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At least 271 records · Page 15

Correlated X‐Ray and Electron Microscopies of a Single Biphasic GaAs Nanowire

Engineering the properties of semiconductors by changing their crystalline phase is a technologically and economically relevant alternative to doping using foreign elements, with strong potential for photonic and electronic applications. Although major advances have been reported recently for crystal‐phase engineering of III‐V and group IV semiconductor nanowires, interfacing two mismatched crystalline phases in a nanostructure induces several deformation mechanisms, which remain largely unexplored. Here, using state‐of‐the‐art synchrotron X‐ray nanobeam diffraction and transmission electron microscopy, subtle twisting and bending is unveiled within an individual GaAs nanowire containing cubic and hexagonal segments. Their role is discussed in accommodating the inter‐reticular spacing fluctuations, and their variations are correlated to the nanoscale phase distribution and to the effect of the NW support. This study brings direct evidence of a complex combination of deformation mechanisms in biphasic nanowires, which opens a new path to tune the nanowire properties with appealing perspectives for device engineering in nanophotonics and nanomechanics.

III-V semiconductors↗

Picosecond Carrier Dynamics in InAs and GaAs Revealed by Ultrafast Electron Microscopy

Understanding the limits of spatio-temporal carrier dynamics, especially in III-V semiconductors, is key to designing ultrafast and ultra-small optoelectronic components. However, identifying such limits and the properties controlling them has been elusive. Here, using scanning ultrafast electron microscopy (SUEM), in bulk n-GaAs and p-InAs, we simultaneously measure picosecond carrier dynamics along with three related quantities: sub-surface band bending, above-surface vacuum potentials, and surface trap densities. We make two surprising observations. First, we uncover a negative-time contrast in secondary electrons resulting from an interplay among these quantities. Second, despite dopant concentrations and surface state densities differing by many orders of magnitude between the two materials, their carrier dynamics, measured by photo-excited band bending and filling of surface states, occur at a seemingly common timescale of about 100 ps. This observation may indicate fundamental kinetic limits tied to a multitude of material and surface properties of optoelectronic III-V semiconductors, and highlights the need for techniques that simultaneously measure electro-optical kinetic properties.

36 MATERIALS SCIENCE↗

Autonomous fabrication of tailored defect structures in 2D materials using machine learning-enabled scanning transmission electron microscopy

Materials with tailored quantum properties can be engineered from atomic-scale assembly techniques, but existing methods often lack the agility and accuracy to precisely and intelligently control the manufacturing process. Here, we demonstrate a fully autonomous approach for fabricating atomic-level defects using electron beams in scanning transmission electron microscopy (STEM) that combines advanced machine learning and automated beam control. As a proof of concept, we achieved controlled fabrication of MoS-nanowire (MoS-NW) edge structures by iterative and targeted exposure of MoS 2 monolayer to a focused electron beam to selectively eject sulfur atoms, utilizing high-angle annular dark-field (HAADF) imaging for feedback-controlled monitoring of structural evolution of defects. A machine learning framework combining a random forest model and a convolutional neural network (CNN) was developed to decode the HAADF image and accurately identify atomic positions and species. This atomic-level information was then integrated into an autonomous decision-making platform, which applied predefined fabrication strategies to instruct beam control about atomic sites to be ejected. The selected sites were subsequently exposed to a localized electron beam using an FPGA-controlled scan routine with precise control over beam positioning and duration. While the MoS-NW edge structures produced exhibit promising mechanical and electronic properties, the proposed methods to build the autonomous fabrication framework is material-agnostic and can be extended to other 2D materials for the creation of diverse defect structures and heterostructures beyond Mo S2 .

Engineering↗

Automated processing of environmental transmission electron microscopy images for quantification of thin film dewetting and carbon nanotube nucleation dynamics

We report scalable production of carbon nanotubes (CNTs) requires catalysts and reaction conditions that provide high nucleation efficiency. In situ characterization methods such as environmental transmission electron microscopy (ETEM) can reveal fundamental mechanisms of synthesis, but to date have primarily provided qualitative observations on small sample sizes. Here, quantitative analysis is performed using high-resolution, high-rate video capture of ETEM experimentation coupled with automated image processing, involving computer vision algorithms and convolutional neural networks. By this approach, we detect distinct nanoparticle formation from an alumina-supported iron thin film and subsequent CNT nucleation from the nanoparticles. The statistical summary of particles in each video shows that, compared to a H 2 -only atmosphere, pretreatment of the catalyst with carbon added to the H 2 atmosphere results in a smaller average particle diameter, a 2-fold increase in particle density (to 5300 particles/μm 2 ), a 3-fold increase in CNT nucleation efficiency (to 92%), and more than a 5-fold increase in CNT density (to 4800/μm 2 ). Addition of carbon during exposure to H 2 is also more effective than NH 3 at dewetting the catalyst film and increasing the CNT nucleation efficiency, in spite of NH 3 being a stronger reducing agent for iron. Insights from this study are applicable to improving CNT yield and productivity in both batch-style and continuous processes.

