ADF STEM Research Articles

Element specific atom counting for heterogeneous nanostructures: Combining multiple ADF STEM images for simultaneous thickness and composition determination

In this paper, a methodology is presented to count the number of atoms in heterogeneous nanoparticles based on the combination of multiple annular dark field scanning transmission electron microscopy (ADF STEM) images. The different non-overlapping annular detector collection regions are selected based on the principles of optimal statistical experiment design for the atom-counting problem. To count the number of atoms, the total intensities of scattered electrons for each atomic column, the so-called scattering cross-sections, are simultaneously compared with simulated library values for the different detector regions by minimising the squared differences. The performance of the method is evaluated for simulated Ni@Pt and Au@Ag core–shell nanoparticles. Our approach turns out to be a dose efficient alternative for the investigation of beam-sensitive heterogeneous materials as compared to the combination of ADF STEM and energy dispersive X-ray spectroscopy.

Atom counting from a combination of two ADF STEM images

To understand the structure–property relationship of nanostructures, reliably quantifying parameters, such as the number of atoms along the projection direction, is important. Advanced statistical methodologies have made it possible to count the number of atoms for monotype crystalline nanoparticles from a single ADF STEM image. Recent developments enable one to simultaneously acquire multiple ADF STEM images. Here, we present an extended statistics-based method for atom counting from a combination of multiple statistically independent ADF STEM images reconstructed from non-overlapping annular detector collection regions which improves the accuracy and allows one to retrieve precise atom-counts, especially for images acquired with low electron doses and multiple element structures.

Multislice Electron Tomography Using Four-Dimensional Scanning Transmission Electron Microscopy

Electron tomography offers useful three-dimensional (3D) structural information, which cannot be observed by two-dimensional imaging. By combining annular dark-field scanning transmission electron microscopy (ADF STEM) with aberration correction, the resolution of electron tomography has reached atomic resolution. However, tomography based on ADF STEM inherently suffers from several issues, including a high electron-dose requirement, poor contrast for light elements, and artifacts from image-contrast nonlinearity. Here, we develop an alternative method called multislice electron tomography (MSET) based on four-dimensional STEM tilt series. Our simulations show that multislice-based 3D reconstruction can effectively reduce undesirable reconstruction artifacts from the nonlinear contrast, allowing precise determination of atomic structures with improved sensitivity for low-Z elements, at considerably low electron-dose conditions. We expect that the MSET method can be applied to a wide variety of materials, including radiation-sensitive samples and materials containing light elements whose 3D atomic structures have never been fully elucidated due to electron-dose limitations or nonlinear imaging contrast.

Three Approaches for Representing the Statistical Uncertainty on Atom-Counting Results in Quantitative ADF STEM.

A decade ago, a statistics-based method was introduced to count the number of atoms from annular dark-field scanning transmission electron microscopy (ADF STEM) images. In the past years, this method was successfully applied to nanocrystals of arbitrary shape, size, and composition (and its high accuracy and precision has been demonstrated). However, the counting results obtained from this statistical framework are so far presented without a visualization of the actual uncertainty about this estimate. In this paper, we present three approaches that can be used to represent counting results together with their statistical error, and discuss which approach is most suited for further use based on simulations and an experimental ADF STEM image.

Interaction of ytterbium pyrosilicate environmental-barrier-coating ceramics with molten calcia-magnesia-aluminosilicate glass: Part II, Interfaces

Interfaces in as-processed β-Yb2Si2O7 environmental barrier coating (EBC) ceramics, and those after high-temperature (1500 °C) interaction with a calcia-magnesia-aluminosilicate (CMAS) glass from Part I are studied in further detail using high-resolution transmission electron microscopy (HRTEM), annular dark field scanning TEM (ADF STEM) and high-angle ADF (HAADF) STEM. Disconnections are detected, or inferred, at twin and general grain-boundaries and also at phase boundaries. Grain-boundary and facet planes are found to be aligned parallel to {110} planes of β-Yb2Si2O7. When detected, step planes are also found to be aligned parallel to β-Yb2Si2O7 {110} planes. At the same time, the dislocation component has major projections aligned parallel to {110} planes of β-Yb2Si2O7. As such, both the step and the dislocation components of the disconnections are anisotropic. The tendency of the grain-boundary and facet planes at interfaces in the system to align parallel to β-Yb2Si2O7{110} planes, both before and after CMAS-interaction, is discussed. The chemistry of grain-boundaries in the vicinity of the disconnections is found to be non-stoichiometric, but this by itself cannot account for the extended contrast variations along twin boundaries. Thus, contrast variations along grain boundaries are associated mainly with the presence of disconnections and associated strain, as well as long-range distortions in the unit cells in twin boundaries. These anisotropic disconnections are associated with the mechanisms of grain-boundary and phase-boundary migration, and thus, they have implications on the evolution of microstructures in this system. Combined insights from Part I and this Part II elucidate the nature of the interfaces in β-Yb2Si2O7 EBC ceramic and the mechanisms of CMAS glass penetration.

