Abstract: We report on the observation of self-organized stripe-like structures on the as-grown surface and in the bulk of (Nd,Eu,Gd)Ba2Cu3Oy single crystals. The periodicity of the stripes on the surface lies between 500800 nm. These are possibly the growth steps of the crystal. Transmission electron microscopy investigations revealed stripes of periodicity in the range of 2040 nm in the bulk. From electron back scattered diffraction investigations, no crystallographic misorientation due to the nanostripes has been found. Scanning tunneling spectroscopic experiments revealed nonsuperconducting regions, running along twin directions, which presumably constitute strong pinning sites.

Abstract: Interfaces of ferroic oxides can show complex magnetic textures which have strong impact on spintronics devices. This has been demonstrated recently for interfaces with insulating antiferromagnets such as BiFeO3. Here, noncollinear spin textures which can be switched in very low magnetic field are reported for conducting ferromagnetic bilayers of La0.7Sr0.3MnO3-SrRuO3 (LSMO-SRO). The magnetic order and switching are fundamentally different for bilayers coherently grown in reversed stacking sequence. The SRO top layer forms a persistent exchange spring which is antiferromagnetically coupled to LSMO and drives switching in low fields of a few milliteslas. Density functional theory reveals the crucial impact of the interface termination on the strength of Mn-Ru exchange coupling across the interface. The observation of an exchange spring agrees with ultrastrong coupling for the MnO2/SrO termination. Our results demonstrate low-field switching of noncollinear spin textures at an interface between conducting oxides, opening a pathway for manipulating and utilizing electron transport phenomena in controlled spin textures at oxide interfaces.

Abstract: Water inside a nanocapillary exhibits unconventional structural and dynamical behavior due to its ordered structure. The confining walls, density, and lateral pressures control profoundly the microscopic structure of trapped water. Here we study the electrostriction of confined water subjected to pressures of the order of GPa for two different setups: (i) a graphene nanochannel containing a constant number of water molecules independent of the height of the channel, (ii) an open nanochannel where water molecules can be exchanged with those in a reservoir. For the former case, a square-rhombic structure of confined water is formed when the height of the channel is d = 6.5 angstrom having a density of rho = 1.42 g cm(-3). By increasing the height of the channel, a transition from a flat to a buckled state occurs, whereas the density rapidly decreases and reaches the bulk density for d congruent to 8.5 angstrom. When a perpendicular electric field is applied, the water structure and the lateral pressure change. For strong electric fields (similar to 1 V/angstrom), the square-rhombic structure is destroyed. For an open setup, a solid phase of confined water consisting of an imperfect square-rhombic structure is formed. By applying a perpendicular field, the density and phase of confined water change. However, the density and pressure inside the channel decrease as compared to the first setup. Our study is closely related to recent experiments on confined water, and it reveals the sensitivity of the microscopic structure of confined water to the size of the channel, the external electric field, and the experimental setup.

Abstract: We show that a carbon nanotube decorated with different types of charged metallic nanoparticles exhibits unusual two-dimensional vibrations when actuated by applied electric field. Such vibrations and diverse possible trajectories are not only fundamentally important but also have minimum two characteristic frequencies that can be directly linked back to the properties of the constituents in the considered nanoresonator. Namely, those frequencies and the maximal deflection during vibrations are very distinctively dependent on the geometry of the nanotube, the shape, element, mass and charge of the nanoparticle, and are vastly tunable by the applied electric field, revealing the unique sensing ability of devices made of molecular filaments and metallic nanoparticles.

Abstract: 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 atom-counting diagnosed by combining a thorough statistical method and detailed image simulations.

Abstract: In the present paper, the principles of detection theory are used to quantify the probability of error for atom-counting from high resolution scanning transmission electron microscopy (HR STEM) images. Binary and multiple hypothesis testing have been investigated in order to determine the limits to the precision with which the number of atoms in a projected atomic column can be estimated. The probability of error has been calculated when using STEM images, scattering cross-sections or peak intensities as a criterion to count atoms. Based on this analysis, we conclude that scattering cross-sections perform almost equally well as images and perform better than peak intensities. Furthermore, the optimal STEM detector design can be derived for atom-counting using the expression for the probability of error. We show that for very thin objects LAADF is optimal and that for thicker objects the optimal inner detector angle increases.

Abstract: An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic-resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for overlap between neighboring columns, enabling the analysis of a large field of view. To provide end-users with this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license. In this chapter, this efficient algorithm is applied to three different nanostructures for which the analysis of a large field of view is required.

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: Quantitative annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique to characterise nano-particles on an atomic scale. Because of their limited size and beam sensitivity, the atomic structure of such particles may become extremely challenging to determine. Therefore keeping the incoming electron dose to a minimum is important. However, this may reduce the reliability of quantitative ADF STEM which will here be demonstrated for nano-particle atom-counting. Based on experimental ADF STEM images of a real industrial catalyst, we discuss the limits for counting the number of atoms in a projected atomic column with single atom sensitivity. We diagnose these limits by combining a thorough statistical method and detailed image simulations.

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.

Abstract: An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for overlap between neighbouring columns, enabling the analysis of a large field of view. For this algorithm, the accuracy and precision with which measurements for the atomic column positions and scattering cross-sections from annular dark field (ADF) STEM images can be estimated, has been investigated. The highest attainable precision is reached even for low dose images. Furthermore, the advantages of the model-based approach taking into account overlap between neighbouring columns are highlighted. This is done for the estimation of the distance between two neighbouring columns as a function of their distance and for the estimation of the scattering cross-section which is compared to the integrated intensity from a Voronoi cell. To provide end-users this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license.