Abstract: Topological superconductivity is of great contemporary interest and has been proposed in doped Bi₂Se₃, in which electron-donating atoms such as Cu, Sr or Nb have been intercalated into the Bi₂Se₃structure. For Nb_{<italic>x</italic>}Bi₂Se₃, with<italic>T</italic>_c ~ 3 K, it is assumed in the literature that Nb is inserted in the van der Waals gap. However, in this work an alternative origin for the superconductivity in Nb-doped Bi₂Se₃is established. In contrast to previous reports, it is deduced that Nb intercalation in Bi₂Se₃does not take place. Instead, the superconducting behaviour in samples of nominal composition Nb_{<italic>x</italic>}Bi₂Se₃results from the (BiSe)_1.10NbSe₂misfit phase that is present in the sample as an impurity phase for small<italic>x</italic>(0.01 ≤ <italic>x</italic> ≤ 0.10) and as a main phase for large<italic>x</italic>(<italic>x</italic> = 0.50). The structure of this misfit phase is studied in detail using a combination of X-ray diffraction and transmission electron microscopy techniques.

Abstract: Recently discovered series of high Tc superconductors, characterized by the existence of two types of cations within the same layer, are presented. The first family concerns the mercury based cuprates, Hg(1-x)M(x)A(2)Ca(m-1)Cu(m)O(2m+2+delta), with A = Ba and/or Sr, which exhibit structures closely related to that of the thallium cuprates TlBa2Cam-1CumO2m+3. They differ from the thallium cuprates by a high oxygen deficiency at the level of the mercury layer. It is shown that cations such as M = Cu, Pb, Tl, Bi, Ce, Pr, Cr, V, Mo, W, Ti, Sr, Ca,... can partially substitute for mercury ions, stabilizing the structures. The cationic composition of the layer depends indeed on the nature of the M cation but also on that of the alkaline earth A. For given A and M cations, the a: value remains unchanged even when the number of copper layers varies. M and Hg cations are either statistically distributed over the same site or ordered. Different types of ordering have been detected. Another way of generating mixed layers is to shear periodically the structure, leading to the formation of the so called ''collapsed phase''. In the collapsed bismuth cuprates, bismuth and copper segments, a few octahedra long, alternate in strongly waving layers. In the collapsed oxycarbonates, carbonate groups and M cations are ordered within the intermediate layer so that they can be simply described from a partial and ordered substitution of carbon for Hg,TI, Bi and other M cations building the intermediate layer. The oxycarbonitrates (Y1-xCax)(n)Ba2nCu3n-1(C,N)O3O7n-3 can also be described as an ordered substitution of carbon for copper in the 123 matrix. The different families of superconducting materials which are generated by such mechanisms are described as well as the way the different species are distributed within the mixed layers. Their influence on the physical properties are discussed.

Abstract: Reduction of La1xCaxMnO3 (0.6 ≤ x ≤ 1) perovskite phases with sodium hydride yields materials of composition La1xCaxMnO2+δ. The calcium-rich phases (x = 0.9, 1) adopt (La0.9Ca0.1)0.5Mn0.5O disordered rocksalt structures. However local structure analysis using reverse Monte Carlo refinement of models against pair distribution functions obtained from neutron total scattering data reveals lanthanum-rich La1xCaxMnO2+δ (x = 0.6, 0.67, 0.7) phases adopt disordered structures consisting of an intergrowth of sheets of MnO6 octahedra and sheets of MnO4 tetrahedra. X-ray absorption data confirm the presence of Mn(I) centers in La1xCaxMnO2+δ phases with x < 1. Low-temperature neutron diffraction data reveal La1xCaxMnO2+δ (x = 0.6, 0.67, 0.7) phases become antiferromagnetically ordered at low temperature.

Abstract: Mn22+Fe2+W6+O6, a new polar magnetic phase, adopts the corundum-derived Ni3TeO6-type structure with large spontaneous polarization (P-S) of 67.8 mu C cm-2, complex antiferromagnetic order below approximate to 75 K, and field-induced first-order transition to a ferrimagnetic phase below approximate to 30 K. First-principles calculations predict a ferrimagnetic (udu) ground state, optimal switching path along the c-axis, and transition to a lower energy udu-udd magnetic double cell.

Abstract: Dielectric properties of materials are crucial in describing the electromagnetic response of materials. As devices are becoming considerably smaller than the optical wavelength, the conventional measuring methods based on optical response are limited by their spatial resolution. Electron energy loss spectroscopy performed in a scanning transmission electron microscope is a good alternative to obtain the dielectric properties with excellent spatial resolution. Due to the overlap of diffraction discs in scanning transmission electron microscopy, it is difficult to apply conventional experimental settings to suppress retardation losses. In this contribution, a relativistic dielectric model for the loss function is presented which is used in a model based optimization scheme to estimate the complex dielectric function of a material. The method is applied to experiments on bulk diamond and SrTiO3 and shows a good agreement with optical reference data when retardation effects are included. Application of this technique to nanoparticles is possible but several theoretical assumptions made in the model of the loss function are violated and interpretation becomes problematic.

