to investigate microstructure-sensitive fatigue and fracture of metals. The coupling between quasi in situ microscopy with actual in situ nondestructive evaluation falls into the ICME framework and the idea of quantitative data-driven characterization of material behavior. To validate the use of AE monitoring inside the SEM chamber, Aluminum 2024-B sharp notch specimen were tested both inside and outside the microscope using a small scale mechanical testing device. Subsequently, the same type of specimen was tested inside the SEM chamber. Load data were correlated with both AE information and observations of microcracks around grain boundaries as well as secondary cracks, voids, and slip bands. The preliminary results are in excellent agreement with similar findings at the mesoscale. Extensions of the application of this novel technique are discussed.

Wisner, Brian↗

DOE OSTI2022

High-Energy X-ray Diffraction Microscopy for Nuclear Forensics FY2022 Project Report

Morphological information on nuclear material has been identified using visible light and scanning electron microscopy. These identify qualitative differences in particle morphology. Three-dimensional imaging of materials through alternating scanning electron microscopy imaging and focused ion beam milling has also been used. Unfortunately, these techniques are time- and labor-intensive, with significant sample preparation required and lengthy analysis times. Further, the resulting 3D images are qualitative, require manual identification, and do not capture statistically-representative populations. High energy X-ray 3D imaging using a direct-beam or diffracted-beam (High-Energy Diffraction Microscopy) have been developed at the Advanced Photon Source and can produce quantitative information on grains (phase, location, etc.) and pores (size distribution, sphericity) in a material. These techniques require only minutes to characterize a sample volume and are non-destructive, thus suitable for a wide range of existing samples and for confirmatory analyses to be carried out using conventional microscopy techniques. In this first year of the project, all uranium oxide samples were synthesized and characterized using conventional analyses by the analytical chemistry laboratory. Conventional analysis methods included powder x-ray diffraction, scanning electron microscopy, impurity analysis via inductively coupled plasma mass spectrometry, and infrared spectroscopy. Impurity analysis shows a drop in boron content from UO 3 to the lowest U 3 O 8 calcination temperature, but otherwise no appreciable difference in any sample. Analysis of diffraction data shows a flip of peaks from UO 3 dominated for the 600 °C calcined sample to U 3 O 8 dominated at 700 °C and 800 °C. Analysis of scanning electron microscopy images shows that with increased calcination temperature the size distribution of particles seems to increase and broaden. Both of these last findings are in line with previously published data, though this work used significantly fewer particles to simply show similar trends instead of getting truly quantitative particle analysis. Infrared analysis similarly shows ingrowth of U 3 O 8 as calcination temperature is increased, along with depression of peaks associated with UO 3 and water. Samples were prepared for analysis at the Advanced Photon Source at beamline 1-ID. It is anticipated that analysis will occur in November of 2022. AI/ML techniques to de-noise data coming out of 1-ID during the analyses was also developed during this time using previously gathered data. Preliminary results using a self-supervision technique called Noise2Selfshow good de-noising of data. Once the uranium oxide samples are analyzed, real data will be used to test the de-noising and other AI/ML techniques that may be developed in the second year of the project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1990

Scanning electron acoustic microscopy of indentation-induced cracks and residual stresses in ceramics

The ability of scanning electron acoustic microscopy (SEAM) to characterize ceramic materials is assessed. SEAM images of Vickers indentations in SiC whisker-reinforced alumina clearly reveal not only the radial cracks, the length of which can be used to estimate the fracture toughness of the material, but also reveal strong contrast, interpreted as arising from the combined effects of lateral cracks and the residual stress field left in the SiC whisker-reinforced alumina by the indenter. The strong contrast is removed after the material is heat treated at 1000 C to relieve the residual stresses around the indentations. A comparison of these observations with SEAM and reflected polarized light observations of Vickers indentations in soda-lime glass both before and after heat treatment confirms the interpretation of the strong contrast.

