Annular Dark-field Scanning Transmission Electron Microscopy Imaging Research Articles

A combined simulation and experimental study of the equilibrium shapes of η′ and α precipitates in Mn-containing 7xxx Al-alloys

The addition of Mn to 7xxx series Al-alloys helps improve tensile properties owed to the presence of α precipitates (Al(Mn,Fe)Si, simple cubic, 50–200 nm, non-shearable) in addition to the η′ precipitates (Mg2Zn5−xAl2+x, hexagonal, 4–6 nm, shearable) commonly observed in the 7xxx series Al-alloys. The coexistence of multiple α and η′ variants, 24 for α and 4 for η′, coupled with their small size-scale, makes the experimental determination by x-ray diffraction (XRD) and scanning transmission electron microscopy (STEM) challenging. This work formulates a phase-field model to predict precipitate shapes in three-dimension (3D) using experimental characterization as inputs to create virtual precipitate cross-sections for use in morphological comparison with experimental 2D (S)TEM images. Based on the atomic structures and orientation relationships observed in the experiments, the lattice site correspondences between the matrix and the two precipitate phases are derived, which are required for the prediction of shapes of coherent precipitates. Systematic phase-field simulations are then carried out to document the 3D shapes for all possible variants, as well as the corresponding 2D cross-sectional shapes when observed parallel to low-index matrix planes. These 2D cross-sectional shapes are compared with high-angle annular dark-field STEM (HAADF-STEM) images, which demonstrates that the identification of Mn precipitate type is possible by such comparisons. This helps unravel some of the complications encountered when characterizing precipitate microstructures in Mn containing Al-alloys by STEM. Finally, the equilibrium shapes as a function of precipitate size and the effect of interfacial energy anisotropy are investigated.

Material Discrimination in Nanoparticle Hetero‐Aggregates by Analysis of Scanning Transmission Electron Microscopy Images

AbstractHetero‐contacts are interfaces between different materials at the nanoscale leading to novel functional properties. In hetero‐aggregates, primary particles of at least two different materials are mixed at primary particle or cluster level. Double flame spray pyrolysis (DFSP) is a versatile technique for the controlled synthesis of such materials. Characterization of hetero‐aggregates by scanning transmission electron microscopy (STEM) requires acquisition and evaluation of many aggregate images in order to derive statistically significant results. Usually, STEM energy dispersive X‐ray spectroscopy (EDXS) is used to acquire elemental maps providing the material distribution of the primary particles within hetero‐aggregates. However, the acquisition of a single EDXS map takes up to several minutes. For this reason, determination of material types of primary particles from the intensity in high‐angle annular dark field STEM images alone is desirable. These images can be acquired within a couple of seconds. In the present work, a method is suggested which allows for achieving this objective. It can be applied to distinguish materials with a significant difference in their atomic number and hence sufficient material contrast in the STEM images.

Statistical Determination of Atomic-Scale Characteristics of Au Nanocrystals Based on Correlative Multiscale Transmission Electron Microscopy

Abstract Atomic-scale characteristics of individual nanocrystals (NCs), such as the crystallographic orientation of their facets and the kind and density of crystal structure defects, play a tremendous role for the functionality and performance of the whole NC population. However, these features are usually quantified only for a small number of individual particles, and thus with limited statistical relevance. In the present work, we developed the multiscale approach available in transmission electron microscopy (TEM) further, and applied it to describe features of different types of Au NCs in a statistical and scale-bridging manner. This approach combines high-resolution TEM, which is capable of describing the characteristics of NCs on atomic scale, with a semi-automatic analysis of low-magnification high-angle annular dark-field scanning TEM images, which reveals the nanoscopic morphological attributes of NCs with good statistics. The results of these complementary techniques are combined and correlated. The potential of this multiscale approach is illustrated on two examples. In the first one, the habitus of Au NCs was classified and assigned to multiply twinned nanoparticles and nanoplates. These classes were quantified and related to different stacking fault densities. The second example demonstrates the statistical determination of crystallographic orientations and configurations of facets in Au nanorods.

