Abstract: In this study, the uptake and elimination of ZnO and CuO nanoparticles in Daphnia magna was tested. Daphnids were exposed during 10 days to sublethal concentrations of ZnO and CuO nanoparticles and corresponding metal salts (ZnCl2 and CuCl2.2H2O), after which they were transferred to unexposed medium for another 10 days. At different times during the exposure and none-exposure, the total and internal zinc or copper concentration of the daphnids was determined and the nanoparticles were localized in the organism using electron microscopy. The exposure concentrations were characterized by measuring the dissolved, nanoparticle and aggregated fraction in the medium. The results showed that the ZnO nanoparticles quickly dissolved after addition to the medium. Contrarily, only a small fraction (corresponding to the dissolved metal salt) of the CuO nanoparticles dissolved, while most of these nanoparticles formed large aggregates. Despite an initial increase in zinc and copper concentration during the first 48 hour to 5 day exposure, the body concentration reached a plateau level that was comparable for the ZnO nanoparticles and ZnCl2, but much higher for the CuO nanoparticles (with visible aggregates accumulating in the gut) than CuCl2.2H2O. During the remaining exposure and subsequent none-exposure phase, the zinc and copper concentration decreased fast to concentrations comparable with the unexposed daphnids. The results indicate that D. magna can regulate its internal zinc and copper concentration after exposure to ZnO and CuO nanoparticles, similar as after exposure to metal salts. The combined dissolution, accumulation and toxicity results confirm that the toxicity of ZnO and CuO nanoparticles is caused by the dissolved fraction. Keywords nano; zinc; copper; dissolution; aggregation; electron microscopy

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: In materials science, high angle annular dark field scanning transmission electron microscopy is often used for tomography at the nanometer scale. In this work, it is shown that a thickness dependent, non-linear damping of the recorded intensities occurs. This results in an underestimated intensity in the interior of reconstructions of homogeneous particles, which is known as the cupping artifact. In this paper, this non-linear effect is demonstrated in experimental images taken under common conditions and is reproduced with a numerical simulation. Furthermore, an analytical derivation shows that these non-linearities can be inverted if the imaging is done quantitatively, thus preventing cupping in the reconstruction.

Abstract: We propose an improved image simulation procedure for atomic-resolution annular dark-field scanning transmission electron microscopy (STEM) based on the multislice formulation, which takes thermal diffuse scattering fully into account. The improvement with regard to the classical frozen phonon approach is realized by separating the lattice configuration statistics from the dynamical scattering so as to avoid repetitive calculations. As an example, the influence of phonon scattering on the image contrast is calculated and investigated. STEM image simulation of crystals can be applied with reasonable computing times to problems involving a large number of atoms and thick or large supercells.

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: Annular dark field TEM images exhibit a dominant mass-thickness contrast that can be quantified to extract single atom scattering cross sections. On top of this incoherent background, additional lattice fringes appear with a nonlinear information limit of 1.2 angstrom at 150 kV. The formation of these fringes is described by coherent nonlinear imaging theory and good agreement is found between experimental and simulated images. Calculations furthermore predict that the use of aberration corrected microscopes will improve the image quality dramatically. (c) 2005 Elsevier B.V. All rights reserved.

Abstract: It is not straightforward to determine resolution for a 3D reconstruction when performing an electron tomography experiment. Different contributions such as missing wedge and misalignment add up and often influence the final resolution in an anisotropic manner. The conventional resolution measures can not be used for all of the reconstruction techniques, especially for iterative techniques which are more commonly used for electron tomography in materials science. Here we define a quantitative resolution measure that determines the resolution in three orthogonal directions of the reconstruction. As an application we use this measure to determine the optimum number of simultaneous iterative reconstruction technique (SIRT) iterations to reconstruct the gold nanoparticles, based on a high angle annular dark field STEM (HAADF-STEM) tilt series.

Abstract: A model-based method is proposed to relatively quantify the chemical composition of atomic columns using high angle annular dark field (HAADF) scanning transmission electron microscopy (STEM) images. The method is based on a quantification of the total intensity of the scattered electrons for the individual atomic columns using statistical parameter estimation theory. In order to apply this theory, a model is required describing the image contrast of the HAADF STEM images. Therefore, a simple, effective incoherent model has been assumed which takes the probe intensity profile into account. The scattered intensities can then be estimated by fitting this model to an experimental HAADF STEM image. These estimates are used as a performance measure to distinguish between different atomic column types and to identify the nature of unknown columns with good accuracy and precision using statistical hypothesis testing. The reliability of the method is supported by means of simulated HAADF STEM images as well as a combination of experimental images and electron energy-loss spectra. It is experimentally shown that statistically meaningful information on the composition of individual columns can be obtained even if the difference in averaged atomic number Z is only 3. Using this method, quantitative mapping at atomic resolution using HAADF STEM images only has become possible without the need of simultaneously recorded electron energy loss spectra.

