Conventional Transmission Electron Microscopy Research Articles

Investigation of the structural stability of polycrystalline cBN under near-industrial grinding process conditions

Cubic boron nitride (cBN) is an important material in the cutting and metal processing industries due to its exceptional hardness and high thermal stability, which allows it to withstand temperatures up to 1400 °C without decomposing. These properties make cBN and, with that, polycrystalline cBN (PcBN) ideal materials for high-speed machining and other applications, resulting in increased efficiency and reduced costs in production processes. Despite its established importance, the possibility of phase transformations into hexagonal boron nitride phases or partial amorphization during industrial PcBN grinding processes remains unclear and, due to the deteriorated mechanical characteristics, raised recently some concerns about possible losses of cBN's hardness, wear resistance, and abrasive properties. In order to address this issue and for identifying such potential structural changes, a commercial PcBN grade was exposed to near-industrial grinding process conditions and then characterized in detail by conventional (scanning) transmission electron microscopy (S)TEM and (scanning) electron diffraction techniques. To understand the influence of the PcBN machining on the material, the grinding process also needs to be assessed via the identification of chip formation mechanisms, which is as well addressed in this work. The main outcome of this study, combining a material analysis and a manufacturing technology point of view, is that there is so far no evidence of any structural instabilities of PcBN under usual processing conditions.

Comparison of differential phase Contrast, Lorentz and non-Lorentz transmission electron microscopy for microstructural and magnetic imaging of alnico magnet

In this work, non-Lorentz, Lorentz transmission electron microscopy (LTEM) and differential phase contrast (DPC) methods were used to observe the phase and magnetic structure of the alnico magnet. All observations were performed on alnico-5 in transverse orientation. The results showed the magnetic contrast of the domain walls in the conventional TEM images despite the effects of the lens magnetic field, which was verified and explained using DPC. Experimental methodology and sample results are summarized with advice for further research.

Particle morphology characterization in an over-aged Al-Cu-Mg-Si alloy using TEM

A quantitative analysis of particle morphologies in a heterophase Al-Cu-Mg-Si alloy after over-aging has been performed using conventional transmission electron microscopy (TEM) imaging in dark- and bright-field modes. An appropriate analytical procedure has been suggested separating {100}Al plate- and 〈100〉Al rod-shaped particles using TEM images taken along 〈100〉Al and 〈110〉Al zone axes. The obtained statistical particle morphology parameters were verified by macroscopic strength contribution calculations.

Reducing two-level systems dissipations in 3D superconducting niobium resonators by atomic layer deposition and high temperature heat treatment

Superconducting qubits have arisen as a leading technology platform for quantum computing, which is on the verge of revolutionizing the world's calculation capacities. Nonetheless, the fabrication of computationally reliable qubit circuits requires increasing the quantum coherence lifetimes, which are predominantly limited by the dissipations of two-level system defects present in the thin superconducting film and the adjacent dielectric regions. In this paper, we demonstrate the reduction of two-level system losses in three-dimensional superconducting radio frequency niobium resonators by atomic layer deposition of a 10 nm aluminum oxide Al2O3 thin films, followed by a high vacuum heat treatment at 650 °C for few hours. By probing the effect of several heat treatments on Al2O3-coated niobium samples by x-ray photoelectron spectroscopy plus scanning and conventional high resolution transmission electron microscopy coupled with electron energy loss spectroscopy and energy dispersive spectroscopy, we witness a dissolution of niobium native oxides and the modification of the Al2O3-Nb interface, which correlates with the enhancement of the quality factor at low fields of two 1.3 GHz niobium cavities coated with 10 nm of Al2O3.

