STEM Imaging Research Articles

Scanning transmission electron tomography to study virus assembly: Review for the retirement of Paul Walther.

In this short and popular review, we summarise some of our findings analysing the replication cycles of large DNA viruses using scanning transmission electron tomography (STEM tomography) that we applied in the laboratory of Paul Walther. It is also a tribute to a very kind and expert scientist, who recently retired. Transmission electron microscopy (TEM), in particular cryo-EM, has benefited tremendously from recent developments in instrumentation. However, TEM imaging remains limited by the thickness of the specimen and classical thin-section TEM typically generates 2D representations of 3D volumes. Although TEM tomography can partly overcome this limitation, the thickness of the sample, the volume that can be analysed in 3D, remains limiting. STEM tomography can partly overcome this problem, as it allows for the analysis of thicker samples, up to 1 µm in thickness. As such, it is an interesting imaging technique to analyse large DNA viruses, some of which measure 1 µm or more, and which is the focus of our research interest.

Deep machine learning for STEM image analysis

The universal, user-friendly online iOk Platform for automatic recognition of any type of objects in images based on deep machine learning is presented. Services aggregated in the iOk Platform significantly reduce the time spent on quantitative image analysis, decrease the influence of the subjective factor and increase the accuracy of the analysis by expanding the set of data that can be analyzed automatically. It is shown how the services can be used to analyze scanning transmission electron microscopy images obtained in heterogeneous catalysis studies, allowing for measurements of thousands of objects in an image, as well as simultaneous analysis of objects of different types, namely: nanoparticles and single sites.

Low Thermal Resistance of Diamond‐AlGaN Interfaces Achieved Using Carbide Interlayers

AbstractThis study investigates thermal transport across nanocrystalline diamond/AlGaN (aluminum gallium nitride) interfaces, crucial for enhancing thermal management in AlGaN‐based electronic devices. Chemical vapor deposition growth of diamond directly on AlGaN resulted in a disordered interface with a high thermal boundary resistance (TBR) of 20.6 m2‐KGW−1. Sputtered carbide interlayers of boron carbide (B4C), silicon carbide (SiC), and a mixture of boron carbide and silicon carbide (B4C/SiC) are employed to reduce thermal boundary resistance in diamond/AlGaN interfaces. The carbide interlayers resulted in record‐low thermal boundary resistance values of 3.4 and 3.7 m2‐KGW−1 for Al0.65Ga0.35N samples with B4C and SiC interlayers, respectively. STEM imaging of the interface reveals interlayer thicknesses between 1.7 and 2.5 nm, with an amorphous structure. Additionally, Fast‐Fourier Transform (FFT) characterization of sections of the STEM images displayed sharp crystalline fringes in the AlGaN layer, confirming it is properly protected from damage from hydrogen plasma during the diamond growth. In order to accurately measure the thermal boundary resistance we develop a hybrid technique, combining time‐domain thermoreflectance and steady‐state thermoreflectance fitting, offering superior sensitivity to buried thermal resistances. The findings underscore the efficacy of interlayer engineering in enhancing thermal transport and demonstrate the importance of innovative measurement techniques in accurately characterizing complex thermal interfaces. This study provides a foundation for future research in improving thermal properties of semiconductor devices through interface engineering and advanced measurement methodologies.

The impact of a customized aesthetic prosthetic leg cover on social interaction cues and attitudes in the general UK population: Two experimental studies.

To explore the impact of an aesthetic prosthetic leg cover on attitudes toward individuals with lower-limb amputation and associated social interaction cues among the general UK population. Two novel experimental methodologies. In study 1, participants (n = 188) viewed 1 of 3 images of an individual: (1) wearing a traditional stem prosthetic, (2) wearing an aesthetic leg cover, or (3) as a nonamputee. They then completed an attitude scale and rated the personality of the individual using the 10-item Big Five Inventory. Study 2 (n = 31) used eye tracking and facial expression software to explore gaze and facial arousal when viewing 1 of 9 manipulated videos of the same individual talking about 3 different scenarios. In study 1, the aesthetic leg cover led to significantly higher ratings of agreeableness than stem and nonamputee images and significantly higher ratings of extraversion than the nonamputee image. Attitudes toward an individual with a prosthesis did not significantly differ depending on which image they viewed and were generally positive. In study 2, all participants focused mainly on the individual's face regardless of scenario topic or leg condition, although participants focused more around the leg cover in more active contexts. Customized aesthetic leg covers may help individuals living with amputation to be perceived more positively in social situations. These experimental methodologies could be extended to explore the differential impact of context, functionality, and activity of specific types of customized aesthetic prosthetics and could help inform shared decision-making processes in clinical settings.

