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Increasing interest in three-dimensional nanostructures adds impetus to electron microscopy techniques capable of imaging at or below the nanoscale in three dimensions. We present a reconstruction algorithm that takes as input a focal series of four-dimensional scanning transmission electron microscopy (4D-STEM) data. We apply the approach to a lead iridate, PbIrO, and yttrium-stabilized zirconia, YZrO, heterostructure from data acquired with the specimen in a single plan-view orientation, with the epitaxial layers stacked along the beam direction. We demonstrate that Pb–Ir atomic columns are visible in the uppermost layers of the reconstructed volume. We compare this approach to the alternative techniques of depth sectioning using differential phase contrast scanning transmission electron microscopy (DPC-STEM) and multislice ptychographic reconstruction.

Recent advances in scanning transmission electron microscopy (STEM) have rekindled interest in multi-channel detectors and prompted the exploration of unconventional scan patterns. These emerging needs are not yet addressed by standard commercial hardware. The system described here incorporates a flexible scan generator that enables exploration of low-acceleration scan patterns, while data are recorded by a scalable eight-channel array of nonmultiplexed analog-to-digital converters. System integration with SerialEM provides a flexible route for automated acquisition protocols including tomography. Using a solid-state quadrant detector with additional annular rings, we explore the generation and detection of various STEM contrast modes. Through-focus bright-field scans relate to phase contrast, similarly to wide-field TEM. More strikingly, comparing images acquired from different off-axis detector elements reveals lateral shifts dependent on defocus. Compensation of this parallax effect leads to decomposition of integrated differential phase contrast (iDPC) to separable contributions relating to projected electric potential and to defocus. Thus, a single scan provides both a computationally refocused phase contrast image and a second image in which the signed intensity, bright or dark, represents the degree of defocus.

Although scanning transmission electron microscopy (STEM) images of individual heavy atoms were reported 50 years ago, the applications of atomic-resolution STEM imaging became wide spread only after the practical realization of aberration correctors on field-emission STEM/TEM instruments to form sub-Ångstrom electron probes. The innovative designs and advances of electron optical systems, the fundamental understanding of electron–specimen interaction processes, and the advances in detector technology all played a major role in achieving the goal of atomic-resolution STEM imaging of practical materials. It is clear that tremendous advances in computer technology and electronics, image acquisition and processing algorithms, image simulations, and precision machining synergistically made atomic-resolution STEM imaging routinely accessible. It is anticipated that further hardware/software development is needed to achieve three-dimensional atomic-resolution STEM imaging with single-atom chemical sensitivity, even for electron-beam-sensitive materials. Artificial intelligence, machine learning, and big-data science are expected to significantly enhance the impact of STEM and associated techniques on many research fields such as materials science and engineering, quantum and nanoscale science, physics and chemistry, and biology and medicine. This review focuses on advances of STEM imaging from the invention of the field-emission electron gun to the realization of aberration-corrected and monochromated atomic-resolution STEM and its broad applications.

The recent development of electron-sensitive and pixelated detectors has attracted the use of four-dimensional scanning transmission electron microscopy (4D-STEM). Here, we present a precession electron diffraction-assisted 4D-STEM technique for automated orientation mapping using diffraction spot patterns directly captured by an in-column scintillator-based complementary metal-oxide-semiconductor (CMOS) detector. We compare the results to a conventional approach, which utilizes a fluorescent screen filmed by an external charge charge-coupled device camera. The high-dynamic range and signal-to-noise characteristics of the detector greatly improve the image quality of the diffraction patterns, especially the visibility of diffraction spots at high scattering angles. In the orientation maps reconstructed via the template matching process, the CMOS data yield a significant reduction of false indexing and higher reliability compared to the conventional approach. The angular resolution of misorientation measurement could also be improved by masking reflections close to the direct beam. This is because the orientation sensitive, weak, and small diffraction spots at high scattering angles are more significant. The results show that fine details, such as nanograins, nanotwins, and sub-grain boundaries, can be resolved with a sub-degree angular resolution which is comparable to orientation mapping using Kikuchi diffraction patterns. © 2021 Cambridge University Press. All rights reserved.

Recent work has revived interest in the scattering matrix formulation of electron scattering in transmission electron microscopy as a stepping stone toward atomic-resolution structure determination in the presence of multiple scattering. We discuss ways of visualizing the scattering matrix that make its properties clear. Through a simulation-based case study incorporating shot noise, we shown how regularizing on this continuity enables the scattering matrix to be reconstructed from 4D scanning transmission electron microscopy (STEM) measurements from a single defocus value. Intriguingly, for crystalline samples, this process also yields the sample thickness to nanometer accuracy with no a priori knowledge about the sample structure. The reconstruction quality is gauged by using the reconstructed scattering matrix to simulate STEM images at defocus values different from that of the data from which it was reconstructed.