Complementary ADF-STEM: a Flexible Approach to Quantitative 4D-STEM

Scanning transmission electron microscopy (STEM) has a broad range of applications in materials characterization, including real-space imaging, spectroscopy, and diffraction, at length scales from the micron to sub-Ångström. The recent development and adoption of high-speed, direct electron STEM detectors has enabled diffraction patterns to be collected at each probe position, generating four-dimensional STEM (4D-STEM) datasets and opening new imaging modalities. However, the limited pixel numbers in these detectors enforce a tradeoff between angular resolution and maximum collection angle. In this paper, we describe a straightforward method for quantifying 4D-STEM data by utilizing the full flux of the electron beam, including electrons scattered beyond the limits of the detector. This enables significantly increased experimental flexibility, including the synthesis of quantitative, high-contrast complementary annular dark field (cADF) STEM images from low-angle diffraction patterns whilst maintaining high angular resolution; as well as the optimization of electron dose and the more effective use of low dynamic range detectors.

3-Dimensional Self-Ordered Multilayered Ge Nanodots on SiGe

Multilayered Ge nanodots have drawn much attention due to their potential applications in optoelectronics, such as photodetectors and lasers. Many groups studied multilayered Ge nanodots with Si spacers on Si(001) grown by Stranski-Krastanov (SK) growth mode and vertically aligned by local tensile strain induced by buried Ge nanodots (1-2). However, to avoid plastic relaxation caused by a 4.2% lattice mismatch between Si and Ge, thick nanodots and/or large layer numbers are challenging. Additionally, laterally-aligned Ge nanodots without pre-structuring have not been reported. In this study, we demonstrate 3-dimensional (3D) self-ordered Ge nanodots on SiGe virtual substrate (VS) by SiGe/Ge cyclic epitaxial growth and show the effects of fabrication parameters.The 3D self-ordered Ge nanodots were fabricated by reduced-pressure chemical vapor deposition. A Si0.4Ge0.6 VS with step-graded buffer deposited on Si(001) wafer was used. This VS was post-annealed at 1000°C, followed by chemical-mechanical polishing. After HF dip, the substrate was baked at 850°C in H2, then cooled down to 550°C for epitaxial growth. A 52-82 nm thick Si0.48Ge0.52 layer was deposited using a H2-SiH4-GeH4 gas mixture, then a self-assembled Ge nanodots layer via SK growth mechanism was deposited with 7.5-15.0 nm Ge coverage using a H2-GeH4 gas mixture. This Si0.48Ge0.52/Ge deposition cycle was repeated 5 to 20 times to fabricate the 3D self-ordered Ge nanodot stack. Atomic force microscopy (AFM) and scanning electron microscopy (SEM) were used to analyze the morphology and alignment of the Ge nanodots. The facets of the Ge nanodots were studied by analyzing the cross-section cuts of AFM images and confirmed by scanning transmission electron microscopy (STEM). Nano-beam diffraction (NBD) was used to study strain in the superlattice.Fig. 1(a-c) show the AFM images of the 5-cycle superlattices with Ge coverage 7.5 to 15.0 nm. In fig. 1(a), we can see mainly two types of nanodots, diamond (32%) and dome (68%). The height of the diamond-like nanodots is 9 nm with a standard deviation (s) of 2.6 nm while that of the dome-like nanodots is 23 nm with s=1.8 nm. With increasing Ge coverage, dome-like nanodots dominate (fig. 1(b)) and some nanodots merge with the adjacent nanodots (fig. 1(c)). Since the dome-like nanodots show a lower s in height than the diamond-like nanodots do, engineering of self-ordering is more feasible with the dome-like nanodot.Fig. 2(a-b) show the angle view of SEM images of Ge nanodots on 5- and 20-cycle superlattice of 12.5 nm-Ge/52 nm-SiGe. The dome-like nanodots are dominant and laterally aligned. The alignment and the uniformity improve with the increasing cycle number of the superlattice. However, when the thickness of Si0.48Ge0.52 spacer increases, the lateral- and vertical alignment of nanodots become random, and the amount of diamond-like nanodots increases (not shown).To study facets of two types of nanodots, the tilt of each facet was calculated from the cross-section cuts of AFM images. Fig. 3(a) shows an AFM image of the dome-like nanodot. Fig. 3(b) shows the cross-section cuts of fig. 3(a) along <110>. These cross-section cuts are well-overlapped with the high-angle annular dark-field (HAADF) STEM image as shown in the background of fig. 3(b). Therefore, it is possible and reliable to estimate the facets from the cross-section cuts of our AFM images. By this method, we confirmed that the diamond-like nanodot is composed of {105} and the dome-like nanodot is composed of {113} and {159}. This is consistent with a study of Ge dot on Si substrate except for {159} facet (3). Instead of {159} facet, a relatively similar facet {3 15 23} was reported. This difference may result from the less compressive strain in our Ge nanodots because SiGe VS was used.To explain the vertical correlation of Ge nanodots, a HAADF STEM image and in- and out-of-plane strain distributions measured by NBD are shown in fig. 4(a-c). The nanodots are vertically aligned (fig. 4(a)). The SiGe on the nanodot shows a relatively higher lattice parameter along <110> (fig. 4(b)) and lower lattice parameter along <001> (fig. 4(c)) compared to that on Ge wetting layer, indicating tensile strain. This tensile strain area is the preferred position for Ge nanodot formation because of less lateral lattice mismatch. Consequently, the nanodots tend to grow above the buried nanodots.3D self-ordered multilayered Ge nanodots on SiGe VS were successfully fabricated, and the facets and the vertical correlation of Ge nanodots were studied. References P.S. Chen et al. Materials Science and Engineering B 108 (2004) 213-218K.L. Wang et al. Proceeding of the IEEE 95 (2007) 1866J.T. Robinson et al. Nanotechnology 20 (2009) 085708 Figure 1