3D Atomic Structure of Supported Metallic Nanoparticles Estimated from 2D ADF STEM Images: A Combination of Atom-Counting and a Local Minima Search Algorithm.

Determining the 3D atomic structure of nanoparticles (NPs) is critical to understand their structure-dependent properties. It is hereby important to perform such analyses under conditions relevant for the envisioned application. Here, the 3D structure of supported Au NPs at high temperature, which is of importance to understand their behavior during catalytic reactions, is investigated. To overcome limitations related to conventional high-resolution electron tomography at high temperature, 3D characterization of NPs with atomic resolution has been performed by applying atom-counting using atomic resolution annular dark-field scanning transmission electron microscopy (ADF STEM) images followed by structural relaxation. However, at high temperatures, thermal displacements, which affect the ADF STEM intensities, should be taken into account. Moreover, it is very likely that the structure of an NP investigated at elevated temperature deviates from a ground state configuration, which is difficult to determine using purely computational energy minimization approaches. In this paper, an optimized approach is therefore proposed using an iterative local minima search algorithm followed by molecular dynamics structural relaxation of candidate structures associated with each local minimum. In this manner, it becomes possible to investigate the 3D atomic structure of supported NPs, which may deviate from their ground stateconfiguration.

Modelling ADF STEM images using elliptical Gaussian peaks and its effects on the quantification of structure parameters in the presence of sample tilt

A small sample tilt away from a main zone axis orientation results in an elongation of the atomic columns in ADF STEM images. An often posed research question is therefore whether the ADF STEM image intensities of tilted nanomaterials should be quantified using a parametric imaging model consisting of elliptical rather than the currently used symmetrical peaks. To this purpose, simulated ADF STEM images corresponding to different amounts of sample tilt are studied using a parametric imaging model that consists of superimposed 2D elliptical Gaussian peaks on the one hand and symmetrical Gaussian peaks on the other hand. We investigate the quantification of structural parameters such as atomic column positions and scattering cross sections using both parametric imaging models. In this manner, we quantitatively study what can be gained from this elliptical model for quantitative ADF STEM, despite the increased parameter space and computational effort. Although a qualitative improvement can be achieved, no significant quantitative improvement in the estimated structure parameters is achieved by the elliptical model as compared to the symmetrical model. The decrease in scattering cross sections with increasing sample tilt is even identical for both types of parametric imaging models. This impedes direct comparison with zone axis image simulations. Nonetheless, we demonstrate how reliable atom-counting can still be achieved in the presence of small sample tilt.

Atomic-Resolution Topographic Imaging of Crystal Surfaces

The surface of metal oxides is of technological importance and is extensively used as a substrate for various electronic and chemical applications. A real surface, however, is not a perfectly well-defined and clean surface, but rather contains a diverse class of atomistic defects. Here, we show the direct determination of the 3D surface atomic structure of SrTiO3 (001) including termination layers and atomistic defects such as vacancies, adatoms, ledges, kinks, and their complex combinations, by using depth sectioning of atomic-resolution annular dark-field scanning transmission electron microscopy (ADF STEM). To overcome the poor depth resolution in STEM, we statistically analyze the column by column depth profiles of ADF STEM images with a Bayesian framework fitting algorithm, and we achieve depth resolution at the entrance surface of ±0.9 Å for 1518 individual atomic columns. The present atomic-resolution 3D electron microscopy at the surface will provide fertile ground especially in surface science.

