Abstract: In the present paper, the optimal detector design is investigated for both detecting and locating light atoms from high resolution scanning transmission electron microscopy (HR STEM) images. The principles of detection theory are used to quantify the probability of error for the detection of light atoms from HR STEM images. To determine the optimal experiment design for locating light atoms, use is made of the so-called Cramer-Rao Lower Bound (CRLB). It is investigated if a single optimal design can be found for both the detection and location problem of light atoms. Furthermore, the incoming electron dose is optimised for both research goals and it is shown that picometre range precision is feasible for the estimation of the atom positions when using an appropriate incoming electron dose under the optimal detector settings to detect light atoms.

Abstract: In this work, a recently developed quantitative approach based on the principles of detection theory is used in order to determine the possibilities and limitations of High Resolution Scanning Transmission Electron Microscopy (HR STEM) and HR TEM for atom-counting. So far, HR STEM has been shown to be an appropriate imaging mode to count the number of atoms in a projected atomic column. Recently, it has been demonstrated that HR TEM, when using negative spherical aberration imaging, is suitable for atom-counting as well. The capabilities of both imaging techniques are investigated and compared using the probability of error as a criterion. It is shown that for the same incoming electron dose, HR STEM outperforms HR TEM under common practice standards, i.e. when the decision is based on the probability function of the peak intensities in HR TEM and of the scattering cross-sections in HR STEM. If the atom-counting decision is based on the joint probability function of the image pixel values, the dependence of all image pixel intensities as a function of thickness should be known accurately. Under this assumption, the probability of error may decrease significantly for atom-counting in HR TEM and may, in theory, become lower as compared to HR STEM under the predicted optimal experimental settings. However, the commonly used standard for atom-counting in HR STEM leads to a high performance and has been shown to work in practice.

Abstract: 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.

Abstract: Pt nanoparticles play an essential role in a wide variety of catalytic reactions. The activity of the particles strongly depends on their three-dimensional (3D) structure and exposed facets, as well as on the reactive environment. High-resolution electron microscopy has often been used to characterize nanoparticle catalysts but unfortunately most observations so far have been either performed in vacuum and/or using conventional (2D) in situ microscopy. The latter however does not provide direct 3D morphological information. We have implemented a quantitative methodology to measure variations of the 3D atomic structure of nanoparticles under the flow of a selected gas. We were thereby able to quantify refaceting of Pt nanoparticles with atomic resolution during various oxidation−reduction cycles. In a H2 environment, a more faceted surface morphology of the particles was observed with {100} and {111} planes being dominant. On the other hand, in O2 the percentage of {100} and {111} facets decreased and a significant increase of higher order facets was found, resulting in a more rounded morphology. This methodology opens up new opportunities toward in situ characterization of catalytic nanoparticles because for the first time it enables one to directly measure 3D morphology variations at the atomic scale in a specific gaseous reaction environment.

Abstract: Urban atmospheres in modern cities carry characteristic mixtures of particulate pollution which are potentially aggravating for chronic respiratory patients (CRP). Although air quality surveys can be detailed, the obtained information is not always useful to evaluate human health effects. This paper presents a novel approach to estimate particle deposition rates in airways of CRP, based on real air pollution data. By combining computational fluid dynamics with physical-chemical characteristics of particulate pollution, deposition rates are estimated for particles of different toxicological relevance, that is, minerals, iron oxides, sea salts, ammonium salts, and carbonaceous particles. Also, it enables some qualitative evaluation of the spatial, temporal, and patient specific effects on the particle dose upon exposure to the urban atmosphere. Results show how heavy traffic conditions increases the deposition of anthropogenic particles in the trachea and lungs of respiratory patients (here, +0.28 and +1.5 μg·h1, respectively). In addition, local and synoptic meteorological conditions were found to have a strong effect on the overall dose. However, the pathology and age of the patient was found to be more crucial, with highest deposition rates for toxic particles in adults with a mild anomaly, followed by mild asthmatic children and adults with severe respiratory dysfunctions (7, 5, and 3 μg·h1, respectively).