Real-Time Integration Center of Mass (riCOM) Reconstruction for 4D STEM.

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.

Optimal experiment design for element specific atom counting using multiple annular dark field scanning transmission electron microscopy detectors

This paper investigates the possible benefits for counting atoms of different chemical nature when analysing multiple 2D scanning transmission electron microscopy (STEM) images resulting from independent annular dark field (ADF) detector regimes. To reach this goal, the principles of statistical detection theory are used to quantify the probability of error when determining the number of atoms in atomic columns consisting of multiple types of elements. In order to apply this theory, atom-counting is formulated as a statistical hypothesis test, where each hypothesis corresponds to a specific number of atoms of each atom type in an atomic column. The probability of error, which is limited by the unavoidable presence of electron counting noise, can then be computed from scattering-cross sections extracted from multiple ADF STEM images. Minimisation of the probability of error as a function of the inner and outer angles of a specified number of independent ADF collection regimes results in optimal experimental designs. Based on simulations of spherical Au@Ag and Au@Pt core–shell nanoparticles, we investigate how the combination of two non-overlapping detector regimes helps to improve the probability of error when unscrambling two types of atoms. In particular, the combination of a narrow low angle ADF detector with a detector formed by the remaining annular collection regime is found to be optimal. The benefit is more significant if the atomic number Z difference becomes larger. In addition, we show the benefit of subdividing the detector regime into three collection areas for heterogeneous nanostructures based on a structure consisting of three types of elements, e.g., a mixture of Au, Ag and Al atoms. Finally, these results are compared with the probability of error resulting when one would ultimately use a pixelated 4D STEM detector and how this could help to further reduce the incident electron dose.