Towards Construction of a Novel Nanometer-Resolution MeV-STEM for Imaging Thick Frozen Biological Samples

Driven by life-science applications, a mega-electron-volt Scanning Transmission Electron Microscope (MeV-STEM) has been proposed here to image thick frozen biological samples as a conventional Transmission Electron Microscope (TEM) may not be suitable to image samples thicker than 300–500 nm and various volume electron microscopy (EM) techniques either suffering from low resolution, or low speed. The high penetration of inelastic scattering signals of MeV electrons could make the MeV-STEM an appropriate microscope for biological samples as thick as 10 μm or more with a nanoscale resolution, considering the effect of electron energy, beam broadening, and low-dose limit on resolution. The best resolution is inversely related to the sample thickness and changes from 6 nm to 24 nm when the sample thickness increases from 1 μm to 10 μm. To achieve such a resolution in STEM, the imaging electrons must be focused on the specimen with a nm size and an mrad semi-convergence angle. This requires an electron beam emittance of a few picometers, which is ~1000 times smaller than the presently achieved nm emittance, in conjunction with less than 10−4 energy spread and 1 nA current. We numerically simulated two different approaches that are potentially applicable to build a compact MeV-STEM instrument: (1) DC (Direct Current) gun, aperture, superconducting radio-frequency (SRF) cavities, and STEM column; (2) SRF gun, aperture, SRF cavities, and STEM column. Beam dynamic simulations show promising results, which meet the needs of an MeV-STEM, a few-picometer emittance, less than 10−4 energy spread, and 0.1–1 nA current from both options. Also, we designed a compact STEM column based on permanent quadrupole quintuplet, not only to demagnify the beam size from 1 μm at the source point to 2 nm at the specimen but also to provide the freedom of changing the magnifications at the specimen and a scanning system to raster the electron beam across the sample with a step size of 2 nm and the repetition rate of 1 MHz. This makes it possible to build a compact MeV-STEM and use it to study thick, large-volume samples in cell biology.

Eosinophil activation during immune responses: an ultrastructural view with an emphasis on viral diseases.

Eosinophils are cells of the innate immune system that orchestrate complex inflammatory responses. The study of the cell biology of eosinophils, particularly associated with cell activation, is of great interest to understand their immune responses. From a morphological perspective, activated eosinophils show ultrastructural signatures that have provided critical insights into the comprehension of their functional capabilities. Application of conventional transmission electron microscopy (TEM) in combination with quantitative assessments (quantitative TEM), molecular imaging (immunoEM), and three-dimensional (3D) electron tomography have generated important insights into mechanisms of eosinophil activation. This review explores a multitude of ultrastructural events taking place in eosinophils activated in vitro and in vivo as key players in allergic and inflammatory diseases, with an emphasis on viral infections. Recent progress in our understanding of biological processes underlying eosinophil activation, including in vivo mitochondrial remodeling, is discussed, and it can bring new thinking to the field.

Electron-translucency and partial defects of synaptic basal lamina in the electrocyte synapse of an electric ray (Narke japonica) in 3D embedment-free section electron microscopy.

The synaptic basal lamina of the electrocytes was disclosed to be electron-translucent to some extent when viewed in an en-face direction in embedment-free section transmission electron microscopy (EFS-TEM), and synaptic vesicles located close to the presynaptic membrane were seen through the synaptic basal lamina together with the presynaptic and postsynaptic membranes. This feature of translucency has the potential to analyze possible spatial interrelations in situ between bioactive molecules in the synaptic basal lamina and the synaptic vesicles in further studies. The synaptic basal lamina, appearing as an electron-dense line sandwiched by two parallel lines representing the presynaptic and postsynaptic membranes in ultrathin sections cut right to the synaptic junctional plane in conventional TEM, was not fully continuous but randomly intermittent along its trajectory. Compatible with the intermittent line appearance, the en-face 3D view in embedment-free section TEM revealed for the first time partial irregular defects of the synaptic basal lamina. Considering the known functional significance of several molecules contained in the synaptic basal lamina in the maintenance and exertion of the synapse, its partial defects may not represent its rigid structural features, but its immature structure under remodeling or its dynamic changes in consistency such as the sol/gel transition, whose validity needs further examination. RESEARCH HIGHLIGHTS: In embedment-free section TEM, a 3D en-face view of synaptic basal lamina in situ is reliably possible. The basal lamina en-face is electron-translucent, which makes it possible to analyze spatial interrelation between pre- and post-synaptic components. Partial irregular defects in the basal lamina are revealed in Torpedo electrocytes, suggesting its remodeling or dynamic changes in consistency.

