A direct comparison between electron transparent transmission electron microscope (TEM) samples prepared with gallium (Ga) and xenon (Xe) focused ion beams (FIBs) is performed to determine if equivalent quality samples can be prepared with both ion species. We prepared samples using Ga FIB and Xe plasma focused ion beam (PFIB) while altering a variety of different deposition and milling parameters. The samples’ final thicknesses were evaluated using STEM-EELS t/λ data. Using the Ga FIB sample as a standard, we compared the Xe PFIB samples to the standard and to each other. We show that although the Xe PFIB sample preparation technique is quite different from the Ga FIB technique, it is possible to produce high-quality, large area TEM samples with Xe PFIB. We also describe best practices for a Xe PFIB TEM sample preparation workflow to enable consistent success for any thoughtful FIB operator. For Xe PFIB, we show that a decision must be made between the ultimate sample thickness and the size of the electron transparent region.

A wide range of X-ray detectors and geometries are available today on transmission/scanning transmission analytical electron microscopes. While there have been numerous reports of their individual performance, no single experimentally reproducible metric has been proposed as a basis of comparison between the systems. In this paper, we detail modeling, experimental procedures, measurements, and specimens which can be used to provide a manufacturer-independent assessment of the performance of an analytical system. Using these protocols, the geometrical collection efficiency, system peaks, and minimum detection limits can be independently assessed and can be used to determine the best conditions to conduct modern hyperspectral and/or spectrally resolved tomographic analyses for an individual instrument. A simple analytical formula and specimen is presented which after suitable system calibrations can be used to experimentally determine the X-ray detector solid angle.

Energy-filtering transmission electron microscopy (TEM) and bright-field TEM can be used to extract local sample thickness $t$ and to generate two-dimensional sample thickness maps. Electron tomography can be used to accurately verify the local $t$. The relations of log-ratio of zero-loss filtered energy-filtering TEM beam intensity ($I_{{\rm ZLP}}$) and unfiltered beam intensity ($I_{\rm u}$) versus sample thickness $t$ were measured for five values of collection angle in a microscope equipped with an energy filter. Furthermore, log-ratio of the incident (primary) beam intensity ($I_{\rm p}$) and the transmitted beam $I_{{\rm tr}}$ versus $t$ in bright-field TEM was measured utilizing a camera before the energy filter. The measurements were performed on a multilayer sample containing eight materials and thickness $t$ up to 800 nm. Local thickness $t$ was verified by electron tomography. The following results are reported:

• The maximum thickness $t_{{\rm max}}$ yielding a linear relation of log-ratio, $\ln ( {I_{\rm u}}/{I_{{\rm ZLP}}})$ and $\ln ( {I_{\rm p}}/{I_{{\rm tr}}} )$, versus $t$.

• Inelastic mean free path ($\lambda _{{\rm in}}$) for five values of collection angle.

• Total mean free path ($\lambda _{{\rm total}}$) of electrons excluded by an angle-limiting aperture.

• $\lambda _{{\rm in}}$ and $\lambda _{{\rm total}}$ are evaluated for the eight materials with atomic number from $\approx$10 to 79.

The results can be utilized as a guide for upper limit of $t$ evaluation in energy-filtering TEM and bright-field TEM and for optimizing electron tomography experiments.

As a three-dimensional characterization method, atom probe tomography can provide key information that other methods cannot offer. Conductive coatings have proved to be an effective way for biological samples, and nonconductive samples in general, to be analyzed using voltage-pulsed atom probe tomography. In this study, we analyzed the effects of graphene coating on an electrically conductive material and were able to confirm the detection of carbon atoms. We compare quantitative electrostatic field metrics for a single-coated and a multi-coated specimen and measure both a reduced voltage after graphene coating and lowered charge-state ratios for different ion species, suggesting a lowered evaporation field related to the graphene coating. This information will be instructive for future studies on graphene-coated, nonconductive biological specimens.