High-precision atomic-scale strain mapping of nanoparticles from STEM images

Strain is a crucial factor that influences the physicochemical properties of nanoparticles. Being able to precisely measure strain is important in understanding the intrinsic mechanism of the enhanced performance of nanoparticles. Techniques that have been developed for strain analysis using scanning transmission electron microscopy (STEM) images can be categorized into diffraction-based method and imaging-based method. Here, using image simulation techniques, it is found that the measured two-dimensional (2D) displacements from annular dark field (ADF) STEM images of a nanoparticle are a good approximation to a projection of the actual three-dimensional (3D) displacements. A methodology for deformation analysis is presented which is based on the detection of atomic columns from atomic-resolution STEM images in real space. Elastic deformation parameters such as strain are usually defined on the basis of a continuum of deformation. The appropriateness of various deformation parameters for atomic-scale investigation on STEM images is explored and a method for determining these is presented. We found that the local lattice parameter and principal strain components are the most physically meaningful parameters to express the materials distortion behaviour. Apart from the local lattice parameter, the other deformation parameters such as normal strains, shear strains and displacements, heavily rely on the choice of reference lattice. It is also found that different reference grids add a series of uniform offsets to these strain variations. Finally, this approach is applied to a PtCo3 bimetallic nanoparticle to quantify its deformation behaviour.

Coupled Compositional and Displacive Modulations in KLaMnWO6 Revealed by Atomic Resolution Imaging.

Complex compositional and displacive modulations of the crystal structure of KLaMnWO6 are imaged with atomic resolution by means of scanning transmission electron microscopy (STEM). This oxide is stabilized by cation vacancies leading to a La1+x/3K1-xMnWO6 stoichiometry. Compositional modulation on both the K and La layers are revealed in the high-angle annular dark-field STEM (HAADF-STEM) images. The compositional modulation within the La layer is coupled with the modulation of the octahedral tilting, which is exposed by imaging of the anion sublattice in annular bright-field STEM (ABF-STEM) images. These complex modulations are accommodated in a 5√2ap × 5√2ap × 2ap perovskite-type structure.

In Situ Resolving the Atomic Reconstruction of SnO2 (110) Surface.

Understanding surface reconstruction of nanocrystals is of great importance to their applications, however it is still challenging due to lack of atomic-level structural information under reconstruction conditions. Herein, through in situ spherical aberration corrected scanning transmission electron microscopy (STEM), the reconstruction of nanocrystalline SnO2 (110) surface was studied. By identifying the precise arrangements of surface/subsurface Sn and O columns through both in situ bright-field and high-angle annular dark-field STEM images, an unexpected added Sn2O model was determined for SnO2 (110)-(1 × 2) surface. The protruded Snδ+ of this surface could act as the active sites for activating O2 molecules according to our density functional theory (DFT) calculations. On the basis of in situ observation of atomic-level reconstruction behaviors and DFT calculations, an energy-driven reconstruction process was also revealed. We anticipate this work would help to clarify the long-standing debate regarding the reconstruction of SnO2 (110) surface and its intrinsic property.

Microstructures and Interface Magnetic Moments in Mn2VAl/Fe Layered Films Showing Exchange Bias.

Heusler alloys are a material class exhibiting various magnetic properties, including antiferromagnetism. A typical application of antiferromagnets is exchange bias that is a shift of the magnetization curve observed in a layered structure consisting of antiferromagnetic and ferromagnetic films. In this study, a layered sample consisting of a Heusler alloy, MnVAl and a ferromagnet, Fe, is selected as a material system exhibiting exchange bias. Although the fully ordered MnVAl is known as a ferrimagnet, with an optimum fabrication condition for the MnVAl layer, the MnVAl/Fe layered structure exhibits exchange bias. The appearance of the antiferromagnetic property in the MnVAl is remarkable; however, the details have been unclear. To clarify the microscopic aspects on the crystal structures and magnetic moments around the MnVAl/Fe interface, cross-sectional scanning transmission electron microscope (STEM) observation, and synchrotron soft X-ray magnetic circular dichroism (XMCD) measurements were employed. The high-angle annular dark-field STEM images demonstrated clusters of MnVAl with the L2 phase distributed only around the interface to the Fe layer in the sample showing the exchange bias. Furthermore, antiferromagnetic coupling between the Mn- and Fe-moments were observed in element-specific hysteresis loops measured using the XMCD. The locally ordered L2 phase and antiferromagnetic Mn-moments in the MnVAl were suggested as important factors for the exchange bias.

