Abstract: The incorporation of aluminum into the silica columns of hierarchical mesoporous materials (HMMs) was studied. The HMMs were synthesized by a combination of hard and soft templating methods, forming mesoporous SBA-15-type silica columns inside the pores of anodic aluminum oxide membranes via evaporation induced self-assembly (EISA). By adding Al-isopropoxide to the EISA-mixture a full tetrahedral incorporation of Al and thus the creation of acid sites was achieved, which was proved by nuclear magnetic resonance spectroscopy. Electron microscopy showed that the use of Al-isopropoxide as an Al source for the HMMs led to a change in the mesopore ordering of silica material from circular hexagonal (donut-like) to columnar hexagonal and a 37% increase in specific surface (BET surface). These results were confirmed by a combination of nitrogen physisorption and small-angle X-ray scattering experiments and can be attributed to a swelling of the P123 micelles with isopropanol. The columnar mesopore ordering of silica is advantageous towards the pore accessibility and therefore preferential for many possible applications including catalysis and adsorption on the acid tetrahedral Al-sites. (C) 2016 Elsevier Inc. All rights reserved.

Abstract: It is commonly agreed that the crystalline structure of seeds dictates the crystallinity of final nanoparticles in a seeded-growth process. Although the formation of monocrystalline particles does require the use of single-crystal seeds, twin planes may stem from either single-or polycrystalline seeds. However, experimental control over twin-plane formation remains difficult to achieve synthetically. Here, we show that a careful interplay between kinetics and selective surface passivation offers a unique handle over the emergence of twin planes (in decahedra and triangles) during the growth over single-crystalline gold nanoparticles of quasi-spherical shape. Twinning can be suppressed under conditions of slow kinetics in the presence of silver ions, yielding single-crystalline particles with high-index facets.

Abstract: In this study, we focus on phase formation in intermixed NiGe thin films as they represent a simplified model of the small intermixed interface layer that is believed to form upon deposition of Ni on Ge and where initial phase formation happens. A combinatorial sputter deposition technique was used to co-deposit a range of intermixed NiGe thin films with Ge concentrations varying between 0 and 50 at.%Ge in a single deposition on both Ge (100) and inert SiO2 substrates. In situ X-ray diffraction and transmission electron microscopy where used to study phase formation. In almost the entire composition range under investigation, crystalline phases where found to be present in the as-deposited films. Between 36 and 48 at.%Ge, high-temperature hexagonal nickel germanides were found to occur metastabily below 300 °C, both on SiO2 and Ge (100) substrates. For Ge concentrations in the range between 36 and 42 at.%, this hexagonal germanide phase was even found to be present at room temperature in the as-deposited films. The results obtained in this work could provide more insight in the phase sequence of a pure Ni film on Ge.

Abstract: Many advanced nanomaterials rely on carefully designed morphology and elemental distribution to achieve their functionalities. Among the few experimental techniques that can directly visualise the 3D elemental distribution on the nanoscale are approaches based on electron tomography in combination with energy-dispersive X-ray spectroscopy (EDXS) and electron energy loss spectroscopy (EELS). Unfortunately, these highly informative methods are severely limited by the fundamentally low signal-to-noise ratio, which makes long experimental times and high electron irradiation doses necessary to obtain reliable 3D reconstructions. Addressing these limitations has been the major research question for the development of these techniques in recent years. This short review outlines the latest progress on the methods to reduce experimental time and electron irradiation dose requirements for 3D elemental distribution analysis and gives an outlook on the development of this field in the near future.

Abstract: We propose the concept of a ‘rainbow’ photocatalyst that consists of TiO2 modified with gold-silver alloy nanoparticles of various sizes and compositions, resulting in a broad plasmon absorption band that covers the entire UV–vis range of the solar spectrum. It is demonstrated that this plasmonic ‘rainbow’ photocatalyst is 16% more effective than TiO2 P25 under both simulated and real solar light for pollutant degradation at the solid-gas interface. With this we provide a promising strategy to maximize the spectral response for solar to chemical energy conversion.