Antimicrobial activity of Zn-nanoparticles synthesized by leaf extract of Capparis spinosa

In the last 2 decades, nanotechnology has developed significantly. It is now easy to perform materials reduction to a nano size called nanoparticles (NPs). One significant development is the use of plant extracts containing phytochemical compounds as reducing agent. Capparis spinosa, a shrub plant, was used in the synthesis of zinc oxide and iron oxide NPs. Synthesis and characterization of ZnONPs by consumed phytochemical compounds of C.spinosa leaf extract was performed. Synthesize ZnONPs from the aqueous leaf extract and characterize them using FT-IR, DLS and STEM and investigate the antimicrobial activity of NPs using agar well diffusion and the minimum inhibitory concentration (MIC). The aqueous leaf extract of C.spinosa contain flavonoids, alkaloids, tannin, phenol and saponin. FT-IR analysis showed peaks in C spinosa extract and ZnONPs spectra where different functional groups with unique peaks for ZnONPs were detected indicating the formation of specific bonds. DLS spectroscopy revealed polydispersity index (PDI) values of 0.638 for ZnONPs and STEM images for ZnONPs showed irregular NPs with sizes ranging from 33.75 to 89.14 nm. Antimicrobial test by agar well diffusion showed an inhibition zone of ZnONPs against all test microbial genera except C. glabrata and higher effect was against P.vulgaris with diameter of inhibition zone equal to 15.5± 0.7 mm. The MIC values of ZnONPs against P.vulgaris and C.Kruesi were the same (0.25mg/ml) while S.aureus, S.pyogens and C.glabrata showed less MIC value (0.125mg/ml). In conclusion, green synthesized ZnONPs showed an antimicrobial effect on skin associated microbial which can be adopted and developed with the aim of using it as an alternative to completely chemically synthesized antibiotics.

Scalable Solid-State Synthesis of Carbon-Supported Ir Electrocatalysts for Acidic Oxygen Evolution Reaction: Exploring the Structure-Activity Relationship.

Enhancing iridium (Ir)-based electrocatalysts to achieve high activity and robust durability for the oxygen evolution reaction (OER) in acidic environments has been an ongoing mission in the commercialization of proton exchange membrane (PEM) electrolyzers. In this study, we present the synthesis of carbon-supported Ir nanoparticles (NPs) using a modified impregnation method followed by solid-state reduction, with Ir loadings of 20 and 40 wt % on carbon. Among the catalysts, the sample with an Ir loading of 20 wt % synthesized at 1000 °C with a heating rate of 300 °C/h demonstrated the highest mass-normalized OER performance of 1209 A gIr-1 and an OER current retention of 80% after 1000 cycles of cyclic voltammetry (CV). High-resolution STEM images confirmed the uniform dispersion of NPs, with diameters of 1.6 ± 0.4 nm across the support. XPS analysis revealed that the C-O and C═O peaks shifted slightly toward higher binding energies for the best-performing catalyst. In comparison, the metallic Ir state shifted toward lower binding energies compared to other samples. This suggests electron transfer from the carbon support to the Ir NPs, indicating a potential interaction between the catalyst and the support. This work underscores the strong potential of the solid-state method for the scalable synthesis of supported Ir catalysts.

Quantification of the hetero-contact formation process for a CuO/CeO2 hetero-aggregate model system prepared by double flame spray pyrolysis

In hetero-aggregates, different materials form sintered hetero-contacts, which lead to new material properties. In this study, the influence of process parameters on the formation of hetero-contacts in Double Flame Spray Pyrolysis (DFSP) was quantified. The mixing of jets was monitored by Particle Image Velocimetry (PIV) measurements as well as by thermocouples and compared to the single flame setting. Overlap of the jets was evaluated using tracers to visualize the mixing zone. Ten CuO/CeO2 model material samples were prepared with different flame inclination angles, nozzle distances and different particle volume fractions. Mixing on hetero-aggregate level was quantified using Convolutional Neural Network (CNN) evaluations of STEM images, Temperature-Programmed Reduction (TPR) and Differential Centrifugal Sedimentation (DCS) disk centrifugation to determine cluster sizes and hetero-coordination numbers as mixing quantifiers. Here, good correlations between the differently measured quantifiers were observed.