Weathering of silicate-rich industrial wastes such as slag can reduce emissions from the steelmaking industry. During slag weathering, different minerals spontaneously react with atmospheric CO2 to produce calcite. Here, we evaluate the CO2 uptake during slag weathering using image-based analysis. The analysis was applied to an X-ray computed tomography (XCT) dataset of a slag sample associated with the former Ravenscraig steelworks in Lanarkshire, Scotland. The element distribution of the sample was studied using scanning electron microscopy (SEM), coupled with energy-dispersive spectroscopy (EDS). Two advanced image segmentation methods, namely trainable WEKA segmentation in the Fiji distribution of ImageJ and watershed segmentation in Avizo ® 9.3.0, were used to segment the XCT images into matrix, pore space, calcite, and other precipitates. Both methods yielded similar volume fractions of the segmented classes. However, WEKA segmentation performed better in segmenting smaller pores, while watershed segmentation was superior in overcoming the partial volume effect presented in the XCT data. We estimate that CO2 has been captured in the studied sample with an uptake between 20 and 17 kg CO2/1,000 kg slag for TWS and WS, respectively, through calcite precipitation.

In the present paper, as part of an interdisciplinary research project (Priority Programme SPP2045), we propose a possible way to design an open access archive for particle-discrete tomographic datasets: the PARROT database (https://parrot.tu-freiberg.de). This archive is the result of a pilot study in the field of particle technology and three use cases are presented for illustrative purposes. Instead of providing a detailed instruction manual, we focus on the methodologies of such an archive. The presented use cases stem from our working group and are intended to demonstrate the advantage of using such an archive with concise and consistent data for potential and ongoing studies. Data and metadata merely serve as examples and need to be adapted for disciplines not concerned here. Since all datasets within the PARROT database and its source code are freely accessible, this study represents a starting point for similar projects.

Electron-excited X-ray microanalysis with energy-dispersive spectrometry (EDS) proceeds through the application of the software that extracts characteristic X-ray intensities and performs corrections for the physics of electron and X-ray interactions with matter to achieve quantitative elemental analysis. NIST DTSA-II is an open-access, fully documented, and freely available comprehensive software platform for EDS quantification, measurement optimization, and spectrum simulation. Spectrum simulation with DTSA-II enables the prediction of the EDS spectrum from any target composition for a specified electron dose and for the solid angle and window parameters of the EDS spectrometer. Comparing the absolute intensities for measured and simulated spectra reveals correspondence within ±25% relative to K-shell and L-shell characteristic X-ray peaks in the range of 1–11 keV. The predicted M-shell intensity exceeds the measured value by a factor of 1.4–2.2 in the range 1–3 keV. The X-ray continuum (bremsstrahlung) generally agrees within ±10% over the range of 1–10 keV. Simulated EDS spectra are useful for developing an analytical strategy for challenging problems such as estimating trace detection levels.

A real-time image reconstruction method for scanning transmission electron microscopy (STEM) is proposed. With an algorithm requiring only the center of mass of the diffraction pattern at one probe position at a time, it is able to update the resulting image each time a new probe position is visited without storing any intermediate diffraction patterns. The results show clear features at high spatial frequency, such as atomic column positions. It is also demonstrated that some common post-processing methods, such as band-pass filtering, can be directly integrated in the real-time processing flow. Compared with other reconstruction methods, the proposed method produces high-quality reconstructions with good noise robustness at extremely low memory and computational requirements. An efficient, interactive open source implementation of the concept is further presented, which is compatible with frame-based, as well as event-based camera/file types. This method provides the attractive feature of immediate feedback that microscope operators have become used to, for example, conventional high-angle annular dark field STEM imaging, allowing for rapid decision-making and fine-tuning to obtain the best possible images for beam-sensitive samples at the lowest possible dose.