Enhanced Atomic-Scale Imaging of PGM-Free Catalysts By Low-Voltage Scanning Transmission Electron Microscopy

Platinum group metal (PGM)-free catalysts are promising candidates to supplant costly precious metal catalysts in hydrogen fuel cells and enable low-cost, commercially viable devices [1]. Recent developments in PGM-free catalysts have enabled performance comparable to Pt catalysts by some metrics [2], but durability remains a significant challenge and limits practical application of these devices [3]. To improve the durability of PGM-free catalysts, understanding and controlling atomic-scale active site structure and the corresponding degradation mechanisms is imperative [1]. Active sites in these catalysts are commonly thought to be FeN4 complexes within a graphene lattice. Many potential active site structures have been predicted by computational methods, however, and a technique capable of directly validating these models is needed to reveal the true nature of these sites and enable increased control over degradation [1].Scanning transmission electron microscopy (STEM) is capable of resolving a wide range of materials properties down to the atomic scale, such as structure, composition, and bonding information. The characteristics of PGM-free materials makes obtaining atomic-scale information about active site structure by STEM challenging, however. These materials are often defect-rich, containing a large number of dopants, holes, etc., and a large portion of proposed active sites exist at edges of the material, all of which increase susceptibility to beam damage. Conventional high-angle annular dark-field (HAADF) STEM imaging exacerbates this problem since only a small proportion of the incident beam electrons generate signal, and this signal is most sensitive to heavy elements. A large electron dose is therefore required to obtain a sufficient signal from light elements such as carbon and nitrogen, which can result in beam-induced atomic displacements at susceptible sites when using standard accelerating voltages. As a consequence, direct structural analysis of active sites is often not possible, impeding our understanding of degradation pathways.In this talk, we will demonstrate advancements in STEM techniques that significantly enhance our ability to directly analyze atomic-scale active site structure in PGM-free materials. We utilize a recently developed dose-efficient imaging technique based on four-dimensional (4D)-STEM [4,5] to reduce the required electron dose and simultaneously increase sensitivity to light elements. To minimize beam damage at sensitive active sites, we perform this dose-efficient 4D-STEM technique in a low-voltage aberration-corrected instrument operated at 30 kV, producing an atomic-scale probe below the threshold energy for beam-induced atomic displacements at many sites. We perform these experiments on a model PGM-free catalyst that contains many monolayer regions, which is ideal for low-voltage 4D-STEM and enables experimental validation through simulations of proposed active site structures. This work demonstrates how low-voltage 4D-STEM will provide new atomic-scale insights into the structure and degradation pathways of PGM-free catalyst active sites, accelerating the development of low-cost hydrogen fuel cells.

Atomic-Scale Studies of Overlapping Grain Boundaries between Parallel and Quasi-Parallel Grains in Low-Symmetry Monolayer ReS2

Summary Grain boundaries (GBs) are significant microstructures that dominate properties of polycrystalline two-dimensional (2D) materials. Low-symmetry rhenium disulfide monolayers provide an ideal platform to investigate diverse configurations of GBs and their orientation-dependent characteristics. Here, we utilize the preferential deposition of platinum-based nanoparticles on grain edges to rapidly locate nanoscale-wide overlapping GBs during microscopic-scale observation. Atomic-resolution investigations by aberration-corrected annular dark-field scanning transmission electron microscopy reveal diverse overlapping GBs constructed by parallel grains with transversal displacement. They prefer to align along several primary lattice directions with different interlayer atomic registries. Calculations show that the electronic band structures of overlapping GBs are strongly direction dependent, suggesting their potential in tunable electronic and photonic devices. Incommensurate overlapping GBs formed by quasi-parallel grains with ultrasmall twist angles are also observed. These results unveil the rich polymorphism of GBs and new opportunities to tailor properties of anisotropic 2D materials via GB engineering.