25 ENERGY STORAGE↗

Transmission electron microscopy of the rapid solidification microstructure evolution and solidification interface velocity determination in hypereutectic Al-20at.%Cu after laser melting

The evolution of rapid solidification (RS) microstructure and solidification interface velocity has been studied experimentally by in-situ transmission electron microscopy and postmortem characterization for hypereutectic Al-20at.%Cu (37 wt.%Cu) after laser melting. Four morphologically distinct regions formed via growth modes changing from θ-Al 2 Cu phase dendrites to eutectic cell growth, possibly α-Al dendrite growth (α-cell), banded growth, and α-Al plane front growth. Tendency for faceting and low capacity for solute trapping limited the θ-phase dendrite growth to solidification interface velocity v < 0.07 m/s. Consequently, formation of pro-eutectic micro-constituent was suppressed, and RS microstructure formation was dominated by eutectic, α-cell, and banded morphology grains for the Al-20at.%Cu alloy. Eutectic growth operated for interface velocity of 0.1 m/s ≤ v < 0.3 m/s, with a transition from regular lamellar, 2-λ and 1-λ mode to a dense irregular morphology dominated by α-phase at v = 0.3 m/s. Interface temperature calculations indicated feasibility of α-cell growth mode for 0.3 m/s ≤ v < 0.7 m/s. Banded growth occurred for 0.7 m/s ≤ v < 1.3 m/s. Plane front α-phase growth was evident for interface velocities v ≥ 1.3 m/s. Previous work on rapid solidification microstructure development in hypereutectic Al-Cu alloys reported a regime of α-cell growth subsequently to eutectic and prior to transition to banded growth for Al-19at.%Cu (36 wt.%Cu), while for Al-22at.%Cu (40 wt.%Cu) eutectic growth transitioned directly to α-plane front growth without emergence of a banded regime. Finally, based on the current study the disappearance of the banded growth regime occurs for a composition larger than 20at.%Cu.

36 MATERIALS SCIENCE↗

Simplex‐based model for nanoparticle grain identification in four‐dimensional scanning transmission electron microscopy data

Grain identification in polycrystalline nanoparticles, for example, determining which crystal phases are present at each spatial location, is fundamental to materials characterisation. This is particularly challenging when grains overlap extensively, as commonly occurs in four-dimensional scanning transmission electron microscopy (4D-STEM) datasets. We propose a simplex-based model (SBM) in which each simplex vertex represents the diffraction pattern (DP) of a pure grain, and the simplex edges and interior represent overlapping grains. Our SBM grain identification algorithm operates on the Bragg disk (BD) data matrix distilled from the 4D-STEM data to identify the grain membership at each scan position, together with a BD feature matrix whose columns represent the DPs for each constituent grain, which is important for identifying the crystal structure of each grain. We solve the model using a two-stage algorithm. In Stage 1, we adapt a linear mixing algorithm to estimate an initial BD feature matrix whose columns represent DPs of potentially overlapping grains. Our Stage 2 algorithm incorporates sparsity considerations to transform the initial BD feature matrix so that its columns represent DPs of pure grains. Using simulated datasets with various grain configurations, we demonstrate that SBM recovers both the BD feature matrix and membership maps more accurately than existing methods, even when a grain lacks any pure region and completely overlaps with other grains.

4D-STEM segmentation↗

Minimizing Crinkling of Soft Specimens Using Holey Gold Films on Molybdenum Grids for Cryogenic Electron Microscopy

We introduce a novel composite holey gold support that prevents cryo-crinkling and reduces beam-induced motion of soft specimens, building on the previously introduced all-gold support. The composite holey gold support for high-resolution cryogenic electron microscopy of soft crystalline membranes was fabricated in two steps. In the first step, a holey gold film was transferred on top of a molybdenum grid. In the second step, a continuous thin carbon film was transferred onto the holey gold film. This support (Au/Mo grid) was used to image crystalline synthetic polymer membranes. The low thermal expansion of Mo is not only expected to avoid cryo-crinkling of the membrane when the grids are cooled to cryogenic temperatures, but it may also act to reduce whatever crinkling existed even before cooling. Here, the Au/Mo grid exhibits excellent performance with specimens tilted to 45°. This is demonstrated by quantifying beam-induced motion and differences in local defocus values. In addition, images of specimens on the Au/Mo grids that are tilted at 45° show high-resolution information of the crystalline membranes that, after lattice-unbending, extends beyond 1.5 Å in the direction perpendicular to the tilt axis.