Cantrell, John H.↗

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 OSTI2019

Continuous-flow synthesis of thermochromic M-phase VO2 particles via rapid one-step hydrothermal reaction – effect of mixers

VO2 particles are promising materials for thermochromic smart windows that reduce building energy loss. Continuous-flow hydrothermal processes showcase advantages for synthesizing VO2 particles compared with traditional batch reaction systems. Mixers play a crucial role in particle fabrication in continuous-flow systems. In this study, a Center T-Mixer and a Collision Cross-Mixer are developed and implemented in a hot water fluidized suspension reaction (HWFSR) system. The influence of the resident time on the particle phase and size was evaluated, and properties of particles derived from systems equipped with differing mixers were compared. The resulting particles were characterized using techniques of X-ray powder diffraction (XRD) analysis, scanning electron microscopy (SEM), and differential scanning calorimetry (DSC). When compared with the Center T-Mixer, results indicate that the Collision Cross-Mixer has better control regarding the morphology and size distribution of resulting particles while improving the transition temperatures of the as-synthesized materials. HWFSR systems containing novel mixer designs are capable of producing pure M-phase VO2 particles in a single step contrary to the current reactor design that use a second postheat treatment step, and they are capable of synthesizing many other nanoparticle species, especially those requiring high temperature and pressure reaction conditions.

continuous-flow process↗

DOE OSTI2024

Unveiling Structural Heterogeneity and Imbalance of Gold Decahedral Nanoparticles using Four-dimensional Scanning Transmission Electron Microscopy

Multi-twinned structures have been observed in technologically important crystal systems, for example diamond cubic and face-centered cubic (FCC) lattices, that include materials such as diamond, silicon, a wide range of noble metals, and their nanoscale counterparts. Beyond atomic building blocks, the special arrangements also occur in the self-assembly of nanoparticles (NP) and μm-sized colloidal particles and occupy parts of their phase diagrams. Spanning a wide range of length scales, the universality of the structures arises when the systems attempt to achieve multitwinned structures by overcoming geometric misfits during minimizing surface energies with entirely {111} or close-packing facets. While it is fundamental to understand how strain is sustained upon twinned structures and symmetry breaking, the knowledge will be paramount in practical aspects such as guiding and controlling the thin film growth, anisotropic NP growth, and self-assembly of NPs. Au decahedral (Dh) NP, as the most prevalent multi-twinned model system, fits five tetrahedral motifs into a circle by sharing an axis resulting in a geometric misfit angle of 7.35°, or a disclination with power of -7.35°. Postulating how Au FCC lattice adopts the misfit, theoretical models have been developed to address the underlying lattice symmetry and inhomogeneous strain distribution separately. Yet, experimental reports regarding the former have been limited due to the relatively large X-ray beam sizes that do not fit the sizes of NPs. On the other hand, though the latter has been widely adapted in the thermodynamics of small (<10 nm) multi-twinned nanoparticles, previous literature has shown that, at edge length of 17 nm, the theory’s is invalidated by shear strain that is observed in a defect-free Au Dh NP by high-resolution transmission electron microscopy (HR-TEM) imaging. Though the advancement of aberrationcorrected scanning transmission electron microscopy (AC-STEM) imaging and ab initio calculation techniques brings new opportunities, along with challenges in complicated image analysis and limitation in particle size (usually below 10 nm), the gap between nanoscale and mesoscale has never been extended to gain insight from atomic system with straightforward interaction potentials.

4D-STEM↗

DOE OSTI2023

Machine learning for automated experimentation in scanning transmission electron microscopy

Abstract Machine learning (ML) has become critical for post-acquisition data analysis in (scanning) transmission electron microscopy, (S)TEM, imaging and spectroscopy. An emerging trend is the transition to real-time analysis and closed-loop microscope operation. The effective use of ML in electron microscopy now requires the development of strategies for microscopy-centric experiment workflow design and optimization. Here, we discuss the associated challenges with the transition to active ML, including sequential data analysis and out-of-distribution drift effects, the requirements for edge operation, local and cloud data storage, and theory in the loop operations. Specifically, we discuss the relative contributions of human scientists and ML agents in the ideation, orchestration, and execution of experimental workflows, as well as the need to develop universal hyper languages that can apply across multiple platforms. These considerations will collectively inform the operationalization of ML in next-generation experimentation.