On the temporal transfer function in STEM imaging from finite detector response time

Faster scanning in scanning transmission electron microscopy has long been desired for the ability to better control dose, minimise effects of environmental distortions, and to capture the dynamics of in-situ experiments. Advances in scan controllers and scan deflection systems have enabled scanning with pixel dwell times on the order of tens of nanoseconds. At these speeds, the finite response time of the electron detector must be considered as the signal from one electron detection event can contribute to multiple pixels, blurring the features within the image. Here we introduce a temporal transfer function (TTF) to describe and model the effects of detector response time on imaging, as well as a framework for incorporating these effects into simulation.

Atomic resolution scanning transmission electron microscopy at liquid helium temperatures for quantum materials

Fundamental quantum phenomena in condensed matter, ranging from correlated electron systems to quantum information processors, manifest their emergent characteristics and behaviors predominantly at low temperatures. This necessitates the use of liquid helium (LHe) cooling for experimental observation. Atomic resolution scanning transmission electron microscopy combined with LHe cooling (cryo-STEM) provides a powerful characterization technique to probe local atomic structural modulations and their coupling with charge, spin and orbital degrees-of-freedom in quantum materials. However, achieving atomic resolution in cryo-STEM is exceptionally challenging, primarily due to sample drifts arising from temperature changes and noises associated with LHe bubbling, turbulent gas flow, etc. In this work, we demonstrate atomic resolution cryo-STEM imaging at LHe temperatures using a commercial side-entry LHe cooling holder. Firstly, we examine STEM imaging performance as a function of He gas flow rate, identifying two primary noise sources: He-gas pulsing and He-gas bubbling. Secondly, we propose two strategies to achieve low noise conditions for atomic resolution STEM imaging: either by temporarily suppressing He gas flow rate using the needle valve or by acquiring images during the natural warming process. Lastly, we show the applications of image acquisition methods and image processing techniques in investigating structural phase transitions in Cr2Ge2Te6, CuIr2S4, and CrCl3. Our findings represent an advance in the field of atomic resolution electron microscopy imaging for quantum materials and devices at LHe temperatures, which can be applied to other commercial side-entry LHe cooling TEM holders.

Characterization of extended defects in 2D materials using aperture-based dark-field STEM in SEM

Quantitative diffraction contrast analysis with defined diffraction vectors is a well-established method in TEM for studying defects in crystalline materials. A comparable transmission technique is however not available in the more widely used SEM platforms. In this work, we transfer the aperture-based dark-field imaging method from the TEM to the SEM, thus enabling quantitative diffraction contrast studies at lower voltages in SEM. This is achieved in STEM mode by inserting a custom-made aperture between the sample and the STEM detector and centering the hole on a desired reflection. To select individual reflections for dark-field imaging, we use our Low Energy Nanodiffraction (LEND) setup [Schweizer et al., Ultramicroscopy 213, 112956 (2020)], which captures transmission diffraction patterns from a fluorescent screen positioned below the sample. The aperture-based dark-field STEM method is particularly useful for studying extended defects in 2D materials, where (i) stronger diffraction at the lower voltages used in SEM is advantageous, but (ii) two-beam conditions cannot be established, making quantitative diffraction contrast analysis with standard bright-field and annular dark-field detectors impossible. We demonstrate the method by studying basal plane dislocations in bilayer graphene, which have attracted considerable research interest due to their exceptional structural and electronic properties. Direct comparison of results obtained on identical dislocations by the established TEM method and by the new aperture-based dark-field STEM method in SEM shows that a reliable Burgers vector analysis is possible by applying the well-known g·b=0 invisibility criterion. We further use the LEND setup to acquire 4D-STEM data and show that the virtual dark-field images match well with those in aperture-based dark-field STEM images for reliable Burgers vector analysis.

In Situ transmission Electron Microscope Observation of Biased-Induced Dynamic Evolution of Two-Dimensional CrS2