36 MATERIALS SCIENCE↗

Resolving Nanoscopic and Mesoscopic Heterogeneity of Fluorinated Species in Battery Solid-Electrolyte Interphases by Cryogenic Electron Microscopy

The stability of lithium batteries is tied to the physicochemical properties of the solid-electrolyte interphase (SEI). Owing to the difficulty in characterizing this sensitive interphase, the nanoscale distribution of SEI components is poorly understood. Here, we use cryogenic scanning transmission electron microscopy (cryo-STEM) to map the spatial distribution of SEI components across the metallic Li anode. We reveal that LiF, an SEI component widely believed to play an important role in battery passivation, is absent within the compact SEI film (~15 nm); instead, LiF particles (100–400 nm) precipitate across the electrode surface. We term this larger length scale as the indirect SEI regime. On the basis of these observations, we conclude that LiF cannot be a dominant contribution to anode passivation nor does it influence Li+ transport across the compact SEI film. We refine the traditional SEI structure derived from ensemble-averaged characterizations and nuance the role of SEI components on battery performance.

25 ENERGY STORAGE↗

Atomic Evolution of Hydrogen Intercalation Wave Dynamics in Palladium Nanocrystals Revealed by Liquid-Phase Transmission Electron Microscopy

Solute-intercalation-induced phase separation creates spatial heterogeneities in host materials, a phenomenon ubiquitous in batteries, hydrogen storage, and other energy devices. Despite many efforts, probing intercalation processes at the atomic scale has been a significant challenge. By utilizing liquid-phase transmission electron microscopy (TEM), we study hydrogen (de)intercalation in palladium nanocrystals as a model system and have achieved unprecedented atomic-resolution imaging of hydrogen intercalation wave dynamics. Our observations reveal that intercalation wave mechanisms, instead of shrinking-core mechanisms, prevail at ambient temperature for palladium nanocubes ranging from ∼60 nm down to ∼10 nm. Systematic image analysis uncovers the atomic evolution of the hydrogen intercalation wave, transitioning from nonplanar and inclined boundaries to those closely aligned with {100} planes. Our kinetic Monte Carlo simulations demonstrate that the observed intercalation wave dynamics correspond to sorption pathways minimizing the lattice mismatch strain at the phase boundary. In conclusion, unveiling the atomic intercalation pathways holds profound implications for engineering intercalation-mediated devices and advancements in energy sciences.

Lee, Daewon [Lawrence Berkeley National Laboratory↗

Probing the in situ volumes of Arabidopsis leaf plastids using three‐dimensional confocal and scanning electron microscopy

SUMMARY Leaf plastids harbor a plethora of biochemical reactions including photosynthesis, one of the most important metabolic pathways on Earth. Scientists are eager to unveil the physiological processes within the organelle but also their interconnection with the rest of the plant cell. An increasingly important feature of this venture is to use experimental data in the design of metabolic models. A remaining obstacle has been the limited in situ volume information of plastids and other cell organelles. To fill this gap for chloroplasts, we established three microscopy protocols delivering in situ volumes based on: (i) chlorophyll fluorescence emerging from the thylakoid membrane, (ii) a CFP marker embedded in the envelope, and (iii) calculations from serial block‐face scanning electron microscopy (SBFSEM). The obtained data were corroborated by comparing wild‐type data with two mutant lines affected in the plastid division machinery known to produce small and large mesophyll chloroplasts, respectively. Furthermore, we also determined the volume of the much smaller guard cell plastids. Interestingly, their volume is not governed by the same components of the division machinery which defines mesophyll plastid size. Based on our three approaches, the average volume of a mature Col‐0 wild‐type mesophyll chloroplasts is 93 μm 3 . Wild‐type guard cell plastids are approximately 18 μm 3 . Lastly, our comparative analysis shows that the chlorophyll fluorescence analysis can accurately determine chloroplast volumes, providing an important tool to research groups without access to transgenic marker lines expressing genetically encoded fluorescence proteins or costly SBFSEM equipment.

