Abstract: Gold nanorods (Au NRs) are an exceptionally promising tool in nanotechnology due to three key factors: (i) their strong interaction with electromagnetic radiation, stemming from their plasmonic nature, (ii) the ease with which the resonance frequency of their longitudinal plasmon mode can be tuned from the visible to the near-infrared region of the electromagnetic spect r u m based on their aspect ratio, and (iii) their simple and cost-effective preparation through seed-mediated chemical growth. In this synthetic method, surfactants play a critical role in controlling the size, shape, and colloidal stabi l i t y of Au NRs. For example, surfactants can stabilize specific crystallographic facets during the formation of Au NRs, leading to t h e formation of NRs with specific morphologies. The process of surfactant adsorption onto the NR surface may result in various assemblies of surfactant molecules, such as spherical micelles, elongated micelles, or bilayers. Again, the assembly mode is critical toward determining the further availabi l i t y of the Au NR surface to the surrounding medium. Despite its importance and a great deal of research effort, the interaction between Au NPs and surfactants remains insufficiently understood, because the assembly process is influenced by numerous factors, including the chemical nature of the surfactant, the surface morphology of Au NPs, and solution parameters. Therefore, gaining a more comprehensive understanding of these interactions is essential to unlock the full potential of the seed-mediated growth method and the applications of plasmonic NPs. A plethora of characterization techniques have been applied to reach such an understanding , but many open questions remain. In this Account, we review the current knowledge on the interactions between surfactants and Au NRs. We briefly introduce the state-of-the-art methods for synthesizing Au NRs and highlight the crucial role of cationic surfactants during this process. The self-assembly and organization of surfactants on the Au NR surface is then discussed to better understand their role in seed-mediated growth. Subsequently, we provide examples and elucidate how chemical additives can be used to modulate micellar assemblies, in turn allowing for a finer control over the growth of Au NRs, including chiral NRs. Next, we review the main experimental characterization and computational modeling techniques that have been applied to shed light on the arrangement of surfactants on Au NRs and summarize the advantages and disadvantages for each technique. The Account ends with a “Conclusions and Outlook” section, outlining promising future research directions and developments that we consider are sti l l required, mostly related to the application of electron microscopy in liquid and in 3D. Finally, we remark on the potential of exploiting machine learning techniques to predict synthetic routes for NPs with predefined structures and properties.

Abstract: The characterization of biological and inorganic materials by determining their three-dimensional structure in conditions closer to their native state is a major challenge of technological research. Environmental scanning electron microscopy (ESEM) provides access to the observation of hydrated samples in water environments. Here, we present a specific device for ESEM in the scanning transmission electron microscopy mode, allowing the acquisition of tilt-series suitable for tomographic reconstructions. The resolution which can be obtained with this device is first determined. Then, we demonstrate the feasibility of tomography on wet materials. The example studied here is hydrophilic mesoporous silica (MCM-41). Finally, the minimum thickness of water which can be detected is calculated from Monte Carlo simulations and compared with the resolution expected in the tomograms.

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: In computed tomography, the reconstruction is typically obtained on a voxel grid. In this work, however, we propose a mesh-based reconstruction method. For tomographic problems, 3D meshes have mostly been studied to simulate data acquisition, but not for reconstruction, for which a 3D mesh means the inverse process of estimating shapes from projections. In this paper, we propose a differentiable forward model for 3D meshes that bridge the gap between the forward model for 3D surfaces and optimization. We view the forward projection as a rendering process, and make it differentiable by extending recent work in differentiable rendering. We use the proposed forward model to reconstruct 3D shapes directly from projections. Experimental results for single-object problems show that the proposed method outperforms traditional voxel-based methods on noisy simulated data. We also apply the proposed method on electron tomography images of nanoparticles to demonstrate the applicability of the method on real data.

Abstract: HAADF-STEM tomography is a widely used experimental technique for analyzing nanometer-scale crystalline structures of a large variety of materials in three dimensions. Unfortunately, the acquisition of conventional HAADF-STEM tilt series can easily take up one hour or more, depending on the complexity of the experiment. It is therefore far from straightforward to investigate samples that do not withstand long acquisition or to acquire large amounts of tilt series during a single TEM experiment. The latter would lead to the ability to obtain statistically meaningful 3D data, or to perform in situ 3D characterizations with a much shorter time resolution. Various HAADF-STEM acquisition strategies have been proposed to accelerate the tomographic acquisition and reduce the required electron dose. These methods include tilting the holder continuously while acquiring a projection “movie” and a hybrid, incremental, methodology which combines the benefits of the conventional and continuous technique. However, until now an experimental evaluation has been lacking. In this paper, the different acquisition strategies will be experimentally compared in terms of speed, resolution and electron dose. This evaluation will be performed based on experimental tilt series acquired for various metallic nanoparticles with different shapes and sizes. We discuss the data processing involved with the fast HAADF-STEM tilt series and provide a general guideline when which acquisition strategy should be preferentially used.