Hidden Markov model for atom-counting from sequential ADF STEM images: Methodology, possibilities and limitations

We present a quantitative method which allows us to reliably measure dynamic changes in the atomic structure of monatomic crystalline nanomaterials from a time series of atomic resolution annular dark field scanning transmission electron microscopy images. The approach is based on the so-called hidden Markov model and estimates the number of atoms in each atomic column of the nanomaterial in each frame of the time series. We discuss the origin of the improved performance for time series atom-counting as compared to the current state-of-the-art atom-counting procedures, and show that the so-called transition probabilities that describe the probability for an atomic column to lose or gain one or more atoms from frame to frame are particularly important. Using these transition probabilities, we show that the method can also be used to estimate the probability and cross section related to structural changes. Furthermore, we explore the possibilities for applying the method to time series recorded under variable environmental conditions. The method is shown to be promising for a reliable quantitative analysis of dynamic processes such as surface diffusion, adatom dynamics, beam effects, or in situ experiments.

Multislice image simulations of sheared needle-like precipitates in an Al-Mg-Si alloy.

The image contrast of sheared needle-like precipitates in the Al-Mg-Si alloy system is investigated with respect to shear-plane positions, the number of shear-planes, and the active matrix slip systems through multislice transmission electron microscopy image simulations and the frozen phonon approximation. It is found that annular dark field scanning transmission electron microscopy (ADF STEM) images are mostly affected by shear-planes within a distance ∼6-18 unit cells from the specimen surface, whereas about 5-10 equidistant shear-planes are required to produce clear differences in HRTEM images. The contrast of the images is affected by the Burgers vector of the slip, but not the slip plane. The simulation results are discussed and compared to experimental data. LAY DESCRIPTION: Pure aluminium is too soft to be viable in most structural applications, but this may be remedied by alloying the metal with various elements. Adding small amounts of silicon and magnesium to pure aluminium allows small particles to precipitate during heat treatment. These precipitates resist plastic deformation and can increase the strength of the alloy and make it viable for a range of industrial applications, such as automotive door panels and load-bearing profiles. However, if subjected to large loads, the precipitates are sheared and the strength of the alloy changes dynamically. Designing safe products such as cars or buildings require physically based predictions on this dynamical change. Developing models that can provide such predictions depend in turn on experimental observations of the shearing process. Because the precipitates are nm long, experimental observations must be done by transmission electron microscopy. However, understanding these results sometimes require computer simulations of atomic models. In this work, we have performed image simulations of various models of sheared precipitates and compared the results with earlier experiments. The simulations indicate that certain conditions must be met for the sheared precipitates to appear different from unsheared precipitates. These conditions are most likely to be met if precipitates are sheared several times in a relatively homogeneous manner. This is important for two reasons. First, a localized shearing process would lead to large dynamical changes in precipitate strength during deformation, and in turn drastically reduce the work hardening of the alloy. Secondly, a localized shearing process would have promoted earlier fracture and failure of the alloy during deformation. Finally, our results also show how different slip directions influences the images of precipitates. In the future, these influences can be used to further understand the shearing process of these precipitates. Hence, our results can be used to improve model predictions of strength, work hardening, and fracture. In turn, this may improve alloy design and reduce the use of prototype testing in, e.g. the automotiveindustry.

Three-Dimensional Imaging of a Single Dopant in a Crystal

Single dopants in materials have strong influences on the fundamental properties in extensive fields. Annular dark-field scanning tranmission electron microscopy (ADF STEM) has been contributed to directly investigate the occupation site of single dopants and their spatial distributions at atomic scale. However, the resultant atomic resolution images are projected in two dimensions, lacking in depth information. Here, we demonstrate the direct determination of three-dimensional atomic locations of single $\mathrm{Ce}$ dopants embedded in cubic boron nitride by ADF STEM depth sectioning with a significantly large illumination angle of 63 mrad in semiangle. Furthermore, we directly evaluate the $\mathrm{Ce}$-$\mathrm{Ce}$ partial pair distribution function in the considerably long distance up to 8.5 nm, which opens the way to study a far-long-range interaction between impurities especially in a dilute doping system.