Self-Assembly of Bowlic Supramolecules on Graphene Imaged at the Individual Molecular Level using Heavy Atom Tagging.

The self-assembly of bowlic supramolecules on graphene surface is studied with single molecular sensitivity. This is achieved by incorporating a heavy metal tag in the form of a single W atom into the tip of the molecular structure, which enables the direct imaging of molecular distribution using annular dark-field scanning transmission electron microscopy (ADF-STEM) along with graphene as an electron transparent support. The bowlic molecules have nonplanar geometry, and their orientations with respect to their graphene substrate and with each other result in various packing configurations. Statistical data on intermolecular distances is obtained from numerous measurements of the bright contrast from the single metal atom tags. The analysis shows that the bowlic molecules lie sideways on the graphene surface with favorable head-to-tail stacking, rather than sitting vertically with the bowl facing toward the graphene surface. In thicker film regions, nanoscale lamellar fringes are observed, demonstrating that large-scale aligned packing extends into 3D. Image simulations and various molecular packing schemes are discussed to help interpret the ADF-STEM images and the possible range of molecular interactions occurring. These results aid the understanding of nonplanar supramolecular assemblies on van der Waals surfaces for potential applications in molecular recognition by porous films.

Atom column detection from simultaneously acquired ABF and ADF STEM images

In electron microscopy, the maximum a posteriori (MAP) probability rule has been introduced as a tool to determine the most probable atomic structure from high-resolution annular dark-field (ADF) scanning transmission electron microscopy (STEM) images exhibiting low contrast-to-noise ratio (CNR). Besides ADF imaging, STEM can also be applied in the annular bright-field (ABF) regime. The ABF STEM mode allows to directly visualize light-element atomic columns in the presence of heavy columns. Typically, light-element nanomaterials are sensitive to the electron beam, limiting the incoming electron dose in order to avoid beam damage and leading to images exhibiting low CNR. Therefore, it is of interest to apply the MAP probability rule not only to ADF STEM images, but to ABF STEM images as well. In this work, the methodology of the MAP rule, which combines statistical parameter estimation theory and model-order selection, is extended to be applied to simultaneously acquired ABF and ADF STEM images. For this, an extension of the commonly used parametric models in STEM is proposed. Hereby, the effect of specimen tilt has been taken into account, since small tilts from the crystal zone axis affect, especially, ABF STEM intensities. Using simulations as well as experimental data, it is shown that the proposed methodology can be successfully used to detect light elements in the presence of heavy elements.

Energy-dispersive X-ray spectroscopy for an atomic-scale quantitative analysis of Pd-Pt core-shell nanoparticles.

The properties of core-shell nanoparticles, which are used for many catalytic processes as an alternative to platinum, depend on the size of both the particle and the shell. It is thus necessary to develop a quantitative method to determine the shell thickness. Pd-Pt core-shell particles were analyzed using scanning transmission electron microscopy (STEM) and energy-dispersive X-ray spectroscopy (EDX). Quantitative EDX line profiles acquired from the core-shell particle were compared to four core-shell models. The results indicate that the thickness of the Pt shell corresponds to two atomic layers. Meanwhile, high-angle annular dark-field STEM images from the same particle were analyzed and compared to simulated images. Again, this experiment demonstrates that the shell thickness was of two atomic layers. Our results indicate that, in small particles, it is possible to use EDX for a precise atomic-scale quantitative analysis.