Knoblauch, Jan↗

Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images

Cutting edge deep learning techniques allow for image segmentation with great speed and accuracy. However, application to problems in materials science is often difficult since these complex models may have difficultly learning meaningful image features that would enable extension to new datasets. In situ electron microscopy provides a clear platform for utilizing automated image analysis. In this work, we consider the case of studying coarsening dynamics in supported nanoparticles, which is important for understanding, for example, the degradation of industrial catalysts. By systematically studying dataset preparation, neural network architecture, and accuracy evaluation, we describe important considerations in applying deep learning to physical applications, where generalizable and convincing models are required. With a focus on unique challenges that arise in high-resolution images, we propose methods for optimizing performance of image segmentation using convolutional neural networks, critically examining the application of complex deep learning models in favor of motivating intentional process design.

36 MATERIALS SCIENCE↗

Towards Mitigating Electron Beam-Induced Damage in MOFs Using Low Dose Electron Microscopy for In-Situ Room-Temperature Measurements

Metal-Organic Frameworks (MOFs) have emerged as a versatile class of materials with applications in gas storage and separation, catalysis, and drug delivery [1]. Understanding their damage mechanisms in under various environmental conditions is crucial for optimizing performance and stability [2]. This study employs a combination of Length Structural Coherence (LSC) analysis in electron scattering and Electron Energy Loss Spectroscopy (EELS) to elucidate the damage mechanisms in two representative MOFs. MIL101(Fe), and MIL101(Cr). Here, the primary objective is to reveal structural and chemical changes that occur under electron beam irradiation in Scanning Transmission Electron Microscopy (STEM), both in the pristine state and during in-situ CO and CO 2 adsorption. By combining LSC in Radial Distribution Function (RDF) analysis with EELS, comprehensive insights into the nanoscale alterations are obtained and correlated to the electron dose rate.

dos Santos, Gabriel T. [Northwestern University, E↗

Developing High-Flux Ion Soft Landing with Mass-Selection for Improved Cryo-Electron Microscopy

The goal of this project is to redesign and repurpose existing high-flux ion soft-landing (SL) instrumentation developed at PNNL for new structural biology applications by integrating SL, mass-selection/separation of high mass-to-charge species, native mass spectrometry (MS), and cryo-electron microscopy (EM) to generate a workflow enabling structural and functional annotation of proteins and other complex biological samples. Ultimately, this work will result in a new instrument for mass-selection and SL based cryo-EM sample preparation and potentially increase the impact of PNNL and the broader microscopy community through commercial licensing.

47 OTHER INSTRUMENTATION↗

Understanding Mechanisms of Selective Crystal Nucleation and Growth Using In Situ Electron Microscopy

Separation processes are essential for purifying and isolating critical materials, but are challenging due to the natural tendency of systems to mix. This project explores far-from-equilibrium separation methods using external electric and magnetic fields to drive selective nucleation and crystal growth. Using in situ electrochemical transmission electron microscopy (TEM), we observed ion transport and crystallization behavior under applied electric fields. We found that ions migrate toward the working electrode, where nucleation preferentially occurs. These findings advance our understanding of non-equilibrium separation mechanisms and support the development of efficient, sustainable methods for extracting critical materials from unconventional domestic sources.

36 MATERIALS SCIENCE↗

Investigation of Nanoparticle Degradation in Hydrogen Fuel Cell Systems through Automated Electron Microscopy

Proton exchange membrane fuel cells (PEMFC) are promising devices for the deployment of hydrogen-powered heavy-duty vehicles, providing a higher efficiency for similar driving range and fueling time than the existing ones. However, PEMFCs still encounter durability challenges mainly due to catalyst degradation in the cathode. Mitigating these performance losses requires a better understanding of the degradation mechanisms under heavy-duty accelerated stress tests (ASTs) [1]. Scanning transmission electron microscopy (STEM) combined with energy dispersive X-ray spectroscopy (EDS) are key tools for the analysis of Pt and PtCo nanoparticle size, spatial distribution and composition [2]. Electron tomography is also used to determine the rate and type of degradation of catalyst nanoparticles as a function of their position on the carbon support. In this work, automated data acquisition software, paired with a custom Python code, have been used to study the effect of different accelerated stress tests (ASTs) on nanoparticle coarsening [2]. Figure 1 shows high-angle annular dark-field (HAADF)-STEM images and EDS maps comparing the cathodes of membrane electrode assemblies (MEAs) following an electrocatalyst AST performed under H2/N2 with that of the heavy-duty AST performed under H2/air. We will discuss how AST conditions affect considerably the spatial distribution of the nanoparticles across the electrode between the membrane and microporous layer. Although the median particle size increased more in the MEA aged under the heavy-duty AST, as determined using a high-throughput image analysis, the quantitative EDS measurements demonstrate that the electrocatalyst AST resulted in more Pt and Co dissolution from the cathode, which is another important indicator of electrocatalyst degradation. We will further present the impact of the relative humidity (% RH) on the degradation mechanisms demonstrated using the same approach. Electron tomography has been used to distinguish the Pt nanoparticles residing on the carbon support surface (exterior) from those within the pore structure (interior) in order to determine the relative stability of interior and exterior nanoparticles. As shown in Figure 2, we will compare the Pt catalyst particle size at the beginning of test (BOT) and end of test (EOT), and discuss the importance of automating the electron tomography workflow, i.e. acquisition, reconstruction, and visualization, to increase sampling and determine the standard deviation of these measurement. The outlook for utilizing low-dose cryo-tomography for limiting damage to the catalyst, support, and especially proton-conducting ionomer will also be discussed [3].