Abstract: Modern TEM enables the investigation of nanostructures at the atomic scale. However, TEM images are only two-dimensional (2D) projections of a three-dimensional (3D) object. Electron tomography can overcome this limitation. The technique is increasingly focused towards quantitative measurements and reaching atomic resolution in 3D has been the ultimate goal for many years. Therefore, one needs to optimize the acquisition of the data, the 3D reconstruction techniques as well as the quantification methods. Here, we will review a broad range of methodologies and examples. Finally, we will provide an outlook and will describe future challenges in the field of electron tomography.

Abstract: In this study the uptake of ZnO and CuO nanoparticles by Daphnia magna was tested. Daphnids were exposed during 48 h to acute concentrations of the nanoparticles and corresponding metal salts. The Daphnia zinc and copper concentration was measured and the nanoparticles were localized using electron microscopy. The aggregation and dissolution in the medium was characterized. A fast dissolution of ZnO in the medium was observed, while most CuO formed large aggregates and only a small fraction dissolved. The Daphnia zinc concentration was comparable for the nanoparticles and salts. Contrarily, a much higher Daphnia copper concentration was observed in the CuO exposure, compared to the copper salt. CuO nanoparticles adsorbed onto the carapace and occurred in the gut but did not internalize in the tissues. The combined dissolution and uptake results indicate that the toxicity of both nanoparticle types was caused by metal ions dissolved from the particles in the medium.

Abstract: The 3D reconstruction of a tilt series for electron tomography is mostly carried out using the weighted backprojection (WBP) algorithm or using one of the iterative algorithms such as the simultaneous iterative reconstruction technique (SIRT). However, it is known that these reconstruction algorithms cannot compensate for the missing wedge. Here, we apply a new reconstruction algorithm for electron tomography, which is based on compressive sensing. This is a field in image processing specialized in finding a sparse solution or a solution with a sparse gradient to a set of ill-posed linear equations. Therefore, it can be applied to electron tomography where the reconstructed objects often have a sparse gradient at the nanoscale. Using a combination of different simulated and experimental datasets, it is shown that missing wedge artefacts are reduced in the final reconstruction. Moreover, it seems that the reconstructed datasets have a higher fidelity and are easier to segment in comparison to reconstructions obtained by more conventional iterative algorithms.

Abstract: Reaching atomic resolution in 3D has been the ultimate goal in the field of electron tomography for many years. Significant progress, both on the theoretical as well as the experimental side has recently resulted in several exciting examples demonstrating the ability to visualise atoms in 3D. In this paper, we will review the different steps that have pushed the resolution in 3D to the atomic level. A broad range of methodologies and practical examples together with their impact on materials science will be discussed. Finally, we will provide an outlook and will describe future challenges in the field of high resolution electron tomography.

Abstract: Colloidal copper(I) sulfide (Cu2-xS) nanocrystals (NCs) have attracted much attention for a wide range of applications because of their unique optoelectronic properties, driving scientists to explore the potential of using Cu2-xS NCs as seeds in the synthesis of heteronanocrystals to achieve new multifunctional materials. Herein, we developed a multistep synthesis strategy toward Cu2-xS/ZnS heteronanorods. The Janus-type Cu2-xS/ZnS heteronanorods are obtained by the injection of hexagonal high-chalcocite Cu2-xS seed NCs in a hot zinc oleate solution in the presence of suitable surfactants, 20 s after the injection of sulfur precursors. The Cu2-xS seed NCs undergo rapid aggregation and coalescence in the first few seconds after the injection, forming larger NCs that act as the effective seeds for heteronucleation and growth of ZnS. The ZnS heteronucleation occurs on a single (100) facet of the Cu2-xS seed NCs and is followed by fast anisotropic growth along a direction that is perpendicular to the c-axis, thus leading to Cu2-xS/ZnS Janus-type heteronanorods with a sharp heterointerface. Interestingly, the high-chalcocite crystal structure of the injected Cu2-xS seed NCs is preserved in the Cu2-xS segments of the heteronanorods because of the highthermodynamic stability of this Cu2-xS phase. The Cu2-xS/ZnS heteronanorods are subsequently converted into single-component Cu2-xS and CuInS2 nanorods by postsynthetic topotactic cation exchange. This work expands the possibilities for the rational synthesis of colloidal multicomponent heteronanorods by allowing the design principles of postsynthetic heteroepitaxial seeded growth and nanoscale cation exchange to be combined, yielding access to a plethora of multicomponent heteronanorods with diameters in the quantum confinement regime.

