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.

Abstract: The modified atomic scattering amplitudes (MASAs) of mixed Ga_1-xIn_xAs, GaAs_1-xN_x, and InAs_1-xN_x are calculated using the density functional theory approach and the results are compared with those of the binary counterparts. The MASAs of N, Ga, As, and In for various scattering vectors in various chemical environments and in the zinc-blende structure are compared with the frequently used Doyle and Turner values. Deviation from the Doyle and Turner results is found for small scattering vectors (s<0.3 Å^-1) and for these scattering vectors the MASAs are found to be sensitive to the orientation of the scattering vector and on the chemical environment. The chemical environment sensitive MASAs are used within zero pressure classical Metropolis Monte Carlo, finite temperature calculations to investigate the effect of well size on the electron 002 and 220 structure factors (SFs). The implications of the use of the 002 (200) spot for the quantification of nanostructured Ga_1-xIn_xAs systems are examined while the 220 SF across the well is evaluated and is found to be very sensitive to the in-plane static displacements.

Abstract: The Stöber method is one of the most important and fundamental processes for the synthesis of inorganic (nano)materials but has the drawback of using a large amount of organic solvent. Herein, ethanol was used as an example to explore if the organic solvent in a typical Stöber method can be omitted. It was found that ethanol increases the particle size of the obtained silica spheres and aids the formation of uniform silica particles rather than forming a gel. Nevertheless, the results indicated that an organic solvent in the initial synthesis mixture is not indispensable. An initially immiscible synthesis method was discovered, which can replace the organic solvent-based Stöber method to successfully synthesize silica particles with the same size ranges as the original Stöber process without addition of organic solvents. Moreover, this process can be of further value for the extension to synthesis processes of other materials based on the Stöber process.

Abstract: MOF-5 nanoparticles were prepared by mixing a solution of [Zn4O(C6H5COO)(6)] with a solution of benzene-1,4-dicarboxylic acid in DMF at ambient conditions. The former species mimics as a secondary building unit (SBU), and the latter acts as linker. Mixing of the two solutions induced the formation of MOF-5 nanoparticles in dilute suspension. The applied conditions were identified as suitable for a closer investigation of the particle formation process by combined light and small angle neutron scattering (SANS). Scattering analysis revealed a significant impact of the molar ratio of the two components in the reaction mixture. Excessive use of the building unit slowed down the process. A similar effect was observed upon addition of 4n-decylbenzoic acid, which is supposed to act as a modulator. The formation mechanism leads to initial intermediates, which turn into cubelike nanoparticles with a diameter of about 60-80 nm. This initial stage is followed by an extended formation period, where nucleation proceeds over hours, leading to an increasing number of nanoparticles with the same final size of 60-80 nm.

Abstract: We report the complete disappearance of the structural modulation in heavily lead-doped Bi2-xPbxSr2CaCu2O8+delta crystals observed by transmission electron microscopy. Crystals with a nominal lead content of x = 0.8, corresponding to an effective lead content of x = 0.39, yield the non-modulated phase. The superconducting properties of this modulation-free phase (beta phase) have been studied and compared to those of undoped crystals displaying the modulated phase (alpha phase). Magnetisation measurements reveal that the irreversibility field H-irr(T) and relaxation rates are strongly improved within the beta phase. Measurements of the lower critical field, H-c1, show that the anisotropy factor, epsilon, is considerably reduced in the modulation-free crystals. This is the signature of stronger coupling between CuO2 layers which in turn deeply influences the effectiveness of the pinning. These measurements explain the enhanced pinning properties in moderately Pb-doped crystals in which the alpha phase and beta phase coexist. The enhanced pinning is not only due to the alpha/beta interfaces, which act as effective pinning centers: the emergence of modulation-free domains, characterized by a strongly reduced anisotropy, also significantly contribute to this effect. (C) 2003 Elsevier B.V. All rights reserved.

Abstract: Biporous carbonsilica materials (CSM) with molecular sieve properties and high sorption capacity were developed by synthesizing nano-sized carbon crystallites in the mesopores of Al-MCM-41.

Abstract: Galvanic replacement reactions on metal nanoparticles are often used for the preparation of hollow nanostructures with tunable porosity and chemical composition, leading to tailored optical and catalytic properties. However, the precise interplay between the three-dimensional (3D) morphology and chemical composition of nanostructures during galvanic replacement is not always well understood as the 3D chemical imaging of nanoscale materials is still challenging. It is especially far from straightforward to obtain detailed information from the inside of hollow nanostructures using electron microscopy techniques such as SEM or TEM. We demonstrate here that a combination of state-of-the-art EDX mapping with electron tomography results in the unambiguous determination of both morphology transformation and elemental composition of nanostructures in 3D, during galvanic replacement of Ag nanocubes. This work provides direct and unambiguous experimental evidence toward understanding the galvanic replacement reaction. In addition, the powerful approach presented here can be applied to a wide range of nanoscale transformation processes, which will undoubtedly guide the development of novel nanostructures.