One of the main capabilities of atom probe tomography (APT) is the ability to not only identify but also characterize early stages of precipitation at length scales that are not achievable by other techniques. One of the most popular methods to identify nanoscale clustering in APT data, based on the density-based spatial clustering of applications with noise (DBSCAN), is used extensively in many branches of research. However, it is common that not all of the steps leading to the selection of certain parameters used in the analysis are reported. Without knowing the rationale behind parameter selection, it may be difficult to compare cluster parameters obtained by different researchers. In this work, a simple open-source tool, PosgenPy, is used to justify cluster search parameter selection via providing a systematic sweep through parameter values with multiple randomizations to minimize a false-positive cluster ratio. The tool is applied to several different microstructures: a simulated material system and two experimental datasets from a low-alloy steel . The analyses show how values for the various parameters can be selected to ensure that the calculated cluster number density and cluster composition are accurate.

Liquid-electron microscopy (EM), the room-temperature correlate to cryo-EM, is a rapidly growing field providing high-resolution insights of macromolecules in solution. Here, we describe how liquid-EM experiments can incorporate automated tools to propel the field to new heights. We demonstrate fresh workflows for specimen preparation, data collection, and computing processes to assess biological structures in liquid. Adeno-associated virus (AAV) and the SARS-CoV-2 nucleocapsid (N) were used as model systems to highlight the technical advances. These complexes were selected based on their major differences in size and natural symmetry. AAV is a highly symmetric, icosahedral assembly with a particle diameter of ~25 nm. At the other end of the spectrum, N protein is an asymmetric monomer or dimer with dimensions of approximately 5–7 nm, depending upon its oligomerization state. Equally important, both AAV and N protein are popular subjects in biomedical research due to their high value in vaccine development and therapeutic efforts against COVID-19. Overall, we demonstrate how automated practices in liquid-EM can be used to decode molecules of interest for human health and disease.

Spatially resolved in situ transmission electron microscopy (TEM), equipped with direct electron detection systems, is a suitable technique to record information about the atom-scale dynamics with millisecond temporal resolution from materials. However, characterizing dynamics or fluxional behavior requires processing short time exposure images which usually have severely degraded signal-to-noise ratios. The poor signal-to-noise associated with high temporal resolution makes it challenging to determine the position and intensity of atomic columns in materials undergoing structural dynamics. To address this challenge, we propose a noise-robust, processing approach based on blob detection, which has been previously established for identifying objects in images in the community of computer vision. In particular, a blob detection algorithm has been tailored to deal with noisy TEM image series from nanoparticle systems. In the presence of high noise content, our blob detection approach is demonstrated to outperform the results of other algorithms, enabling the determination of atomic column position and its intensity with a higher degree of precision.

As the feature size of crystalline materials gets smaller, the ability to correctly interpret geometrical sample information from electron backscatter diffraction (EBSD) data becomes more important. This paper uses the notion of transition curves, associated with line scans across grain boundaries (GBs), to correctly account for the finite size of the excitation volume (EV) in the determination of the geometry of the boundary. Various metrics arising from the EBSD data are compared to determine the best experimental proxy for actual numbers of backscattered electrons that are tracked in a Monte Carlo simulation. Consideration of the resultant curves provides an accurate method of determining GB position (at the sample surface) and indicates a significant potential for error in determining GB position using standard EBSD software. Subsequently, simple criteria for comparing experimental and simulated transition curves are derived. Finally, it is shown that the EV is too shallow for the curves to reveal subsurface geometry of the GB (i.e., GB inclination angle) for most values of GB inclination.

Since it is now possible to record vibrational spectra at nanometer scales in the electron microscope, it is of interest to explore whether extended defects in crystals such as dislocations or grain boundaries will result in measurable changes of the phonon densities of states (dos) that are reflected in the spectra. Phonon densities of states were calculated for a set of high angle grain boundaries in silicon. The boundaries are modeled by supercells with up to 160 atoms, and the vibrational densities of states were calculated by taking the Fourier transform of the velocity–velocity autocorrelation function from molecular dynamics simulations with larger supercells doubled in all three directions. In selected cases, the results were checked on the original supercells by comparison with the densities of states obtained by diagonalizing the dynamical matrix calculated using density functional theory. Near the core of the grain boundary, the height of the optic phonon peak in the dos at 60 meV was suppressed relative to features due to acoustic phonons that are largely unchanged relative to their bulk values. This can be attributed to the variation in the strength of bonds in grain boundary core regions where there is a range of bond lengths.