The proteome of bacterial membrane vesicles in Escherichia coli-a time course comparison study in two different media.

Bacteria inhabit the in- and outside of the human body, such as skin, gut or the oral cavity where they play an innoxious, beneficial or even pathogenic role. It is well known that bacteria can secrete membrane vesicles (MVs) like eukaryotic cells with extracellular vesicles (EVs). Several studies indicate that bacterial membrane vesicles (bMVs) play a crucial role in microbiome-host interactions. However, the composition of such bMVs and their functionality under different culture conditions are still largely unknown. To gain a better insight into bMVs, we investigated the composition and functionality of E. coli (DSM 105380) bMVs from the culture media Lysogeny broth (LB) and RPMI 1640 throughout the different phases of growth (lag-, log- and stationary-phase). bMVs from three time points (8 h, 54 h, and 168 h) and two media (LB and RPMI 1640) were isolated by ultracentrifugation and analyzed using nanoparticle tracking analysis (NTA), cryogenic electron microscopy (Cryo-EM), conventional transmission electron microscopy (TEM) and mass spectrometry-based proteomics (LC-MS/MS). Furthermore, we examined pro-inflammatory cytokines IL-1β and IL-8 in the human monocyte cell line THP-1 upon bMV treatment. Particle numbers increased with inoculation periods. The bMV morphologies in Cryo-EM/TEM were similar at each time point and condition. Using proteomics, we identified 140 proteins, such as the common bMV markers OmpA and GroEL, present in bMVs isolated from both media and at all time points. Additionally, we were able to detect growth-condition-specific proteins. Treatment of THP-1 cells with bMVs of all six groups lead to significantly high IL-1β and IL-8 expressions. Our study showed that the choice of medium and the duration of culturing significantly influence both E. coli bMV numbers and protein composition. Our TEM/Cryo-EM results demonstrated the presence of intact E. coli bMVs. Common E. coli proteins, including OmpA, GroEL, and ribosome proteins, can consistently be identified across all six tested growth conditions. Furthermore, our functional assays imply that bMVs isolated from the six groups retain their function and result in comparable cytokine induction.

Deep learning-enabled probing of irradiation-induced defects in time-series micrographs

Modeling time-series data with convolutional neural networks (CNNs) requires building a model to learn in batches as opposed to training sequentially. Coupling CNNs with in situ or operando techniques opens the possibility of accurately segmenting dynamic reactions and mass transport phenomena to understand how materials behave under the conditions in which they are used. In this article, in situ ion irradiation transmission electron microscopy (TEM) images are used as inputs into the CNN to assess the defect generation rate, defect cluster density, and saturation of defects. We then use the output segmentation maps to correlate with conventional TEM micrographs to assess the model’s ability to detail nanoscale interactions. Next, we discuss the implications of preprocessing and hyperparameters on model variability, accuracy when expanded to other datasets, and the role of regularization when controlling model variance. Ultimately, we eliminate human bias when extrapolating physical metrics, speed up analysis time, decouple reactions that happen at 100 ms intervals, and deploy models that are both accurate and transferable to similar experiments.

In-situ heating-and-electron tomography for materials research: from 3D (in-situ 2D) to 4D (in-situ 3D).

In-situ observation has expanded the application of transmission electron microscopy (TEM) and has made a significant contribution to materials research and development for energy, biomedical, quantum, etc. Recent technological developments related to in-situ TEM have empowered the incorporation of three-dimensional observation, which was previously considered incompatible. In this review article, we take up heating as the most commonly used external stimulus for in-situ TEM observation and overview recent in-situ TEM studies. Then, we focus on the electron tomography (ET) and in-situ heating combined observation by introducing the authors' recent research as an example. Assuming that in-situ heating observation is expanded from two dimensions to three dimensions using a conventional TEM apparatus and a commercially available in-situ heating specimen holder, the following in-situ heating-and-ET observation procedure is proposed: (i) use a rapid heating-and-cooling function of a micro-electro-mechanical system holder; (ii) heat and cool the specimen intermittently and (iii) acquire a tilt-series dataset when the specimen heating is stopped. This procedure is not too technically challenging and can have a wide range of applications. Essential technical points for a successful 4D (space and time) observation will be discussed through reviewing the authors' example application.