36 MATERIALS SCIENCE↗

DOE OSTI2025

BEACON—automated aberration correction for scanning transmission electron microscopy using Bayesian optimization

Aberration correction is an important aspect of modern high-resolution scanning transmission electron microscopy. Most methods of aligning aberration correctors require specialized sample regions and are unsuitable for fine-tuning aberrations without interrupting on-going experiments. Here, we present an automated method of correcting first- and second-order aberrations called BEACON, which uses Bayesian optimization of the normalized image variance to efficiently determine the optimal corrector settings. We demonstrate its use on gold nanoparticles and a hafnium dioxide thin film showing its versatility in nano- and atomic-scale experiments. BEACON can correct all first- and second-order aberrations simultaneously to achieve an initial alignment and first- and second-order aberrations independently for fine alignment. Ptychographic reconstructions are used to demonstrate an improvement in probe shape and a reduction in the target aberration.

techniques and instrumentation↗

DOE OSTI2019

Structure retrieval from four-dimensional scanning transmission electron microscopy: Statistical analysis of potential pitfalls in high-dimensional data

Four-dimensional (4D) scanning transmission electron microscopy is one of the most rapidly growing modes of electron microscopy imaging. The advent of fast pixelated cameras and the associated data infrastructure have greatly accelerated this process. Yet conversion of the 4D datasets into physically meaningful structure images in real space remains an open issue. In this work, we demonstrate that it is possible to systematically create filters that will affect the apparent resolution or even qualitative features of the real-space structure image, reconstructing artificially generated patterns. As initial efforts, we explore statistical model selection algorithms, aiming for robustness and reliability of estimated filters. This statistical model selection analysis demonstrates the need for regularization and cross validation of inversion methods to robustly recover structure from high-dimensional diffraction datasets.

36 MATERIALS SCIENCE↗

DOE OSTI2021

IMS Rapid Response FY21 Summary Report for: Integrating Patterned Probes with Four-Dimensional Scanning Transmission Electron Microscopy for Unrivaled Crystallographic Structure Determination in Nanomaterials

The initial goal of our 4-dimensional scanning transmission electron microscopy (4D-STEM)-based project was to develop strain resolution two orders of magnitude better than what is now currently possible with electron-based scattering techniques, all while collecting scattering information from 7 different tilt axes at one time [multi-beam electron diffraction (MBED)1 ] through the development of a new electron probe-forming aperture with non-circular features (patterned probes 2 ). We set out to accomplish this through a collaboration with Drs. Colin Ophus and Ben Savitsky at Lawrence Berkeley Laboratory (they are the world-leading experts in developing the complex computational codes required to perform orientation analysis and quantitative strain mapping on our 4D-STEM data sets. We are motivated to invest in this area as it will be the only technique sensitive enough to perform three- dimensional automated crystallographic orientation mapping (ACOM) and strain mapping for materials exposed to external stimulus (a focus of our larger efforts).

36 MATERIALS SCIENCE↗

DOE OSTI2024

Random forest prediction of crystal structure from electron diffraction patterns incorporating multiple scattering

Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here, in this study, we train an architecture of hierarchical random forest models capable of predicting the crystal system, space group, and lattice parameters from one or more unknown two-dimensional electron diffraction patterns. Our initial model correctly identifies the crystal system of a simulated electron diffraction pattern from a 20-nm-thick specimen of arbitrary orientation 67% of the time. We achieve a topline accuracy of 79% when aggregating predictions from ten patterns of the same material but different zone axes. The space group and lattice predictions range from 70% to 90% accuracy and median errors of 0.01-0.5Å, respectively, for cubic, hexagonal, trigonal, and tetragonal crystal systems while being less reliable on orthorhombic and monoclinic systems. We apply this architecture to a four-dimensional scanning transmission electron microscopy scan of gold nanoparticles, where it accurately predicts the crystal structure and lattice constants. These random forest models can be used to significantly accelerate the analysis of electron diffraction patterns, particularly in the case of unknown crystal structures. Additionally, due to the speed of inference, these models could be integrated into live transmission electron microscopy experiments, allowing real-Time labeling of a specimen.

36 MATERIALS SCIENCE↗