Manual selection of targets in experimental or diagnostic samples by transmission electron microscopy (TEM), based on single overview and detail micrographs, has been time-consuming and susceptible to bias. Substantial information and throughput gain may now be achieved by the automated acquisition of virtually all structures in a given EM section. Resulting datasets allow the convenient pan-and-zoom examination of tissue ultrastructure with preserved microanatomical orientation. The technique is, however, critically sensitive to artifacts in sample preparation. We, therefore, established a methodology to prepare large-scale digitization samples (LDS) designed to acquire entire sections free of obscuring flaws. For evaluation, we highlight the supreme performance of scanning EM in transmission mode compared with other EM technology. The use of LDS will substantially facilitate access to EM data for a broad range of applications.

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.

Current reconstruction methodologies for atom probe tomography (APT) contain serious geometric artifacts that are difficult to address due to their reliance on empirical factors to generate a reconstructed volume. To overcome this limitation, a reconstruction technique is demonstrated where the analyzed volume is instead defined by the specimen geometry and crystal structure as determined by transmission electron microscopy (TEM) and diffraction acquired before and after APT analysis. APT data are reconstructed using a bottom-up approach, where the post-APT TEM image is used to define the substrate upon which APT detection events are placed. Transmission electron diffraction enables the quantification of the relationship between atomic positions and the evaporated specimen volume. Using an example dataset of ZnMgO:Ga grown epitaxially on c-plane sapphire, a volume is reconstructed that has the correct geometry and atomic spacings in 3D. APT data are thus reconstructed in 3D without using empirical parameters for the reverse projection reconstruction algorithm.

Achieving sub-picometer precision measurements of atomic column positions in high-resolution scanning transmission electron microscope images using nonrigid registration (NRR) and averaging of image series requires careful optimization of experimental conditions and the parameters of the registration algorithm. On experimental data from SrTiO3 [100], sub-pm precision requires alignment of the sample to the zone axis to within 1 mrad tilt and sample drift of less than 1 nm/min. At fixed total electron dose for the series, precision in the fast scan direction improves with shorter pixel dwell time to the limit of our microscope hardware, but the best precision along the slow scan direction occurs at 6 μs/px dwell time. Within the NRR algorithm, the “smoothness factor” that penalizes large estimated shifts is the most important parameter for sub-pm precision, but in general, the precision of NRR images is robust over a wide range of parameters.

Single-particle reconstruction can be used to perform three-dimensional (3D) imaging of homogeneous populations of nano-sized objects, in particular viruses and proteins. Here, it is demonstrated that it can also be used to obtain 3D reconstructions of heterogeneous populations of inorganic nanoparticles. An automated acquisition scheme in a scanning transmission electron microscope is used to collect images of thousands of nanoparticles. Particle images are subsequently semi-automatically clustered in terms of their properties and separate 3D reconstructions are performed from selected particle image clusters. The result is a 3D dataset that is representative of the full population. The study demonstrates a methodology that allows 3D imaging and analysis of inorganic nanoparticles in a fully automated manner that is truly representative of large particle populations.

The use of fast pixelated detectors and direct electron detection technology is revolutionising many aspects of scanning transmission electron microscopy (STEM). The widespread adoption of these new technologies is impeded by the technical challenges associated with them. These include issues related to hardware control, and the acquisition, real-time processing and visualisation, and storage of data from such detectors. We discuss these problems and present software solutions for them, with a view to making the benefits of new detectors in the context of STEM more accessible. Throughout, we provide examples of the application of the technologies presented, using data from a Medipix3 direct electron detector. Most of our software is available under an open source licence, permitting transparency of the implemented algorithms, and allowing the community to freely use and further improve upon them., 16 pages, 7 figures, post revision

Complex material systems in which microstructure and microchemistry are nonuniformly dispersed require three-dimensional (3D) rendering(s) to provide an accurate determination of the physio-chemical nature of the system. Current scanning transmission electron microscope (STEM)-based tomography techniques enable 3D visualization but can be time-consuming, so only select systems or regions are analyzed in this manner. Here, it is presented that through high-efficiency multidimensional STEM acquisition and reconstruction, complex point cloud-like microstructural features can quickly and effectively be reconstructed in 3D. The proposed set of techniques is demonstrated, analyzed, and verified for a high-chromium steel with heterogeneously situated features induced using high-energy neutron bombardment.