Centriole and transition zone structures in photoreceptor cilia revealed by cryo-electron tomography.

Primary cilia mediate sensory signaling in multiple organisms and cell types but have structures adapted for specific roles. Structural defects in them lead to devastating diseases known as ciliopathies in humans. Key to their functions are structures at their base: the basal body, the transition zone, the "Y-shaped links," and the "ciliary necklace." We have used cryo-electron tomography with subtomogram averaging and conventional transmission electron microscopy to elucidate the structures associated with the basal region of the "connecting cilia" of rod outer segments in mouse retina. The longitudinal variations in microtubule (MT) structures and the lumenal scaffold complexes connecting them have been determined, as well as membrane-associated transition zone structures: Y-shaped links connecting MT to the membrane, and ciliary beads connected to them that protrude from the cell surface and form a necklace-like structure. These results represent a clearer structural scaffold onto which molecules identified by genetics, proteomics, and superresolution fluorescence can be placed in our emerging model of photoreceptor sensory cilia.

GoldDigger and Checkers, computational developments in cryo-scanning transmission electron tomography to improve the quality of reconstructed volumes.

In this work, we present a pair of tools to improve the fiducial tracking and reconstruction quality of cryo-scanning transmission electron tomography (STET) datasets. We then demonstrate the effectiveness of these two tools on experimental cryo-STET data. The first tool, GoldDigger, improves the tracking of fiducials in cryo-STET by accommodating the changed appearance of highly defocussed fiducial markers. Since defocus effects are much stronger in scanning transmission electron microscopy than in conventional transmission electron microscopy, existing alignment tools do not perform well without manual intervention. The second tool, Checkers, combines image inpainting and unsupervised deep learning for denoising tomograms. Existing tools for denoising cryo-tomography often rely on paired noisy image frames, which are unavailable in cryo-STET datasets, necessitating a new approach. Finally, we make the two software tools freely available for the cryo-STET community.

An introduction to scanning transmission electron microscopy for the study of protozoans.

Since its inception in the 1930s, transmission electron microscopy (TEM) has been a powerful method to explore the cellular structure of parasites. TEM usually requires samples of <100 nm thick and with protozoans being larger than 1 μm, their study requires resin embedding and ultrathin sectioning. During the past decade, several new methods have been developed to improve, facilitate, and speed up the structural characterisation of biological samples, offering new imaging modalities for the study of protozoans. In particular, scanning transmission electron microscopy (STEM) can be used to observe sample sections as thick as 1 μm thus becoming an alternative to conventional TEM. STEM can also be performed under cryogenic conditions in combination with cryo-electron tomography providing access to the study of thicker samples in their native hydrated states in 3D. This method, called cryo-scanning transmission electron tomography (cryo-STET), was first developed in 2014. This review presents the basic concepts and benefits of STEM methods and provides examples to illustrate the potential for new insights into the structure and ultrastructure of protozoans.

Optimized procedure for conventional TEM sample preparation using birefringence

Specimens for quality transmission electron microscopy (TEM) analyses must fulfil a range of requirements, which demand high precision during the prior preparation process. In this work, an optimized procedure for conventional TEM specimen preparation is presented that exploits the thickness-dependence of interference colors occurring in birefringent materials. It facilitates the correct estimation of specimen thickness to avoid damage or breaking during mechanical thinning and reduces ion-milling times below 30minutes. The benefits of the approach are shown on sapphire and silicon carbide cross-section samples. The presented method is equally suitable for assessing specimen thickness during dimpling and wedge-polishing, and is particularly useful at thicknesses below 20 μm, where the accuracy of mechanical techniques is insufficient. It is precise enough to be employed for a visual thickness estimation during the thinning process, but can be additionally optimized by analyzing the RGB spectrum of the occurring interference colors.

