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: In this chapter, a statistical model-based method to count the number of atoms of monotype crystalline nanostructures from high-resolution annular dark-field (ADF) scanning transmission electron microscopy (STEM) images is discussed in detail together with a thorough study on the possibilities and inherent limitations. We show that this method can be applied to nanocrystals of arbitrary shape, size, and atom type. The validity of the atom-counting results is confirmed by means of detailed image simulations and it is shown that the high sensitivity of our method enables us to count atoms with single atom sensitivity.

Abstract: This chapter provides an overview of statistical and quantitative methodologies that have pushed (scanning) transmission electron microscopy ((S)TEM) toward accurate and precise measurements of unknown structure parameters for understanding the relation between the structure of a material and its properties. Hereby, statistical parameter estimation theory has extensively been used which enabled not only measuring atomic column positions, but also quantifying the number of atoms, and detecting atomic columns as accurately and precisely as possible from experimental images. As a general conclusion, it can be stated that advanced statistical techniques are ideal tools to perform quantitative electron microscopy at the atomic scale. In the future, statistical methods will continue to be developed and novel quantification procedures will open up new possibilities for studying material structures at the atomic scale.

Abstract: In this chapter, the principles of statistical parameter estimation theory for a quantitative analysis of atomic-resolution electron microscopy images are introduced. Within this framework, electron microscopy images are described by a parametric statistical model. Here, parametric models are introduced for different types of electron microscopy images: reconstructed exit waves, annular dark-field (ADF) scanning transmission electron microscopy (STEM) images, and simultaneously acquired ADF and annular bright-field (ABF) STEM images. Furthermore, the Cramér-Rao lower bound (CRLB) is introduced, i.e. a theoretical lower bound on the variance of any unbiased estimator. This CRLB is used to quantify the precision of the structure parameters of interest, such as the atomic column positions and the integrated atomic column intensities.

Abstract: Advances in controlling energy migration pathways in core-shell lanthanide (Ln)-based hetero-nanocrystals (HNCs) have relied heavily on assumptions about how optically active centers are distributed within individual HNCs. In this article, it is demonstrated that different types of interface patterns can be formed depending on shell growth conditions. Such interface patterns are not only identified but also characterized with spatial resolution ranging from the nanometer- to the atomic-scale. In the most favorable cases, atomic-scale resolved maps of individual particles are obtained. It is also demonstrated that, for the same type of core-shell architecture, the interface pattern can be engineered with thicknesses of just 1 nm up to several tens of nanometers. Total alloying between the core and shell domains is also possible when using ultra-small particles as seeds. Finally, with different types of interface patterns (same architecture and chemical composition of the core and shell domains) it is possible to modify the output color (yellow, red, and green-yellow) or change (improvement or degradation) the absolute upconversion quantum yield. The results presented in this article introduce an important paradigm shift and pave the way toward the emergence of a new generation of core-shell Ln-based HNCs with better control over their atomic-scale organization.

Abstract: A new methodology is presented to count the number of atoms in multimetallic nanocrystals by combining energy dispersive X-ray spectroscopy (EDX) and high angle annular dark field scanning transmission electron microscopy (HAADF STEM). For this purpose, the existence of a linear relationship between the incoherent HAADF STEM and EDX images is exploited. Next to the number of atoms for each element in the atomic columns, the method also allows quantification of the error in the obtained number of atoms, which is of importance given the noisy nature of the acquired EDX signals. Using experimental images of an Au@Ag core–shell nanorod, it is demonstrated that 3D structural information can be extracted at the atomic scale. Furthermore, simulated data of an Au@Pt core–shell nanorod show the prospect to characterize heterogeneous nanostructures with adjacent atomic numbers.

Abstract: Quantitative structure determination is needed in order to study and understand nanomaterials at the atomic scale. Materials characterisation resulting in precise structural information is a crucial point to understand the structure–property relation of materials. Counting the number of atoms and retrieving the 3D atomic structure of nanoparticles plays an important role here. In this paper, an overview will be given of the atom-counting methodology and its applications over the past decade. The procedure to count the number of atoms will be discussed in detail and it will be shown how the performance of the method can be further improved. Furthermore, advances toward mixed element nanostructures, 3D atomic modelling based on the atom-counting results, and quantifying the nanoparticle dynamics will be highlighted.

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: Introduction: Noninvasive ventilation (NIV) is a well-established treatment for acute-on-chronic respiratory failure in hypercapnic COPD patients. Less is known about the effects of a long-term treatment with NIV in hypercapnic COPD patients and about the factors that may predict response in terms of improved oxygenation and lowered CO2 retention.Methods: In this study, we randomized 15 patients to a routine pharmacological treatment (n = 5, age 66 [standard deviation ± 6] years, FEV1 30.5 [±5.1] %pred, PaO2 65 [±6] mmHg, PaCO2 52.4 [±6.0] mmHg) or to a routine treatment and NIV (using the Synchrony BiPAP device [Respironics, Inc, Murrsville, PA]) (n = 10, age 65 [±7] years, FEV1 29.5 [±9.0] %pred, PaO2 59 [±13] mmHg, PaCO2 55.4 [±7.7] mmHg) for 6 months. We looked at arterial blood gasses, lung function parameters and performed a low-dose computed tomography of the thorax, which was later used for segmentation (providing lobe and airway volumes, iVlobe and iVaw) and post-processing with computer methods (providing airway resistance, iRaw) giving overall a functional image of the separate airways and lobes.Results: In both groups there was a nonsignificant change in FEV1 (NIV group 29.5 [9.0] to 38.5 [14.6] %pred, control group 30.5 [5.1] to 36.8 [8.7] mmHg). PaCO2 dropped significantly only in the NIV group (NIV: 55.4 [7.7] → 44.5 [4.70], P = 0.0076; control: 52.4 [6.0] → 47.6 [8.2], NS). Patients actively treated with NIV developed a more inhomogeneous redistribution of mass flow than control patients. Subsequent analysis indicated that in NIV-treated patients that improve their blood gases, mass flow was also redistributed towards areas with higher vessel density and less emphysema, indicating that flow was redistributed towards areas with better perfusion. There was a highly significant correlation between the % increase in mass flow towards lobes with a blood vessel density of >9% and the increase in PaO2. Improved ventilation–perfusion match and recruitment of previously occluded small airways can explain the improvement in blood gases.Conclusion: We can conclude that in hypercapnic COPD patients treated with long-term NIV over 6 months, a mass flow redistribution occurs, providing a better ventilation–perfusion match and hence better blood gases and lung function. Control patients improve homogeneously in iVaw and iRaw, without improvement in gas exchange since there is no improved ventilation/perfusion ratio or increased alveolar ventilation. These differences in response can be detected through functional imaging, which gives a more detailed report on regional lung volumes and resistances than classical lung function tests do. Possibly only patients with localized small airway disease are good candidates for long-term NIV treatment. To confirm this and to see if better arterial blood gases also lead to better health related quality of life and longer survival, we have to study a larger population.

Abstract: We introduce a Bayesian genetic algorithm for reconstructing atomic models of monotype crystalline nanoparticles from a single projection using Z-contrast imaging. The number of atoms in a projected atomic column obtained from annular dark field scanning transmission electron microscopy images serves as an input for the initial three-dimensional model. The algorithm minimizes the energy of the structure while utilizing a priori information about the finite precision of the atom-counting results and neighbor-mass relations. The results show promising prospects for obtaining reliable reconstructions of beam-sensitive nanoparticles during dynamical processes from images acquired with sufficiently low incident electron doses.