From simple averaging to more sophisticated registration and restoration strategies, such as super-resolution (SR), there exist different computational techniques that use a series of images of the same object to generate enhanced images where noise and other distortions have been reduced. In this work, we provide qualitative and quantitative measurements of this enhancement for high-angle annular dark-field scanning transmission electron microscopy imaging. These images are compared in two ways, qualitatively through visual inspection in real and reciprocal space, and quantitatively, through the calculation of objective measurements, such as signal-to-noise ratio and atom column roundness. Results show that these techniques improve the quality of the images. In this paper, we use an SR methodology that allows us to take advantage of the information present in the image frames and to reliably facilitate the analysis of more difficult regions of interest in experimental images, such as surfaces and interfaces. By acquiring a series of cross-sectional experimental images of magnetite (Fe3O4) thin films (111), we have generated interpolated images using averaging and SR, and reconstructed the atomic structure of the very top surface layer that consists of a full monolayer of Fe, with topmost Fe atoms in tetrahedrally coordinated sites.

Scanning transmission electron microscopy (STEM) is widely used for imaging, diffraction, and spectroscopy of materials down to atomic resolution. Recent advances in detector technology and computational methods have enabled many experiments that record a full image of the STEM probe for many probe positions, either in diffraction space or real space. In this paper, we review the use of these four-dimensional STEM experiments for virtual diffraction imaging, phase, orientation and strain mapping, measurements of medium-range order, thickness and tilt of samples, and phase contrast imaging methods, including differential phase contrast, ptychography, and others.

Robust atomic-to-meso-scale chirality is now observed in the one-dimensional form of tellurium. This enables a large and counter-intuitive circular-polarization dependent second harmonic generation response above 0.2 which is not present in two-dimensional tellurium. Orientation variations in 1D tellurium nanowires obtained by four-dimensional scanning transmission electron microscopy (4D-STEM) and their correlation with unconventional non-linear optical properties by second harmonic generation circular dichroism (SHG-CD) uncovers an unexpected circular-polarization dependent SHG response from 1D nanowire bundles – an order-of-magnitude higher than in single-crystal two-dimensional tellurium structures – suggesting the atomic- and meso-scale crystalline structure of the 1D material possesses an inherent chirality not present in its 2D form; and which is strong enough to manifest even in the aggregate non-linear optical (NLO) properties of aggregates.

Surface phonon polaritons (SPhPs) are coupled photon-phonon excitations that emerge at the surfaces of nanostructured materials. Although they strongly influence the optical and thermal behavior of nanomaterials, no technique has been able to reveal the complete three-dimensional (3D) vectorial picture of their electromagnetic density of states. Using a highly monochromated electron beam in a scanning transmission electron microscope, we could visualize varying SPhP signatures from nanoscale MgO cubes as a function of the beam position, energy loss, and tilt angle. The SPhPs' response was described in terms of eigenmodes and used to tomographically reconstruct the phononic surface electromagnetic fields of the object. Such 3D information promises insights in nanoscale physical phenomena and is invaluable to the design and optimization of nanostructures for fascinating new uses.

Layered transition metal dichalcogenides (TMDs) have attracted interest due to their promise for future electronic and optoelectronic technologies. As one approaches the two-dimensional (2D) limit, thickness and local topology can greatly influence the macroscopic properties of a material. To understand the unique behavior of TMDs it is therefore important to identify the number of atomic layers and their stacking in a sample. The goal of this work is to extract the thickness and stacking sequence of TMDs directly by matching experimentally recorded high-angle annular dark-field scanning transmission electron microscope images and convergent-beam electron diffraction (CBED) patterns to quantum mechanical, multislice scattering simulations. Advantageously, CBED approaches do not require a resolved lattice in real space and are capable of neglecting the thickness contribution of amorphous surface layers. Here we demonstrate the crystal thickness can be determined from CBED in exfoliated 1T-TaS2 and 2H-MoS2 to within a single layer for ultrathin ≲9 layers and ±1 atomic layer (or better) in thicker specimens while also revealing information about stacking order—even when the crystal structure is unresolved in real space.