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: 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: 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: We present the ASTRA Toolbox as an open platform for 3D image reconstruction in tomography. Most of the software tools that are currently used in electron tomography offer limited flexibility with respect to the geometrical parameters of the acquisition model and the algorithms used for reconstruction. The ASTRA Toolbox provides an extensive set of fast and flexible building blocks that can be used to develop advanced reconstruction algorithms, effectively removing these limitations. We demonstrate this flexibility, the resulting reconstruction quality, and the computational efficiency of this toolbox by a series of experiments, based on experimental dual-axis tilt series.

Abstract: In electron tomography, the fidelity of the 3D reconstruction strongly depends on the employed reconstruction algorithm. In this paper, the properties of SIRT, TVM and DART reconstructions are studied with respect to having only a limited number of electrons available for imaging and applying different angular sampling schemes. A well-defined realistic model is generated, which consists of tubular domains within a matrix having slab-geometry. Subsequently, the electron tomography workflow is simulated from calculated tilt-series over experimental effects to reconstruction. In comparison with the model, the fidelity of each reconstruction method is evaluated qualitatively and quantitatively based on global and local edge profiles and resolvable distance between particles. Results show that the performance of all reconstruction methods declines with the total electron dose. Overall, SIRT algorithm is the most stable method and insensitive to changes in angular sampling. TVM algorithm yields significantly sharper edges in the reconstruction, but the edge positions are strongly influenced by the tilt scheme and the tubular objects become thinned. The DART algorithm markedly suppresses the elongation artifacts along the beam direction and moreover segments the reconstruction which can be considered a significant advantage for quantification. Finally, no advantage of TVM and DART to deal better with fewer projections was observed.

Abstract: In this work, the simultaneous iterative reconstruction technique (SIRT), the total variation minimization (TVM) reconstruction technique and the discrete algebraic reconstruction technique (DART) for electron tomography are compared and the advantages and disadvantages are discussed. Furthermore, we describe how the result of a three dimensional (3D) reconstruction based on TVM can provide objective information that is needed as the input for a DART reconstruction. This approach results in a tomographic reconstruction of which the segmentation is carried out in an objective manner.

Abstract: We report the controlled preparation of water processable nanoparticles (NPs) employing the push-pull polymer PCDTBT and the fullerene acceptor PC71BM in order to enable solar cell processing using eco-friendly solvent (i.e. water). The presented method provides the possibility to separate the formation of the active layer blend and the deposition of the active layer into two different processes. For the first time, the benefits of aqueous processability for the high-potential class of push-pull polymers, generally requiring high boiling solvents, are made accessible. With our method we demonstrate excellent control over the blend stoichiometry and efficient mixing. Furthermore, we provide visualization of the nano morphology of the different NPs to obtain structural information down to similar to 2 nm resolution using advanced analytical electron microscopy. The imaging directly reveals very small compositional demixing in the PCDTBT:PC71BM blend NPs, in the size range of about <5 nm, indicating fine mixing at the molecular level. The suitability of the proposed methodology and materials towards the aspects of eco-friendly processing of organic solar cells is demonstrated through a processing of lab scale NPs solar cell prototypes reaching a power conversion efficiency of 1.9%. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: Herein, we describe for the first time the synthesis of the highly porous Hf-tetracarboxylate porphyrin-based metal-organic framework (MOF) (Hf)PCN-224(M) (M = H2, Co2+). (Hf)PCN-224(H2) was easily and efficiently prepared following a simple microwave-assisted procedure with good yields (56–67%; space-time yields: 1100–1270 kg m−3·day−1), high crystallinity and phase purity by using trifluoromethanesulfonic acid and benzoic acid as modulators in less than 30 min. By simply introducing a preliminary step (10 min), 5,10,15,20-(tetra-4-carboxyphenyl)porphyrin linker (TCPP) was quantitatively metalated with Co2+ without additional purification and/or time consuming protection/deprotection steps to further obtain (Hf)PCN-224(Co). (Hf)PCN-224(Co) was then tested as catalyst in CO2 cycloaddition reaction with different epoxides to yield cyclic carbonates, showing the best catalytic performance described to date compared to other PCNs, under mild conditions (1 bar CO2, room temperature, 18–24 h). Twelve epoxides were tested, obtaining from moderate to excellent conversions (35–96%). Moreover, this reaction was gram scaled-up (x50) without significant loss of yield to cyclic carbonates. (Hf)PCN-224(Co) maintained its integrity and crystallinity even after 8 consecutive runs, and poisoning was efficiently reverted by a simple thermal treatment (175 °C, 6 h), fully recovering the initial catalytic activity.