Abstract: The increasing need for precise determination of the atomic arrangement of non-periodic structures in materials design and the control of nanostructures explains the growing interest in quantitative transmission electron microscopy. The aim is to extract precise and accurate numbers for unknown structure parameters including atomic positions, chemical concentrations and atomic numbers. For this purpose, statistical parameter estimation theory has been shown to provide reliable results. In this theory, observations are considered purely as data planes, from which structure parameters have to be determined using a parametric model describing the images. As such, the positions of atom columns can be measured with a precision of the order of a few picometres, even though the resolution of the electron microscope is still one or two orders of magnitude larger. Moreover, small differences in average atomic number, which cannot be distinguished visually, can be quantified using high-angle annular dark-field scanning transmission electron microscopy images. In addition, this theory allows one to measure compositional changes at interfaces, to count atoms with single-atom sensitivity, and to reconstruct atomic structures in three dimensions. This feature article brings the reader up to date, summarizing the underlying theory and highlighting some of the recent applications of quantitative model-based transmisson electron microscopy.

Abstract: Over the last decade, scanning transmission electron microscopy has become one of the most powerful tools to characterise nanomaterials at the atomic scale. Often, the ultimate goal is to retrieve the three-dimensional structure, which is very challenging since small species are typically sensitive to electron irradiation. Nevertheless, measuring individual atomic positions is crucial to understand the relation between the structure and physicochemical properties of these (nano)materials. In this review, we highlight the latest approaches that are available to reveal the 3D atomic structure of small species. Finally, we will provide an outlook and will describe future challenges where the limits of electron microscopy will be pushed even further.

Abstract: Zinc is routinely employed in the synthesis of InP quantum dots (QDs) to improve the photoluminescence efficiency and carrier mobility of the resulting In(Zn)P alloy nanostructures. The exact location of Zn in the final structures and the mechanism by which it enhances the optoelectronic properties of the QDs is debated. We use synchrotron X-ray absorbance spectroscopy to show that the majority of Zn in In(Zn)P QDs is located at their surface as Zn-carboxylates. However, a small amount of Zn is present inside the bulk of the QDs with the consequent contraction of their lattice, as confirmed by combining high resolution high-angle annular dark-field imaging scanning transmission electron microscopy (HAADF-STEM) with statistical parameter estimation theory. We further demonstrate that the Zn content and its incorporation into the QDs can be tuned by the ligation of commonly employed Zn carboxylate precursors: the use of highly reactive Zn-acetate leads to the formation of undesired Zn3P2 and the final nanostructures being characterized by broad optical features, whereas Zn-carboxylates with longer carbon chains lead to InP crystals with much lower zinc content and narrow optical features. These results can explain the differences between structural and optical properties of In(Zn)P samples reported across the literature, and provide a rational method to tune the amount of Zn in InP nanocrystals and to drive the incorporation of Zn either as surface Zn-carboxylate, as a substitutional dopant inside the InP crystal lattice, or even predominantly as Zn3P2.

Abstract: Recording the electron energy loss spectroscopy data cube with a series of energy filtered images is a dose inefficient process because the energy slit blocks most of the electrons. When recording the data cube by scanning an electron probe over the sample, perfect dose efficiency is attained; but due to the low current in nanoprobes, this often is slower, with a smaller field of view. In W. Van den Broek et al. [Ultramicroscopy, 106 (2006) 269], we proposed a new method to record the data cube, which is more dose efficient than an energy filtered series. It produces a set of projections of the data cube and then tomographically reconstructs it. In this article, we demonstrate these projections in practice, we present a simple geometrical model that allows for quantification of the projection angles and we present the first successful experimental reconstruction, all on a standard post-column instrument.

Abstract: Over the last two decades, three-dimensional (3D) imaging by transmission electron microscopy or “electron tomography” has evolved into a powerful tool to investigate a variety of nanomaterials in different fields, such as life sciences, chemistry, solid-state physics, and materials science. Most of these results were obtained with nanometer-scale resolution, but different approaches have recently pushed the resolution to the atomic level. Such information is a prerequisite to understand the specific relationship between the atomic structure and the physicochemical properties of (nano) materials. We provide an overview of the latest progress in the field of atomic-resolution electron tomography. Different imaging and reconstruction approaches are presented, and state-of-the-art results are discussed. This article demonstrates the power and importance of electron tomography with atomic-scale resolution.