Quantification of 3D Atomic Structures and Their Dynamics by Atom-Counting from an ADF STEM Image

Quantification of 3D Atomic Structures and Their Dynamics by Atom-Counting from an ADF STEM Image

Insights into image contrast from dislocations in ADF-STEM

Competitive mechanisms contribute to image contrast from dislocations in annular dark-field scanning transmission electron microscopy (ADF-STEM). A clear theoretical understanding of the mechanisms underlying the ADF-STEM contrast is therefore essential for correct interpretation of dislocation images. This paper reports on a systematic study of the ADF-STEM contrast from dislocations in a GaN specimen, both experimentally and computationally. Systematic experimental ADF-STEM images of the edge-character dislocations reveal a number of characteristic contrast features that are shown to depend on both the angular detection range and specific position of the dislocation in the sample. A theoretical model based on electron channelling and Bloch-wave scattering theories, supported by numerical simulations based on Grillo's strain-channelling equation, is proposed to elucidate the physical origin of such complex contrast phenomena.

Evaluating the 3D Structures of PtNi Nanoparticles from Single Projection ADF STEM Images and EDX Maps

Evaluating the 3D Structures of PtNi Nanoparticles from Single Projection ADF STEM Images and EDX Maps

Simultaneous iDPC and ADF STEM Imaging at the Limit of Contrast and Resolution

Simultaneous iDPC and ADF STEM Imaging at the Limit of Contrast and Resolution

Hybrid statistics-simulations based method for atom-counting from ADF STEM images

A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials.

Quantification of ADF STEM Image Data for Nanoparticle Structure and Strain Measurements

Journal Article Quantification of ADF STEM Image Data for Nanoparticle Structure and Strain Measurements Get access P D Nellist, P D Nellist Department of Materials, University of Oxford, 16 Parks Road, Oxford, UK Search for other works by this author on: Oxford Academic Google Scholar L Jones, L Jones Department of Materials, University of Oxford, 16 Parks Road, Oxford, UK Search for other works by this author on: Oxford Academic Google Scholar A Varambhia, A Varambhia Department of Materials, University of Oxford, 16 Parks Road, Oxford, UK Search for other works by this author on: Oxford Academic Google Scholar A De Backer, A De Backer EMAT, University of Antwerp, Groenenborgerlaan 171, Antwerp, Belgium Search for other works by this author on: Oxford Academic Google Scholar S Van Aert, S Van Aert EMAT, University of Antwerp, Groenenborgerlaan 171, Antwerp, Belgium Search for other works by this author on: Oxford Academic Google Scholar D Ozkaya D Ozkaya Johnson Matthey Technology Centre, Sonning Common, Reading, UK Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 22, Issue S3, 1 July 2016, Pages 896–897, https://doi.org/10.1017/S1431927616005328 Published: 25 July 2016

Quantitative ADF STEM: acquisition, analysis and interpretation

Quantitative annular dark-field in the scanning transmission electron microscope (ADF STEM), where image intensities are used to provide composition and thickness measurements, has enjoyed a renaissance during the last decade. Now in a post aberration-correction era many aspects of the technique are being revisited. Here the recent progress and emerging best-practice for such aberration corrected quantitative ADF STEM is discussed including issues relating to proper acquisition of experimental data and its calibration, approaches for data analysis, the utility of such data, its interpretation and limitations.

Quantitative annular dark field scanning transmission electron microscopy for nanoparticle atom-counting: What are the limits?

Quantitative atomic resolution annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique for nanoparticle atom-counting. However, a lot of nanoparticles provide a severe characterisation challenge because of their limited size and beam sensitivity. Therefore, quantitative ADF STEM may greatly benefit from statistical detection theory in order to optimise the instrumental microscope settings such that the incoming electron dose can be kept as low as possible whilst still retaining single-atom precision. The principles of detection theory are used to quantify the probability of error for atom-counting. This enables us to decide between different image performance measures and to optimise the experimental detector settings for atom-counting in ADF STEM in an objective manner. To demonstrate this, ADF STEM imaging of an industrial catalyst has been conducted using the near-optimal detector settings. For this experiment, we discussed the limits for atomcounting diagnosed by combining a thorough statistical method and detailed image simulations.

Optimal ADF STEM imaging parameters for tilt-robust image quantification

An approach towards experiment design and optimisation is proposed for achieving improved accuracy of ADF STEM quantification. In particular, improved robustness to small sample mis-tilts can be achieved by optimising detector collection and probe convergence angles. A decrease in cross section is seen for tilted samples due to the reduction in channelling, resulting in a quantification error, if this is not taken into account. At a smaller detector collection angle the increased contribution from elastic scattering, which initially increases with tilt, can be used to offset the decrease in the TDS signal.