Abstract: An extension to model-based electron energy loss spectroscopy (EELS) quantification is reported to improve the possibility of modelling fine structure changes in electron energy loss spectra. An equalisation function is used in the energy loss near edge structure (ELNES) region to model the differences between a single atom differential cross section and the cross section for an atom in a crystal. The equalisation function can be shown to approximate the relative density of unoccupied states for the given excitation edge. On a set of 200 experimental h-BN spectra, this technique leads to statistically acceptable models resulting into unbiased estimates of relative concentrations and making the estimated precisions come very close to the Cramer-Rao lower bound (CRLB). The method greatly expands the useability of model-based EELS quantification to spectra with pronounced fine structure. Another benefit of this model is that one also gets an estimate of the unoccupied density of states for a given excitation edge, without having to do background removal and deconvolution, making the outcome intrinsically more reliable and less noisy. (c) 2006 Elsevier B.V. All rights reserved.

Abstract: Electron energy loss spectroscopy (EELS) is an ideal tool to obtain chemical information from nanoscale volumes. Quantification of the experimental spectra however has prevented for a long time access to the available information in a reliable and reproducible way. We present recent advances in model-based quantification of EELS spectra and show that we obtain the best possible precision for a given dataset, as well as remarkably good accuracies when applied to three different materials. The results are shown to be far superior over conventional quantification techniques and could hold a promise for standardless quantification of EELS spectra.

Abstract: The capacitance-voltage (C-V) characteristic is calculated for p-type In_0.53Ga_0.47As metal-oxide-semiconductor (MOS) structures based on a self-consistent PoissonSchrödinger solution. For strong inversion, charge quantization leads to occupation of the satellite valleys which appears as a sharp increase in the capacitance toward the oxide capacitance. The results indicate that the charge quantization, even in the absence of interface defects (D_it), is a contributing factor to the experimental observation of an almost symmetric C-V response for In_0.53Ga_0.47As MOS structures. In addition, nonparabolic corrections are shown to enhance the depopulation of the Γ valley, shifting the capacitance increase to lower inversion charge densities.

Abstract: 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.

Abstract: Nanomaterials are materials that have at least one dimension in the nanometer length scale, which corresponds to a billionth of a meter. When three dimensions are confined to the nanometer scale, these materials are referred to as nanoparticles. These materials are of great interest since they exhibit unique physical and chemical properties that cannot be observed for bulk systems. Due to their unique and often superior properties, nanomaterials have become central in the field of electronics, catalysis, and medicine. Moreover, they are expected to be one of the most promising systems to tackle many challenges that our society is facing, such as reducing the emission of greenhouse gases and finding effective treatments for cancer. The unique properties of nanomaterials are linked to their size, shape, structure, and composition. If one is able to measure the positions of the atoms, their chemical nature, and the bonding between them, it becomes possible to predict the physicochemical properties of nanomaterials. In this manner, the development of novel nanostructures can be triggered. However, the morphology and structure of nanomaterials are highly sensitive to the conditions for relevant applications, such as elevated temperatures or intense light illumination. Furthermore, any small change in the local structure at higher temperatures or pressures may significantly modify their performance. Hence, three-dimensional (3D) characterization of nanomaterials under application-relevant conditions is important in designing them with desired functional properties for specific applications. Among different structural characterization approaches, transmission electron microscopy (TEM) is one of the most efficient and versatile tools to investigate the structure and composition of nanomaterials since it can provide atomically resolved images, which are sensitive to the local 3D structure of the investigated sample. However, TEM only provides two-dimensional (2D) images of the 3D nanoparticle, which may lead to an incomplete understanding of their structure-property relationship. The most known and powerful technique for the 3D characterization of nanomaterials is electron tomography, where the images of a nanostructured material taken from different directions are mathematically combined to retrieve its 3D structure. Although these experiments are already state-of-the-art, 3D characterization by TEM is typically performed under ultra-high vacuum conditions and at room temperature. Such conditions are unfortunately not sufficient to understand transformations during synthesis or applications of nanomaterials. This limitation can be overcome by in situ TEM where external stimuli, such as heat, gas, and liquids, can be controllably introduced inside the TEM using specialized holders. However, there are some technical limitations to successful perform 3D in situ electron tomography experiments. For example, the long acquisition time required to collect a tilt series limits this technique when one wants to observe 3D dynamic changes with atomic resolution. A solution for this problem is the estimation of the 3D structure of nanomaterials from 2D projection images acquired along a single viewing direction. For this purpose, annular dark field scanning TEM (ADF STEM) imaging mode provides a valuable tool for quantitative structural investigation of nanomaterials from single 2D images due to its thickness and mass sensitivity. For quantitative analysis, an ADF STEM image is considered as a 2D array of pixels where relative variation of pixel intensity values is proportional to the total number of atoms and the atomic number of the elements in the sample. By applying advanced statistical approaches to these images, structural information, such as the number or types of atoms, can be retrieved with high accuracy and precision. The outcome can then be used to build a 3D starting model for energy minimization by atomistic simulations, for example, molecular dynamics simulations or the Monte Carlo method. However, this methodology needs to be further evaluated for in situ experiments. This thesis is devoted to presenting robust approaches to accurately define the 3D atomic structure of nanoparticles under application-relevant conditions and understand the mechanism behind the atomic-scale dynamics in nanoparticles in response to environmental stimuli.