Abstract: Accurate segmentation of nanoparticles within various matrix materials is a difficult problem in electron tomography. Due to artifacts related to image series acquisition and reconstruction, global thresholding of reconstructions computed by established algorithms, such as weighted backprojection or SIRT, may result in unreliable and subjective segmentations. In this paper, we introduce the Partially Discrete Algebraic Reconstruction Technique (PDART) for computing accurate segmentations of dense nanoparticles of constant composition. The particles are segmented directly by the reconstruction algorithm, while the surrounding regions are reconstructed using continuously varying gray levels. As no properties are assumed for the other compositions of the sample, the technique can be applied to any sample where dense nanoparticles must be segmented, regardless of the surrounding compositions. For both experimental and simulated data, it is shown that PDART yields significantly more accurate segmentations than those obtained by optimal global thresholding of the SIRT reconstruction.

Abstract: Electron tomography is an essential imaging technique for the investigation of morphology and 3D structure of nanomaterials. This method, however, suffers from well-known missing wedge artifacts due to a restricted tilt range, which limits the objectiveness, repeatability and efficiency of quantitative structural analysis. Discrete tomography represents one of the promising reconstruction techniques for materials science, potentially capable of delivering higher fidelity reconstructions by exploiting the prior knowledge of the limited number of material compositions in a specimen. However, the application of discrete tomography to practical datasets remains a difficult task due to the underlying challenging mathematical problem. In practice, it is often hard to obtain consistent reconstructions from experimental datasets. In addition, numerous parameters need to be tuned manually, which can lead to bias and non-repeatability. In this paper, we present the application of a new
iterative reconstruction technique, named TVR-DART, for discrete electron tomography. The technique is capable of consistently delivering reconstructions with significantly reduced missing wedge artifacts for a variety of challenging data and imaging conditions, and can automatically estimate its key parameters. We describe the principles of the technique and apply it to datasets from three different types of samples acquired under diverse imaging modes. By further reducing the available tilt range and number of projections, we show that the
proposed technique can still produce consistent reconstructions with minimized missing wedge artifacts. This new development promises to provide the electron microscopy community with an easy-to-use and robust tool for high-fidelity 3D characterization of nanomaterials.

Abstract: Gold nanoparticles are studied extensively due to their unique optical and catalytical properties. Their exact shape determines the properties and thereby the possible applications. Electron tomography is therefore often used to examine the three-dimensional (3D) shape of nanoparticles. However, since the acquisition of the experimental tilt series and the 3D reconstructions are very time consuming, it is difficult to obtain statistical results concerning the 3D shape of nanoparticles. Here, we propose a new approach for electron tomography that is based on artificial neural networks. The use of a new reconstruction approach enables us to reduce the number of projection images with a factor of 5 or more. The decrease in acquisition time of the tilt series and use of an efficient reconstruction algorithm allows us to examine a large amount of nanoparticles in order to retrieve statistical results concerning the 3D shape.

Abstract: The concept of protecting groups, widely used in organic chemistry, has been applied for the synthesis of Au-silica Janus stars, in which gold branches protrude from one half of Au-silica Janus spheres. This configuration opens up new possibilities to apply the plasmonic properties of gold nanostars, as well as a variety of chemical functionalizations on the silica component.

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.