Amichi, Lynda↗

In situ transmission electron microscopy observations of CaCO 3 crystallization onto polysaccharide-coated nanoparticles

Polysaccharides and proteoglycans are widely associated with the organic matrix at sites of CaCO 3 biomineralization, and previous studies indicate that these macromolecules may confer greater roles in mineral nucleation than previously recognized. This investigation uses in situ liquid-phase transmission electron microscopy (LP-TEM) to observe CaCO 3 nucleation onto aminated silica (SiO 2 –NH 3 + ) nanoparticles treated with a layer of chitosan (near-neutral derivative of chitin) or heparin (a carboxylated and highly sulfated glycosaminoglycan). In the absence of polysaccharides, few CaCO 3 particles formed and exhibited mobility. However, the SiO 2 –NH 3 + nanoparticles were enveloped in a region of higher mass density relative to the bulk solution, suggesting the development of a local solute-rich environment that surrounds the charged NH 3 + groups. The heparin- or chitosan-coated silica particles also exhibited regions of higher mass density around the nanoparticles. In the presence of these polysaccharide coatings, we observed the nucleation of abundant CaCO 3 particles whereby the polyanionic heparin promoted more nucleation than the weakly cationic chitosan. Many crystallites appeared to form at the polysaccharide–TEM cell membrane–solution interface, further indicating interfacial and macromolecule-specific control on crystallization. The combined results demonstrate that chitosan and heparin have an appreciable effect on the timing, size, and location of CaCO 3 nucleation compared to the polysaccharide-free nanoparticles.

15 GEOTHERMAL ENERGY↗

Quantitative nanoscale tracking of oxygen vacancy diffusion inside single ceria grains by in situ transmission electron microscopy

Oxygen vacancy formation and migration in ceria is critical to its electrochemical and catalytic properties in systems for chemical and energy transformation, but its quantification is rather challenging especially at atomic-scale because of disordered distribution. Here we report a rational approach to track oxygen vacancy diffusion in single grains of pure and Sm-doped ceria at -20 °C to 160 °C using in situ (scanning) transmission electron microscopy ((S)TEM). To create a gradient in oxygen vacancy concentration, a small region (~30 nm in diameter) inside a ceria grain is reduced to the C-type CeO 1.68 phase by the ionization or radiolysis effect of a high-energy electron beam. The evolution in oxygen vacancy concentration is then mapped through lattice expansion measurement using scanning nano-beam diffraction or 4D STEM at a spatial resolution better than 2 nm; this allows direct determination of local oxygen vacancy diffusion coefficients in a very small domain inside pure and Sm-doped ceria at different temperatures. Further, the activation energies for oxygen transport are determined to be 0.59, 0.66, 1.12, and 1.27 eV for pure CeO 2 , Ce 0.94 Sm 0.06 O 1.97 , Ce 0.89 Sm 0.11 O 1.945 , and Ce 0.8 Sm 0.2 O 1.9 , respectively, implying that activation energy increases due to impurity scattering. The results are qualitatively supported by density functional theory (DFT) calculations. In addition, our in situ TEM investigation reveals that dislocations impede oxygen vacancy diffusion by absorbing oxygen vacancies from the surrounding areas and pinning them locally. With more oxygen vacancies absorbed, dislocations show extended strain fields with local tensile zone sandwiched between the compressed ones. Therefore, dislocation density should be reduced in order to minimize the resistance to oxygen vacancy diffusion at low temperatures.

36 MATERIALS SCIENCE↗