Abstract: A powerful method to study carbon nanotubes (CNTs) grown in patterned substrates for potential interconnects applications is transmission electron microscopy (TEM). However, high-quality TEM samples are necessary for such a study. Here, TEM specimen preparation by focused ion beam (FIB) has been used to obtain lamellae of patterned samples containing CNTs grown inside contact holes. A dual-cap Pt protection layer and an extensive 5 kV cleaning procedure are applied in order to preserve the CNTs and avoid deterioration during milling. TEM results show that the inner shell structure of the carbon nanotubes has been preserved, which proves that focused ion beam is a useful technique to prepare TEM samples of CNT interconnects.

Abstract: It is very challenging to measure the chemical composition of hetero nanostructures in a reliable and quantitative manner. Here, we propose a novel and straightforward approach that can be used to quantify energy dispersive X-ray spectra acquired in a transmission electron microscope. Our method is based on a combination of electron tomography and the so-called ζ-factor technique. We will demonstrate the reliability of our approach as well as its applicability by investigating Au-Ag and Au-Pt hetero nanostructures. Given its simplicity, we expect that the method could become a new standard in the field of chemical characterization using electron microscopy.

Abstract: Aberration correction in scanning transmission electron microscopy (STEM) has greatly improved the lateral and depth resolution. When using depth sectioning, a technique during which a series of images is recorded at different defocus values, single impurity atoms can be visualised in three dimensions. In this paper, we investigate new possibilities emerging when combining depth sectioning and precise atom-counting in order to reconstruct nanosized particles in three dimensions. Although the depth resolution does not allow one to precisely locate each atom within an atomic column, it will be shown that the depth location of an atomic column as a whole can be measured precisely. In this manner, the morphology of a nanoparticle can be reconstructed in three dimensions. This will be demonstrated using simulations and experimental data of a gold nanorod.

Abstract: A three-dimensional (3D) chemical characterization of nanomaterials can be obtained using tomography based on high angle annular dark field (HAADF) scanning transmission electron microscopy (STEM) or energy dispersive X-ray spectroscopy (EDS) STEM. These two complementary techniques have both advantages and disadvantages. The Z-contrast images have good image quality but lack robustness in the compositional analysis, while the elemental maps give more element-specific information, but at a low signal-to-noise ratio and a longer exposure time. Our aim is to combine these two types of complementary information in one single tomographic reconstruction process. Therefore, an imaging model is proposed combining both HAADF-STEM
and EDS-STEM. Based on this model, the elemental distributions can be reconstructed using both types of information simultaneously during the reconstruction process. The performance of the new technique is evaluated using simulated data and real experimental data. The results demonstrate that combining two imaging modalities leads to tomographic reconstructions with suppressed noise and enhanced contrast.

Abstract: <script type='text/javascript'>document.write(unpmarked('HAADF-STEM tomography is a common technique for characterizing the three-dimensional morphology of nanomaterials. In conventional tomographic reconstruction algorithms, the image intensity is assumed to be a linear projection of a physical property of the specimen. However, this assumption of linearity is not completely valid due to the nonlinear damping of signal intensities. The nonlinear damping effects increase w.r.t the specimen thickness and lead to so-called \u0022cupping artifacts\u0022, due to a mismatch with the linear model used in the reconstruction algorithm. Moreover, nonlinear damping effects can strongly limit the applicability of advanced reconstruction approaches such as Total Variation Minimization and discrete tomography. In this paper, we propose an algorithm for automatically correcting the nonlinear effects and the subsequent cupping artifacts. It is applicable to samples in which chemical compositions can be segmented based on image gray levels. The correction is realized by iteratively estimating the nonlinear relationship between projection intensity and sample thickness, based on which the projections are linearized. The correction and reconstruction algorithms are tested on simulated and experimental data. (C) 2017 Elsevier B.V. All rights reserved.'));

Abstract: Colloidal nanoparticles (NPs) including nanowires and nanosheets made by chemical methods involve many organic ligands. When the structure of NPs is investigated via transmission electron microscopy (TEM), the organic ligands act as a source for e-beam induced deposition and this causes substantial build-up of carbon layers in the investigated areas, which is typically referred to as “contamination” in the eld of electron mi- croscopy. This contamination is often more severe for scanning TEM, a technique that is based on a focused electron beam and hence higher electron dose rate. In this paper, we report a simple and effective method to clean drop-cast TEM grids that contain NPs with ligands. Using a combination of activated carbon and ethanol, this method effectively reduces the amount of ligands on TEM grids, and therefore greatly improves the quality of electron microscopy images and subsequent analytical measurements. This ef cient and facile method can be helpful during electron microscopy investigation of different kinds of nanomaterials that suffer from ligand- induced contamination.

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.