Characterization of irradiation-induced dislocation loops and helium bubbles via electron channeling contrast imaging

Characterizing irradiation-induced defects is essential to understand damage mechanisms and develop irradiation-resistant materials. Prevailing strategies rely on transmission electron microscopy (TEM) observations which require rigorous prerequisite to prepare high-quality foils, making it difficult for rapid screening of irradiation-resistant materials. Here, we propose that the electron channeling contrast imaging (ECCI) is expected to provide a novel strategy for characterizing surface irradiation defects of ion-irradiated materials. The comparison between ECCI and conventional cross-sectional TEM for the observation of dislocation loops and helium (He) bubbles is analyzed in a common FeCoNiCr high-entropy alloy. The results indicate that the ECCI images of irradiation-induced defects are optimal at the extra-high tension of 20 kV, with a limit resolution of ∼1.5 nm for visible defects. The irradiation-induced dislocation loops show sharper contrast than bubbles in ECCI images, and the acceptable misorientation was within 4° of sample tilt. These findings offer a promising solution to the challenges for rapid assessment of irradiation damage in ion-irradiated materials.

Dislocations in naturally deformed olivine: Example of a mylonitic peridotite

We have investigated the microstructure of naturally deformed olivine (chemically equilibrated at 1000 °C) by conventional transmission electron microscopy and electron tomography. The peridotite specimen, from Oman ophiolite, has a mylonitic microstructure with remnant, strongly deformed, millimetric porphyroclasts co-existing with small newly formed olivine grains generated by dynamic recrystallization. Imaging by transmission electron microscopy reveals that both newly formed grains and porphyroclasts display [100] and [001] dislocations activity. Subgrain boundaries are composed of either [100] or [001] dislocations. The characterization of this natural sample also permits to identify sporadic [100] dislocation loops, rare [010] dislocation, infrequent melt, and intragranular bubbles or along subgrain boundaries. Electron tomography permits to identify several glide planes, which are similar to previous observations acquired on experimentally deformed polycrystalline olivine, more importantly electron tomography also permits to evidence combination of glide, climb and mixed climb (dislocation moving in an intermediate plane between the plane of glide plane and the plane of pure climb). Our study further infers the diversity of linear defects responsible for plastic deformation of olivine at lithospheric conditions.

3D characterization of abnormal grain growth in nanocrystalline nickel

AbstractAbnormal grain growth, a pervasive phenomenon witnessed during the annealing of nanocrystalline metals, precipitates a swift diminution of the distinctive properties inherent to such materials. Historically, conventional transmission electron microscopy has struggled to efficiently procure comprehensive five‐parameter crystallographic information from a substantial number of grain boundaries in nanocrystalline metals, thus inhibiting a deeper understanding of abnormal grain growth behavior within nanocrystalline materials. In this study, we utilize a high‐throughput characterization method—three‐dimensional orientation mapping in the TEM (3D‐OMiTEM) to characterize the crystallographic five‐parameter character of grain boundaries with an area of over 3.4 × 106 nm2 in an abnormally grown nanocrystalline nickel sample. When coupled with existing theoretical simulation results, it is discerned that the grain boundary population shows a relatively large scatter when it is correlated to the calculated grain boundary energy; the grain boundaries of abnormally grown grains exhibit lower grain boundary energy compared to those that have not undergone abnormal growth. Merging high‐throughput grain boundary information obtained from three‐dimensional orientation mapping data with grain boundary properties derived from high‐throughput theoretical calculations following the concept of materials genome engineering will undoubtedly facilitate further advancements in comprehending and discerning the interfacial behaviors of crystalline materials.

Spatially and Chemically Resolved Visualization of Fe Incorporation into NiO Octahedra during the Oxygen Evolution Reaction.