Two-Dimensional transition-metal dichalcogenides (2D-TMDs) have attracted great attention recently owing to their potential to become the important material for next generation semiconductor devices. While using the device, it needs to ensure high density current and biased voltage for a long time. However, the study on TMDs in high-energy environment is insufficient. In this work, the phase evolution of CrS2 are revealed via in-situ biasing experiments and recorded by transmission electron microscope (TEM) at atomic scale. The ultra-thin layered (~1.6nm) CrS2 was synthesized through atmospheric pressure chemical vapor deposition (APCVD), followed by transferring the as-grown samples onto specialized TEM electrical chips. The TEM characterization of CrS2 initial sample provided the basic understanding of this Cr-based TMD, identified as pure 1T phase with single crystal structure as shown in Figure 1. The advanced in situ technique was employed to record the structural evolution and was tested the endurance of CrS2 during biasing. Moreover, the results can make significant contributions to future semiconductor device designs and demonstrate CrS2 has great potential as a semiconductor device with its outstanding characteristic of biased-endurance. Figure1. (a) Low-magnification TEM image of 1T-CrS2. (b) High-resolution TEM image of 1T-CrS2, corresponding with FFT along [001] zone axis. (c) AFM image of the as-grown CrS2 sample, blue bar in the image is X axis of (d). (d) AFM height profile of as-grown 1T-CrS2 with average thickness of~1.6nm. (e) STEM image of 1T-CrS2 and shows d-spacing~0.336 nm. (f) Low-magnification TEM image of the device, showing that the transferred CrS2 layer was suspended on the membrane with Au electrodes on both sides. (g,h) In-situ TEM observation of the biasing experiment after 5V biasing for 5 min of 1T-CrS2. Time-sequencing TEM images showing the structural evolution of biasing. The inset shows the corresponding FFT-DP to reveal the variation of crystallinity of the sample. (g) Initial structure of 1T-CrS2. (h) 1T-CrS2 under in-situ biasing experiment after 10 minutes. Figure 1

Atomic Structure and Chemistry of High-Entropy Oxide Grain Boundaries revealed by STEM Imaging, Strain Mapping, and Spectroscopy

Atomic Structure and Chemistry of High-Entropy Oxide Grain Boundaries revealed by STEM Imaging, Strain Mapping, and Spectroscopy

Multi-Dimensional Characterization of Nanostructures in Titanium Alloys using 2D Aberration-Corrected STEM and 3D Atom Probe Tomography

Multi-Dimensional Characterization of Nanostructures in Titanium Alloys using 2D Aberration-Corrected STEM and 3D Atom Probe Tomography

Exploring Optimal Imaging Conditions for STEM Tomography on Biological Samples Using Integrated Differential Phase Contrast Imaging Method

Exploring Optimal Imaging Conditions for STEM Tomography on Biological Samples Using Integrated Differential Phase Contrast Imaging Method

Real-time Denoising Algorithm for STEM Imaging Using Markov Random Field Model

Real-time Denoising Algorithm for STEM Imaging Using Markov Random Field Model

High Spatiotemporal Resolution STEM Imaging at High Temperature

High Spatiotemporal Resolution STEM Imaging at High Temperature

Automated Defect Detection in Atomic Resolution STEM Images: A Machine Learning Approach with Variational Convolutional Autoencoders

Automated Defect Detection in Atomic Resolution STEM Images: A Machine Learning Approach with Variational Convolutional Autoencoders

High-resolution STEM Image Acquisition Method for Tilted Specimen Using a New Type of Aberration Corrector

High-resolution STEM Image Acquisition Method for Tilted Specimen Using a New Type of Aberration Corrector

Improved STEM Imaging Using Deep Learning Based Compressed Sensing

Improved STEM Imaging Using Deep Learning Based Compressed Sensing

Critical microstructural modifications of Cu/Zn/Al2O3 catalyst during CO2 hydrogenation to methanol

This contribution reports the impact of the reaction pressure (1, 10, 20 and 30 bar) on the deactivation of the commercial catalyst Cu/ZnO/Al2O3 during the CO2 hydrogenation to CH3OH. The best performance was obtained at 30 bar with ≈ 30 % of initial CO2 conversion (XCO2) and CH3OH space-time-yield (STYMEOH) of 255 mgMeOH/gcat.h. Although the initial conversion decreased drastically the activity was kept along all the reaction time, ≈ 5 %. The analysis of fresh and post-reaction samples using X-ray Diffraction (XRD), Thermogravimetric Analysis (TGA), Electron Microscopy (SEM-FEG, STEM, HRTEM), and Raman Spectroscopy demonstrated profound microstructural changes, characterized by phase sintering, formation of Cu-aluminate, segregation of phases, an imbalance among Cu-species, as well as the presence of coke. As the catalyst Cu/ZnO/Al2O3 has a particular microstructure, these modifications provoked the loss of the geometric configuration of the active sites, which might also originate a disturbance in the electronic interactions, resulting in activity loss. HRTEM and STEM image (dark field) of the passivated sample showed the presence of crystalline nanostructures (d < 4 nm) attributed to Cu0, surrounded by amorphous phases. STEM images of spent samples also reveals the development of hierarchical and elongated nanostructures spread on all the spent catalysts. This result foresees the co-existence of small nanoparticles (< 5 nm) with large ones in all the catalyst surface, corroborating XRD results. It is noteworthy that the hydrothermal environmental developed inside the reactor originated from the high pressure and the continuous H2O production, both which may favor the phase sintering and aluminate formation.