The occurrence of multi-hit events and the separation distance between multi-hit ion pairs field evaporated from III-nitride semiconductors can potentially provide insights on neighboring chemistry, crystal structure, and field conditions. In this work, we quantify the range of variation in major III-N and III-III ion-pair separation to establish correlations with bulk composition, growth method, and ion-pair chemistry. The analysis of ion-pair separation along the AlGaN/GaN heterostructure system allows for comparison of Ga-N and Ga-Ga ion-pair separation between events evaporated from pure GaN and Al0.3Ga0.7N. From this, we aim to define a relative measure for the bond length of ion pairs within an AlGaN/GaN heterostructure. The distributions of pair separation revealed a distinct bimodal behavior that is unique to Al-N2+ ion pairs, suggesting the occurrence of both co-evaporation and molecular dissociation. Finally, we demonstrated that the two modes of ion-pair events align with the known variation in the surface electric field of the AlGaN(0001) structure. These findings demonstrate the utility of atom probe tomography in studying the crystallographic nature of nitride semiconductors.

This paper exploited an alternative approach to prepare high-quality speckle patterns by uniformly dispersing nano-silica particles onto sample surfaces, helping digital image correlation (DIC) acquire the maximum spatial resolution of local strain up to 92 nm. A case study was carried out by combining this speckle pattern fabrication method with SEM-DIC and electron backscattering diffraction (EBSD). Thus, in situ mapping of local strain with ultra-high spatial resolution and microstructure in commercially pure titanium during plastic deformation could be achieved, which favored revealing the effect of slip transfer on shear strain near grain boundaries. Moreover, the slip systems could be easily identified via the combination of the SEM-DIC and EBSD techniques even though no obvious deformation trace was captured in secondary electron images. Additionally, the complex geometric compatibility factor $( {m}^{\prime}_c)$ relating to geometric compatibility factors (mʹ) and Schmid factors was proposed to predict the shear strain (εxy) at grain boundaries.

A position and energy-sensitive detector has been developed for atom probe tomography (APT) instruments in order to deal with some mass peak overlap issues encountered in APT experiments. Through this new type of detector, quantitative and qualitative improvements could be considered for critical materials with mass peak overlaps, such as nitrogen and silicon in TiSiN systems, or titanium and carbon in cemented carbide materials. This new detector is based on a thin carbon foil positioned on the front panel of a conventional MCP-DLD detector. According to several studies, it has been demonstrated that the impact of ions on thin carbon foils has the effect of generating a number of transmitted and reflected secondary electrons. The number generated mainly depends on both the kinetic energy and the mass of incident particles. Despite the fact that this phenomenon is well known and has been widely discussed for decades, no studies have been performed to date for using it as a means to discriminate particles energy. Therefore, this study introduces the first experiments on a potential new generation of APT detectors that would be able to resolve mass peak overlaps through the energy-sensitivity of thin carbon foils.

A common problem in analytical scanning electron microscopy (SEM) using electron backscatter diffraction (EBSD) is the differentiation of phases with distinct chemistry but the same or very similar crystal structure. X-ray energy dispersive spectroscopy (EDS) is useful to help differentiate these phases of similar crystal structures but different elemental makeups. However, open, automated, and unbiased methods of differentiating phases of similar EBSD responses based on their EDS response are lacking. This paper describes a simple data analytics-based method, using a combination of singular value decomposition and cluster analysis, to merge simultaneously acquired EDS + EBSD information and automatically determine phases from both their crystal and elemental data. I use hexagonal TiB2 ceramic contaminated with multiple crystallographically ambiguous but chemically distinct cubic phases to illustrate the method. Code, in the form of a Python 3 Jupyter Notebook, and the necessary data to replicate the analysis are provided as Supplementary material.