Abstract: Background: Inhaled formulations using extrafine particles of long-acting beta(2)-agonists and corticosteroids were developed to optimize asthma treatment. Findings that these combinations reach and treat smaller airways more effectively are predominantly based on general non-specific outcomes with little information on regional characteristics. Objectives: This study aims to assess long-term effects of extrafine beclomethasone/formoterol on small airways of asthmatic patients using novel functional imaging methods. Methods: Twenty-four stable asthma patients were subdivided into three groups (steroid naive, n = 7; partially controlled, n = 6; well controlled, n = 11). Current treatment was switched to a fixed combination of extrafine beclomethasone/formoterol (Foster (R); Chiesi Pharmaceuticals, Parma, Italy). Patients underwent lung function evaluation and thorax high-resolution computerized tomography (HRCT) scan. Local airway resistance was obtained from computational fluid dynamics (CFD). Results: After 6 months, the entire population showed improvement in pre-bronchodilation imaging parameters, including small airway volume (p = 0.0007), resistance (p = 0.011), and asthma control score (p = 0.016). Changes in small airway volume correlated with changes in asthma control score (p = 0.004). Forced expiratory volume in 1 s (p = 0.044) and exhaled nitric oxide (p = 0.040) also improved. Functional imaging provided more detail and clinical relevance compared to lung function tests, especially in the well-controlled group where only functional imaging parameters showed significant improvement, while the correlation with asthma control score remained. Conclusions: Extrafine beclomethasone/formoterol results in a significant reduction of small airway obstruction, detectable by functional imaging (HRCT/CFD). Changes in imaging parameters correlated significantly with clinically relevant improvements. This indicates that functional imaging is a useful tool for sensitive assessment of changes in the respiratory system after asthma treatment. Copyright (C) 2013 S. Karger AG, Basel

Abstract: A new tungsten bronze in the SbWO system has been prepared in a solid state reaction from Sb2O3, WO3 and W metal powder. The average structure was determined by single crystal X-ray diffraction. SbxWO3+y (x ∼ 0.11) crystallizes in the orthorhombic space group Pm21n (no. 31), a = 27.8135(9) Å, b = 7.3659(2) Å and c = 3.8672(1) Å. The structure belongs to the (n)-ITB class of intergrowth tungsten bronzes. It contains slabs of hexagonal channels formed by six WO6 octahedra. These slabs are separated by three layers of WO6 octahedra that are arranged in a WO3-type fashion. The WO6 octahedra share all vertices to build up a three-dimensional framework. The hexagonal channels are filled with Sb atoms to ∼80% and additional O atoms. The atoms are shifted out of the center of the channels. Exit-wave reconstruction of focal series of high resolution-transmission-electron-microscope (HRTEM) images combined with statistical paramäeter estimation techniques allowed to study local ordering in the channels. Sb atoms in neighbouring channels tend to be displaced in the same direction, which is in agreement with total energy calculations on ordered structure models, but the ratio of the occupation of the two possible Sb sites varies from channel to channel. The structure of SbxWO3+y exhibits pronounced local modulations.

Abstract: We report an innovative method to explore the optimal experimental settings to detect light atoms from scanning transmission electron microscopy (STEM) images. Since light elements play a key role in many technologically important materials, such as lithium-battery devices or hydrogen storage applications, much effort has been made to optimize the STEM technique in order to detect light elements. Therefore, classical performance criteria, such as contrast or signal-to-noise ratio, are often discussed hereby aiming at improvements of the direct visual interpretability. However, when images are interpreted quantitatively, one needs an alternative criterion, which we derive based on statistical detection theory. Using realistic simulations of technologically important materials, we demonstrate the benefits of the proposed method and compare the results with existing approaches.

Abstract: Understanding nanostructures down to the atomic level is the key to optimizing the design of advancedmaterials with revolutionary novel properties. This requires characterization methods capable of quantifying the three-dimensional (3D) atomic structure with the highest possible precision. A successful approach to reach this goal is to count the number of atoms in each atomic column from 2D annular dark field scanning transmission electron microscopy images. To count atoms with single atom sensitivity, a minimum electron dose has been shown to be necessary, while on the other hand beam damage, induced by the high energy electrons, puts a limit on the tolerable dose. An important challenge is therefore to develop experimental strategies to optimize the electron dose by balancing atom-counting fidelity vs the risk of knock-on damage. To achieve this goal, a statistical framework combined with physics-based modeling of the dose-dependent processes is here proposed and experimentally verified. This model enables an investigator to theoretically predict, in advance of an experimental measurement, the optimal electron dose resulting in an unambiguous quantification of nanostructures in their native state with the highest attainable precision.