In this work, we compare the results of different Cliff–Lorimer (Cliff & Lorimer 1975) based methods in the case of a quantitative energy dispersive spectrometry investigation of light elements in ternary C–O–Si thin films. To determine the Cliff–Lorimer (C–L) k-factors, we fabricated, by focused ion beam, a standard consisting of a wedge lamella with a truncated tip, composed of two parallel SiO2 and 4H-SiC stripes. In 4H-SiC, it was not possible to obtain reliable k-factors from standard extrapolation methods owing to the strong CK-photon absorption. To overcome this problem, an extrapolation method exploiting the shape of the truncated tip of the lamella is proposed herein. The k-factors thus determined, were then used in an application of the C–L quantification procedure to a defect found at the SiO2/4H-SiC interface in the channel region of a metal-oxide field-effect-transistor device. As in this procedure, the sample thickness is required, a method to determine this quantity from the averaged and normalized scanning transmission electron microscopy intensity is also detailed. Monte Carlo simulations were used to investigate the discrepancy between experimental and theoretical k-factors and to bridge the gap between the k-factor and the Watanabe and Williams ζ-factor methods (Watanabe & Williams, 2006).

The ability to characterize recombination and carrier trapping processes in group-III nitride-based nanowires is vital to further improvements in their overall efficiencies. While advances in scanning transmission electron microscope (STEM)-based cathodoluminescence (CL) have offered some insight into nanowire behavior, inconsistencies in nanowire emission along with CL detector limitations have resulted in the incomplete understanding in nanowire emission processes. Here, two nanowire heterostructures were explored with STEM-CL: a polarization-graded AlGaN nanowire light-emitting diode (LED) with a GaN quantum disk and a polarization-graded AlGaN nanowire with three different InGaN quantum disks. Most nanowires explored in this study did not emit. For the wires that did emit in both structures, they exhibited asymmetrical emission consistent with the polarization-induced electric fields in the barrier regions of the nano-LEDs. In the AlGaN/InGaN sample, two of the quantum disks exhibited no emission potentially due to the three-dimensional landscape of the sample or due to limitations in the CL detection.

Sub-angstrom scanning transmission electron microscopy (STEM) allows quantitative column-by-column analysis of crystalline specimens via annular dark-field images. The intensity of electrons scattered from a particular location in an atomic column depends on the intensity of the electron probe at that location. Electron beam channeling causes oscillations in the STEM probe intensity during specimen propagation, which leads to differences in the beam intensity incident at different depths. Understanding the parameters that control this complex behavior is critical for interpreting experimental STEM results. In this work, theoretical analysis of the STEM probe intensity reveals that intensity oscillations during specimen propagation are regulated by changes in the beam’s angular distribution. Three distinct regimes of channeling behavior are observed: the high-atomic-number (Z) regime, in which atomic scattering leads to significant angular redistribution of the beam; the low-Zregime, in which the probe’s initial angular distribution controls intensity oscillations; and the intermediate-Zregime, in which the behavior is mixed. These contrasting regimes are shown to exist for a wide range of probe parameters. These results provide a new understanding of the occurrence and consequences of channeling phenomena and conditions under which their influence is strengthened or weakened by characteristics of the electron probe and sample.

The morphology, composition, and structure of precipitates in an Al–Si–Mg–Hf alloy after heat treatment at 560°C for 20 h were studied by means of Cs-corrected high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), energy dispersive X-ray spectrometry (EDS), high-resolution transmission electron microscopy (HRTEM), and first-principle calculations. Precipitates with three kinds of morphologies were observed. The rectangular and square precipitates were predominantly (Si2−xAlx)Hf phases, while the nanobelt-like precipitate is the Si2Hf phase. First-principle calculations were used to show that the Si6 and Si8 sites were the most favorable sites for Al incorporation in the orthorhombic Si2Hf phase.

Essentially all biological processes are highly dependent on the nanoscale architecture of the cellular components where these processes take place. Statistical measures, such as the autocorrelation function (ACF) of the three-dimensional (3D) mass–density distribution, are widely used to characterize cellular nanostructure. However, conventional methods of reconstruction of the deterministic 3D mass–density distribution, from which these statistical measures can be calculated, have been inadequate for thick biological structures, such as whole cells, due to the conflict between the need for nanoscale resolution and its inverse relationship with thickness after conventional tomographic reconstruction. To tackle the problem, we have developed a robust method to calculate the ACF of the 3D mass–density distribution without tomography. Assuming the biological mass distribution is isotropic, our method allows for accurate statistical characterization of the 3D mass–density distribution by ACF with two data sets: a single projection image by scanning transmission electron microscopy and a thickness map by atomic force microscopy. Here we present validation of the ACF reconstruction algorithm, as well as its application to calculate the statistics of the 3D distribution of mass–density in a region containing the nucleus of an entire mammalian cell. This method may provide important insights into architectural changes that accompany cellular processes.