The activity of Ni (hydr)oxides for the electrochemical evolution of oxygen (OER), a key component of the overall water splitting reaction, is known to be greatly enhanced by the incorporation of Fe. However, a complete understanding of the role of cationic Fe species and the nature of the catalyst surface under reaction conditions remains unclear. Here, using a combination of electrochemical cell and conventional transmission electron microscopy, we show how the surface of NiO electrocatalysts, with initially well-defined surface facets, restructures under applied potential and forms an active NiFe layered double (oxy)hydroxide (NiFe-LDH) when Fe3+ ions are present in the electrolyte. Continued OER under these conditions, however, leads to the creation of additional FeOx aggregates. Electrochemically, the NiFe-LDH formation correlates with a lower onset potential toward the OER, whereas the formation of the FeOx aggregates is accompanied by a gradual decrease in the OER activity. Complementary insight into the catalyst near-surface composition, structure, and chemical state is further extracted using X-ray photoelectron spectroscopy, operando Raman spectroscopy, and operando X-ray absorption spectroscopy together with measurements of Fe uptake by the electrocatalysts using time-resolved inductively coupled plasma mass spectrometry. Notably, we identified that the catalytic deactivation under stationary conditions is linked to the degradation of in situ-created NiFe-LDH. These insights exemplify the complexity of the active state formation and show how its structural and morphological evolution under different applied potentials can be directly linked to the catalyst activation and degradation.

Reliable identification of the complex or superlattice nature of intrinsic and extrinsic stacking faults in the L12 phase by high-resolution imaging

Planar defect-based deformation mechanisms are becoming increasingly important for understanding and tuning the mechanical properties of superalloys. Typically, to elucidate such deformation mechanisms, the type of planar defect is determined by conventional transmission electron microscopy or by high-resolution imaging along 〈110〉 crystallographic directions. However, an unambiguous identification of the complex or non-complex nature of intrinsic and extrinsic stacking faults in the L12 phase may not be possible by analyzing only one projection. To overcome this limitation, we present a straightforward approach to identify the superlattice or complex character of intrinsic and extrinsic faults in the L12 structure in high-resolution scanning transmission electron microscopy by tilting to a different zone axis and examining the shift of superlattice planes. Using this approach, two key aspects of the Kolbe mechanism for the formation of superlattice extrinsic stacking faults are verified for the first time: the presence of a complex intrinsic fault segment at the leading end and the occurrence of re-ordering.

Comparative of machine learning classification strategies for electron energy loss spectroscopy: Support vector machines and artificial neural networks

Machine Learning (ML) strategies applied to Scanning and conventional Transmission Electron Microscopy have become a valuable tool for analyzing the large volumes of data generated by various S/TEM techniques. In this work, we focus on Electron Energy Loss Spectroscopy (EELS) and study two ML techniques for classifying spectra in detail: Support Vector Machines (SVM) and Artificial Neural Networks (ANN). Firstly, we systematically analyze the optimal configurations and architectures for ANN classifiers using random search and the tree-structured Parzen estimator methods. Secondly, a new kernel strategy is introduced for the soft-margin SVMs, the cosine kernel, which offers a significant advantage over the previously studied kernels and other ML classification strategies. This kernel allows us to bypass the normalization of EEL spectra, achieving accurate classification. This result is highly relevant for the EELS community since we also assess the impact of common normalization techniques on our spectra using Uniform Manifold Approximation and Projection (UMAP), revealing a strong bias introduced in the spectra once normalized. In order to evaluate and study both classification strategies, we focus on determining the oxidation state of transition metals through their EEL spectra, examining which feature is more suitable for oxidation state classification: the oxygen K peak or the transition metal white lines. Subsequently, we compare the resistance to energy loss shifts for both classifiers and present a strategy to improve their resistance. The results of this study suggest the use of soft-margin SVMs for simpler EELS classification tasks with a limited number of spectra, as they provide performance comparable to ANNs while requiring lower computational resources and reduced training times. Conversely, ANNs are better suited for handling complex classification problems with extensive training data.