Atomic resolution convergent beam electron diffraction analysis using convolutional neural networks

Two types of convolutional neural network (CNN) models, a discrete classification network and a continuous regression network, were trained to determine local sample thickness from convergent beam diffraction (CBED) patterns of SrTiO3 collected in a scanning transmission electron microscope (STEM) at atomic column resolution. Acquisition of atomic resolution CBED patterns for this purpose requires careful balancing of CBED feature size in pixels, acquisition speed, and detector dynamic range. The training datasets were derived from multislice simulations, which must be convolved with incoherent source broadening. Sample thicknesses were also determined using quantitative high-angle annular dark-field (HAADF) STEM images acquired simultaneously. The regression CNN performed well on sample thinner than 35 nm, with 70% of the CNN results within 1 nm of HAADF thickness, and 1.0 nm overall root mean square error between the two measurements. The classification CNN was trained for a thicknesses up to 100 nm and yielded 66% of CNN results within one classification increment of 2 nm of HAADF thickness. Our approach depends on methods from computer vision including transfer learning and image augmentation.

Atomic Resolution Convergent Beam Electron Diffraction Analysis Using Convolutional Neural Networks

Abstract Two types of convolutional neural network (CNN) models, a discrete classification network and a continuous regression network, were trained to determine local sample thickness from convergent beam diffraction (CBED) patterns of SrTiO3 collected in a scanning transmission electron microscope (STEM) at atomic column resolution. Acquisition of atomic resolution CBED patterns for this purpose requires careful balancing of CBED feature size in pixels, acquisition speed, and detector dynamic range. The training datasets were derived from multislice simulations, which must be convolved with incoherent source broadening. Sample thicknesses were also determined using quantitative high-angle annular dark-field (HAADF) STEM images acquired simultaneously. The regression CNN performed well on sample thinner than 35 nm, with 70% of the CNN results within 1 nm of HAADF thickness, and 1.0 nm overall root mean square error between the two measurements. The classification CNN was trained for a thicknesses up to 100 nm and yielded 66% of CNN results within one classification increment of 2 nm of HAADF thickness. Our approach depends on methods from computer vision including transfer learning and image augmentation.

Displacement fields around Guinier–Preston 1 zones in Al–Cu alloys: investigations using MD and ADF-STEM image simulations

ABSTRACTThe displacements of atoms around Guinier–Preston 1 (GP1) zones in Al–Cu alloys at a temperature of 295 K have been investigated using molecular dynamics (MD) simulations. The magnitude of the displacements at the first Al layer adjacent to a GP1 zone reached 24% strain and this value decreased with distance from the zone to zero at about 40th Al layer. Strain fields near a GP1 zone were evaluated by calculating strain tensors around individual atoms. The obtained strain maps suggested that the equilibrium Cu content in a GP1 zone should be 100%. The atomic configurations determined by MD simulations were utilised for multislice image simulations of annular dark-field scanning transmission electron microscopy (ADF-STEM) to investigate the effect of foil thickness and the depth position of a GP1 zone in a foil on ADF-STEM images. The atomic displacements in ADF-STEM images were smaller than the MD result due to foil thickness and electron channelling.

Microstructure characterization of BaSnO3 thin films on LaAlO3 and PrScO3 substrates from transmission electron microscopy

Detailed microstructure analysis of epitaxial thin films is a vital step towards understanding essential structure-property relationships. Here, a combination of transmission electron microscopy (TEM) techniques is utilized to determine in detail the microstructure of epitaxial La-doped BaSnO3 films grown on two different perovskite substrates: LaAlO3 and PrScO3. These BaSnO3 films are of high current interest due to outstanding electron mobility at ambient. The rotational disorder of low-angle grain boundaries, namely the in-plane twist and out-of-plane tilt, is visualized by conventional TEM under a two-beam condition, and the degree of twists in grains of such films is quantified by selected-area electron diffraction. The investigation of the atomic arrangement near the film-substrate interfaces, using high-resolution annular dark-field scanning TEM imaging, reveals that edge dislocations with a Burgers vector along [001] result in the out-of-plane tilt. It is shown that such TEM-based analyses provide detailed information about the microstructure of the films, which, when combined with complimentary high-resolution X-ray diffraction, yields a complete structural characterization of the films. In particular, stark differences in out-of-plane tilt on the two substrates are shown to result from differences in misfit dislocation densities at the interface, explaining a puzzling observation from X-ray diffraction.